Clinical adequacy assessment of autocontours for prostate IMRT with meaningful endpoints

Abstract

Purpose: To determine if radiation treatment plans created based on autosegmented (AS) regionsof-interest (ROI)s are clinically equivalent to plans created based on manually segmented ROIs, where equivalence is evaluated using probabilistic dosimetric metrics and probabilistic biological endpoints for prostate IMRT. Method and materials: Manually drawn contours and autosegmented ROIs were created for 167 CT image sets acquired from 19 prostate patients. Autosegmentation was performed utilizing Pinnacle's Smart Probabilistic Image Contouring Engine. For each CT set, 78 Gy/39 fraction 7-beam IMRT treatment plans with 1 cm CTV-to-PTV margins were created for each of the three contour scenarios; P MD using manually delineated (MD) ROIs, P AS using autosegmented ROIs, and P AM using autosegmented organ-at-risks (OAR)s and the manually drawn target. For each plan, 1000 virtual treatment simulations with different systematic errors for each simulation and a different random error for each fraction were performed. The statistical probability of achieving dose-volume metrics (coverage probability (CP)), expectation values for normal tissue complication probability (NTCP), and tumor control probability (TCP) metrics for all possible cross-evaluation pairs of ROI types and planning scenarios were reported. In evaluation scenarios, the root mean square loss (RMSL) and maximum absolute loss (MAL) of coverage probability of dose-volume objectives, E[TCP], and E [NTCP] were compared with respect to the base plan created and evaluated with manually drawn contours. Results: Femoral head dose objectives were satisfied in all situations, as well as the maximum dose objectives for all ROIs. Bladder metrics were within the clinical coverage tolerances except D 35Gy for the autosegmented plan evaluated with the manual contours. Dosimetric indices for CTV and rectum could be highly compromised when the definition of the ROIs switched from manually delineated to autosegmented. Seventy-two percent of CT image sets satisfied the worst-case CP thresholds for all dosimetric objectives in all scenarios, the percentage dropped to 50% if biological indices were taken into account. Among evaluation scenarios, (MD,P AM ) bore the highest resemblance to (MD,P MD ) where 99% and 88% of cases met all CP thresholds for bladder and rectum, respectively. Conclusions: When including daily setup variations in prostate IMRT, the dose-volume metric CP, and biological indices of ROIs were approximately equivalent for the plans created based on manually drawn targets and autosegmented OARs in 88% of cases. The accuracy of autosegmented prostates and rectums are impediment to attain statistically equivalent plans created based on manually drawn ROIs.

Clinical Evaluation of Deep Learning and Atlas-Based Auto-Contouring of Bladder and Rectum for Prostate Radiation Therapy

“…5,10,12,21 In addition, dosimetric analysis was performed using static plans only, and therefore geometric uncertainties were not taken into account. 32…”

Quality assurance tool for organ at risk delineation in radiation therapy using a parametric statistical approach

“…Breunig et al showed that standardized training with individual feedback mechanism decreased interobserver delineation variability . Automatic OAR delineation can potentially improve consistency, however, at least some automatic delineated structures required user intervention …”

Dose escalation in the definite target volume

“…Previous work on delivery simulation shows 1,000 treatment courses reduces dosimetric variations to <1%. 29 In order to perform treatment simulation, let X 2 R k denote a sampled random shift vector (for each treatment fraction) and a sampled systematic shift vector (for each simulated treatment course). The elements of these vector samples comprise k independent normally distributed random variables x i $ N 0; r 2 ð Þ.…”