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

Abstract

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.

Improving the registration stability of cone-beam computed tomography with the Sphere-Mask Optical Positioning System: a feasibility study

“…This was attributed to the existence of thickness (typically 3 or 5 mm) between layers of data acquired by planning CT (usually helical CT). Therefore, compared with those of the horizontal data, the reconstruction results of the LNG data were poor, which would affect the accuracy of CBCT registration ( 41 , 42 ). In addition, during manual verification, it was difficult for the radiation therapists to select the data with large errors in the LNG direction from the sagittal plane image or coronal plane image with poor reconstruction results.…”

Multi-Intensity Optimization-Based CT and Cone Beam CT Image Registration

“…Typically, considering the difference in beam energy, CBCT is widely applied in the clinical IGRT routine [10][11][12][13]. The development of IGRT has promoted the research and application of related new technologies for cancer treatment [14][15][16]. For CBCT-based guided radiotherapy, it is meaningful that, with the help of imaging registration techniques, the shift data generated according to the comparison of on-site images can correct the treatment table per fraction, subsequently resulting in more precise patient positioning.…”