Surrogate-driven respiratory motion model for projection-resolved motion estimation and motion compensated cone-beam CT reconstruction from unsorted projection data
AffiliationThe Christie NHS Foundation Trust, Wilmslow Road, Manchester, M20 4BX,
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AbstractOBJECTIVE: As the most common solution to motion artefact for Cone-Beam CT (CBCT) in radiotherapy, 4DCBCT suffers from long acquisition time and phase sorting error. This issue could be addressed if the motion at each projection could be known, which is a severely ill-posed problem. This study aims to obtain the motion at each time point and motion-free image simultaneously from unsorted projection data of a standard 3DCBCT scan.
Approach: Respiration surrogate signals were extracted by the Intensity Analysis method. A general framework was then deployed to fit a surrogate-driven motion model that characterized the relation between the motion and surrogate signals at each time point. Motion model fitting and motion compensated reconstruction were alternatively and iteratively performed. Stochastic subset gradient based method was used to significantly reduce the computation time. The performance of our method was comprehensively evaluated through digital phantom simulation and also validated on clinical scans from six patients.
Results: For digital phantom experiments, motion models fitted with ground-truth or extracted surrogate signals both achieved a much lower motion estimation error and higher image quality, compared with non motion-compensated results.For the public SPARE Challenge datasets, more clear lung tissues and less blurry diaphragm could be seen in the motion compensated reconstruction, comparable to the benchmark 4DCBCT images but with a higher temporal resolution. Similar results were observed for two real clinical 3DCBCT scans. SIGNIFICANCE: This study demonstrated the feasibility of our proposed framework for simultaneous motion model fitting and motion compensated reconstruction using unsorted 3D CBCT projection data.
CitationHuang Y, Thielemans K, Price GJ, McClelland JR. Surrogate-driven respiratory motion model for projection-resolved motion estimation and motion compensated Cone-Beam CT reconstruction from unsorted projection data. Physics in medicine and biology. 2023 Dec 13. PubMed PMID: 38091611. Epub 2023/12/13. eng.
JournalPhysics in Medicine and Biology