(Thursday, 8/2/2018) 10:00 AM - 12:00 PM
Room: Karl Dean Ballroom C
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: Ten patients with 2D FSPGR-MR cine scans of the head and neck were obtained from a parent clinical trial with serial MR scans 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 18 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. Next 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 15 frames of each cine scan were contoured. The registration for one cine scan (7 ROIs over 15 frames) averaged roughly 15 minutes to run. A number of 1757 registrations were successfully batch processed without human interaction after the contours were drawn. The average registration error for all ROIs and all patients was 0.37 mm (range: 0.19 mm - 1.05 mm). Average maximum motion of all ROIs in the 10 patients is 8.7 mm (range: 0.0 mm - 40.3 mm) and larynx has the average largest motion in inferior direction of all structures under consideration (range: 9.2 mm - 31.4 mm).
Conclusion: We developed and validated a deformable registration framework to automate the estimation of swallowing motion from 2D MR cine scans.
Funding Support, Disclosures, and Conflict of Interest: This research was supported in part by an NCI R01 grant CA218148.
Keywords
Taxonomy
IM/TH- Image registration : MRI
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