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Automatic registration of 2D MR cine images for swallowing motion estimation

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posted on 2021-01-27, 04:49 authored by J Yang, ASR Mohamed, H Bahig, Y Ding, J Wang, Sweet NgSweet Ng, S Lai, A Miller, KA Hutcheson, CD Fuller
© 2020 Yang et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Purpose To automate the estimation of swallowing motion from 2D MR cine images using deformable registration for future applications of personalized margin reduction in head and neck radiotherapy and outcome assessment of radiation-associated dysphagia. Methods Twenty-one patients with serial 2D FSPGR-MR cine scans of the head and neck conducted through the course of definitive radiotherapy for oropharyngeal cancer. Included patients had at least one cine scan before, during, or after radiotherapy, with a total of 52 cine scans. Contours of 7 swallowing related regions-of-interest (ROIs), including pharyngeal constrictor, epiglottis, base of tongue, geniohyoid, hyoid, soft palate, and larynx, were manually delineated from consecutive frames of the cine scan covering at least one swallowing cycle. We applied a modified thin-plate-spline robust-point-matching algorithm to register the point sets of each ROI automatically over frames. The deformation vector fields from the registration were then used to estimate the motion during swallowing for each ROI. Registration errors were estimated by comparing the deformed contours with the manual contours. Results On average 22 frames of each cine scan were contoured. The registration for one cine scan (7 ROIs over 22 frames) on average took roughly 22 minutes. A number of 8018 registrations were successfully batch processed without human interaction after the contours were drawn. The average registration error for all ROIs and all patients was 0.36 mm (range: 0.06 mm– 2.06 mm). Larynx had the average largest motion in superior direction of all structures under consideration (range: 0.0 mm– 58.7 mm). Geniohyoid had the smallest overall motion of all ROIs under consideration and the superior-inferior motion was larger than the anterior-posterior motion for all ROIs. Conclusion We developed and validated a deformable registration framework to automate the estimation of swallowing motion from 2D MR cine scans.


This work is directly supported by the NIH/NCI Early Phase Clinical Trials in Imaging and Image-Guided Interventions Program (1R01CA218148) and the Andrew Sabin Family Foundation; Dr. Fuller is a Sabin Family Foundation Fellow. Dr. Yang received funding support from Elekta and MD Anderson Cancer Center Institutional Research Grant. Drs. Mohamed, Lai, Hutcheson, and Fuller receive(d) funding support from the National Institutes of Health (NIH)/National Institute for Dental and Craniofacial Research (1R01DE025248-01/R56DE025248-01) and NIH/NCI Early Phase Clinical Trials in Imaging and Image-Guided Interventions Program (1R01CA218148-01). Dr. Fuller received/receives federal grant and/or salary support from: the NIH/National Cancer Institute (NCI) Head and Neck Specialized Programs of Research Excellence (SPORE) Developmental Research Program Award (P50CA097007-10) and Pau l Calabresi Clinical Oncology Program Award (K12 CA088084-06); a National Science Foundation (NSF), Division of Mathematical Sciences, Joint NIH/NSF Initiative on Quantitative Approaches to Biomedical Big Data (QuBBD) Grant (NSF 1557679); the NIH Big Data to Knowledge (BD2K) Program of the National Cancer Institute (NCI) Early Stage Development of Technologies in Biomedical Computing, Informatics, and Big Data Science Award (1R01CA214825-01); and the Cancer center Support Grant Radiation Oncology/Cancer Imaging Program Seed Grant (5P30CA016672). Dr. Fuller receives(d) industry grant support and speaker travel funding from Elekta AB. Dr. Ng was supported by the Australian Postgraduate Award and the Royal Australian and New Zealand College of Radiologists (RANZCR) research grants. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.


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