Technology assessment of automated atlas based segmentation in prostate bed contouring

Abstract

BackgroundProstate 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.MethodsAn 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.ResultsThe 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).ConclusionThe 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.

The utility of atlas-assisted segmentation in the male pelvis is dependent on the interobserver agreement of the structures segmented

“…These data are in broad agreement with other studies in this area. 5,16,17 The statistical analysis of the various agreement metrics used in this study does not indicate any significant change in the interobserver agreement with and without the use of ABAS apart from the prostate. For this structure, interobserver agreement was significantly improved on three metrics (DSC, logit DSC and MDC) with the use of ABAS using paired Student's t-test.…”

“…1,4,5,16 Two of these 4,16 address the male pelvis. Lin et al 4 gives the timings for individual structures (femurs, prostate, bladder and rectum) and found broadly similar time savings-the rectum was the structure that showed the least time saving in their study.…”

Assessment of Multiple Atlas Based Segmentation in Prostate Bed Contouring

“…Five pelvic CT simulation datasets (512 x 512 pixels, 3mm slice thickness, 120 kVp) of five different prostate bed patients were each contoured by an expert panel of five radiation oncologists [1]. The six structures specifically delineated were prostate bed, rectum, bladder, penile bulb, and left and right femoral heads.…”

“…Previous studies have demonstrated that AABS decreases inter-and intra-observer variability as well as contouring time in multiple cancer types [1,[3][4][5]. Yet, some research suggests the need for further improvement of AABS approaches, as illustrated by Hwee, et al where they found that only 12% of their auto-contoured images were considered clinically acceptable by blinded human observers [1]. Previous studies have not characterized, in particular, any differences between single best matching (SBM) and multiple best matching (MBM) approaches, or differences between contours when the number of best matches is varied when using MBM.…”

“…Advancements in radiotherapy, such as intensity-modulated radiotherapy (IMRT) and imageguided radiotherapy (IGRT), improve therapeutic outcome by facilitating dose escalation in target tissue, while sparing adjacent normal tissues [1]. These advancements also demand highcontouring accuracy from radiation oncologists in order to optimize patient outcomes.…”