title: Evaluation of 4-dimensional computed tomography to 4-dimensional cone-beam computed tomography deformable image registration for lung cancer adaptive radiation therapy.
abstract: OBJECTIVE
  To evaluate 2 deformable image registration (DIR) algorithms for the purpose of contour mapping to support image-guided adaptive radiation therapy with 4-dimensional cone-beam CT (4DCBCT).
  
  
  METHODS
  One planning 4D fan-beam CT (4DFBCT) and 7 weekly 4DCBCT scans were acquired for 10 locally advanced non-small cell lung cancer patients. The gross tumor volume was delineated by a physician in all 4D images. End-of-inspiration phase planning 4DFBCT was registered to the corresponding phase in weekly 4DCBCT images for day-to-day registrations. For phase-to-phase registration, the end-of-inspiration phase from each 4D image was registered to the end-of-expiration phase. Two DIR algorithms-small deformation inverse consistent linear elastic (SICLE) and Insight Toolkit diffeomorphic demons (DEMONS)-were evaluated. Physician-delineated contours were compared with the warped contours by using the Dice similarity coefficient (DSC), average symmetric distance, and false-positive and false-negative indices. The DIR results are compared with rigid registration of tumor.
  
  
  RESULTS
  For day-to-day registrations, the mean DSC was 0.75 ± 0.09 with SICLE, 0.70 ± 0.12 with DEMONS, 0.66 ± 0.12 with rigid-tumor registration, and 0.60 ± 0.14 with rigid-bone registration. Results were comparable to intraobserver variability calculated from phase-to-phase registrations as well as measured interobserver variation for 1 patient. SICLE and DEMONS, when compared with rigid-bone (4.1 mm) and rigid-tumor (3.6 mm) registration, respectively reduced the average symmetric distance to 2.6 and 3.3 mm. On average, SICLE and DEMONS increased the DSC to 0.80 and 0.79, respectively, compared with rigid-tumor (0.78) registrations for 4DCBCT phase-to-phase registrations.
  
  
  CONCLUSIONS
  Deformable image registration achieved comparable accuracy to reported interobserver delineation variability and higher accuracy than rigid-tumor registration. Deformable image registration performance varied with the algorithm and the patient.
authors: Department of Radiation Oncology, Virginia Commonwealth University, Richmond, Virginia, USA.
authors: Salim
authors: S
authors: Balik
authors: Elisabeth
authors: E
authors: Weiss
authors: Nuzhat
authors: N
authors: Jan
authors: Nicholas
authors: N
authors: Roman
authors: William C
authors: WC
authors: Sleeman
authors: Mirek
authors: M
authors: Fatyga
authors: Gary E
authors: GE
authors: Christensen
authors: Cheng
authors: C
authors: Zhang
authors: Martin J
authors: MJ
authors: Murphy
authors: Jun
authors: J
authors: Lu
authors: Paul
authors: P
authors: Keall
authors: Jeffrey F
authors: JF
authors: Williamson
authors: Geoffrey D
authors: GD
authors: Hugo
mesh_terms: D000465:Algorithms; D002289:Carcinoma, Non-Small-Cell Lung / Q000000981:diagnostic imaging* / Q000473:pathology / Q000532:radiotherapy; D054893:Cone-Beam Computed Tomography / Q000379:methods*; D056973:Four-Dimensional Computed Tomography / Q000379:methods*; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology / Q000532:radiotherapy; D015588:Observer Variation; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012119:Respiration; D047368:Tumor Burden