title: Clinical adequacy assessment of autocontours for prostate IMRT with meaningful endpoints.
abstract: OBJECTIVE
  To determine if radiation treatment plans created based on autosegmented (AS) regions-of-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.
  
  
  METHODS
  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; PMDusing manually delineated (MD) ROIs, PASusing autosegmented ROIs, and PAMusing 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 D35Gyfor 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,PAM) bore the highest resemblance to (MD,PMD) 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.
authors.affiliation: Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA.
authors.forename: Hamidreza
authors.initials: H
authors.lastname: Nourzadeh
authors.affiliation: Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA.
authors.forename: William T
authors.initials: WT
authors.lastname: Watkins
authors.affiliation: Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA.
authors.forename: Mahmoud
authors.initials: M
authors.lastname: Ahmed
authors.affiliation: Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA.
authors.forename: Cheukkai
authors.initials: C
authors.lastname: Hui
authors.affiliation: Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA.
authors.forename: David
authors.initials: D
authors.lastname: Schlesinger
authors.affiliation: Department of Radiation Oncology, University of Virginia, Charlottesville, VA, 22908, USA.
authors.forename: Jeffrey V
authors.initials: JV
authors.lastname: Siebers
mesh_terms: D023381:Endpoint Determination; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008297:Male; D011336:Probability; D011471:Prostatic Neoplasms / Q000000981:diagnostic imaging / Q000532:radiotherapy*; D011880:Radiotherapy Planning, Computer-Assisted; D050397:Radiotherapy, Intensity-Modulated / Q000379:methods*
keywords: autocontour; prostate cancer; treatment planning; uncertainties in radiation therapy