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Title: MO-C-17A-03: A GPU-Based Method for Validating Deformable Image Registration in Head and Neck Radiotherapy Using Biomechanical Modeling

Abstract

Purpose: Deformable image registration (DIR) plays a pivotal role in head and neck adaptive radiotherapy but a systematic validation of DIR algorithms has been limited by a lack of quantitative high-resolution groundtruth. We address this limitation by developing a GPU-based framework that provides a systematic DIR validation by generating (a) model-guided synthetic CTs representing posture and physiological changes, and (b) model-guided landmark-based validation. Method: The GPU-based framework was developed to generate massive mass-spring biomechanical models from patient simulation CTs and contoured structures. The biomechanical model represented soft tissue deformations for known rigid skeletal motion. Posture changes were simulated by articulating skeletal anatomy, which subsequently applied elastic corrective forces upon the soft tissue. Physiological changes such as tumor regression and weight loss were simulated in a biomechanically precise manner. Synthetic CT data was then generated from the deformed anatomy. The initial and final positions for one hundred randomly-chosen mass elements inside each of the internal contoured structures were recorded as ground truth data. The process was automated to create 45 synthetic CT datasets for a given patient CT. For instance, the head rotation was varied between +/− 4 degrees along each axis, and tumor volumes were systematically reduced up to 30%.more » Finally, the original CT and deformed synthetic CT were registered using an optical flow based DIR. Results: Each synthetic data creation took approximately 28 seconds of computation time. The number of landmarks per data set varied between two and three thousand. The validation method is able to perform sub-voxel analysis of the DIR, and report the results by structure, giving a much more in depth investigation of the error. Conclusions: We presented a GPU based high-resolution biomechanical head and neck model to validate DIR algorithms by generating CT equivalent 3D volumes with simulated posture changes and physiological regression.« less

Authors:
; ; ; ;  [1]
  1. UCLA School of Medicine, Los Angeles, CA (United States)
Publication Date:
OSTI Identifier:
22407759
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 41; Journal Issue: 6; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; DATASETS; HEAD; IMAGE PROCESSING; NECK; NEOPLASMS; PATIENTS; RADIOTHERAPY

Citation Formats

Neylon, J, Min, Y, Qi, S, Kupelian, P, and Santhanam, A. MO-C-17A-03: A GPU-Based Method for Validating Deformable Image Registration in Head and Neck Radiotherapy Using Biomechanical Modeling. United States: N. p., 2014. Web. doi:10.1118/1.4889126.
Neylon, J, Min, Y, Qi, S, Kupelian, P, & Santhanam, A. MO-C-17A-03: A GPU-Based Method for Validating Deformable Image Registration in Head and Neck Radiotherapy Using Biomechanical Modeling. United States. https://doi.org/10.1118/1.4889126
Neylon, J, Min, Y, Qi, S, Kupelian, P, and Santhanam, A. 2014. "MO-C-17A-03: A GPU-Based Method for Validating Deformable Image Registration in Head and Neck Radiotherapy Using Biomechanical Modeling". United States. https://doi.org/10.1118/1.4889126.
@article{osti_22407759,
title = {MO-C-17A-03: A GPU-Based Method for Validating Deformable Image Registration in Head and Neck Radiotherapy Using Biomechanical Modeling},
author = {Neylon, J and Min, Y and Qi, S and Kupelian, P and Santhanam, A},
abstractNote = {Purpose: Deformable image registration (DIR) plays a pivotal role in head and neck adaptive radiotherapy but a systematic validation of DIR algorithms has been limited by a lack of quantitative high-resolution groundtruth. We address this limitation by developing a GPU-based framework that provides a systematic DIR validation by generating (a) model-guided synthetic CTs representing posture and physiological changes, and (b) model-guided landmark-based validation. Method: The GPU-based framework was developed to generate massive mass-spring biomechanical models from patient simulation CTs and contoured structures. The biomechanical model represented soft tissue deformations for known rigid skeletal motion. Posture changes were simulated by articulating skeletal anatomy, which subsequently applied elastic corrective forces upon the soft tissue. Physiological changes such as tumor regression and weight loss were simulated in a biomechanically precise manner. Synthetic CT data was then generated from the deformed anatomy. The initial and final positions for one hundred randomly-chosen mass elements inside each of the internal contoured structures were recorded as ground truth data. The process was automated to create 45 synthetic CT datasets for a given patient CT. For instance, the head rotation was varied between +/− 4 degrees along each axis, and tumor volumes were systematically reduced up to 30%. Finally, the original CT and deformed synthetic CT were registered using an optical flow based DIR. Results: Each synthetic data creation took approximately 28 seconds of computation time. The number of landmarks per data set varied between two and three thousand. The validation method is able to perform sub-voxel analysis of the DIR, and report the results by structure, giving a much more in depth investigation of the error. Conclusions: We presented a GPU based high-resolution biomechanical head and neck model to validate DIR algorithms by generating CT equivalent 3D volumes with simulated posture changes and physiological regression.},
doi = {10.1118/1.4889126},
url = {https://www.osti.gov/biblio/22407759}, journal = {Medical Physics},
issn = {0094-2405},
number = 6,
volume = 41,
place = {United States},
year = {Sun Jun 15 00:00:00 EDT 2014},
month = {Sun Jun 15 00:00:00 EDT 2014}
}