TY - JOUR
T1 - Automatic registration of 2D MR cine images for swallowing motion estimation
AU - the Joint Head and Neck Radiotherapy MRI Development Cooperative
AU - Yang, Jinzhong
AU - Mohamed, Abdallah S.R.
AU - Bahig, Houda
AU - Ding, Yao
AU - Wang, Jihong
AU - Ng, Sweet Ping
AU - Lai, Stephen
AU - Miller, Austin
AU - Hutcheson, Kate A.
AU - Fuller, Clifton Dave
N1 - Publisher Copyright:
© 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.
PY - 2020/2/1
Y1 - 2020/2/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85079339149&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85079339149&partnerID=8YFLogxK
U2 - 10.1371/journal.pone.0228652
DO - 10.1371/journal.pone.0228652
M3 - Article
C2 - 32045464
AN - SCOPUS:85079339149
SN - 1932-6203
VL - 15
JO - PloS one
JF - PloS one
IS - 2
M1 - e0228652
ER -