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Proceedings Paper

Estimating tongue deformation during laryngoscopy using hybrid FEM-multibody model and intraoperative tracking: a cadaver pilot study
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Paper Abstract

Minimally invasive approaches to treating tumors of the pharynx and larynx like trans-oral surgery have improved patient outcome, but challenges remain in localizing tumors for margin control. Introducing necessary retractors and scopes deforms the anatomy and the tumor, rendering preoperative imaging inaccurate and making tumor localization difficult. This paper describes a pipeline that uses preoperative imaging to generate a hybrid FEM-multibody model and then dynamically simulates tongue deformation due to insertion of an electromagnetically-tracked laryngoscope. We hypothesize that the simulation output will be a sufficient estimate of the final intraoperative state and thus provide the surgeon with more accurate guidance during surgical resection. This pipeline was trialed on a cadaver head. The skull, mandible, and laryngoscope were tracked, and fiducial clips were embedded in the tongue for calculating target localization error (TLE) between the simulated and real tongue deformation. Registration accuracies were 1.1, 1.3, and 0.8 mm, respectively, for the tracked skull, mandible, and laryngoscope, and tracking and segmentation validation between the last tracked frame and the ground-truth intraoperative CT was 0.8, 0.9, and 1.2 mm, respectively. TLE of 6.4±2.5 mm was achieved for the full pipeline, in contrast to the total tongue deformation of 37.2±11.4 mm (via tongue clips) between the preoperative and intraoperative CT. Use of tracking and deformation modeling is viable to estimate deformation of the tongue during laryngoscopy. Future work involves additional intraoperative data streams to help further refine model parameters and improve localization.

Paper Details

Date Published: 16 March 2020
PDF: 6 pages
Proc. SPIE 11315, Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling, 113151E (16 March 2020); doi: 10.1117/12.2550471
Show Author Affiliations
Xiaotian Wu, Gordon Ctr. for Medical Imaging (United States)
C. Antonio Sánchez, The Univ. of British Columbia (Canada)
John Lloyd, The Univ. of British Columbia (Canada)
Heather Borgard, The Univ. of British Columbia (Canada)
Sidney Fels, The Univ. of British Columbia (Canada)
Joseph A. Paydarfar, Dartmouth-Hitchcock Medical Ctr. (United States)
Ryan J. Halter, Thayer School of Engineering at Dartmouth (United States)


Published in SPIE Proceedings Vol. 11315:
Medical Imaging 2020: Image-Guided Procedures, Robotic Interventions, and Modeling
Baowei Fei; Cristian A. Linte, Editor(s)

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