@article {Yeo2017, title = {3D Segmentation as a Surgical Planning Tool for Residents in Liver Resection Surgery}, year = {In Press}, abstract = {

Introduction: Liver surgery requires identification of tumor(s) in relation to key vessels to preserve healthy tissue, while obtaining negative margins. Current planning is mentally strenuous for residents as it relies on mental 3D reconstruction, anatomical knowledge, spatial sense, and experience. The purpose of this study is to determine if 3D segmentation improves resident ability to devise appropriate liver resection plans.

Methods: Senior general surgery residents were recruited. Pre-operative CT/MR images were selected if they reflected actual surgeries performed. Images were segmented to create interactive 3D models. Residents were asked to devise surgical plans for case-matched 2D and 3D models in an alternating, randomly generated order. Primary outcome was correct preoperative plan based on actual surgery performed. Secondary outcome was time (seconds(s)) to devise plan. Planning data was analyzed using Wilcoxon test, time was analyzed using paired t-test.

Results: All 14 senior residents from our institution participated. The average correct response was 1.7 of 5 (34\%; range 1 to 4) for the 2D group, and 3.1 of 5 (62\%; range 0 to 4) for the 3D group (p\<0.01). The average time to complete each plan was 156{\textpm}107s for the 2D group, and 84{\textpm}73s for the 3D group (p\<0.01).

Conclusions: The results show that 3D segmentation increases accuracy of surgical planning and decreases amount of time required. 3D segmentation is useful as a teaching tool as it reduces cognitive load required to mentally reconstruct 2D images, allowing the resident to focus on surgical planning. It improves understanding of spatial liver anatomy and serves as an adjunct to current 2D planning methods. This has the potential to be developed into a module for teaching liver surgery relevant to a competency-based curriculum.

}, author = {Yeo, Caitlin T and MacDonald, Andrew and Tamas Ungi and Andras Lasso and Diederick Jalink and Gabor Fichtinger and Nanji, Sulaiman} } @article {Gauvin2019, title = {Real-time electromagnetic navigation for breast-conserving surgery using NaviKnife technology: A matched case-control study}, journal = {The Breast Journal}, volume = {26}, number = {3}, year = {2020}, month = {09/2019}, pages = {399-405}, doi = {10.1111/tbj.13480}, author = {Gabrielle Gauvin and Yeo, Caitlin T and Tamas Ungi and Shaila Merchant and Andras Lasso and Doris Jabs and Thomas Vaughan and John Rudan and Ross Walker and Gabor Fichtinger and C. Jay Engel} } @article {Lia2018b, title = {Basic suturing training using Microsoft HoloLens}, year = {2018}, month = {03/2018}, address = {Toronto, ON}, author = {H. Lia and Paulin, Gregory and Yeo, Caitlin T and Andrews, Jessica and Yi, Nelson and Haq, Hassan and Emmanuel, Steve and Ludig, Kristian and Keri, Zsuzsanna and Andras Lasso and Gabor Fichtinger} } @conference {Lia2018a, title = {HoloLens in Suturing Training}, booktitle = {SPIE Medical Imaging 2018: Image-Guided Procedures, Robotic Interventions, and Modeling}, year = {2018}, month = {03/2018}, address = {Houston, Texas}, author = {H. Lia and Paulin, Gregory and Yeo, Caitlin T and Andrews, Jessica and Yi, Nelson and Haq, Hassan and Emmanuel, Steve and Ludig, Kristian and Keri, Zsuzsanna and Andras Lasso and Gabor Fichtinger} } @article {Yeo2017, title = {Utility of 3D Reconstruction of 2D Liver Computed Tomography/Magnetic Resonance Images as a Surgical Planning Tool for Residents in Liver Resection Surgery}, journal = {Journal of Surgical Education}, volume = {75}, number = {3}, year = {2018}, month = {08/2017}, pages = {792-797}, abstract = {

Objective

A fundamental aspect of surgical planning in liver resections is the identification of key vessel tributaries to preserve healthy liver tissue while fully resecting the tumor(s). Current surgical planning relies primarily on the surgeon{\textquoteright}s ability to mentally reconstruct 2D computed tomography/magnetic resonance (CT/MR) images into 3D and plan resection margins. This creates significant cognitive load, especially for trainees, as it relies on image interpretation, anatomical and surgical knowledge, experience, and spatial sense. The purpose of this study is to determine if 3D reconstruction of preoperative CT/MR images will assist resident-level trainees in making appropriate operative plans for liver resection surgery.

Design

Ten preoperative patient CT/MR images were selected. Images were case-matched, 5 to 2D planning and 5 to 3D planning. Images from the 3D group were segmented to create interactive digital models that the resident can manipulate to view the tumor(s) in relation to landmark hepatic structures. Residents were asked to evaluate the images and devise a surgical resection plan for each image. The resident alternated between 2D and 3D planning, in a randomly generated order. The primary outcome was the accuracy of resident{\textquoteright}s plan compared to expert opinion. Time to devise each surgical plan was the secondary outcome. Residents completed a prestudy and poststudy questionnaire regarding their experience with liver surgery and the 3D planning software.

Setting and Participants

Senior level surgical residents from the Queen{\textquoteright}s University General Surgery residency program were recruited to participate.

Results

A total of 14 residents participated in the study. The median correct response rate was 2 of 5 (40\%; range: 0-4) for the 2D group, and 3 of 5 (60\%; range: 1-5) for the 3D group (p \< 0.01). The average time to complete each plan was 156 {\textpm} 107 seconds for the 2D group, and 84 {\textpm} 73 seconds for the 3D group (p \< 0.01). A total 13 of 14 residents found the 3D model easier to use than the 2D. Most residents noticed a difference between the 2 modalities and found that the 3D model improved their confidence with the surgical plan proposed.

Conclusions

The results of this study show that 3D reconstruction for liver surgery planning increases accuracy of resident surgical planning and decreases amount of time required. 3D reconstruction would be a useful model for improving trainee understanding of liver anatomy and surgical resection, and would serve as an adjunct to current 2D planning methods. This has the potential to be developed into a module for teaching liver surgery in a competency-based medical curriculum.

}, doi = {http://dx.doi.org/10.1016/j.jsurg.2017.07.031}, author = {Yeo, Caitlin T and MacDonald, Andrew and Tamas Ungi and Andras Lasso and Diederick Jalink and Boris Zevin and Gabor Fichtinger and Nanji, Sulaiman} } @article {Gauvin2016a, title = {Breast-Conserving Surgery using NaviKnife Technology: Pilot Study on Non-Palpable Tumors}, year = {2016}, month = {08/2016}, author = {Gabrielle Gauvin and Tamas Ungi and Andras Lasso and Yeo, Caitlin T and Gabor Fichtinger and Doris Jabs and Ross Walker and Shaila Merchant and John Rudan and C. Jay Engel} } @article {McGraw2015a, title = {Development and evaluation of a simulation-based curriculum for ultrasound guided central venous catheterization}, journal = {Canadian Journal of Emergency Medicine}, volume = {18}, number = {6}, year = {2016}, month = {11/2016}, pages = {405-413}, doi = {10.1017/cem.2016.329}, author = {McGraw, Robert C and Tim Chaplin and Conor McKaigney and Louise Rang and Melanie Jaeger and Damian Redfearn and Colleen Davison and Tamas Ungi and M. Holden and Yeo, Caitlin T and Keri, Zsuzsanna and Gabor Fichtinger} } @article {Ungi2015c, title = {Clinical Translation of Real Time Cautery Navigation for Breast Surgery}, year = {2015}, month = {06/2015}, pages = {19-20}, isbn = {978-0-9563776-6-1}, author = {Tamas Ungi and Gabrielle Gauvin and Andras Lasso and Yeo, Caitlin T and John Rudan and C. Jay Engel and Gabor Fichtinger} } @article {Yeo2015a, title = {Examination of learning trajectories for simulated lumbar puncture training using hand motion analysis}, journal = {Academic Emergency Medicine}, volume = {22}, number = {10}, year = {2015}, month = {10/2015}, pages = {1187-1195}, doi = {10.1111/acem.12753}, author = {Yeo, Caitlin T and Colleen Davison and Tamas Ungi and M. Holden and Gabor Fichtinger and McGraw, Robert C} } @article {Ungi2015b, title = {Navigated breast tumor excision using electromagnetically tracked ultrasound and surgical instruments}, journal = {IEEE Transactions on Biomedical Engineering}, year = {2015}, month = {08/2015 }, abstract = {

OBJECTIVE:

Lumpectomy, breast conserving tumor excision, is the standard surgical treatment in early stage breast cancer. A common problem with lumpectomy is that the tumor may not be completely excised, and additional surgery becomes necessary. We investigated if a surgical navigation system using intraoperative ultrasound improves the outcomes of lumpectomy, and if such a system can be implemented in the clinical environment.

METHODS:

Position sensors were applied on the tumor localization needle, the ultrasound probe, and the cautery, and three-dimensional navigation views were generated using real time tracking information. The system was tested against standard wire-localization procedures on phantom breast models by eight surgical residents. Clinical safety and feasibility was tested in six palpable tumor patients undergoing lumpectomy by two experienced surgical oncologists.

RESULTS:

Navigation resulted in significantly less tissue excised compared to control procedures (10.3 {\textpm} 4.4 vs. 18.6 {\textpm} 8.7 g, p = 0.01) and lower number of tumorpositive margins (1/8 vs. 4/8) in the phantom experiments. Excision-tumor distance was also more consistently outside the tumor margins with navigation in phantoms. The navigation system has been successfully integrated in an operating room, and user experience was rated positively by surgical oncologists.

CONCLUSION:

Electromagnetic navigation may improve the outcomes of lumpectomy by making the tumor excision more accurate.

SIGNIFICANCE:

Breast cancer is the most common cancer in women, and lumpectomy is its first choice treatment. Therefore, improvement of lumpectomy outcomes have a significant impact on a large patient population.

}, issn = {0018-9294}, doi = {10.1109/TBME.2015.2466591}, url = {http://www.ncbi.nlm.nih.gov/pubmed/26302503}, author = {Tamas Ungi and Gabrielle Gauvin and Andras Lasso and Yeo, Caitlin T and Padina Pezeshki and Thomas Vaughan and Kaci Carter and John Rudan and C. Jay Engel and Gabor Fichtinger} } @conference {Ungi2015a, title = {Real Time Navigation In Breast Tumor Surgery}, booktitle = {Computer Assisted Radiology and Surgery, 29th International Congress}, volume = {10}, year = {2015}, month = {06/2015}, pages = {S59-60}, doi = {10.1007/s11548-015-1213-2}, author = {Tamas Ungi and Gabrielle Gauvin and Yeo, Caitlin T and C. Jay Engel and John Rudan and Gabor Fichtinger} } @conference {Sadjadi2014c, title = {Electromagnetic tracking performance analysis and optimization}, booktitle = {International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC)}, year = {2014}, month = {09/2014}, author = {Yu Qi and Hossein Sadjadi and Yeo, Caitlin T and Keyvan Hashtrudi-Zaad and Gabor Fichtinger} } @article {Gauvin2014b, title = {Real-time electromagnetic navigation for breast tumor resection: proof of concept}, year = {2014}, month = {06/2014}, address = {Kingston, ON, Canada}, author = {Gabrielle Gauvin and Yeo, Caitlin T and Tamas Ungi and Gabor Fichtinger and John Rudan and C. Jay Engel} } @article {Gauvin2014c, title = {Real-Time Electromagnetic Navigation for Breast Tumor Resection: Proof of Concept}, year = {2014}, month = {09/2014}, address = {Vancouver, BC, Canada}, author = {Gabrielle Gauvin and Yeo, Caitlin T and Tamas Ungi and C. Jay Engel and Gabor Fichtinger and John Rudan} } @conference {Gauvin2014d, title = {Real-time electromagnetic navigation for breast tumor resection: proof of concept}, booktitle = {The Hamlyn Symposium on Medical Robotics}, year = {2014}, month = {07/2014}, pages = {39-40}, address = {London, UK}, author = {Gabrielle Gauvin and Yeo, Caitlin T and Tamas Ungi and Gabor Fichtinger and John Rudan and C. Jay Engel} } @article {Gauvin2014a, title = {Real-time EM navigated breast conserving surgery: phantom and cadaver experiments}, year = {2014}, month = {09/2014}, address = {Cambridge, MA, USA}, author = {Gabrielle Gauvin and Yeo, Caitlin T and Tamas Ungi and Gabor Fichtinger and Nanji, Sulaiman and John Rudan and C. Jay Engel} } @conference {Ungi2011b, title = {Augmented Reality Needle Guidance Improves Facet Joint Injection Training}, booktitle = {SPIE Medical Imaging}, volume = {7964}, number = {1}, year = {2011}, month = {03/2011}, pages = {79642E 1-7}, publisher = {SPIE}, organization = {SPIE}, address = {Lake Buena Vista, Florida, USA}, doi = {10.1117/12.877830}, url = {http://link.aip.org/link/?PSI/7964/79642E/1}, author = {Tamas Ungi and Yeo, Caitlin T and Paweena U-Thainual and McGraw, Robert C and Gabor Fichtinger} } @conference {Ungi2011a, title = {Augmented reality training to improve needle-based percutaneous interventions}, booktitle = {ImNO2011 - Imaging Network Ontario Symposium}, year = {2011}, month = {01/2011}, address = {Toronto, ON, Canada, Jan 31-Feb 1}, author = {Tamas Ungi and Paweena U-Thainual and Andras Lasso and Yeo, Caitlin T and McGraw, Robert C and Gabor Fichtinger} } @article {Yeo2011, title = {The Effect of Augmented Reality Training on Percutaneous Needle Placement in Spinal Facet Joint Injections}, journal = {IEEE Transactions on Biomedical Engineering}, volume = {58}, year = {2011}, month = {07/2011}, pages = {2031-7}, keywords = {augmented reality, surgical training}, issn = {0018-9294}, doi = {10.1109/TBME.2011.2132131}, url = {http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=5739103\&tag=1}, author = {Yeo, Caitlin T and Tamas Ungi and Paweena U-Thainual and Andras Lasso and McGraw, Robert C and Gabor Fichtinger} } @article {Ungi2011c, title = {Perk Station image overlay improves training of facet joint injections}, volume = {4}, year = {2011}, month = {10/2011}, pages = {118}, address = {Arlington VA, October 12-13, 2011}, author = {Tamas Ungi and Paweena U-Thainual and Yeo, Caitlin T and Andras Lasso and McGraw, Robert C and Gabor Fichtinger} }