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Using previously registered cone beam computerized tomography images to facilitate online computerized tomography to cone beam computerized tomography image registration in lung stereotactic body radiation therapy
Author(s) -
Liang Jian,
Liu Qiang,
Grills Inga,
Guerrero Thomas,
Stevens Craig,
Yan Di
Publication year - 2022
Publication title -
journal of applied clinical medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.83
H-Index - 48
ISSN - 1526-9914
DOI - 10.1002/acm2.13549
Subject(s) - image registration , cone beam computed tomography , image guided radiation therapy , nuclear medicine , medicine , medical physics , computer science , cone beam ct , artificial intelligence , computer vision , computed tomography , medical imaging , radiology , image (mathematics)
Purpose In our conventional image registration workflow, the four‐dimensional (4D) CBCT was directly registered to the reference helical CT (HCT) using a dual registration approach within the Elekta XVI software. In this study, we proposed a new HCT–CBCT auto‐registration strategy using a previously registered CBCT (CBCTpre) as the reference image and tested its clinical feasibility. Methods From a previous CBCT session, the registered average 4D CBCT was selected as CBCTpre and the HCT–CBCTpre registration vector from the clinician's manual registration result was recorded. In the new CBCT session, auto‐registration was performed between the new average 4D CBCT (CBCTtx) and CBCTpre (CBCTpre‐CBCTtx). The overall HCT–CBCTtx registration result was then derived by combing the results from two registrations (i.e., HCT–CBCTpre + CBCTpre–CBCTtx). The results from the proposed method were compared with clinician's manually adjusted HCT–CBCTtx registration results (“ground truth”) to evaluate its accuracy using a test dataset consisting of 32 challenging registration cases. Results The uncertainty of the proposed auto‐registration method was −0.1 ± 0.5, 0.1 ± 1.0, and −0.1 ± 0.7 mm in three translational directions (lateral, longitudinal, and vertical) and 0.0° ± 0.9°, 0.3° ± 0.9°, and 0.4° ± 0.7° in three rotation directions, respectively. Two patients (6.3%) had translational uncertainty > 2 mm (max = 3.1 mm) and both occurred in the longitudinal direction. Meanwhile, the uncertainty of the conventional direct HCT–CBCTtx auto‐registration was −0.4 ± 2.6, −0.2 ± 7.4, −1.4 ± 3.6 mm for translations and −0.3° ± 1.2°, 0.0° ± 1.6°, and 0.1 ± 1.1° for rotations. Eleven patients (34.4%) had translation uncertainty > 2 mm (max = 26.2 mm) in at least one direction. Accuracy in translation was improved with the new method, while rotation accuracy stayed in the same order. Conclusion We demonstrated the feasibility of incorporating prior clinical registration knowledge into the online HCT–CBCT registration process. The proposed auto‐registration method provides a quick and reliable starting solution for online HCT–CBCT registration.

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