Biography
Gabor Fichtinger received BSc and MSc degrees in Electrical Engineering, and Doctoral degree in Computer Science from the Technical University of Budapest, Hungary, in 1986, 1988, and 1990, respectively. He has a balanced academic, industrial, and clinical background in the development and clinical inauguration of image-guided surgery and interventional navigation systems. His specialty is image-guided needle-placement procedures, primarily for cancer diagnosis and therapy and musculoskeletal conditions. Dr. Fichtinger is a Professor of Computer Science, with cross appointments in Electrical and Computer Engineering, Mechanical and Materials Engineering, Surgery and Pathology at Queen’s University, Canada, with adjunct appointments at the Johns Hopkins University, USA, Western University, Canada and the medical University of Vienna, Austria. Dr. Fichtinger holds a Cancer Ontario Research Chair in Cancer Imagin
Affiliations
- Professor and Canada Research Chair (Tier 1) in Computer-Integrated Surgery, School of Computing, w/ cross appointments in Surgery, Pathology and Molecular Medicine, Mechanical and Materials Engineering, Electrical and Computer Engineering, Queen’s University, Kingston, Ontario, Canada
- Fellow of RSC (Royal Society of Canada)
- Fellow of IEEE (Institute of Electrical and Electronics Engineers)
- Fellow of AIMBE (American Institute for Medical and Biological Engineering)
- Fellow of MICCAI (Medical Image Computing and Computer Assisted Interventions)
- Adjunct Professor of Medical Physics and Biomedical Engineering, Medical University of Vienna, Austria
- Adjunct Professor of Computer Science and Radiology and Radiological Science, Johns Hopkins University, Baltimore, MD, USA
- Adjunct Research Professor of Medical Biophysics, Western University, London, ON, Canada
- Affiliated Faculty, The Techna Institute, University Health Network and University of Toronto, Canada
- Honorary University Professor, Obuda University, Budapest, Hungary
Publications
Elkind, Emese; Tun, Aung Tin; Radcliffe, Olivia; Connolly, Laura; Davison, Colleen; Purkey, Eva; Mousavi, Parvin; Fichtinger, Gabor; Thornton, Kanchana
2024 Canadian Conference on Global Health, Canadian Association for Global Health, 2024.
@conference{Elkind2024b,
title = {Enhancing healthcare access by developing low-cost 3D printed prosthetics along the Thai-Myanmar border},
author = {Emese Elkind and Aung Tin Tun and Olivia Radcliffe and Laura Connolly and Colleen Davison and Eva Purkey and Parvin Mousavi and Gabor Fichtinger and Kanchana Thornton
},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/10/EElkind_CCGH2024.pdf},
year = {2024},
date = {2024-10-25},
urldate = {2024-10-25},
booktitle = {2024 Canadian Conference on Global Health},
publisher = {Canadian Association for Global Health},
abstract = {Background/Objective
Inadequacies in the Burmese healthcare system, heightened by the 2021 military coup of the civil war in Myanmar and the COVID-19 pandemic, have driven thousands of refugees to Thailand seeking medical aid. Without immigration status, these refugees, especially those who have experienced limb loss, are challenged by the inability to receive healthcare. Burma Children Medical Fund (BCMF, www.burmachildren.com) based in Mae Sot, Tak, Thailand focuses on funding underserved Burmese communities’ medical treatment and providing support services.
Prosthetics in lower-income countries are usually passive, therefore, patients cannot fully perform their daily functions, impacting their abilities to work and affecting family caretakers. BCMF aims to make body-powered prosthetics that work best in low-resource settings using open-source designs, which only allow for fixed hand positions. The usage of prosthetic arms depends heavily on their functionality and comfort. Patients are more likely to consistently use prosthetics if it aids them in returning to normalcy and reducing family burdens. My objective is to design an interchangeable hand to enable critical rotational movements.
Methodology
The BCMF prosthetics project makes custom-fitted, low-cost, 3D-printed prostheses. BCMF uses open-source prosthetic models such as the Kwawu Arm 2.0, which provides an OpenSCAD (openscad.org) file for adjusting the model to the recipient's measurements. To maintain BCMF’s workflow, the interchangeable wrist model was created using the 3D design software, Autodesk Fusion 360, and designs from NIOP Q-C v1 and v2 Quick-Connect Wrist. The wrist was merged onto the Kwawu Arm, printed, assembled, and tested. This is an iterative process where patient feedback ensures the prosthetics cater to the diverse needs of the recipients.
Results
Since the launch of the prosthetics project in 2019, BCMF has provided 3D-printed prosthetics to 76 patients. The interchangeable hand provides a solution to many patients' everyday activities and can rotate the hand 360 degrees.
Conclusions
This project provides a low-cost solution to healthcare challenges in the context of poly-crisis experienced in Myanmar, enhancing the resilience and adaptability of affected refugee communities.
Relevance to Sub-Theme
This presentation aligns with sub-theme 2 by developing and testing methods to improve healthcare access and quality in areas affected by war, migration, poverty, and racial disparities.},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Background/Objective
Inadequacies in the Burmese healthcare system, heightened by the 2021 military coup of the civil war in Myanmar and the COVID-19 pandemic, have driven thousands of refugees to Thailand seeking medical aid. Without immigration status, these refugees, especially those who have experienced limb loss, are challenged by the inability to receive healthcare. Burma Children Medical Fund (BCMF, www.burmachildren.com) based in Mae Sot, Tak, Thailand focuses on funding underserved Burmese communities’ medical treatment and providing support services.
Prosthetics in lower-income countries are usually passive, therefore, patients cannot fully perform their daily functions, impacting their abilities to work and affecting family caretakers. BCMF aims to make body-powered prosthetics that work best in low-resource settings using open-source designs, which only allow for fixed hand positions. The usage of prosthetic arms depends heavily on their functionality and comfort. Patients are more likely to consistently use prosthetics if it aids them in returning to normalcy and reducing family burdens. My objective is to design an interchangeable hand to enable critical rotational movements.
Methodology
The BCMF prosthetics project makes custom-fitted, low-cost, 3D-printed prostheses. BCMF uses open-source prosthetic models such as the Kwawu Arm 2.0, which provides an OpenSCAD (openscad.org) file for adjusting the model to the recipient's measurements. To maintain BCMF’s workflow, the interchangeable wrist model was created using the 3D design software, Autodesk Fusion 360, and designs from NIOP Q-C v1 and v2 Quick-Connect Wrist. The wrist was merged onto the Kwawu Arm, printed, assembled, and tested. This is an iterative process where patient feedback ensures the prosthetics cater to the diverse needs of the recipients.
Results
Since the launch of the prosthetics project in 2019, BCMF has provided 3D-printed prosthetics to 76 patients. The interchangeable hand provides a solution to many patients' everyday activities and can rotate the hand 360 degrees.
Conclusions
This project provides a low-cost solution to healthcare challenges in the context of poly-crisis experienced in Myanmar, enhancing the resilience and adaptability of affected refugee communities.
Relevance to Sub-Theme
This presentation aligns with sub-theme 2 by developing and testing methods to improve healthcare access and quality in areas affected by war, migration, poverty, and racial disparities.
Inadequacies in the Burmese healthcare system, heightened by the 2021 military coup of the civil war in Myanmar and the COVID-19 pandemic, have driven thousands of refugees to Thailand seeking medical aid. Without immigration status, these refugees, especially those who have experienced limb loss, are challenged by the inability to receive healthcare. Burma Children Medical Fund (BCMF, www.burmachildren.com) based in Mae Sot, Tak, Thailand focuses on funding underserved Burmese communities’ medical treatment and providing support services.
Prosthetics in lower-income countries are usually passive, therefore, patients cannot fully perform their daily functions, impacting their abilities to work and affecting family caretakers. BCMF aims to make body-powered prosthetics that work best in low-resource settings using open-source designs, which only allow for fixed hand positions. The usage of prosthetic arms depends heavily on their functionality and comfort. Patients are more likely to consistently use prosthetics if it aids them in returning to normalcy and reducing family burdens. My objective is to design an interchangeable hand to enable critical rotational movements.
Methodology
The BCMF prosthetics project makes custom-fitted, low-cost, 3D-printed prostheses. BCMF uses open-source prosthetic models such as the Kwawu Arm 2.0, which provides an OpenSCAD (openscad.org) file for adjusting the model to the recipient's measurements. To maintain BCMF’s workflow, the interchangeable wrist model was created using the 3D design software, Autodesk Fusion 360, and designs from NIOP Q-C v1 and v2 Quick-Connect Wrist. The wrist was merged onto the Kwawu Arm, printed, assembled, and tested. This is an iterative process where patient feedback ensures the prosthetics cater to the diverse needs of the recipients.
Results
Since the launch of the prosthetics project in 2019, BCMF has provided 3D-printed prosthetics to 76 patients. The interchangeable hand provides a solution to many patients' everyday activities and can rotate the hand 360 degrees.
Conclusions
This project provides a low-cost solution to healthcare challenges in the context of poly-crisis experienced in Myanmar, enhancing the resilience and adaptability of affected refugee communities.
Relevance to Sub-Theme
This presentation aligns with sub-theme 2 by developing and testing methods to improve healthcare access and quality in areas affected by war, migration, poverty, and racial disparities.
Warren, Jade; Jamzad, Amoon; Jamaspishvili, Tamara; Iseman, Rachael; Syeda, Ayesha; Kaufmann, Martin; Rudan, John; Fichtinger, Gabor; Berman, David M.; Mousavi, Parvin
Towards Improving Surgical Margins in Tumour Resection Using Mass Spectrometry Imaging Proceedings
2024, ISBN: 979-8-3503-7163-5.
@proceedings{10667088,
title = {Towards Improving Surgical Margins in Tumour Resection Using Mass Spectrometry Imaging},
author = {Jade Warren and Amoon Jamzad and Tamara Jamaspishvili and Rachael Iseman and Ayesha Syeda and Martin Kaufmann and John Rudan and Gabor Fichtinger and David M. Berman and Parvin Mousavi},
doi = {10.1109/CCECE59415.2024.10667088},
isbn = {979-8-3503-7163-5},
year = {2024},
date = {2024-09-21},
urldate = {2024-09-21},
abstract = {Successful cancer resection is limited by the inability to differentiate between cancer and normal tissue intraoperatively. Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is an emerging and powerful analytical technique that offers a rapid and low cost approach for assessing surgical margins by generating detailed metabolic profiles. However, exploiting this data for tissue characterization based on molecular signals requires machine learning methods to handle its complexity. In this work, we utilize machine learning models for the characterization of tissue using DESI-MSI data obtained from prostate tissue samples. We use ViPRE, a novel open-source software, to annotate a large DESI-MSI dataset. We explore various machine learning models and train test schemes for cancer classification. Cross-validation of our models result in high balanced accuracy, sensitivity and specificity for cancer classification. Furthermore, we simulate the prospective application of perioperative tissue characterization, generating a qualitative visual prediction for whole slides that match pathology annotations. Finally, the application of linear transformation and classification algorithms on DESI-MSI data effectively distinguished between the molecular profiles associated with different cancer grades. Our findings highlight the promise of combining machine learning with large DESI-MSI datasets for tissue characterization, thereby improving surgical margin precision.},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
Successful cancer resection is limited by the inability to differentiate between cancer and normal tissue intraoperatively. Desorption electrospray ionization mass spectrometry imaging (DESI-MSI) is an emerging and powerful analytical technique that offers a rapid and low cost approach for assessing surgical margins by generating detailed metabolic profiles. However, exploiting this data for tissue characterization based on molecular signals requires machine learning methods to handle its complexity. In this work, we utilize machine learning models for the characterization of tissue using DESI-MSI data obtained from prostate tissue samples. We use ViPRE, a novel open-source software, to annotate a large DESI-MSI dataset. We explore various machine learning models and train test schemes for cancer classification. Cross-validation of our models result in high balanced accuracy, sensitivity and specificity for cancer classification. Furthermore, we simulate the prospective application of perioperative tissue characterization, generating a qualitative visual prediction for whole slides that match pathology annotations. Finally, the application of linear transformation and classification algorithms on DESI-MSI data effectively distinguished between the molecular profiles associated with different cancer grades. Our findings highlight the promise of combining machine learning with large DESI-MSI datasets for tissue characterization, thereby improving surgical margin precision.
Kim, Andrew S.; Yeung, Chris; Szabo, Robert; Sunderland, Kyle; Hisey, Rebecca; Morton, David; Kikinis, Ron; Diao, Babacar; Mousavi, Parvin; Ungi, Tamas; Fichtinger, Gabor
SPIE, 2024.
@proceedings{Kim2024,
title = {Percutaneous nephrostomy needle guidance using real-time 3D anatomical visualization with live ultrasound segmentation},
author = {Andrew S. Kim and Chris Yeung and Robert Szabo and Kyle Sunderland and Rebecca Hisey and David Morton and Ron Kikinis and Babacar Diao and Parvin Mousavi and Tamas Ungi and Gabor Fichtinger},
editor = {Maryam E. Rettmann and Jeffrey H. Siewerdsen},
doi = {10.1117/12.3006533},
year = {2024},
date = {2024-03-29},
urldate = {2024-03-29},
publisher = {SPIE},
abstract = {
PURPOSE: Percutaneous nephrostomy is a commonly performed procedure to drain urine to provide relief in patients with hydronephrosis. Conventional percutaneous nephrostomy needle guidance methods can be difficult, expensive, or not portable. We propose an open-source real-time 3D anatomical visualization aid for needle guidance with live ultrasound segmentation and 3D volume reconstruction using free, open-source software. METHODS: Basic hydronephrotic kidney phantoms were created, and recordings of these models were manually segmented and used to train a deep learning model that makes live segmentation predictions to perform live 3D volume reconstruction of the fluid-filled cavity. Participants performed 5 needle insertions with the visualization aid and 5 insertions with ultrasound needle guidance on a kidney phantom in randomized order, and these were recorded. Recordings of the trials were analyzed for needle tip distance to the center of the target calyx, needle insertion time, and success rate. Participants also completed a survey on their experience. RESULTS: Using the visualization aid showed significantly higher accuracy, while needle insertion time and success rate were not statistically significant at our sample size. Participants mostly responded positively to the visualization aid, and 80% found it easier to use than ultrasound needle guidance. CONCLUSION: We found that our visualization aid produced increased accuracy and an overall positive experience. We demonstrated that our system is functional and stable and believe that the workflow with this system can be applied to other procedures. This visualization aid system is effective on phantoms and is ready for translation with clinical data.},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
PURPOSE: Percutaneous nephrostomy is a commonly performed procedure to drain urine to provide relief in patients with hydronephrosis. Conventional percutaneous nephrostomy needle guidance methods can be difficult, expensive, or not portable. We propose an open-source real-time 3D anatomical visualization aid for needle guidance with live ultrasound segmentation and 3D volume reconstruction using free, open-source software. METHODS: Basic hydronephrotic kidney phantoms were created, and recordings of these models were manually segmented and used to train a deep learning model that makes live segmentation predictions to perform live 3D volume reconstruction of the fluid-filled cavity. Participants performed 5 needle insertions with the visualization aid and 5 insertions with ultrasound needle guidance on a kidney phantom in randomized order, and these were recorded. Recordings of the trials were analyzed for needle tip distance to the center of the target calyx, needle insertion time, and success rate. Participants also completed a survey on their experience. RESULTS: Using the visualization aid showed significantly higher accuracy, while needle insertion time and success rate were not statistically significant at our sample size. Participants mostly responded positively to the visualization aid, and 80% found it easier to use than ultrasound needle guidance. CONCLUSION: We found that our visualization aid produced increased accuracy and an overall positive experience. We demonstrated that our system is functional and stable and believe that the workflow with this system can be applied to other procedures. This visualization aid system is effective on phantoms and is ready for translation with clinical data.
Klosa, Elizabeth; Levendovics, Renáta; Takács, Kristóf; Fichtinger, Gabor; Haidegger, Tamás
Exploring heart rate variability metrics for stress assessment in robot-assisted surgery training Conference
2024.
@conference{nokey,
title = {Exploring heart rate variability metrics for stress assessment in robot-assisted surgery training},
author = {Elizabeth Klosa and Renáta Levendovics and Kristóf Takács and Gabor Fichtinger and Tamás Haidegger},
url = {https://www.imno.ca/sites/default/files/ImNO2024-Proceedings.pdf},
year = {2024},
date = {2024-03-20},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Elkind, Emese; Barr, Keiran; Barr, Colton; Moga, Kristof; Garamvolgy, Tivadar; Haidegger, Tamas; Ungi, Tamas; Fichtinger, Gabor
Modifying Radix Lenses to Survive Low-Cost Sterilization: An Exploratory Study Conference
Imaging Network of Ontario (ImNO) Symposium, Imaging Network of Ontario (ImNO) Symposium, 2024.
@conference{Elkind2024,
title = {Modifying Radix Lenses to Survive Low-Cost Sterilization: An Exploratory Study},
author = {Emese Elkind and Keiran Barr and Colton Barr and Kristof Moga and Tivadar Garamvolgy and Tamas Haidegger and Tamas Ungi and Gabor Fichtinger},
url = {https://labs.cs.queensu.ca/perklab/wp-content/uploads/sites/3/2024/10/EmeseElkindImNO2024-2.docx},
year = {2024},
date = {2024-03-19},
urldate = {2024-03-19},
booktitle = {Imaging Network of Ontario (ImNO) Symposium},
publisher = {Imaging Network of Ontario (ImNO) Symposium},
abstract = {INTRODUCTION: A major challenge with deploying infrared camera-tracked surgical navigation solutions, such as NousNav [1], in low-resource settings is the high cost and unavailability of disposable retroreflective infrared markers. Developing an accessible method to reuse and sterilize retroreflective markers could lead to significant increase in the uptake of this technology. As none of the known infrared markers can endure standard autoclaving and most places do not have access to gas sterilization, attention is focused on cold liquid sterilisation methods commonly used in laparoscopy and other optical tools that cannot be sterilized in a conventional autoclave.
METHODS: We propose to modify NDI Radix™ Lens [1], single-use retroreflective spherical marker manufactured by Northern Digital, Waterloo, Canada. Radix lenses are uniquely promising candidates for liquid sterilization given their smooth, spherical surface. This quality also makes them easier to clean perioperatively compared to other retroreflective infrared marker designs. Initial experiments show that liquid sterilization agents degrade the marker’s retroreflective gold coating (Fig. 1). Hence the objective of this project is to develop a method to protect the Radix Lenses with a layer of coating material that does not allow the sanitizing agent to degrade the coating to enable the lens to survive multiple sanitation cycles while retaining sufficient tracking accuracy. We employed two cold liquid sterilisation agents, household bleach which is a common ingredient of liquid sterilisation solutions and Sekusept™ Aktiv (Ecolab, Saint Paul, MN, USA), which is widely known for sterilizing laparoscopy instruments. Store-bought nail polish and Zink-Alu Spray were used to coat the lenses. Data were obtained by recording five tests each with five rounds of sterilization, each tested with six trials, for a total of 150 recordings. The five tests were as follows: 1) Radix lens coated with nail polish and bleached, 2) uncoated and bleached, 3) coated with nail polish and sanitised, 4) uncoated and sanitised, and 5) coated with Zink-Alu Spray and sanitised. To assess the impact of the sterilization on the lens’s fiducial localization error, two metal marker frames equipped with four sockets designed for the Radix lenses were used. The reference marker frame was secured to a flat table while the other marker frame moved along a fixed path on the table. The position and orientation of the marker clusters were streamed into 3D Slicer using the Public Library for Ultrasound Toolkit (PLUS). A plane was then fit to the recorded marker poses in 3D Slicer using Iterative Closest Point and the marker registration error was computed. Distance from the camera, angle of view, and distance from the edges of the field of view were held constant.
RESULTS: With each round of sterilization, the error of coated lenses was lower than the unprotected lenses, and the error showed a slightly increasing trend (Fig. 2). The lenses appeared fainter in the tracking software the lenses appeared fainter while all lenses remained trackable and visible despite the significant removal of reflective coating.
When reflective coating was fully rubbed off the lenses, the tracking software could still localize the markers; however, the lenses did appear much fainter in the tracking software. We observed that the reflective coating rubs off the lens in routine handling, and recoating with Zink-Alu spray can partially restore marker visibility. Using protective nail polish coating prevented the reflective coating from rubbing off altogether.
CONCLUSIONS: This exploratory study represents a promising step toward achieving low-cost sterilization of retroreflective infrared markers. Studies with the NousNav system need to be undertaken to measure the extent of degradation in tracking accuracy is tolerable as a side effect of marker sterilization. Before using coated Radix lenses on human subjects, it must be verified that the protective coating (common nail polish in our study) is fully biocompatible and remains undamaged by the cold sterilization agent (Sekusept™ Aktiv in our study.)
REFERENCES: [1] NousNav: A low-cost neuronavigation system for deployment in lower-resource settings, International Journal of Computer Assisted Radiology and Surgery, 2022 Sep;17(9):1745-1750. [2] NDI Radix™ Lens (https://www.ndigital.com/optical-measurement-technology/radix-lens/) },
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
INTRODUCTION: A major challenge with deploying infrared camera-tracked surgical navigation solutions, such as NousNav [1], in low-resource settings is the high cost and unavailability of disposable retroreflective infrared markers. Developing an accessible method to reuse and sterilize retroreflective markers could lead to significant increase in the uptake of this technology. As none of the known infrared markers can endure standard autoclaving and most places do not have access to gas sterilization, attention is focused on cold liquid sterilisation methods commonly used in laparoscopy and other optical tools that cannot be sterilized in a conventional autoclave.
METHODS: We propose to modify NDI Radix™ Lens [1], single-use retroreflective spherical marker manufactured by Northern Digital, Waterloo, Canada. Radix lenses are uniquely promising candidates for liquid sterilization given their smooth, spherical surface. This quality also makes them easier to clean perioperatively compared to other retroreflective infrared marker designs. Initial experiments show that liquid sterilization agents degrade the marker’s retroreflective gold coating (Fig. 1). Hence the objective of this project is to develop a method to protect the Radix Lenses with a layer of coating material that does not allow the sanitizing agent to degrade the coating to enable the lens to survive multiple sanitation cycles while retaining sufficient tracking accuracy. We employed two cold liquid sterilisation agents, household bleach which is a common ingredient of liquid sterilisation solutions and Sekusept™ Aktiv (Ecolab, Saint Paul, MN, USA), which is widely known for sterilizing laparoscopy instruments. Store-bought nail polish and Zink-Alu Spray were used to coat the lenses. Data were obtained by recording five tests each with five rounds of sterilization, each tested with six trials, for a total of 150 recordings. The five tests were as follows: 1) Radix lens coated with nail polish and bleached, 2) uncoated and bleached, 3) coated with nail polish and sanitised, 4) uncoated and sanitised, and 5) coated with Zink-Alu Spray and sanitised. To assess the impact of the sterilization on the lens’s fiducial localization error, two metal marker frames equipped with four sockets designed for the Radix lenses were used. The reference marker frame was secured to a flat table while the other marker frame moved along a fixed path on the table. The position and orientation of the marker clusters were streamed into 3D Slicer using the Public Library for Ultrasound Toolkit (PLUS). A plane was then fit to the recorded marker poses in 3D Slicer using Iterative Closest Point and the marker registration error was computed. Distance from the camera, angle of view, and distance from the edges of the field of view were held constant.
RESULTS: With each round of sterilization, the error of coated lenses was lower than the unprotected lenses, and the error showed a slightly increasing trend (Fig. 2). The lenses appeared fainter in the tracking software the lenses appeared fainter while all lenses remained trackable and visible despite the significant removal of reflective coating.
When reflective coating was fully rubbed off the lenses, the tracking software could still localize the markers; however, the lenses did appear much fainter in the tracking software. We observed that the reflective coating rubs off the lens in routine handling, and recoating with Zink-Alu spray can partially restore marker visibility. Using protective nail polish coating prevented the reflective coating from rubbing off altogether.
CONCLUSIONS: This exploratory study represents a promising step toward achieving low-cost sterilization of retroreflective infrared markers. Studies with the NousNav system need to be undertaken to measure the extent of degradation in tracking accuracy is tolerable as a side effect of marker sterilization. Before using coated Radix lenses on human subjects, it must be verified that the protective coating (common nail polish in our study) is fully biocompatible and remains undamaged by the cold sterilization agent (Sekusept™ Aktiv in our study.)
REFERENCES: [1] NousNav: A low-cost neuronavigation system for deployment in lower-resource settings, International Journal of Computer Assisted Radiology and Surgery, 2022 Sep;17(9):1745-1750. [2] NDI Radix™ Lens (https://www.ndigital.com/optical-measurement-technology/radix-lens/)
METHODS: We propose to modify NDI Radix™ Lens [1], single-use retroreflective spherical marker manufactured by Northern Digital, Waterloo, Canada. Radix lenses are uniquely promising candidates for liquid sterilization given their smooth, spherical surface. This quality also makes them easier to clean perioperatively compared to other retroreflective infrared marker designs. Initial experiments show that liquid sterilization agents degrade the marker’s retroreflective gold coating (Fig. 1). Hence the objective of this project is to develop a method to protect the Radix Lenses with a layer of coating material that does not allow the sanitizing agent to degrade the coating to enable the lens to survive multiple sanitation cycles while retaining sufficient tracking accuracy. We employed two cold liquid sterilisation agents, household bleach which is a common ingredient of liquid sterilisation solutions and Sekusept™ Aktiv (Ecolab, Saint Paul, MN, USA), which is widely known for sterilizing laparoscopy instruments. Store-bought nail polish and Zink-Alu Spray were used to coat the lenses. Data were obtained by recording five tests each with five rounds of sterilization, each tested with six trials, for a total of 150 recordings. The five tests were as follows: 1) Radix lens coated with nail polish and bleached, 2) uncoated and bleached, 3) coated with nail polish and sanitised, 4) uncoated and sanitised, and 5) coated with Zink-Alu Spray and sanitised. To assess the impact of the sterilization on the lens’s fiducial localization error, two metal marker frames equipped with four sockets designed for the Radix lenses were used. The reference marker frame was secured to a flat table while the other marker frame moved along a fixed path on the table. The position and orientation of the marker clusters were streamed into 3D Slicer using the Public Library for Ultrasound Toolkit (PLUS). A plane was then fit to the recorded marker poses in 3D Slicer using Iterative Closest Point and the marker registration error was computed. Distance from the camera, angle of view, and distance from the edges of the field of view were held constant.
RESULTS: With each round of sterilization, the error of coated lenses was lower than the unprotected lenses, and the error showed a slightly increasing trend (Fig. 2). The lenses appeared fainter in the tracking software the lenses appeared fainter while all lenses remained trackable and visible despite the significant removal of reflective coating.
When reflective coating was fully rubbed off the lenses, the tracking software could still localize the markers; however, the lenses did appear much fainter in the tracking software. We observed that the reflective coating rubs off the lens in routine handling, and recoating with Zink-Alu spray can partially restore marker visibility. Using protective nail polish coating prevented the reflective coating from rubbing off altogether.
CONCLUSIONS: This exploratory study represents a promising step toward achieving low-cost sterilization of retroreflective infrared markers. Studies with the NousNav system need to be undertaken to measure the extent of degradation in tracking accuracy is tolerable as a side effect of marker sterilization. Before using coated Radix lenses on human subjects, it must be verified that the protective coating (common nail polish in our study) is fully biocompatible and remains undamaged by the cold sterilization agent (Sekusept™ Aktiv in our study.)
REFERENCES: [1] NousNav: A low-cost neuronavigation system for deployment in lower-resource settings, International Journal of Computer Assisted Radiology and Surgery, 2022 Sep;17(9):1745-1750. [2] NDI Radix™ Lens (https://www.ndigital.com/optical-measurement-technology/radix-lens/)
Yeung, Chris; Ungi, Tamas; Hu, Zoe; Jamzad, Amoon; Kaufmann, Martin; Walker, Ross; Merchant, Shaila; Engel, Cecil Jay; Jabs, Doris; Rudan, John; Mousavi, Parvin; Fichtinger, Gabor
From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery Journal Article
In: International Journal of Computer Assisted Radiology and Surgery, pp. 1-9, 2024.
@article{yeung2024,
title = {From quantitative metrics to clinical success: assessing the utility of deep learning for tumor segmentation in breast surgery},
author = {Chris Yeung and Tamas Ungi and Zoe Hu and Amoon Jamzad and Martin Kaufmann and Ross Walker and Shaila Merchant and Cecil Jay Engel and Doris Jabs and John Rudan and Parvin Mousavi and Gabor Fichtinger},
url = {https://link.springer.com/article/10.1007/s11548-024-03133-y},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {International Journal of Computer Assisted Radiology and Surgery},
pages = {1-9},
publisher = {Springer International Publishing},
abstract = {Purpose
Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real time. However, evaluation of such models with respect to pathology outcomes is necessary for their successful translation into clinical practice.
Methods
Sixteen deep learning models based on established architectures in the literature are trained on 7318 ultrasound images from 33 patients. Models are ranked by an expert based on their contours generated from images in our test set. Generated contours from each model are also analyzed using recorded cautery trajectories of five navigated BCS cases to predict margin status. Predicted margins are compared with pathology reports.
Results
The best-performing model using both quantitative evaluation and our visual …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real time. However, evaluation of such models with respect to pathology outcomes is necessary for their successful translation into clinical practice.
Methods
Sixteen deep learning models based on established architectures in the literature are trained on 7318 ultrasound images from 33 patients. Models are ranked by an expert based on their contours generated from images in our test set. Generated contours from each model are also analyzed using recorded cautery trajectories of five navigated BCS cases to predict margin status. Predicted margins are compared with pathology reports.
Results
The best-performing model using both quantitative evaluation and our visual …
Preventing positive margins is essential for ensuring favorable patient outcomes following breast-conserving surgery (BCS). Deep learning has the potential to enable this by automatically contouring the tumor and guiding resection in real time. However, evaluation of such models with respect to pathology outcomes is necessary for their successful translation into clinical practice.
Methods
Sixteen deep learning models based on established architectures in the literature are trained on 7318 ultrasound images from 33 patients. Models are ranked by an expert based on their contours generated from images in our test set. Generated contours from each model are also analyzed using recorded cautery trajectories of five navigated BCS cases to predict margin status. Predicted margins are compared with pathology reports.
Results
The best-performing model using both quantitative evaluation and our visual …
d'Albenzio, Gabriella; Hisey, Rebecca; Srikanthan, Dilakshan; Ungi, Tamas; Lasso, Andras; Aghayan, Davit; Fichtinger, Gabor; Palomar, Rafael
Using NURBS for virtual resections in liver surgery planning: a comparative usability study Journal Article
In: vol. 12927, pp. 235-241, 2024.
@article{fichtinger2024f,
title = {Using NURBS for virtual resections in liver surgery planning: a comparative usability study},
author = {Gabriella d'Albenzio and Rebecca Hisey and Dilakshan Srikanthan and Tamas Ungi and Andras Lasso and Davit Aghayan and Gabor Fichtinger and Rafael Palomar},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12927/129270Z/Using-NURBS-for-virtual-resections-in-liver-surgery-planning/10.1117/12.3006486.short},
year = {2024},
date = {2024-01-01},
volume = {12927},
pages = {235-241},
publisher = {SPIE},
abstract = {PURPOSE
Accurate preoperative planning is crucial for liver resection surgery due to the complex anatomical structures and variations among patients. The need of virtual resections utilizing deformable surfaces presents a promising approach for effective liver surgery planning. However, the range of available surface definitions poses the question of which definition is most appropriate.
METHODS
The study compares the use of NURBS and B´ezier surfaces for the definition of virtual resections through a usability study, where 25 participants (19 biomedical researchers and 6 liver surgeons) completed tasks using varying numbers of control points driving surface deformations and different surface types. Specifically, participants aim to perform virtual liver resections using 16 and 9 control points for NURBS and B´ezier surfaces. The goal is to assess whether they can attain an optimal resection plan, effectively …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
PURPOSE
Accurate preoperative planning is crucial for liver resection surgery due to the complex anatomical structures and variations among patients. The need of virtual resections utilizing deformable surfaces presents a promising approach for effective liver surgery planning. However, the range of available surface definitions poses the question of which definition is most appropriate.
METHODS
The study compares the use of NURBS and B´ezier surfaces for the definition of virtual resections through a usability study, where 25 participants (19 biomedical researchers and 6 liver surgeons) completed tasks using varying numbers of control points driving surface deformations and different surface types. Specifically, participants aim to perform virtual liver resections using 16 and 9 control points for NURBS and B´ezier surfaces. The goal is to assess whether they can attain an optimal resection plan, effectively …
Accurate preoperative planning is crucial for liver resection surgery due to the complex anatomical structures and variations among patients. The need of virtual resections utilizing deformable surfaces presents a promising approach for effective liver surgery planning. However, the range of available surface definitions poses the question of which definition is most appropriate.
METHODS
The study compares the use of NURBS and B´ezier surfaces for the definition of virtual resections through a usability study, where 25 participants (19 biomedical researchers and 6 liver surgeons) completed tasks using varying numbers of control points driving surface deformations and different surface types. Specifically, participants aim to perform virtual liver resections using 16 and 9 control points for NURBS and B´ezier surfaces. The goal is to assess whether they can attain an optimal resection plan, effectively …
Connolly, Laura; Fooladgar, Fahimeh; Jamzad, Amoon; Kaufmann, Martin; Syeda, Ayesha; Ren, Kevin; Abolmaesumi, Purang; Rudan, John F; McKay, Doug; Fichtinger, Gabor; Mousavi, Parvin
ImSpect: Image-driven self-supervised learning for surgical margin evaluation with mass spectrometry Journal Article
In: International Journal of Computer Assisted Radiology and Surgery, pp. 1-8, 2024.
@article{fichtinger2024e,
title = {ImSpect: Image-driven self-supervised learning for surgical margin evaluation with mass spectrometry},
author = {Laura Connolly and Fahimeh Fooladgar and Amoon Jamzad and Martin Kaufmann and Ayesha Syeda and Kevin Ren and Purang Abolmaesumi and John F Rudan and Doug McKay and Gabor Fichtinger and Parvin Mousavi},
url = {https://link.springer.com/article/10.1007/s11548-024-03106-1},
year = {2024},
date = {2024-01-01},
journal = {International Journal of Computer Assisted Radiology and Surgery},
pages = {1-8},
publisher = {Springer International Publishing},
abstract = {Purpose
Real-time assessment of surgical margins is critical for favorable outcomes in cancer patients. The iKnife is a mass spectrometry device that has demonstrated potential for margin detection in cancer surgery. Previous studies have shown that using deep learning on iKnife data can facilitate real-time tissue characterization. However, none of the existing literature on the iKnife facilitate the use of publicly available, state-of-the-art pretrained networks or datasets that have been used in computer vision and other domains.
Methods
In a new framework we call ImSpect, we convert 1D iKnife data, captured during basal cell carcinoma (BCC) surgery, into 2D images in order to capitalize on state-of-the-art image classification networks. We also use self-supervision to leverage large amounts of unlabeled, intraoperative data to accommodate the data requirements of these networks.
Results
Through extensive ablation …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
Real-time assessment of surgical margins is critical for favorable outcomes in cancer patients. The iKnife is a mass spectrometry device that has demonstrated potential for margin detection in cancer surgery. Previous studies have shown that using deep learning on iKnife data can facilitate real-time tissue characterization. However, none of the existing literature on the iKnife facilitate the use of publicly available, state-of-the-art pretrained networks or datasets that have been used in computer vision and other domains.
Methods
In a new framework we call ImSpect, we convert 1D iKnife data, captured during basal cell carcinoma (BCC) surgery, into 2D images in order to capitalize on state-of-the-art image classification networks. We also use self-supervision to leverage large amounts of unlabeled, intraoperative data to accommodate the data requirements of these networks.
Results
Through extensive ablation …
Real-time assessment of surgical margins is critical for favorable outcomes in cancer patients. The iKnife is a mass spectrometry device that has demonstrated potential for margin detection in cancer surgery. Previous studies have shown that using deep learning on iKnife data can facilitate real-time tissue characterization. However, none of the existing literature on the iKnife facilitate the use of publicly available, state-of-the-art pretrained networks or datasets that have been used in computer vision and other domains.
Methods
In a new framework we call ImSpect, we convert 1D iKnife data, captured during basal cell carcinoma (BCC) surgery, into 2D images in order to capitalize on state-of-the-art image classification networks. We also use self-supervision to leverage large amounts of unlabeled, intraoperative data to accommodate the data requirements of these networks.
Results
Through extensive ablation …
Kaufmann, Martin; Jamzad, Amoon; Ungi, Tamas; Rodgers, Jessica R; Koster, Teaghan; Yeung, Chris; Ehrlich, Josh; Santilli, Alice; Asselin, Mark; Janssen, Natasja; McMullen, Julie; Solberg, Kathryn; Cheesman, Joanna; Carlo, Alessia Di; Ren, Kevin Yi Mi; Varma, Sonal; Merchant, Shaila; Engel, Cecil Jay; Walker, G Ross; Gallo, Andrea; Jabs, Doris; Mousavi, Parvin; Fichtinger, Gabor; Rudan, John F
Abstract PO2-23-07: Three-dimensional navigated mass spectrometry for intraoperative margin assessment during breast cancer surgery Journal Article
In: Cancer Research, vol. 84, iss. 9_Supplement, pp. PO2-23-07-PO2-23-07, 2024.
@article{fichtinger2024c,
title = {Abstract PO2-23-07: Three-dimensional navigated mass spectrometry for intraoperative margin assessment during breast cancer surgery},
author = {Martin Kaufmann and Amoon Jamzad and Tamas Ungi and Jessica R Rodgers and Teaghan Koster and Chris Yeung and Josh Ehrlich and Alice Santilli and Mark Asselin and Natasja Janssen and Julie McMullen and Kathryn Solberg and Joanna Cheesman and Alessia Di Carlo and Kevin Yi Mi Ren and Sonal Varma and Shaila Merchant and Cecil Jay Engel and G Ross Walker and Andrea Gallo and Doris Jabs and Parvin Mousavi and Gabor Fichtinger and John F Rudan},
url = {https://aacrjournals.org/cancerres/article/84/9_Supplement/PO2-23-07/743683},
year = {2024},
date = {2024-01-01},
journal = {Cancer Research},
volume = {84},
issue = {9_Supplement},
pages = {PO2-23-07-PO2-23-07},
publisher = {The American Association for Cancer Research},
abstract = {Positive resection margins occur in approximately 25% of breast cancer (BCa) surgeries, requiring re-operation. Margin status is not routinely available during surgery; thus, technologies that identify residual cancer on the specimen or cavity are needed to provide intraoperative decision support that may reduce positive margin rates. Rapid evaporative ionization mass spectrometry (REIMS) is an emerging technique that chemically profiles the plume generated by tissue cauterization to classify the ablated tissue as either cancerous or non-cancerous, on the basis of detected lipid species. Although REIMS can distinguish cancer and non-cancerous breast tissue by the signals generated, it does not indicate the location of the classified tissue in real-time. Our objective was to combine REIMS with spatio-temporal navigation (navigated REIMS), and to compare performance of navigated REIMS with conventional …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Positive resection margins occur in approximately 25% of breast cancer (BCa) surgeries, requiring re-operation. Margin status is not routinely available during surgery; thus, technologies that identify residual cancer on the specimen or cavity are needed to provide intraoperative decision support that may reduce positive margin rates. Rapid evaporative ionization mass spectrometry (REIMS) is an emerging technique that chemically profiles the plume generated by tissue cauterization to classify the ablated tissue as either cancerous or non-cancerous, on the basis of detected lipid species. Although REIMS can distinguish cancer and non-cancerous breast tissue by the signals generated, it does not indicate the location of the classified tissue in real-time. Our objective was to combine REIMS with spatio-temporal navigation (navigated REIMS), and to compare performance of navigated REIMS with conventional …
Hintz, Lucas; Nanziri, Sarah C; Dance, Sarah; Jawed, Kochai; Oetgen, Matthew; Ungi, Tamas; Fichtinger, Gabor; Schlenger, Christopher; Cleary, Kevin
3D volume reconstruction for pediatric scoliosis evaluation using motion-tracked ultrasound Journal Article
In: vol. 12928, pp. 223-227, 2024.
@article{fichtinger2024g,
title = {3D volume reconstruction for pediatric scoliosis evaluation using motion-tracked ultrasound},
author = {Lucas Hintz and Sarah C Nanziri and Sarah Dance and Kochai Jawed and Matthew Oetgen and Tamas Ungi and Gabor Fichtinger and Christopher Schlenger and Kevin Cleary},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12928/1292811/3D-volume-reconstruction-for-pediatric-scoliosis-evaluation-using-motion-tracked/10.1117/12.3008629.short},
year = {2024},
date = {2024-01-01},
volume = {12928},
pages = {223-227},
publisher = {SPIE},
abstract = {We have evaluated AI-segmented 3D spine ultrasound for scoliosis measurement in a feasibility study of pediatric patients enrolled over two months in the orthopedic clinic at Children’s National Hospital. Patients who presented to clinic for scoliosis evaluation were invited to participate and their spines were scanned using the method. Our system consists of three Optitrack cameras which track a Clarius wireless ultrasound probe and infrared marked waistbelt. Proprietary SpineUs software uses neural networks to build a volumetric reproduction of the spine in real-time using a laptop computer. We can approximate the maximal lateral curvature using the transverse process angle of the virtual reconstruction; these angles were compared to those from the radiographic exams for each patient from the same visit. Scans and radiographs from five patients were examined and demonstrate a linear correlation between …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We have evaluated AI-segmented 3D spine ultrasound for scoliosis measurement in a feasibility study of pediatric patients enrolled over two months in the orthopedic clinic at Children’s National Hospital. Patients who presented to clinic for scoliosis evaluation were invited to participate and their spines were scanned using the method. Our system consists of three Optitrack cameras which track a Clarius wireless ultrasound probe and infrared marked waistbelt. Proprietary SpineUs software uses neural networks to build a volumetric reproduction of the spine in real-time using a laptop computer. We can approximate the maximal lateral curvature using the transverse process angle of the virtual reconstruction; these angles were compared to those from the radiographic exams for each patient from the same visit. Scans and radiographs from five patients were examined and demonstrate a linear correlation between …
Kaufmann, Martin; Jamzad, Amoon; Ungi, Tamas; Rodgers, Jessica; Koster, Teaghan; Chris, Yeung; Janssen, Natasja; McMullen, Julie; Solberg, Kathryn; Cheesman, Joanna; Ren, Kevin Ti Mi; Varma, Sonal; Merchant, Shaila; Engel, Cecil Jay; Walker, G Ross; Gallo, Andrea; Jabs, Doris; Mousavi, Parvin; Fichtinger, Gabor; Rudan, John
Three-dimensional navigated mass spectrometry for intraoperative margin assessment during breast cancer surgery Journal Article
In: vol. 31, iss. 1, pp. S10-S10, 2024.
@article{fichtinger2024i,
title = {Three-dimensional navigated mass spectrometry for intraoperative margin assessment during breast cancer surgery},
author = {Martin Kaufmann and Amoon Jamzad and Tamas Ungi and Jessica Rodgers and Teaghan Koster and Yeung Chris and Natasja Janssen and Julie McMullen and Kathryn Solberg and Joanna Cheesman and Kevin Ti Mi Ren and Sonal Varma and Shaila Merchant and Cecil Jay Engel and G Ross Walker and Andrea Gallo and Doris Jabs and Parvin Mousavi and Gabor Fichtinger and John Rudan},
url = {https://scholar.google.com/scholar?cluster=16985799098796735653&hl=en&oi=scholarr},
year = {2024},
date = {2024-01-01},
volume = {31},
issue = {1},
pages = {S10-S10},
publisher = {SPRINGER},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Barr, Colton; Groves, Leah; Ungi, Tamas; Siemens, D Robert; Diao, Babacar; Kikinis, Ron; Mousavi, Parvin; Fichtinger, Gabor
Extracting 3D Prostate Geometry from 2D Optically-Tracked Transrectal Ultrasound Images Journal Article
In: pp. 32-37, 2024.
@article{barr2024,
title = {Extracting 3D Prostate Geometry from 2D Optically-Tracked Transrectal Ultrasound Images},
author = {Colton Barr and Leah Groves and Tamas Ungi and D Robert Siemens and Babacar Diao and Ron Kikinis and Parvin Mousavi and Gabor Fichtinger},
year = {2024},
date = {2024-01-01},
pages = {32-37},
publisher = {IEEE},
abstract = {The technical challenges of traditional transrectal ultrasound-guided prostate biopsy, combined with the limited availability of more advanced prostate imaging techniques, have exacerbated existing differences in prostate cancer outcomes between high-resource and low-resource healthcare settings. The objective of this paper is to improve the tools available to clinicians in low-resource settings by working towards an inexpensive ultrasound-guided prostate biopsy navigation system. The principal contributions detailed here are the design, implementation, and testing of a system capable of generating a 3D model of the prostate from spatially-tracked 2D ultrasound images. The system uses open-source software, low-cost materials, and deep learning to segment and localize cross-sections of the prostate in order to produce a patient-specific 3D prostate model. A user study was performed to evaluate the …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The technical challenges of traditional transrectal ultrasound-guided prostate biopsy, combined with the limited availability of more advanced prostate imaging techniques, have exacerbated existing differences in prostate cancer outcomes between high-resource and low-resource healthcare settings. The objective of this paper is to improve the tools available to clinicians in low-resource settings by working towards an inexpensive ultrasound-guided prostate biopsy navigation system. The principal contributions detailed here are the design, implementation, and testing of a system capable of generating a 3D model of the prostate from spatially-tracked 2D ultrasound images. The system uses open-source software, low-cost materials, and deep learning to segment and localize cross-sections of the prostate in order to produce a patient-specific 3D prostate model. A user study was performed to evaluate the …
Yang, Jianming; Hisey, Rebecca; Bierbrier, Joshua; Law, Christine; Fichtinger, Gabor; Holden, Matthew
Frame Selection Methods to Streamline Surgical Video Annotation for Tool Detection Tasks Journal Article
In: pp. 892-898, 2024.
@article{yang2024,
title = {Frame Selection Methods to Streamline Surgical Video Annotation for Tool Detection Tasks},
author = {Jianming Yang and Rebecca Hisey and Joshua Bierbrier and Christine Law and Gabor Fichtinger and Matthew Holden},
year = {2024},
date = {2024-01-01},
pages = {892-898},
publisher = {IEEE},
abstract = {Given the growing volume of surgical data and the increasing demand for annotation, there is a pressing need to streamline the annotation process for surgical videos. Previously, annotation tools for object detection tasks have greatly evolved, reducing time expense and enhancing ease. There are also many initial frame selection approaches for Artificial Intelligence (AI) assisted annotation tasks to further reduce human effort. However, these methods have rarely been implemented and reported in the context of surgical datasets, especially in cataract surgery datasets. The identification of initial frames to annotate before the use of any tools or algorithms determines annotation efficiency. Therefore, in this paper, we chose to prioritize the development of a method for selecting initial frames to facilitate the subsequent automated annotation process. We propose a customized initial frames selection method based on …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Given the growing volume of surgical data and the increasing demand for annotation, there is a pressing need to streamline the annotation process for surgical videos. Previously, annotation tools for object detection tasks have greatly evolved, reducing time expense and enhancing ease. There are also many initial frame selection approaches for Artificial Intelligence (AI) assisted annotation tasks to further reduce human effort. However, these methods have rarely been implemented and reported in the context of surgical datasets, especially in cataract surgery datasets. The identification of initial frames to annotate before the use of any tools or algorithms determines annotation efficiency. Therefore, in this paper, we chose to prioritize the development of a method for selecting initial frames to facilitate the subsequent automated annotation process. We propose a customized initial frames selection method based on …
Hashtrudi-Zaad, Kian; Ungi, Tamas; Yeung, Chris; Baum, Zachary; Cernelev, Pavel-Dumitru; Hage, Anthony N; Schlenger, Christopher; Fichtinger, Gabor
Expert-guided optimization of ultrasound segmentation models for 3D spine imaging Journal Article
In: pp. 680-685, 2024.
@article{hashtrudi-zaad2024,
title = {Expert-guided optimization of ultrasound segmentation models for 3D spine imaging},
author = {Kian Hashtrudi-Zaad and Tamas Ungi and Chris Yeung and Zachary Baum and Pavel-Dumitru Cernelev and Anthony N Hage and Christopher Schlenger and Gabor Fichtinger},
year = {2024},
date = {2024-01-01},
pages = {680-685},
publisher = {IEEE},
abstract = {We explored ultrasound for imaging bones, specifically the spine, as a safer and more accessible alternative to conventional X-ray. We aimed to improve how well deep learning segmentation models filter bone signals from ultrasound frames with the goal of using these segmented images for reconstructing the 3-dimensional spine volume.Our dataset consisted of spatially tracked ultrasound scans from 25 patients. Image frames from these scans were also manually annotated to provide training data for image segmentation deep learning. To find the optimal automatic segmentation method, we assessed five different artificial neural network models and their variations by hyperparameter tuning. Our main contribution is a new approach for model selection, employing an Elo rating system to efficiently rank trained models based on their visual performance as assessed by clinical users. This method addresses the …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
We explored ultrasound for imaging bones, specifically the spine, as a safer and more accessible alternative to conventional X-ray. We aimed to improve how well deep learning segmentation models filter bone signals from ultrasound frames with the goal of using these segmented images for reconstructing the 3-dimensional spine volume.Our dataset consisted of spatially tracked ultrasound scans from 25 patients. Image frames from these scans were also manually annotated to provide training data for image segmentation deep learning. To find the optimal automatic segmentation method, we assessed five different artificial neural network models and their variations by hyperparameter tuning. Our main contribution is a new approach for model selection, employing an Elo rating system to efficiently rank trained models based on their visual performance as assessed by clinical users. This method addresses the …
Amin, Silvani; Dewey, Hannah; Lasso, Andras; Sabin, Patricia; Han, Ye; Vicory, Jared; Paniagua, Beatriz; Herz, Christian; Nam, Hannah; Cianciulli, Alana; Flynn, Maura; Laurence, Devin W; Harrild, David; Fichtinger, Gabor; Cohen, Meryl S; Jolley, Matthew A
Euclidean and shape-based analysis of the dynamic mitral annulus in children using a novel open-source framework Journal Article
In: Journal of the American Society of Echocardiography, vol. 37, iss. 2, pp. 259-267, 2024.
@article{fichtinger2024b,
title = {Euclidean and shape-based analysis of the dynamic mitral annulus in children using a novel open-source framework},
author = {Silvani Amin and Hannah Dewey and Andras Lasso and Patricia Sabin and Ye Han and Jared Vicory and Beatriz Paniagua and Christian Herz and Hannah Nam and Alana Cianciulli and Maura Flynn and Devin W Laurence and David Harrild and Gabor Fichtinger and Meryl S Cohen and Matthew A Jolley},
url = {https://www.sciencedirect.com/science/article/pii/S0894731723005941},
year = {2024},
date = {2024-01-01},
journal = {Journal of the American Society of Echocardiography},
volume = {37},
issue = {2},
pages = {259-267},
publisher = {Mosby},
abstract = {Background
The dynamic shape of the normal adult mitral annulus has been shown to be important to mitral valve function. However, annular dynamics of the healthy mitral valve in children have yet to be explored. The aim of this study was to model and quantify the shape and major modes of variation of pediatric mitral valve annuli in four phases of the cardiac cycle using transthoracic echocardiography.
Methods
The mitral valve annuli of 100 children and young adults with normal findings on three-dimensional echocardiography were modeled in four different cardiac phases using the SlicerHeart extension for 3D Slicer. Annular metrics were quantified using SlicerHeart, and optimal normalization to body surface area was explored. Mean annular shapes and the principal components of variation were computed using custom code implemented in a new SlicerHeart module (Annulus Shape Analyzer). Shape was …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background
The dynamic shape of the normal adult mitral annulus has been shown to be important to mitral valve function. However, annular dynamics of the healthy mitral valve in children have yet to be explored. The aim of this study was to model and quantify the shape and major modes of variation of pediatric mitral valve annuli in four phases of the cardiac cycle using transthoracic echocardiography.
Methods
The mitral valve annuli of 100 children and young adults with normal findings on three-dimensional echocardiography were modeled in four different cardiac phases using the SlicerHeart extension for 3D Slicer. Annular metrics were quantified using SlicerHeart, and optimal normalization to body surface area was explored. Mean annular shapes and the principal components of variation were computed using custom code implemented in a new SlicerHeart module (Annulus Shape Analyzer). Shape was …
The dynamic shape of the normal adult mitral annulus has been shown to be important to mitral valve function. However, annular dynamics of the healthy mitral valve in children have yet to be explored. The aim of this study was to model and quantify the shape and major modes of variation of pediatric mitral valve annuli in four phases of the cardiac cycle using transthoracic echocardiography.
Methods
The mitral valve annuli of 100 children and young adults with normal findings on three-dimensional echocardiography were modeled in four different cardiac phases using the SlicerHeart extension for 3D Slicer. Annular metrics were quantified using SlicerHeart, and optimal normalization to body surface area was explored. Mean annular shapes and the principal components of variation were computed using custom code implemented in a new SlicerHeart module (Annulus Shape Analyzer). Shape was …
Kaufmann, Martin; Vaysse, Pierre-Maxence; Savage, Adele; Kooreman, Loes FS; Janssen, Natasja; Varma, Sonal; Ren, Kevin Yi Mi; Merchant, Shaila; Engel, Cecil Jay; Damink, Steven WM Olde; Smidt, Marjolein L; Shousha, Sami; Chauhan, Hemali; Karali, Evdoxia; Kazanc, Emine; Poulogiannis, George; Fichtinger, Gabor; Tauber, Boglárka; Leff, Daniel R; Pringle, Steven D; Rudan, John F; Heeren, Ron MA; Siegel, Tiffany Porta; Takáts, Zoltán; Balog, Júlia
Testing of rapid evaporative mass spectrometry for histological tissue classification and molecular diagnostics in a multi-site study Journal Article
In: British Journal of Cancer, pp. 1-11, 2024.
@article{kaufmann2024,
title = {Testing of rapid evaporative mass spectrometry for histological tissue classification and molecular diagnostics in a multi-site study},
author = {Martin Kaufmann and Pierre-Maxence Vaysse and Adele Savage and Loes FS Kooreman and Natasja Janssen and Sonal Varma and Kevin Yi Mi Ren and Shaila Merchant and Cecil Jay Engel and Steven WM Olde Damink and Marjolein L Smidt and Sami Shousha and Hemali Chauhan and Evdoxia Karali and Emine Kazanc and George Poulogiannis and Gabor Fichtinger and Boglárka Tauber and Daniel R Leff and Steven D Pringle and John F Rudan and Ron MA Heeren and Tiffany Porta Siegel and Zoltán Takáts and Júlia Balog},
year = {2024},
date = {2024-01-01},
journal = {British Journal of Cancer},
pages = {1-11},
publisher = {Nature Publishing Group UK},
abstract = {Background
While REIMS technology has successfully been demonstrated for the histological identification of ex-vivo breast tumor tissues, questions regarding the robustness of the approach and the possibility of tumor molecular diagnostics still remain unanswered. In the current study, we set out to determine whether it is possible to acquire cross-comparable REIMS datasets at multiple sites for the identification of breast tumors and subtypes.
Methods
A consortium of four sites with three of them having access to fresh surgical tissue samples performed tissue analysis using identical REIMS setups and protocols. Overall, 21 breast cancer specimens containing pathology-validated tumor and adipose tissues were analyzed and results were compared using uni- and multivariate statistics on normal, WT and PIK3CA mutant ductal carcinomas.
Results
Statistical analysis of data from standards showed significant …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background
While REIMS technology has successfully been demonstrated for the histological identification of ex-vivo breast tumor tissues, questions regarding the robustness of the approach and the possibility of tumor molecular diagnostics still remain unanswered. In the current study, we set out to determine whether it is possible to acquire cross-comparable REIMS datasets at multiple sites for the identification of breast tumors and subtypes.
Methods
A consortium of four sites with three of them having access to fresh surgical tissue samples performed tissue analysis using identical REIMS setups and protocols. Overall, 21 breast cancer specimens containing pathology-validated tumor and adipose tissues were analyzed and results were compared using uni- and multivariate statistics on normal, WT and PIK3CA mutant ductal carcinomas.
Results
Statistical analysis of data from standards showed significant …
While REIMS technology has successfully been demonstrated for the histological identification of ex-vivo breast tumor tissues, questions regarding the robustness of the approach and the possibility of tumor molecular diagnostics still remain unanswered. In the current study, we set out to determine whether it is possible to acquire cross-comparable REIMS datasets at multiple sites for the identification of breast tumors and subtypes.
Methods
A consortium of four sites with three of them having access to fresh surgical tissue samples performed tissue analysis using identical REIMS setups and protocols. Overall, 21 breast cancer specimens containing pathology-validated tumor and adipose tissues were analyzed and results were compared using uni- and multivariate statistics on normal, WT and PIK3CA mutant ductal carcinomas.
Results
Statistical analysis of data from standards showed significant …
Simpson, Amber L; Peoples, Jacob; Creasy, John M; Fichtinger, Gabor; Gangai, Natalie; Keshavamurthy, Krishna N; Lasso, Andras; Shia, Jinru; D’Angelica, Michael I; Do, Richard KG
Preoperative CT and survival data for patients undergoing resection of colorectal liver metastases Journal Article
In: Scientific Data, vol. 11, iss. 1, pp. 172, 2024.
@article{fichtinger2024,
title = {Preoperative CT and survival data for patients undergoing resection of colorectal liver metastases},
author = {Amber L Simpson and Jacob Peoples and John M Creasy and Gabor Fichtinger and Natalie Gangai and Krishna N Keshavamurthy and Andras Lasso and Jinru Shia and Michael I D’Angelica and Richard KG Do},
url = {https://www.nature.com/articles/s41597-024-02981-2},
year = {2024},
date = {2024-01-01},
journal = {Scientific Data},
volume = {11},
issue = {1},
pages = {172},
publisher = {Nature Publishing Group UK},
abstract = {The liver is a common site for the development of metastases in colorectal cancer. Treatment selection for patients with colorectal liver metastases (CRLM) is difficult; although hepatic resection will cure a minority of CRLM patients, recurrence is common. Reliable preoperative prediction of recurrence could therefore be a valuable tool for physicians in selecting the best candidates for hepatic resection in the treatment of CRLM. It has been hypothesized that evidence for recurrence could be found via quantitative image analysis on preoperative CT imaging of the future liver remnant before resection. To investigate this hypothesis, we have collected preoperative hepatic CT scans, clinicopathologic data, and recurrence/survival data, from a large, single-institution series of patients (n = 197) who underwent hepatic resection of CRLM. For each patient, we also created segmentations of the liver, vessels, tumors, and …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The liver is a common site for the development of metastases in colorectal cancer. Treatment selection for patients with colorectal liver metastases (CRLM) is difficult; although hepatic resection will cure a minority of CRLM patients, recurrence is common. Reliable preoperative prediction of recurrence could therefore be a valuable tool for physicians in selecting the best candidates for hepatic resection in the treatment of CRLM. It has been hypothesized that evidence for recurrence could be found via quantitative image analysis on preoperative CT imaging of the future liver remnant before resection. To investigate this hypothesis, we have collected preoperative hepatic CT scans, clinicopathologic data, and recurrence/survival data, from a large, single-institution series of patients (n = 197) who underwent hepatic resection of CRLM. For each patient, we also created segmentations of the liver, vessels, tumors, and …
Hisey, Rebecca; Ndiaye, Fatou Bintou; Sunderland, Kyle; Seck, Idrissa; Mbaye, Moustapha; Keita, Mohammed; Diahame, Mamadou; Kikinis, Ron; Diao, Babacar; Fichtinger, Gabor; Camara, Mamadou
Feasibility of video‐based skill assessment for percutaneous nephrostomy training in Senegal Journal Article
In: Healthcare Technology Letters, 2024.
@article{hisey2024a,
title = {Feasibility of video‐based skill assessment for percutaneous nephrostomy training in Senegal},
author = {Rebecca Hisey and Fatou Bintou Ndiaye and Kyle Sunderland and Idrissa Seck and Moustapha Mbaye and Mohammed Keita and Mamadou Diahame and Ron Kikinis and Babacar Diao and Gabor Fichtinger and Mamadou Camara},
year = {2024},
date = {2024-01-01},
journal = {Healthcare Technology Letters},
abstract = {Percutaneous nephrostomy can be an effective means of preventing irreparable renal damage from obstructive renal disease thereby providing patients with more time to access treatment to remove the source of the blockage. In sub‐Saharan Africa, where there is limited access to treatments such as dialysis and transplantation, a nephrostomy can be life‐saving. Training this procedure in simulation can allow trainees to develop their technical skills without risking patient safety, but still requires an ex‐pert observer to provide performative feedback. In this study, the feasibility of using video as an accessible method to assess skill in simulated percutaneous nephrostomy is evaluated. Six novice urology residents and six expert urologists from Ouakam Military Hospital in Dakar, Senegal performed 4 nephrostomies each using the setup. Motion‐based metrics were computed for each trial from the predicted bounding …},
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pubstate = {published},
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}
Percutaneous nephrostomy can be an effective means of preventing irreparable renal damage from obstructive renal disease thereby providing patients with more time to access treatment to remove the source of the blockage. In sub‐Saharan Africa, where there is limited access to treatments such as dialysis and transplantation, a nephrostomy can be life‐saving. Training this procedure in simulation can allow trainees to develop their technical skills without risking patient safety, but still requires an ex‐pert observer to provide performative feedback. In this study, the feasibility of using video as an accessible method to assess skill in simulated percutaneous nephrostomy is evaluated. Six novice urology residents and six expert urologists from Ouakam Military Hospital in Dakar, Senegal performed 4 nephrostomies each using the setup. Motion‐based metrics were computed for each trial from the predicted bounding …
Hisey, Rebecca; Ndiaye, Fatou Bintou; Sunderland, Kyle; Seck, Idrissa; Mbaye, Moustapha; Keita, Mohamed; Diahame, Mamadou; Kikinis, Ron; Diao, Babacar; Fichtinger, Gabor; Camara, Mamadou
Feasibility of video-based skill assessment for percutaneous nephrostomy training in Senegal Journal Article
In: 2024.
@article{hisey2024,
title = {Feasibility of video-based skill assessment for percutaneous nephrostomy training in Senegal},
author = {Rebecca Hisey and Fatou Bintou Ndiaye and Kyle Sunderland and Idrissa Seck and Moustapha Mbaye and Mohamed Keita and Mamadou Diahame and Ron Kikinis and Babacar Diao and Gabor Fichtinger and Mamadou Camara},
year = {2024},
date = {2024-01-01},
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Connolly, Laura; Kumar, Aravind S; Mehta, Kapi Ketan; Al-Zogbi, Lidia; Kazanzides, Peter; Mousavi, Parvin; Fichtinger, Gabor; Krieger, Axel; Tokuda, Junichi; Taylor, Russell H; Leonard, Simon; Deguet, Anton
SlicerROS2: A Research and Development Module for Image-Guided Robotic Interventions Journal Article
In: IEEE Transactions on Medical Robotics and Bionics, 2024.
@article{connolly2024,
title = {SlicerROS2: A Research and Development Module for Image-Guided Robotic Interventions},
author = {Laura Connolly and Aravind S Kumar and Kapi Ketan Mehta and Lidia Al-Zogbi and Peter Kazanzides and Parvin Mousavi and Gabor Fichtinger and Axel Krieger and Junichi Tokuda and Russell H Taylor and Simon Leonard and Anton Deguet},
year = {2024},
date = {2024-01-01},
journal = {IEEE Transactions on Medical Robotics and Bionics},
publisher = {IEEE},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Radcliffe, Olivia; Connolly, Laura; Ungi, Tamas; Yeo, Caitlin; Rudan, John F.; Fichtinger, Gabor; Mousavi, Parvin
Navigated surgical resection cavity inspection for breast conserving surgery Proceedings
2023.
@proceedings{nokey,
title = {Navigated surgical resection cavity inspection for breast conserving surgery},
author = {Olivia Radcliffe and Laura Connolly and Tamas Ungi and Caitlin Yeo and John F. Rudan and Gabor Fichtinger and Parvin Mousavi},
doi = {https://doi.org/10.1117/12.2654015},
year = {2023},
date = {2023-04-03},
abstract = {Up to 40% of Breast Conserving Surgery (BCS) patients must undergo repeat surgery because cancer is left behind in the resection cavity. The mobility of the breast resection cavity makes it difficult to localize residual cancer and, therefore, cavity shaving is a common technique for cancer removal. Cavity shaving involves removing an additional layer of tissue from the entire resection cavity, often resulting in unnecessary healthy tissue loss. In this study, we demonstrated a navigation system and open-source software module that facilitates visualization of the breast resection cavity for targeted localization of residual cancer.},
keywords = {},
pubstate = {published},
tppubtype = {proceedings}
}
Up to 40% of Breast Conserving Surgery (BCS) patients must undergo repeat surgery because cancer is left behind in the resection cavity. The mobility of the breast resection cavity makes it difficult to localize residual cancer and, therefore, cavity shaving is a common technique for cancer removal. Cavity shaving involves removing an additional layer of tissue from the entire resection cavity, often resulting in unnecessary healthy tissue loss. In this study, we demonstrated a navigation system and open-source software module that facilitates visualization of the breast resection cavity for targeted localization of residual cancer.
Cernelev, Pavel-Dumitru; Moga, Kristof; Groves, Leah; Haidegger, Tamás; Fichtinger, Gabor; Ungi, Tamas
Determining boundaries of accurate tracking for electromagnetic sensors Conference
SPIE, 2023.
@conference{Cernelev2023,
title = {Determining boundaries of accurate tracking for electromagnetic sensors},
author = {Pavel-Dumitru Cernelev and Kristof Moga and Leah Groves and Tamás Haidegger and Gabor Fichtinger and Tamas Ungi},
editor = {Cristian A. Linte and Jeffrey H. Siewerdsen},
doi = {10.1117/12.2654428},
year = {2023},
date = {2023-04-03},
urldate = {2023-04-03},
publisher = {SPIE},
keywords = {},
pubstate = {published},
tppubtype = {conference}
}
Klosa, Elizabeth; Hisey, Rebecca; Hashtrudi-Zaad, Kian; Zevin, Boris; Ungi, Tamas; Fichtinger, Gabor
Comparing methods of identifying tissues for workflow recognition of simulated open hernia repair Conference
2023.
@conference{nokey,
title = {Comparing methods of identifying tissues for workflow recognition of simulated open hernia repair},
author = {Elizabeth Klosa and Rebecca Hisey and Kian Hashtrudi-Zaad and Boris Zevin and Tamas Ungi and Gabor Fichtinger},
url = {https://imno.ca/sites/default/files/ImNO2023Proceedings.pdf},
year = {2023},
date = {2023-03-24},
urldate = {2024-03-24},
keywords = {},
pubstate = {published},
tppubtype = {conference}
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Orosz, Gábor; Szabó, Róbert Zsolt; Ungi, Tamás; Barr, Colton; Yeung, Chris; Fichtinger, Gábor; Gál, János; Haidegger, Tamás
Lung Ultrasound Imaging and Image Processing with Artificial Intelligence Methods for Bedside Diagnostic Examinations Journal Article
In: Acta Polytechnica Hungarica, vol. 20, iss. 8, 2023.
@article{fichtinger2023d,
title = {Lung Ultrasound Imaging and Image Processing with Artificial Intelligence Methods for Bedside Diagnostic Examinations},
author = {Gábor Orosz and Róbert Zsolt Szabó and Tamás Ungi and Colton Barr and Chris Yeung and Gábor Fichtinger and János Gál and Tamás Haidegger},
url = {https://acta.uni-obuda.hu/Orosz_Szabo_Ungi_Barr_Yeung_Fichtinger_Gal_Haidegger_137.pdf},
year = {2023},
date = {2023-01-01},
journal = {Acta Polytechnica Hungarica},
volume = {20},
issue = {8},
abstract = {Artificial Intelligence-assisted radiology has shown to offer significant benefits in clinical care. Physicians often face challenges in identifying the underlying causes of acute respiratory failure. One method employed by experts is the utilization of bedside lung ultrasound, although it has a significant learning curve. In our study, we explore the potential of a Machine Learning-based automated decision-support system to assist inexperienced practitioners in interpreting lung ultrasound scans. This system incorporates medical ultrasound, advanced data processing techniques, and a neural network implementation to achieve its objective. The article provides a comprehensive overview of the steps involved in data preparation and the implementation of the neural network. The accuracy and error rate of the most effective model are presented, accompanied by illustrative examples of their predictions. Furthermore, the paper concludes with an evaluation of the results, identification of limitations, and recommendations for future enhancements.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Artificial Intelligence-assisted radiology has shown to offer significant benefits in clinical care. Physicians often face challenges in identifying the underlying causes of acute respiratory failure. One method employed by experts is the utilization of bedside lung ultrasound, although it has a significant learning curve. In our study, we explore the potential of a Machine Learning-based automated decision-support system to assist inexperienced practitioners in interpreting lung ultrasound scans. This system incorporates medical ultrasound, advanced data processing techniques, and a neural network implementation to achieve its objective. The article provides a comprehensive overview of the steps involved in data preparation and the implementation of the neural network. The accuracy and error rate of the most effective model are presented, accompanied by illustrative examples of their predictions. Furthermore, the paper concludes with an evaluation of the results, identification of limitations, and recommendations for future enhancements.
Tomalty, Diane; Giovannetti, Olivia; Velikonja, Leah; Munday, Jasica; Kaufmann, Martin; Iaboni, Natasha; Jamzad, Amoon; Rubino, Rachel; Fichtinger, Gabor; Mousavi, Parvin; Nicol, Christopher JB; Rudan, John F; Adams, Michael A
Molecular characterization of human peripheral nerves using desorption electrospray ionization mass spectrometry imaging Journal Article
In: Journal of Anatomy, vol. 243, iss. 5, pp. 758-769, 2023.
@article{fichtinger2023j,
title = {Molecular characterization of human peripheral nerves using desorption electrospray ionization mass spectrometry imaging},
author = {Diane Tomalty and Olivia Giovannetti and Leah Velikonja and Jasica Munday and Martin Kaufmann and Natasha Iaboni and Amoon Jamzad and Rachel Rubino and Gabor Fichtinger and Parvin Mousavi and Christopher JB Nicol and John F Rudan and Michael A Adams},
url = {https://onlinelibrary.wiley.com/doi/abs/10.1111/joa.13909},
year = {2023},
date = {2023-01-01},
journal = {Journal of Anatomy},
volume = {243},
issue = {5},
pages = {758-769},
abstract = {Desorption electrospray ionization mass spectrometry imaging (DESI‐MSI) is a molecular imaging method that can be used to elucidate the small‐molecule composition of tissues and map their spatial information using two‐dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI‐MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for …},
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Desorption electrospray ionization mass spectrometry imaging (DESI‐MSI) is a molecular imaging method that can be used to elucidate the small‐molecule composition of tissues and map their spatial information using two‐dimensional ion images. This technique has been used to investigate the molecular profiles of variety of tissues, including within the central nervous system, specifically the brain and spinal cord. To our knowledge, this technique has yet to be applied to tissues of the peripheral nervous system (PNS). Data generated from such analyses are expected to advance the characterization of these structures. The study aimed to: (i) establish whether DESI‐MSI can discriminate the molecular characteristics of peripheral nerves and distinguish them from surrounding tissues and (ii) assess whether different peripheral nerve subtypes are characterized by unique molecular profiles. Four different nerves for …
Ndiaye, Fatou Bintou; Groves, Leah; Hisey, Rebecca; Ungi, Tamas; Diop, Idy; Mousavi, Parvin; Fichtinger, Gabor; Camara, Mamadou Samba
Desing and realization of a computer-assisted nephrostomy guidance system Journal Article
In: pp. 1-6, 2023.
@article{fichtinger2023l,
title = {Desing and realization of a computer-assisted nephrostomy guidance system},
author = {Fatou Bintou Ndiaye and Leah Groves and Rebecca Hisey and Tamas Ungi and Idy Diop and Parvin Mousavi and Gabor Fichtinger and Mamadou Samba Camara},
url = {https://ieeexplore.ieee.org/abstract/document/10253146/},
year = {2023},
date = {2023-01-01},
pages = {1-6},
publisher = {IEEE},
abstract = {Background and purpose
Nowadays, computerized nephrostomy techniques exist. Although relatively safe, several factors make it difficult for inexperienced users. A computer-assisted nephrostomy guidance system has been studied to increase the success rate of this intervention and reduce the work and difficulties encountered by the actors.
Methods
To design the system, two methods will be studied. Following this study, this system was designed based on method 2. SmartSysNephro is composed of a hardware part whose manipulations made by the user are visualized and assisted by the computer. This nephrostomy procedure that the user simulates is monitored by webcam. Using the data from this Intel Real Sense webcam, allowed to propose a CNN YOLO model.
Results
The results obtained show that the objectives set have been achieved globally. The SmartSysNephro system gives real time warning …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background and purpose
Nowadays, computerized nephrostomy techniques exist. Although relatively safe, several factors make it difficult for inexperienced users. A computer-assisted nephrostomy guidance system has been studied to increase the success rate of this intervention and reduce the work and difficulties encountered by the actors.
Methods
To design the system, two methods will be studied. Following this study, this system was designed based on method 2. SmartSysNephro is composed of a hardware part whose manipulations made by the user are visualized and assisted by the computer. This nephrostomy procedure that the user simulates is monitored by webcam. Using the data from this Intel Real Sense webcam, allowed to propose a CNN YOLO model.
Results
The results obtained show that the objectives set have been achieved globally. The SmartSysNephro system gives real time warning …
Nowadays, computerized nephrostomy techniques exist. Although relatively safe, several factors make it difficult for inexperienced users. A computer-assisted nephrostomy guidance system has been studied to increase the success rate of this intervention and reduce the work and difficulties encountered by the actors.
Methods
To design the system, two methods will be studied. Following this study, this system was designed based on method 2. SmartSysNephro is composed of a hardware part whose manipulations made by the user are visualized and assisted by the computer. This nephrostomy procedure that the user simulates is monitored by webcam. Using the data from this Intel Real Sense webcam, allowed to propose a CNN YOLO model.
Results
The results obtained show that the objectives set have been achieved globally. The SmartSysNephro system gives real time warning …
Groves, Leah A; Keita, Mohamed; Talla, Saidou; Kikinis, Ron; Fichtinger, Gabor; Mousavi, Parvin; Camara, Mamadou
A Review of Low-cost Ultrasound Compatible Phantoms Journal Article
In: 2023.
@article{fichtinger2023m,
title = {A Review of Low-cost Ultrasound Compatible Phantoms},
author = {Leah A Groves and Mohamed Keita and Saidou Talla and Ron Kikinis and Gabor Fichtinger and Parvin Mousavi and Mamadou Camara},
url = {https://ieeexplore.ieee.org/abstract/document/10157973/},
year = {2023},
date = {2023-01-01},
publisher = {IEEE},
abstract = {Ultrasound-compatible phantoms are used to develop novel US-based systems and train simulated medical interventions. The price difference between lab-made and commercially available ultrasound-compatible phantoms lead to the publication of many papers categorized as low-cost in the literature. The aim of this review was to improve the phantom selection process by summarizing the pertinent literature. We compiled papers on US-compatible spine, prostate, vascular, breast, kidney, and li ver phantoms. We reviewed papers for cost and accessibility, providing an overview of the materials, construction time, shelf life, needle insertion limits, and manufacturing and evaluation methods. This information was summarized by anatomy. The clinical application associated with each phantom was also reported for those interested in a particular intervention. Techniques and common practices for building low-cost …},
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}
Ultrasound-compatible phantoms are used to develop novel US-based systems and train simulated medical interventions. The price difference between lab-made and commercially available ultrasound-compatible phantoms lead to the publication of many papers categorized as low-cost in the literature. The aim of this review was to improve the phantom selection process by summarizing the pertinent literature. We compiled papers on US-compatible spine, prostate, vascular, breast, kidney, and li ver phantoms. We reviewed papers for cost and accessibility, providing an overview of the materials, construction time, shelf life, needle insertion limits, and manufacturing and evaluation methods. This information was summarized by anatomy. The clinical application associated with each phantom was also reported for those interested in a particular intervention. Techniques and common practices for building low-cost …
Alqaoud, Motaz; Plemmons, John; Feliberti, Eric; Kaipa, Krishnanand; Fichtinger, Gabor; Xiao, Yiming; Rashid, Tanweer; Audette, Michel
Multi-Material, Approach-Guided, Controlled-Resolution Breast Meshing for Fe-Based Interactive Surgery Simulation Journal Article
In: pp. 402-412, 2023.
@article{fichtinger2023n,
title = {Multi-Material, Approach-Guided, Controlled-Resolution Breast Meshing for Fe-Based Interactive Surgery Simulation},
author = {Motaz Alqaoud and John Plemmons and Eric Feliberti and Krishnanand Kaipa and Gabor Fichtinger and Yiming Xiao and Tanweer Rashid and Michel Audette},
url = {https://ieeexplore.ieee.org/abstract/document/10155366/},
year = {2023},
date = {2023-01-01},
pages = {402-412},
publisher = {IEEE},
abstract = {This paper proposes a guided, controlled resolution framework for 3D multi-material meshing. Using data from magnetic resonance (MR) images, we efficiently focused on demonstrating our framework for patient-specific breast cases. As a result, we can preserve the shared boundaries and enhance the resolution without negating the aspect of simulation computing time needed for finite element analysis (FEA). Our output is a high-quality volumetric mesh comprising 21K cells representing the three main parts for breast surgery simulation and planning, fat, fibroglandular (FGT), and tumor mass. Our approach combines three steps, surface meshing, surface mesh decimation, and generating a volumetric mesh. We showed experimental results for every stage and compared our final output to other literature, proving our method's efficiency in an accurate, simple, and high-quality presentation of a patient-specific …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper proposes a guided, controlled resolution framework for 3D multi-material meshing. Using data from magnetic resonance (MR) images, we efficiently focused on demonstrating our framework for patient-specific breast cases. As a result, we can preserve the shared boundaries and enhance the resolution without negating the aspect of simulation computing time needed for finite element analysis (FEA). Our output is a high-quality volumetric mesh comprising 21K cells representing the three main parts for breast surgery simulation and planning, fat, fibroglandular (FGT), and tumor mass. Our approach combines three steps, surface meshing, surface mesh decimation, and generating a volumetric mesh. We showed experimental results for every stage and compared our final output to other literature, proving our method's efficiency in an accurate, simple, and high-quality presentation of a patient-specific …
Hashtrudi-Zaad, Kian; Hisey, Rebecca; Klosa, Elizabeth; Zevin, Boris; Ungi, Tamas; Fichtinger, Gabor
Using object detection for surgical tool recognition in simulated open inguinal hernia repair surgery Journal Article
In: vol. 12466, pp. 96-101, 2023.
@article{fichtinger2023p,
title = {Using object detection for surgical tool recognition in simulated open inguinal hernia repair surgery},
author = {Kian Hashtrudi-Zaad and Rebecca Hisey and Elizabeth Klosa and Boris Zevin and Tamas Ungi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660E/Using-object-detection-for-surgical-tool-recognition-in-simulated-open/10.1117/12.2654393.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {96-101},
publisher = {SPIE},
abstract = {Following the shift from time-based medical education to a competency-based approach, a computer-assisted training platform would help relieve some of the new time burden placed on physicians. A vital component of these platforms is the computation of competency metrics which are based on surgical tool motion. Recognizing the class and motion of surgical tools is one step in the development of a training platform. Object detection can achieve tool recognition. While previous literature has reported on tool recognition in minimally invasive surgeries, open surgeries have not received the same attention. Open Inguinal Hernia Repair (OIHR), a common surgery that general surgery residents must learn, is an example of such surgeries. We present a method for object detection to recognize surgical tools in simulated OIHR. Images were extracted from six video recordings of OIHR performed on phantoms. Tools …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Following the shift from time-based medical education to a competency-based approach, a computer-assisted training platform would help relieve some of the new time burden placed on physicians. A vital component of these platforms is the computation of competency metrics which are based on surgical tool motion. Recognizing the class and motion of surgical tools is one step in the development of a training platform. Object detection can achieve tool recognition. While previous literature has reported on tool recognition in minimally invasive surgeries, open surgeries have not received the same attention. Open Inguinal Hernia Repair (OIHR), a common surgery that general surgery residents must learn, is an example of such surgeries. We present a method for object detection to recognize surgical tools in simulated OIHR. Images were extracted from six video recordings of OIHR performed on phantoms. Tools …
Yeung, Chris; Ehrlich, Joshua; Jamzad, Amoon; Kaufmann, Martin; Rudan, John; Engel, Cecil Jay; Mousavi, Parvin; Ungi, Tamas; Fichtinger, Gabor
Cautery trajectory analysis for evaluation of resection margins in breast-conserving surgery Journal Article
In: vol. 12466, pp. 495-501, 2023.
@article{fichtinger2023q,
title = {Cautery trajectory analysis for evaluation of resection margins in breast-conserving surgery},
author = {Chris Yeung and Joshua Ehrlich and Amoon Jamzad and Martin Kaufmann and John Rudan and Cecil Jay Engel and Parvin Mousavi and Tamas Ungi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/1246622/Cautery-trajectory-analysis-for-evaluation-of-resection-margins-in-breast/10.1117/12.2654497.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {495-501},
publisher = {SPIE},
abstract = {After breast-conserving surgery, positive margins occur when breast cancer cells are found on the resection margin, leading to a higher chance of recurrence and the need for repeat surgery. The NaviKnife is an electromagnetic tracking-based surgical navigation system that helps to provide visual and spatial feedback to the surgeon. In this study, we conduct a gross evaluation of this navigation system with respect to resection margins. The trajectory of the surgical cautery relative to ultrasound-visible tumor will be visualized, and its distance and location from the tumor will be compared with pathology reports. Six breast-conserving surgery cases that resulted in positive margins were performed using the NaviKnife system. Trackers were placed on the surgical tools and their positions in three-dimensional space were recorded throughout the procedure. The closest distance between the cautery and the tumor …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
After breast-conserving surgery, positive margins occur when breast cancer cells are found on the resection margin, leading to a higher chance of recurrence and the need for repeat surgery. The NaviKnife is an electromagnetic tracking-based surgical navigation system that helps to provide visual and spatial feedback to the surgeon. In this study, we conduct a gross evaluation of this navigation system with respect to resection margins. The trajectory of the surgical cautery relative to ultrasound-visible tumor will be visualized, and its distance and location from the tumor will be compared with pathology reports. Six breast-conserving surgery cases that resulted in positive margins were performed using the NaviKnife system. Trackers were placed on the surgical tools and their positions in three-dimensional space were recorded throughout the procedure. The closest distance between the cautery and the tumor …
Syeda, Ayesha; Fooladgar, Fahimeh; Jamzad, Amoon; Srikanthan, Dilakshan; Kaufmann, Martin; Ren, Kevin; Engel, Jay; Walker, Ross; Merchant, Shaila; McKay, Doug; Varma, Sonal; Fichtinger, Gabor; Rudan, John; Mousavi, Parvin
Self-supervised learning and uncertainty estimation for surgical margin detection Journal Article
In: vol. 12466, pp. 76-83, 2023.
@article{fichtinger2023r,
title = {Self-supervised learning and uncertainty estimation for surgical margin detection},
author = {Ayesha Syeda and Fahimeh Fooladgar and Amoon Jamzad and Dilakshan Srikanthan and Martin Kaufmann and Kevin Ren and Jay Engel and Ross Walker and Shaila Merchant and Doug McKay and Sonal Varma and Gabor Fichtinger and John Rudan and Parvin Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660B/Self-supervised-learning-and-uncertainty-estimation-for-surgical-margin-detection/10.1117/12.2654104.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {76-83},
publisher = {SPIE},
abstract = {Up to 35% of breast-conserving surgeries fail to resect all the tumors completely. Ideally, machine learning methods using the iKnife data, which uses Rapid Evaporative Ionization Mass Spectrometry (REIMS), can be utilized to predict tissue type in real-time during surgery, resulting in better tumor resections. As REIMS data is heterogeneous and weakly labeled, and datasets are often small, model performance and reliability can be adversely affected. Self-supervised training and uncertainty estimation of the prediction can be used to mitigate these challenges by learning the signatures of input data without their label as well as including predictive confidence in output reporting. We first design an autoencoder model using a reconstruction pretext task as a self-supervised pretraining step without considering tissue type. Next, we construct our uncertainty-aware classifier using the encoder part of the model with …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Up to 35% of breast-conserving surgeries fail to resect all the tumors completely. Ideally, machine learning methods using the iKnife data, which uses Rapid Evaporative Ionization Mass Spectrometry (REIMS), can be utilized to predict tissue type in real-time during surgery, resulting in better tumor resections. As REIMS data is heterogeneous and weakly labeled, and datasets are often small, model performance and reliability can be adversely affected. Self-supervised training and uncertainty estimation of the prediction can be used to mitigate these challenges by learning the signatures of input data without their label as well as including predictive confidence in output reporting. We first design an autoencoder model using a reconstruction pretext task as a self-supervised pretraining step without considering tissue type. Next, we construct our uncertainty-aware classifier using the encoder part of the model with …
Klosa, Elizabeth; Hisey, Rebecca; Hashtrudi-Zaad, Kian; Zevin, Boris; Ungi, Tamas; Fichtinger, Gabor
Identifying tool-tissue interactions to distinguish steps in simulated open inguinal hernia repair Journal Article
In: vol. 12466, pp. 479-486, 2023.
@article{fichtinger2023s,
title = {Identifying tool-tissue interactions to distinguish steps in simulated open inguinal hernia repair},
author = {Elizabeth Klosa and Rebecca Hisey and Kian Hashtrudi-Zaad and Boris Zevin and Tamas Ungi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/1246620/Identifying-tool-tissue-interactions-to-distinguish-steps-in-simulated-open/10.1117/12.2654394.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {479-486},
publisher = {SPIE},
abstract = {As medical education adopts a competency-based training approach, assessment of skills and timely provision of formative feedback is required. Provision of such assessment and feedback places a substantial time burden on surgeons. To reduce this time burden, we look to develop a computer-assisted training platform to provide both instruction and feedback to residents learning open Inguinal Hernia Repairs (IHR). To provide feedback on residents’ technical skills, we must first find a method of workflow recognition of the IHR. We thus aim to recognize and distinguish between workflow steps of an open IHR based on the presence and frequencies of different tool-tissue interactions occurring during each step. Based on ground truth tissue segmentations and tool bounding boxes, we identify the visible tissues within a bounding box. This provides an estimation of which tissues a tool is interacting with. The …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
As medical education adopts a competency-based training approach, assessment of skills and timely provision of formative feedback is required. Provision of such assessment and feedback places a substantial time burden on surgeons. To reduce this time burden, we look to develop a computer-assisted training platform to provide both instruction and feedback to residents learning open Inguinal Hernia Repairs (IHR). To provide feedback on residents’ technical skills, we must first find a method of workflow recognition of the IHR. We thus aim to recognize and distinguish between workflow steps of an open IHR based on the presence and frequencies of different tool-tissue interactions occurring during each step. Based on ground truth tissue segmentations and tool bounding boxes, we identify the visible tissues within a bounding box. This provides an estimation of which tissues a tool is interacting with. The …
Radcliffe, Olivia; Connolly, Laura; Ungi, Tamas; Yeo, Caitlin; Rudan, John F; Fichtinger, Gabor; Mousavi, Parvin
Navigated surgical resection cavity inspection for breast conserving surgery Journal Article
In: vol. 12466, pp. 234-241, 2023.
@article{fichtinger2023t,
title = {Navigated surgical resection cavity inspection for breast conserving surgery},
author = {Olivia Radcliffe and Laura Connolly and Tamas Ungi and Caitlin Yeo and John F Rudan and Gabor Fichtinger and Parvin Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660Z/Navigated-surgical-resection-cavity-inspection-for-breast-conserving-surgery/10.1117/12.2654015.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {234-241},
publisher = {SPIE},
abstract = {Up to 40% of Breast Conserving Surgery (BCS) patients must undergo repeat surgery because cancer is left behind in the resection cavity. The mobility of the breast resection cavity makes it difficult to localize residual cancer and, therefore, cavity shaving is a common technique for cancer removal. Cavity shaving involves removing an additional layer of tissue from the entire resection cavity, often resulting in unnecessary healthy tissue loss. In this study, we demonstrated a navigation system and open-source software module that facilitates visualization of the breast resection cavity for targeted localization of residual cancer.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Up to 40% of Breast Conserving Surgery (BCS) patients must undergo repeat surgery because cancer is left behind in the resection cavity. The mobility of the breast resection cavity makes it difficult to localize residual cancer and, therefore, cavity shaving is a common technique for cancer removal. Cavity shaving involves removing an additional layer of tissue from the entire resection cavity, often resulting in unnecessary healthy tissue loss. In this study, we demonstrated a navigation system and open-source software module that facilitates visualization of the breast resection cavity for targeted localization of residual cancer.
Barr, Keiran; Hookey, Lawrence; Ungi, Tamas; Fichtinger, Gabor; Holden, Matthew
Analyzing colonoscopy training learning curves using comparative hand tracking assessment Journal Article
In: vol. 12466, pp. 466-472, 2023.
@article{fichtinger2023w,
title = {Analyzing colonoscopy training learning curves using comparative hand tracking assessment},
author = {Keiran Barr and Lawrence Hookey and Tamas Ungi and Gabor Fichtinger and Matthew Holden},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124661Y/Analyzing-colonoscopy-training-learning-curves-using-comparative-hand-tracking-assessment/10.1117/12.2654309.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {466-472},
publisher = {SPIE},
abstract = {A competency-based approach for colonoscopy training is particularly important, since the amount of practice required for proficiency varies widely between trainees. Though numerous objective proficiency assessment frameworks have been validated in the literature, these frameworks rely on expert observers. This process is time-consuming, and as a result, there has been increased interest in automated proficiency rating of colonoscopies. This work aims to investigate sixteen automatically computed performance metrics, and whether they can measure improvements in novices following a series of practice attempts. This involves calculating motion-tracking parameters for three groups: untrained novices, those same novices after undergoing training exercises, and experts. Both groups had electromagnetic tracking markers fixed to their hands and the scope tip. Each participant performed eight testing …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A competency-based approach for colonoscopy training is particularly important, since the amount of practice required for proficiency varies widely between trainees. Though numerous objective proficiency assessment frameworks have been validated in the literature, these frameworks rely on expert observers. This process is time-consuming, and as a result, there has been increased interest in automated proficiency rating of colonoscopies. This work aims to investigate sixteen automatically computed performance metrics, and whether they can measure improvements in novices following a series of practice attempts. This involves calculating motion-tracking parameters for three groups: untrained novices, those same novices after undergoing training exercises, and experts. Both groups had electromagnetic tracking markers fixed to their hands and the scope tip. Each participant performed eight testing …
Morton, David; Connolly, Laura; Groves, Leah; Sunderland, Kyle; Jamzad, Amoon; Rudan, John F; Fichtinger, Gabor; Ungi, Tamas; Mousavi, Parvin
Tracked tissue sensing for tumor bed inspection Journal Article
In: vol. 12466, pp. 378-385, 2023.
@article{fichtinger2023x,
title = {Tracked tissue sensing for tumor bed inspection},
author = {David Morton and Laura Connolly and Leah Groves and Kyle Sunderland and Amoon Jamzad and John F Rudan and Gabor Fichtinger and Tamas Ungi and Parvin Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124661K/Tracked-tissue-sensing-for-tumor-bed-inspection/10.1117/12.2654217.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {378-385},
publisher = {SPIE},
abstract = {Up to 30% of breast-conserving surgery patients require secondary surgery to remove cancerous tissue missed in the initial intervention. We hypothesize that tracked tissue sensing can improve the success rate of breast-conserving surgery. Tissue sensor tracking allows the surgeon to intraoperatively scan the tumor bed for leftover cancerous tissue. In this study, we characterize the performance of our tracked optical scanning testbed using an experimental pipeline. We assess the Dice similarity coefficient, accuracy, and latency of the testbed.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Up to 30% of breast-conserving surgery patients require secondary surgery to remove cancerous tissue missed in the initial intervention. We hypothesize that tracked tissue sensing can improve the success rate of breast-conserving surgery. Tissue sensor tracking allows the surgeon to intraoperatively scan the tumor bed for leftover cancerous tissue. In this study, we characterize the performance of our tracked optical scanning testbed using an experimental pipeline. We assess the Dice similarity coefficient, accuracy, and latency of the testbed.
Austin, Catherine; Hisey, Rebecca; O'Driscoll, Olivia; Ungi, Tamas; Fichtinger, Gabor
Using uncertainty quantification to improve reliability of video-based skill assessment metrics in central venous catheterization Journal Article
In: vol. 12466, pp. 84-88, 2023.
@article{fichtinger2023y,
title = {Using uncertainty quantification to improve reliability of video-based skill assessment metrics in central venous catheterization},
author = {Catherine Austin and Rebecca Hisey and Olivia O'Driscoll and Tamas Ungi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660C/Using-uncertainty-quantification-to-improve-reliability-of-video-based-skill/10.1117/12.2654419.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {84-88},
publisher = {SPIE},
abstract = {Computed-based skill assessment relies on accurate metrics to provide comprehensive feedback to trainees. Improving the accuracy of video-based metrics computed using object detection is generally done by improving the performance of the object detection network, however increasing its performance requires resources that cannot always be obtained. This study aims to improve the accuracy of metrics in central venous catheterization without requiring a high performing object detection network by removing false positive predictions identified using uncertainty quantification. The uncertainty for each bounding box was calculated using an entropy equation. The uncertainties were then compared to an uncertainty threshold computed using the optimal point of a Receiver Operating Characteristic curve. Predictions were removed if the uncertainty fell below the predefined threshold. 50 videos were recorded and …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Computed-based skill assessment relies on accurate metrics to provide comprehensive feedback to trainees. Improving the accuracy of video-based metrics computed using object detection is generally done by improving the performance of the object detection network, however increasing its performance requires resources that cannot always be obtained. This study aims to improve the accuracy of metrics in central venous catheterization without requiring a high performing object detection network by removing false positive predictions identified using uncertainty quantification. The uncertainty for each bounding box was calculated using an entropy equation. The uncertainties were then compared to an uncertainty threshold computed using the optimal point of a Receiver Operating Characteristic curve. Predictions were removed if the uncertainty fell below the predefined threshold. 50 videos were recorded and …
Whyne, Cari M; Underwood, Grace; Davidson, Sean RH; Robert, Normand; Huang, Christine; Akens, Margarete K; Fichtinger, Gabor; Yee, Albert JM; Hardisty, Michael
Development and validation of a radiofrequency ablation treatment planning system for vertebral metastases Journal Article
In: International Journal of Computer Assisted Radiology and Surgery, vol. 18, iss. 12, pp. 2339-2347, 2023.
@article{fichtinger2023e,
title = {Development and validation of a radiofrequency ablation treatment planning system for vertebral metastases},
author = {Cari M Whyne and Grace Underwood and Sean RH Davidson and Normand Robert and Christine Huang and Margarete K Akens and Gabor Fichtinger and Albert JM Yee and Michael Hardisty},
url = {https://link.springer.com/article/10.1007/s11548-023-02952-9},
year = {2023},
date = {2023-01-01},
journal = {International Journal of Computer Assisted Radiology and Surgery},
volume = {18},
issue = {12},
pages = {2339-2347},
publisher = {Springer International Publishing},
abstract = {Purpose
Bone-targeted radiofrequency ablation (RFA) is widely used in the treatment of vertebral metastases. While radiation therapy utilizes established treatment planning systems (TPS) based on multimodal imaging to optimize treatment volumes, current RFA of vertebral metastases has been limited to qualitative image-based assessment of tumour location to direct probe selection and access. This study aimed to design, develop and evaluate a computational patient-specific RFA TPS for vertebral metastases.
Methods
A TPS was developed on the open-source 3D slicer platform, including procedural setup, dose calculation (based on finite element modelling), and analysis/visualization modules. Usability testing was carried out by 7 clinicians involved in the treatment of vertebral metastases on retrospective clinical imaging data using a simplified dose calculation engine. In vivo evaluation was performed in a …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
Bone-targeted radiofrequency ablation (RFA) is widely used in the treatment of vertebral metastases. While radiation therapy utilizes established treatment planning systems (TPS) based on multimodal imaging to optimize treatment volumes, current RFA of vertebral metastases has been limited to qualitative image-based assessment of tumour location to direct probe selection and access. This study aimed to design, develop and evaluate a computational patient-specific RFA TPS for vertebral metastases.
Methods
A TPS was developed on the open-source 3D slicer platform, including procedural setup, dose calculation (based on finite element modelling), and analysis/visualization modules. Usability testing was carried out by 7 clinicians involved in the treatment of vertebral metastases on retrospective clinical imaging data using a simplified dose calculation engine. In vivo evaluation was performed in a …
Bone-targeted radiofrequency ablation (RFA) is widely used in the treatment of vertebral metastases. While radiation therapy utilizes established treatment planning systems (TPS) based on multimodal imaging to optimize treatment volumes, current RFA of vertebral metastases has been limited to qualitative image-based assessment of tumour location to direct probe selection and access. This study aimed to design, develop and evaluate a computational patient-specific RFA TPS for vertebral metastases.
Methods
A TPS was developed on the open-source 3D slicer platform, including procedural setup, dose calculation (based on finite element modelling), and analysis/visualization modules. Usability testing was carried out by 7 clinicians involved in the treatment of vertebral metastases on retrospective clinical imaging data using a simplified dose calculation engine. In vivo evaluation was performed in a …
Pose-Díez-de-la-Lastra, Alicia; Ungi, Tamas; Morton, David; Fichtinger, Gabor; Pascau, Javier
Real-time integration between Microsoft HoloLens 2 and 3D Slicer with demonstration in pedicle screw placement planning Journal Article
In: International Journal of Computer Assisted Radiology and Surgery, vol. 18, iss. 11, pp. 2023-2032, 2023.
@article{fichtinger2023f,
title = {Real-time integration between Microsoft HoloLens 2 and 3D Slicer with demonstration in pedicle screw placement planning},
author = {Alicia Pose-Díez-de-la-Lastra and Tamas Ungi and David Morton and Gabor Fichtinger and Javier Pascau},
url = {https://link.springer.com/article/10.1007/s11548-023-02977-0},
year = {2023},
date = {2023-01-01},
journal = {International Journal of Computer Assisted Radiology and Surgery},
volume = {18},
issue = {11},
pages = {2023-2032},
publisher = {Springer International Publishing},
abstract = {Purpose
Up to date, there has been a lack of software infrastructure to connect 3D Slicer to any augmented reality (AR) device. This work describes a novel connection approach using Microsoft HoloLens 2 and OpenIGTLink, with a demonstration in pedicle screw placement planning.
Methods
We developed an AR application in Unity that is wirelessly rendered onto Microsoft HoloLens 2 using Holographic Remoting. Simultaneously, Unity connects to 3D Slicer using the OpenIGTLink communication protocol. Geometrical transform and image messages are transferred between both platforms in real time. Through the AR glasses, a user visualizes a patient’s computed tomography overlaid onto virtual 3D models showing anatomical structures. We technically evaluated the system by measuring message transference latency between the platforms. Its functionality was assessed in pedicle screw placement planning …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Purpose
Up to date, there has been a lack of software infrastructure to connect 3D Slicer to any augmented reality (AR) device. This work describes a novel connection approach using Microsoft HoloLens 2 and OpenIGTLink, with a demonstration in pedicle screw placement planning.
Methods
We developed an AR application in Unity that is wirelessly rendered onto Microsoft HoloLens 2 using Holographic Remoting. Simultaneously, Unity connects to 3D Slicer using the OpenIGTLink communication protocol. Geometrical transform and image messages are transferred between both platforms in real time. Through the AR glasses, a user visualizes a patient’s computed tomography overlaid onto virtual 3D models showing anatomical structures. We technically evaluated the system by measuring message transference latency between the platforms. Its functionality was assessed in pedicle screw placement planning …
Up to date, there has been a lack of software infrastructure to connect 3D Slicer to any augmented reality (AR) device. This work describes a novel connection approach using Microsoft HoloLens 2 and OpenIGTLink, with a demonstration in pedicle screw placement planning.
Methods
We developed an AR application in Unity that is wirelessly rendered onto Microsoft HoloLens 2 using Holographic Remoting. Simultaneously, Unity connects to 3D Slicer using the OpenIGTLink communication protocol. Geometrical transform and image messages are transferred between both platforms in real time. Through the AR glasses, a user visualizes a patient’s computed tomography overlaid onto virtual 3D models showing anatomical structures. We technically evaluated the system by measuring message transference latency between the platforms. Its functionality was assessed in pedicle screw placement planning …
Jamzad, Amoon; Fooladgar, Fahimeh; Connolly, Laura; Srikanthan, Dilakshan; Syeda, Ayesha; Kaufmann, Martin; Ren, Kevin YM; Merchant, Shaila; Engel, Jay; Varma, Sonal; Fichtinger, Gabor; Rudan, John F; Mousavi, Parvin
Bridging Ex-Vivo Training and Intra-operative Deployment for Surgical Margin Assessment with Evidential Graph Transformer Journal Article
In: pp. 562-571, 2023.
@article{fichtinger2023g,
title = {Bridging Ex-Vivo Training and Intra-operative Deployment for Surgical Margin Assessment with Evidential Graph Transformer},
author = {Amoon Jamzad and Fahimeh Fooladgar and Laura Connolly and Dilakshan Srikanthan and Ayesha Syeda and Martin Kaufmann and Kevin YM Ren and Shaila Merchant and Jay Engel and Sonal Varma and Gabor Fichtinger and John F Rudan and Parvin Mousavi},
url = {https://link.springer.com/chapter/10.1007/978-3-031-43990-2_53},
year = {2023},
date = {2023-01-01},
pages = {562-571},
publisher = {Springer Nature Switzerland},
abstract = {PURPOSE
The use of intra-operative mass spectrometry along with Graph Transformer models showed promising results for margin detection on ex-vivo data. Although highly interpretable, these methods lack the ability to handle the uncertainty associated with intra-operative decision making. In this paper for the first time, we propose Evidential Graph Transformer network, a combination of attention mapping and uncertainty estimation to increase the performance and interpretability of surgical margin assessment.
METHODS
The Evidential Graph Transformer was formulated to output the uncertainty estimation along with intermediate attentions. The performance of the model was compared with different baselines in an ex-vivo cross-validation scheme, with extensive ablation study. The association of the model with clinical features were explored. The model was further validated for a prospective ex-vivo data, as …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
PURPOSE
The use of intra-operative mass spectrometry along with Graph Transformer models showed promising results for margin detection on ex-vivo data. Although highly interpretable, these methods lack the ability to handle the uncertainty associated with intra-operative decision making. In this paper for the first time, we propose Evidential Graph Transformer network, a combination of attention mapping and uncertainty estimation to increase the performance and interpretability of surgical margin assessment.
METHODS
The Evidential Graph Transformer was formulated to output the uncertainty estimation along with intermediate attentions. The performance of the model was compared with different baselines in an ex-vivo cross-validation scheme, with extensive ablation study. The association of the model with clinical features were explored. The model was further validated for a prospective ex-vivo data, as …
The use of intra-operative mass spectrometry along with Graph Transformer models showed promising results for margin detection on ex-vivo data. Although highly interpretable, these methods lack the ability to handle the uncertainty associated with intra-operative decision making. In this paper for the first time, we propose Evidential Graph Transformer network, a combination of attention mapping and uncertainty estimation to increase the performance and interpretability of surgical margin assessment.
METHODS
The Evidential Graph Transformer was formulated to output the uncertainty estimation along with intermediate attentions. The performance of the model was compared with different baselines in an ex-vivo cross-validation scheme, with extensive ablation study. The association of the model with clinical features were explored. The model was further validated for a prospective ex-vivo data, as …
Szabó, Róbert Zsolt; Orosz, Gábor; Ungi, Tamás; Barr, Colton; Yeung, Chris; Incze, Roland; Fichtinger, Gabor; Gál, János; Haidegger, Tamás
Automation of lung ultrasound imaging and image processing for bedside diagnostic examinations Journal Article
In: pp. 000779-000784, 2023.
@article{fichtinger2023h,
title = {Automation of lung ultrasound imaging and image processing for bedside diagnostic examinations},
author = {Róbert Zsolt Szabó and Gábor Orosz and Tamás Ungi and Colton Barr and Chris Yeung and Roland Incze and Gabor Fichtinger and János Gál and Tamás Haidegger},
url = {https://ieeexplore.ieee.org/abstract/document/10158672/},
year = {2023},
date = {2023-01-01},
pages = {000779-000784},
publisher = {IEEE},
abstract = {The causes of acute respiratory failure can be difficult to identify for physicians. Experts can differentiate these causes using bedside lung ultrasound, but lung ultrasound has a considerable learning curve. We investigate if an automated decision-support system could help novices interpret lung ultrasound scans. The system utilizes medical ultrasound, data processing, and a neural network implementation to achieve this goal. The article details the steps taken in the data preparation, and the implementation of the neural network. The best model’s accuracy and error rate are presented, along with examples of its predictions. The paper concludes with an evaluation of the results, identification of limitations, and suggestions for future improvements.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The causes of acute respiratory failure can be difficult to identify for physicians. Experts can differentiate these causes using bedside lung ultrasound, but lung ultrasound has a considerable learning curve. We investigate if an automated decision-support system could help novices interpret lung ultrasound scans. The system utilizes medical ultrasound, data processing, and a neural network implementation to achieve this goal. The article details the steps taken in the data preparation, and the implementation of the neural network. The best model’s accuracy and error rate are presented, along with examples of its predictions. The paper concludes with an evaluation of the results, identification of limitations, and suggestions for future improvements.
Srikanthan, Dilakshan; Kaufmann, Martin; Jamzad, Amoon; Syeda, Ayesha; Santilli, Alice; Sedghi, Alireza; Fichtinger, Gabor; Purzner, Jamie; Rudan, John; Purzner, Teresa; Mousavi, Parvin
Attention-based multi-instance learning for improved glioblastoma detection using mass spectrometry Journal Article
In: vol. 12466, pp. 248-253, 2023.
@article{fichtinger2023i,
title = {Attention-based multi-instance learning for improved glioblastoma detection using mass spectrometry},
author = {Dilakshan Srikanthan and Martin Kaufmann and Amoon Jamzad and Ayesha Syeda and Alice Santilli and Alireza Sedghi and Gabor Fichtinger and Jamie Purzner and John Rudan and Teresa Purzner and Parvin Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/1246611/Attention-based-multi-instance-learning-for-improved-glioblastoma-detection-using/10.1117/12.2654436.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {248-253},
publisher = {SPIE},
abstract = {Glioblastoma Multiforme (GBM) is the most common and most lethal primary brain tumor in adults with a five-year survival rate of 5%. The current standard of care and survival rate have remained largely unchanged due to the degree of difficulty in surgically removing these tumors, which plays a crucial role in survival, as better surgical resection leads to longer survival times. Thus, novel technologies need to be identified to improve resection accuracy. Our study features a curated database of GBM and normal brain tissue specimens, which we used to train and validate a multi-instance learning model for GBM detection via rapid evaporative ionization mass spectrometry. This method enables real-time tissue typing. The specimens were collected by a surgeon, reviewed by a pathologist, and sampled with an electrocautery device. The dataset comprised 276 normal tissue burns and 321 GBM tissue burns. Our multi …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Glioblastoma Multiforme (GBM) is the most common and most lethal primary brain tumor in adults with a five-year survival rate of 5%. The current standard of care and survival rate have remained largely unchanged due to the degree of difficulty in surgically removing these tumors, which plays a crucial role in survival, as better surgical resection leads to longer survival times. Thus, novel technologies need to be identified to improve resection accuracy. Our study features a curated database of GBM and normal brain tissue specimens, which we used to train and validate a multi-instance learning model for GBM detection via rapid evaporative ionization mass spectrometry. This method enables real-time tissue typing. The specimens were collected by a surgeon, reviewed by a pathologist, and sampled with an electrocautery device. The dataset comprised 276 normal tissue burns and 321 GBM tissue burns. Our multi …
Fichtinger, Gabor; Holden, Matthew; Jannin, Pierre; Haegelen, Claire; Zhao, Yulong
Proficiency assessment system and method for deep brain stimulation (DBS) Journal Article
In: 2023.
@article{fichtinger2023k,
title = {Proficiency assessment system and method for deep brain stimulation (DBS)},
author = {Gabor Fichtinger and Matthew Holden and Pierre Jannin and Claire Haegelen and Yulong Zhao},
url = {https://patents.google.com/patent/US11756689B2/en},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
abstract = {A method for simulating a deep-brain stimulation in a computer-assisted platform that includes providing to a neurosurgeon, through a man-machine interface, visual information of a pre-operative situation, including a representation of a brain. The method also includes monitoring inputs of said neurosurgeon on the man-machine interface, until a trajectory is determined between an entry point and a target for the placement of an electrode. The method further includes comparing said trajectory to a set of previously-established trajectories for the pre-operative situation, so as to determine an overall measurement representative of a quality of the trajectory compared to the previously-established trajectories.},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
A method for simulating a deep-brain stimulation in a computer-assisted platform that includes providing to a neurosurgeon, through a man-machine interface, visual information of a pre-operative situation, including a representation of a brain. The method also includes monitoring inputs of said neurosurgeon on the man-machine interface, until a trajectory is determined between an entry point and a target for the placement of an electrode. The method further includes comparing said trajectory to a set of previously-established trajectories for the pre-operative situation, so as to determine an overall measurement representative of a quality of the trajectory compared to the previously-established trajectories.
Nam, Hannah H; Flynn, Maura; Lasso, Andras; Herz, Christian; Sabin, Patricia; Wang, Yan; Cianciulli, Alana; Vigil, Chad; Huang, Jing; Vicory, Jared; Paniagua, Beatriz; Allemang, David; Goldberg, David J; Nuri, Mohammed; Cohen, Meryl S; Fichtinger, Gabor; Jolley, Matthew A
Modeling of the tricuspid valve and right ventricle in hypoplastic left heart syndrome with a Fontan circulation Journal Article
In: Circulation: Cardiovascular Imaging, vol. 16, iss. 3, pp. e014671, 2023.
@article{fichtinger2023c,
title = {Modeling of the tricuspid valve and right ventricle in hypoplastic left heart syndrome with a Fontan circulation},
author = {Hannah H Nam and Maura Flynn and Andras Lasso and Christian Herz and Patricia Sabin and Yan Wang and Alana Cianciulli and Chad Vigil and Jing Huang and Jared Vicory and Beatriz Paniagua and David Allemang and David J Goldberg and Mohammed Nuri and Meryl S Cohen and Gabor Fichtinger and Matthew A Jolley},
url = {https://www.ahajournals.org/doi/abs/10.1161/CIRCIMAGING.122.014671},
year = {2023},
date = {2023-01-01},
journal = {Circulation: Cardiovascular Imaging},
volume = {16},
issue = {3},
pages = {e014671},
publisher = {Lippincott Williams & Wilkins},
abstract = {Background
In hypoplastic left heart syndrome, tricuspid regurgitation (TR) is associated with circulatory failure and death. We hypothesized that the tricuspid valve (TV) structure of patients with hypoplastic left heart syndrome with a Fontan circulation and moderate or greater TR differs from those with mild or less TR, and that right ventricle volume is associated with TV structure and dysfunction.
Methods
TV of 100 patients with hypoplastic left heart syndrome and a Fontan circulation were modeled using transthoracic 3-dimensional echocardiograms and custom software in SlicerHeart. Associations of TV structure to TR grade and right ventricle function and volume were investigated. Shape parameterization and analysis was used to calculate the mean shape of the TV leaflets, their principal modes of variation, and to characterize associations of TV leaflet shape to TR.
Results
In univariate modeling, patients with …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Background
In hypoplastic left heart syndrome, tricuspid regurgitation (TR) is associated with circulatory failure and death. We hypothesized that the tricuspid valve (TV) structure of patients with hypoplastic left heart syndrome with a Fontan circulation and moderate or greater TR differs from those with mild or less TR, and that right ventricle volume is associated with TV structure and dysfunction.
Methods
TV of 100 patients with hypoplastic left heart syndrome and a Fontan circulation were modeled using transthoracic 3-dimensional echocardiograms and custom software in SlicerHeart. Associations of TV structure to TR grade and right ventricle function and volume were investigated. Shape parameterization and analysis was used to calculate the mean shape of the TV leaflets, their principal modes of variation, and to characterize associations of TV leaflet shape to TR.
Results
In univariate modeling, patients with …
In hypoplastic left heart syndrome, tricuspid regurgitation (TR) is associated with circulatory failure and death. We hypothesized that the tricuspid valve (TV) structure of patients with hypoplastic left heart syndrome with a Fontan circulation and moderate or greater TR differs from those with mild or less TR, and that right ventricle volume is associated with TV structure and dysfunction.
Methods
TV of 100 patients with hypoplastic left heart syndrome and a Fontan circulation were modeled using transthoracic 3-dimensional echocardiograms and custom software in SlicerHeart. Associations of TV structure to TR grade and right ventricle function and volume were investigated. Shape parameterization and analysis was used to calculate the mean shape of the TV leaflets, their principal modes of variation, and to characterize associations of TV leaflet shape to TR.
Results
In univariate modeling, patients with …
Kitner, Nicole; Rodgers, Jessica R; Ungi, Tamas; Korzeniowski, Martin; Olding, Timothy; Mousavi, Parvin; Fichtinger, Gabor
Multi-catheter modelling in reconstructed 3D transrectal ultrasound images from prostate brachytherapy Journal Article
In: vol. 12466, pp. 126-135, 2023.
@article{fichtinger2023b,
title = {Multi-catheter modelling in reconstructed 3D transrectal ultrasound images from prostate brachytherapy},
author = {Nicole Kitner and Jessica R Rodgers and Tamas Ungi and Martin Korzeniowski and Timothy Olding and Parvin Mousavi and Gabor Fichtinger},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124660I/Multi-catheter-modelling-in-reconstructed-3D-transrectal-ultrasound-images-from/10.1117/12.2654019.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {126-135},
publisher = {SPIE},
abstract = {High-dose-rate brachytherapy is an accepted standard-of-care treatment for prostate cancer. In this procedure, catheters are inserted using three-dimensional (3D) transrectal ultrasound image-guidance. Their positions are manually segmented for treatment planning and delivery. The transverse ultrasound sweep, which is subject to tip and depth error for catheter localization, is a commonly used ultrasound imaging option available for image acquisition. We propose a two-step pipeline that uses a deep-learning network and curve fitting to automatically localize and model catheters in transversely reconstructed 3D ultrasound images. In the first step, a 3D U-Net was trained to automatically segment all catheters in a 3D ultrasound image. Following this step, curve fitting was implemented to detect the shapes of individual catheters using polynomial fitting. Of the 343 catheters (from 20 patients) in the testing data, the …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
High-dose-rate brachytherapy is an accepted standard-of-care treatment for prostate cancer. In this procedure, catheters are inserted using three-dimensional (3D) transrectal ultrasound image-guidance. Their positions are manually segmented for treatment planning and delivery. The transverse ultrasound sweep, which is subject to tip and depth error for catheter localization, is a commonly used ultrasound imaging option available for image acquisition. We propose a two-step pipeline that uses a deep-learning network and curve fitting to automatically localize and model catheters in transversely reconstructed 3D ultrasound images. In the first step, a 3D U-Net was trained to automatically segment all catheters in a 3D ultrasound image. Following this step, curve fitting was implemented to detect the shapes of individual catheters using polynomial fitting. Of the 343 catheters (from 20 patients) in the testing data, the …
Kaufmann, Martin; Iaboni, Natasha; Jamzad, Amoon; Hurlbut, David; Ren, Kevin Yi Mi; Rudan, John F; Mousavi, Parvin; Fichtinger, Gabor; Varma, Sonal; Caycedo-Marulanda, Antonio; Nicol, Christopher JB
In: Metabolites, vol. 13, iss. 4, pp. 508, 2023.
@article{fichtinger2023,
title = {Metabolically active zones involving fatty acid elongation delineated by DESI-MSI correlate with pathological and prognostic features of colorectal cancer},
author = {Martin Kaufmann and Natasha Iaboni and Amoon Jamzad and David Hurlbut and Kevin Yi Mi Ren and John F Rudan and Parvin Mousavi and Gabor Fichtinger and Sonal Varma and Antonio Caycedo-Marulanda and Christopher JB Nicol},
url = {https://www.mdpi.com/2218-1989/13/4/508},
year = {2023},
date = {2023-01-01},
journal = {Metabolites},
volume = {13},
issue = {4},
pages = {508},
publisher = {MDPI},
abstract = {Colorectal cancer (CRC) is the second leading cause of cancer deaths. Despite recent advances, five-year survival rates remain largely unchanged. Desorption electrospray ionization mass spectrometry imaging (DESI) is an emerging nondestructive metabolomics-based method that retains the spatial orientation of small-molecule profiles on tissue sections, which may be validated by ‘gold standard’ histopathology. In this study, CRC samples were analyzed by DESI from 10 patients undergoing surgery at Kingston Health Sciences Center. The spatial correlation of the mass spectral profiles was compared with histopathological annotations and prognostic biomarkers. Fresh frozen sections of representative colorectal cross sections and simulated endoscopic biopsy samples containing tumour and non-neoplastic mucosa for each patient were generated and analyzed by DESI in a blinded fashion. Sections were then hematoxylin and eosin (H and E) stained, annotated by two independent pathologists, and analyzed. Using PCA/LDA-based models, DESI profiles of the cross sections and biopsies achieved 97% and 75% accuracies in identifying the presence of adenocarcinoma, using leave-one-patient-out cross validation. Among the m/z ratios exhibiting the greatest differential abundance in adenocarcinoma were a series of eight long-chain or very-long-chain fatty acids, consistent with molecular and targeted metabolomics indicators of de novo lipogenesis in CRC tissue. Sample stratification based on the presence of lympovascular invasion (LVI), a poor CRC prognostic indicator, revealed the abundance of oxidized phospholipids, suggestive …},
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}
Colorectal cancer (CRC) is the second leading cause of cancer deaths. Despite recent advances, five-year survival rates remain largely unchanged. Desorption electrospray ionization mass spectrometry imaging (DESI) is an emerging nondestructive metabolomics-based method that retains the spatial orientation of small-molecule profiles on tissue sections, which may be validated by ‘gold standard’ histopathology. In this study, CRC samples were analyzed by DESI from 10 patients undergoing surgery at Kingston Health Sciences Center. The spatial correlation of the mass spectral profiles was compared with histopathological annotations and prognostic biomarkers. Fresh frozen sections of representative colorectal cross sections and simulated endoscopic biopsy samples containing tumour and non-neoplastic mucosa for each patient were generated and analyzed by DESI in a blinded fashion. Sections were then hematoxylin and eosin (H and E) stained, annotated by two independent pathologists, and analyzed. Using PCA/LDA-based models, DESI profiles of the cross sections and biopsies achieved 97% and 75% accuracies in identifying the presence of adenocarcinoma, using leave-one-patient-out cross validation. Among the m/z ratios exhibiting the greatest differential abundance in adenocarcinoma were a series of eight long-chain or very-long-chain fatty acids, consistent with molecular and targeted metabolomics indicators of de novo lipogenesis in CRC tissue. Sample stratification based on the presence of lympovascular invasion (LVI), a poor CRC prognostic indicator, revealed the abundance of oxidized phospholipids, suggestive …
Kitner, Nicole; Rodgers, Jessica R.; Ungi, Tamas; Olding, Timothy; Joshi, C. P.; Mousavi, Parvin; Fichtinger, Gabor; Korzeniowski, Martin
Automated catheter localization in ultrasound images from High-dose-rate prostate brachytherapy using deep learning and feature extraction Conference
Canadian Association for Radiation Oncologists (CARO) Annual Scientific Meeting, Canadian Association for Radiation Oncologists, 2022.
@conference{Kitner2022ab,
title = {Automated catheter localization in ultrasound images from High-dose-rate prostate brachytherapy using deep learning and feature extraction},
author = {Nicole Kitner and Jessica R. Rodgers and Tamas Ungi and Timothy Olding and C. P. Joshi and Parvin Mousavi and Gabor Fichtinger and Martin Korzeniowski},
year = {2022},
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Fooladgar, Fahimeh; Jamzad, Amoon; Connolly, Laura; Santilli, Alice; Kaufmann, Martin; Ren, Kevin; Abolmaesumi, Purang; Rudan, John; McKay, Doug; Fichtinger, Gabor; Mousavi, Parvin
Uncertainty estimation for margin detection in cancer surgery using mass spectrometry Journal Article
In: International Journal of Computer Assisted Radiology and Surgery, 2022.
@article{Fooladgar2022,
title = {Uncertainty estimation for margin detection in cancer surgery using mass spectrometry},
author = {Fahimeh Fooladgar and Amoon Jamzad and Laura Connolly and Alice Santilli and Martin Kaufmann and Kevin Ren and Purang Abolmaesumi and John Rudan and Doug McKay and Gabor Fichtinger and Parvin Mousavi},
doi = {https://doi.org/10.1007/s11548-022-02764-3},
year = {2022},
date = {2022-09-01},
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Connolly, Laura; Degeut, Anton; Leonard, Simon; Tokuda, Junichi; Ungi, Tamas; Krieger, Axel; Kazanzides, Peter; Mousavi, Parvin; Fichtinger, Gabor; Taylor, Russell H.
Bridging 3D Slicer and ROS2 for Image-Guided Robotic Interventions Journal Article
In: Sensors, vol. 22, 2022.
@article{Connolly2022c,
title = {Bridging 3D Slicer and ROS2 for Image-Guided Robotic Interventions},
author = {Laura Connolly and Anton Degeut and Simon Leonard and Junichi Tokuda and Tamas Ungi and Axel Krieger and Peter Kazanzides and Parvin Mousavi and Gabor Fichtinger and Russell H. Taylor},
doi = {https://doi.org/10.3390/s22145336},
year = {2022},
date = {2022-07-01},
journal = {Sensors},
volume = {22},
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Kitner, Nicole; Rodgers, Jessica R.; Ungi, Tamas; Korzeniowski, Martin; Olding, Timothy; Joshi, C. P.; Mousavi, Parvin; Fichtinger, Gabor
Automated Automatic catheter modelling in 3D transrectal ultrasound images from high-dose-rate prostate brachytherapy using a deep learning and feature extraction pipeline Conference
Canadian Organization of Medical Physicists (COMP) Annual Scientific Meeting, Canadian Organization of Medical Physicists, 2022.
@conference{Kitner2022a,
title = {Automated Automatic catheter modelling in 3D transrectal ultrasound images from high-dose-rate prostate brachytherapy using a deep learning and feature extraction pipeline},
author = {Nicole Kitner and Jessica R. Rodgers and Tamas Ungi and Martin Korzeniowski and Timothy Olding and C. P. Joshi and Parvin Mousavi and Gabor Fichtinger},
year = {2022},
date = {2022-06-01},
urldate = {2022-06-01},
booktitle = {Canadian Organization of Medical Physicists (COMP) Annual Scientific Meeting},
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Hu, Zoe; Fauerbach, Paola V. Nasute; Yeung, Chris; Ungi, Tamas; Rudan, John; Engel, C. Jay; Mousavi, Parvin; Fichtinger, Gabor; Jabs, Doris
Real-time automatic tumor segmentation for ultrasound-guided breast-conserving surgery navigation Journal Article
In: International Journal of Computer Assisted Radiology and Surgery, vol. 17, no. 9, pp. 1663–1672, 2022.
@article{Hu2022,
title = {Real-time automatic tumor segmentation for ultrasound-guided breast-conserving surgery navigation},
author = {Zoe Hu and Paola V. Nasute Fauerbach and Chris Yeung and Tamas Ungi and John Rudan and C. Jay Engel and Parvin Mousavi and Gabor Fichtinger and Doris Jabs},
doi = {10.1007/s11548-022-02658-4},
year = {2022},
date = {2022-05-01},
urldate = {2022-05-01},
journal = {International Journal of Computer Assisted Radiology and Surgery},
volume = {17},
number = {9},
pages = {1663–1672},
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