title: A novel approach for establishing benchmark CBCT/CT deformable image registrations in prostate cancer radiotherapy.
abstract: Deformable image registration (DIR) is an integral component for adaptive radiation therapy. However, accurate registration between daily cone-beam computed tomography (CBCT) and treatment planning CT is challenging, due to significant daily variations in rectal and bladder fillings as well as the increased noise levels in CBCT images. Another significant challenge is the lack of 'ground-truth' registrations in the clinical setting, which is necessary for quantitative evaluation of various registration algorithms. The aim of this study is to establish benchmark registrations of clinical patient data. Three pairs of CT/CBCT datasets were chosen for this institutional review board approved retrospective study. On each image, in order to reduce the contouring uncertainty, ten independent sets of organs were manually delineated by five physicians. The mean contour set for each image was derived from the ten contours. A set of distinctive points (round natural calcifications and three implanted prostate fiducial markers) were also manually identified. The mean contours and point features were then incorporated as constraints into a B-spline based DIR algorithm. Further, a rigidity penalty was imposed on the femurs and pelvic bones to preserve their rigidity. A piecewise-rigid registration approach was adapted to account for the differences in femur pose and the sliding motion between bones. For each registration, the magnitude of the spatial Jacobian (|JAC|) was calculated to quantify the tissue compression and expansion. Deformation grids and finite-element-model-based unbalanced energy maps were also reviewed visually to evaluate the physical soundness of the resultant deformations. Organ DICE indices (indicating the degree of overlap between registered organs) and residual misalignments of the fiducial landmarks were quantified. Manual organ delineation on CBCT images varied significantly among physicians with overall mean DICE index of only 0.7 among redundant contours. Seminal vesicle contours were found to have the lowest correlation amongst physicians (DICE = 0.5). After DIR, the organ surfaces between CBCT and planning CT were in good alignment with mean DICE indices of 0.9 for prostate, rectum, and bladder, and 0.8 for seminal vesicles. The Jacobian magnitudes |JAC| in the prostate, rectum, and seminal vesicles were in the range of 0.4-1.5, indicating mild compression/expansion. The bladder volume differences were larger between CBCT and CT images with mean |JAC| values of 2.2, 0.7, and 1.0 for three respective patients. Bone deformation was negligible (|JAC| = ∼ 1.0). The difference between corresponding landmark points between CBCT and CT was less than 1.0 mm after DIR. We have presented a novel method of establishing benchmark DIR accuracy between CT and CBCT images in the pelvic region. The method incorporates manually delineated organ surfaces and landmark points as well as pixel similarity in the optimization, while ensuring bone rigidity and avoiding excessive deformation in soft tissue organs. Redundant contouring is necessary to reduce the overall registration uncertainty.
authors.forename: Jinkoo
authors.initials: J
authors.lastname: Kim
authors.forename: Sanath
authors.initials: S
authors.lastname: Kumar
authors.forename: Chang
authors.initials: C
authors.lastname: Liu
authors.forename: Hualiang
authors.initials: H
authors.lastname: Zhong
authors.forename: Deepak
authors.initials: D
authors.lastname: Pradhan
authors.forename: Mira
authors.initials: M
authors.lastname: Shah
authors.forename: Richard
authors.initials: R
authors.lastname: Cattaneo
authors.forename: Raphael
authors.initials: R
authors.lastname: Yechieli
authors.forename: Jared R
authors.initials: JR
authors.lastname: Robbins
authors.forename: Mohamed A
authors.initials: MA
authors.lastname: Elshaikh
authors.forename: Indrin J
authors.initials: IJ
authors.lastname: Chetty
mesh_terms: D016477:Artifacts; D019985:Benchmarking; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008297:Male; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging* / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted; D012189:Retrospective Studies