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.
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}
}
Kim, Andrew; Yeung, Chris; Szabo, Robert; Sunderland, Kyle; Hisey, Rebecca; Morton, David; Kikinis, Ron; Diao, Babacar; Mousavi, Parvin; Ungi, Tamas; Fichtinger, Gabor
Percutaneous nephrostomy needle guidance using real-time 3D anatomical visualization with live ultrasound segmentation Journal Article
In: vol. 12928, pp. 163-168, 2024.
@article{fichtinger2024h,
title = {Percutaneous nephrostomy needle guidance using real-time 3D anatomical visualization with live ultrasound segmentation},
author = {Andrew 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},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12928/129280S/Percutaneous-nephrostomy-needle-guidance-using-real-time-3D-anatomical-visualization/10.1117/12.3006533.short},
year = {2024},
date = {2024-01-01},
volume = {12928},
pages = {163-168},
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 …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
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 …
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 …
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 …
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 …
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{fichtinger2024d,
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},
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 …
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 …
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 …
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 …
Connolly, Laura; Fooladgar, Fahimeh; Jamzad, Amoon; Kaufmann, Martin; Syeda, Ayesha; Ren, Kevin; Abolmaesumi, Purang; Rudan, John F; McKay, Doug; Fichtinger, Gabor; others,
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{connolly2024imspect,
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 others},
doi = {https://doi.org/10.1007/s11548-024-03106-1},
year = {2024},
date = {2024-01-01},
urldate = {2024-01-01},
journal = {International Journal of Computer Assisted Radiology and Surgery},
pages = {1–8},
publisher = {Springer},
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}
}
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 …
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.
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 …
Ehrlich, J; Yeung, C; Kaufman, M; Jamzad, A; Rudan, J; Mousavi, P; Fichtinger, G; Ungi, T
Determining the time-delay of a mass spectrometry-based tissue sensor Journal Article
In: vol. 12466, pp. 324-327, 2023.
@article{fichtinger2023v,
title = {Determining the time-delay of a mass spectrometry-based tissue sensor},
author = {J Ehrlich and C Yeung and M Kaufman and A Jamzad and J Rudan and P Mousavi and G Fichtinger and T Ungi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/124661D/Determining-the-time-delay-of-a-mass-spectrometry-based-tissue/10.1117/12.2654359.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {324-327},
publisher = {SPIE},
abstract = {Breast cancer commonly requires surgical treatment. A procedure used to remove breast cancer is lumpectomy, which removes a minimal healthy tissue margin surrounding the tumor, called a negative margin. A cancer-free margin is difficult to achieve because tumors are not visible or palpable, and the breast deforms during surgery. One notable solution is Rapid Evaporative Ionization Mass Spectrometry (REIMS), which differentiates tumor from healthy tissue with high accuracy from the vapor generated by the surgical cautery. REIMS combined with navigation could detect where the surgical cautery breaches tumor tissue. However, fusing position tracking and REIMS data for navigation is challenging. REIMS has a time-delay dependent on a series of factors. Our objective was to evaluate REIMS time-delay for surgical navigation. The average time-delay of REIMS classifications was measured by video …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Breast cancer commonly requires surgical treatment. A procedure used to remove breast cancer is lumpectomy, which removes a minimal healthy tissue margin surrounding the tumor, called a negative margin. A cancer-free margin is difficult to achieve because tumors are not visible or palpable, and the breast deforms during surgery. One notable solution is Rapid Evaporative Ionization Mass Spectrometry (REIMS), which differentiates tumor from healthy tissue with high accuracy from the vapor generated by the surgical cautery. REIMS combined with navigation could detect where the surgical cautery breaches tumor tissue. However, fusing position tracking and REIMS data for navigation is challenging. REIMS has a time-delay dependent on a series of factors. Our objective was to evaluate REIMS time-delay for surgical navigation. The average time-delay of REIMS classifications was measured by video …
Elmi, H; Jamzad, A; Sharp, M; Rodgers, JR; Kaufmann, M; Jamaspishvili, T; Iseman, R; Berman, D; Rudan, J; Fichtinger, G; Mousavi, P
ViPRE: an open-source software implementation for end-to-end analysis of mass spectrometry data Journal Article
In: vol. 12466, pp. 487-494, 2023.
@article{fichtinger2023u,
title = {ViPRE: an open-source software implementation for end-to-end analysis of mass spectrometry data},
author = {H Elmi and A Jamzad and M Sharp and JR Rodgers and M Kaufmann and T Jamaspishvili and R Iseman and D Berman and J Rudan and G Fichtinger and P Mousavi},
url = {https://www.spiedigitallibrary.org/conference-proceedings-of-spie/12466/1246621/ViPRE–an-open-source-software-implementation-for-end-to/10.1117/12.2654425.short},
year = {2023},
date = {2023-01-01},
volume = {12466},
pages = {487-494},
publisher = {SPIE},
abstract = {Mass Spectrometry Imaging (MSI) is a powerful tool capable of visualizing molecular patterns to identify disease markers in tissue analysis. However, data analysis is computationally heavy and currently time-consuming as there is no single platform capable of performing the entire preprocessing, visualization, and analysis pipeline end-to-end. Using different software tools and file formats required for such tools also makes the process prone to error. The purpose of this work is to develop a free, open-source software implementation called “Visualization, Preprocessing, and Registration Environment” (ViPRE), capable of end-to-end analysis of MSI data. ViPRE was developed to provide various functionalities required for MSI analysis including data import, data visualization, data registration, Region of Interest (ROI) selection, spectral data alignment and data analysis. The software implementation is offered as an …},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mass Spectrometry Imaging (MSI) is a powerful tool capable of visualizing molecular patterns to identify disease markers in tissue analysis. However, data analysis is computationally heavy and currently time-consuming as there is no single platform capable of performing the entire preprocessing, visualization, and analysis pipeline end-to-end. Using different software tools and file formats required for such tools also makes the process prone to error. The purpose of this work is to develop a free, open-source software implementation called “Visualization, Preprocessing, and Registration Environment” (ViPRE), capable of end-to-end analysis of MSI data. ViPRE was developed to provide various functionalities required for MSI analysis including data import, data visualization, data registration, Region of Interest (ROI) selection, spectral data alignment and data analysis. The software implementation is offered as an …
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.
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 …