title: Technology assessment of automated atlas based segmentation in prostate bed contouring.
abstract: BACKGROUND
  Prostate bed (PB) contouring is time consuming and associated with inter-observer variability. We evaluated an automated atlas-based segmentation (AABS) engine in its potential to reduce contouring time and inter-observer variability.
  
  
  METHODS
  An atlas builder (AB) manually contoured the prostate bed, rectum, left femoral head (LFH), right femoral head (RFH), bladder, and penile bulb of 75 post-prostatectomy cases to create an atlas according to the recent RTOG guidelines. 5 other Radiation Oncologists (RO) and the AABS contoured 5 new cases. A STAPLE contour for each of the 5 patients was generated. All contours were anonymized and sent back to the 5 RO to be edited as clinically necessary. All contouring times were recorded. The dice similarity coefficient (DSC) was used to evaluate the unedited- and edited- AABS and inter-observer variability among the RO. Descriptive statistics, paired t-tests and a Pearson correlation were performed. ANOVA analysis using logit transformations of DSC values was calculated to assess inter-observer variability.
  
  
  RESULTS
  The mean time for manual contours and AABS was 17.5- and 14.1 minutes respectively (p = 0.003). The DSC results (mean, SD) for the comparison of the unedited-AABS versus STAPLE contours for the PB (0.48, 0.17), bladder (0.67, 0.19), LFH (0.92, 0.01), RFH (0.92, 0.01), penile bulb (0.33, 0.25) and rectum (0.59, 0.11). The DSC results (mean, SD) for the comparison of the edited-AABS versus STAPLE contours for the PB (0.67, 0.19), bladder (0.88, 0.13), LFH (0.93, 0.01), RFH (0.92, 0.01), penile bulb (0.54, 0.21) and rectum (0.78, 0.12). The DSC results (mean, SD) for the comparison of the edited-AABS versus the expert panel for the PB (0.47, 0.16), bladder (0.67, 0.18), LFH (0.83, 0.18), RFH (0.83, 0.17), penile bulb (0.31, 0.23) and rectum (0.58, 0.09). The DSC results (mean, SD) for the comparison of the STAPLE contours and the 5 RO are PB (0.78, 0.15), bladder (0.96, 0.02), left femoral head (0.87, 0.19), right femoral head (0.87, 0.19), penile bulb (0.70, 0.17) and the rectum (0.89, 0.06). The ANOVA analysis suggests inter-observer variability among at least one of the 5 RO (p value = 0.002).
  
  
  CONCLUSIONS
  The AABS tool results in a time savings, and when used to generate auto-contours for the femoral heads, bladder and rectum had superior to good spatial overlap. However, the generated auto-contours for the prostate bed and penile bulb need improvement.
authors: Department of Epidemiology and Biostatistics, University of Western Ontario, London, Ontario, Canada.
authors: Jeremiah
authors: J
authors: Hwee
authors: Alexander V
authors: AV
authors: Louie
authors: Stewart
authors: S
authors: Gaede
authors: Glenn
authors: G
authors: Bauman
authors: David
authors: D
authors: D'Souza
authors: Tracy
authors: T
authors: Sexton
authors: Michael
authors: M
authors: Lock
authors: Belal
authors: B
authors: Ahmad
authors: George
authors: G
authors: Rodrigues
mesh_terms: D001331:Automation; D006801:Humans; D008297:Male; D008495:Medical Oncology / Q000379:methods; D008953:Models, Anatomic; D015233:Models, Statistical; D015588:Observer Variation; D011467:Prostate / Q000033:anatomy & histology / Q000000981:diagnostic imaging* / Q000473:pathology; D011468:Prostatectomy / Q000379:methods; D011471:Prostatic Neoplasms / Q000532:radiotherapy*; D011859:Radiography; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012016:Reference Values; D015203:Reproducibility of Results; D013673:Technology Assessment, Biomedical; D013997:Time Factors