title: Contouring variability of human- and deformable-generated contours in radiotherapy for prostate cancer.
abstract: This study was designed to evaluate contouring variability of human-and deformable-generated contours on planning CT (PCT) and CBCT for ten patients with low-or intermediate-risk prostate cancer. For each patient in this study, five radiation oncologists contoured the prostate, bladder, and rectum, on one PCT dataset and five CBCT datasets. Consensus contours were generated using the STAPLE method in the CERR software package. Observer contours were compared to consensus contour, and contour metrics (Dice coefficient, Hausdorff distance, Contour Distance, Center-of-Mass [COM] Deviation) were calculated. In addition, the first day CBCT was registered to subsequent CBCT fractions (CBCTn: CBCT2-CBCT5) via B-spline Deformable Image Registration (DIR). Contours were transferred from CBCT1 to CBCTn via the deformation field, and contour metrics were calculated through comparison with consensus contours generated from human contour set. The average contour metrics for prostate contours on PCT and CBCT were as follows: Dice coefficient-0.892 (PCT), 0.872 (CBCT-Human), 0.824 (CBCT-Deformed); Hausdorff distance-4.75 mm (PCT), 5.22 mm (CBCT-Human), 5.94 mm (CBCT-Deformed); Contour Distance (overall contour)-1.41 mm (PCT), 1.66 mm (CBCT-Human), 2.30 mm (CBCT-Deformed); COM Deviation-2.01 mm (PCT), 2.78 mm (CBCT-Human), 3.45 mm (CBCT-Deformed). For human contours on PCT and CBCT, the difference in average Dice coefficient between PCT and CBCT (approx. 2%) and Hausdorff distance (approx. 0.5 mm) was small compared to the variation between observers for each patient (standard deviation in Dice coefficient of 5% and Hausdorff distance of 2.0 mm). However, additional contouring variation was found for the deformable-generated contours (approximately 5.0% decrease in Dice coefficient and 0.7 mm increase in Hausdorff distance relative to human-generated contours on CBCT). Though deformable contours provide a reasonable starting point for contouring on CBCT, we conclude that contours generated with B-Spline DIR require physician review and editing if they are to be used in the clinic.
authors.affiliation: Department of Radiation Oncology, Josephine Ford Cancer Institute, Henry Ford Health System, Detroit, MI 48202, USA.
authors.forename: Stephen J
authors.initials: SJ
authors.lastname: Gardner
authors.forename: Ning
authors.initials: N
authors.lastname: Wen
authors.forename: Jinkoo
authors.initials: J
authors.lastname: Kim
authors.forename: Chang
authors.initials: C
authors.lastname: Liu
authors.forename: Deepak
authors.initials: D
authors.lastname: Pradhan
authors.forename: Ibrahim
authors.initials: I
authors.lastname: Aref
authors.forename: Richard
authors.initials: R
authors.lastname: Cattaneo
authors.forename: Sean
authors.initials: S
authors.lastname: Vance
authors.forename: Benjamin
authors.initials: B
authors.lastname: Movsas
authors.forename: Indrin J
authors.initials: IJ
authors.lastname: Chetty
authors.forename: Mohamed A
authors.initials: MA
authors.lastname: Elshaikh
mesh_terms: D000465:Algorithms; D006801:Humans; D008297:Male; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*