Main Session
Sep 28
Pres Poster 01 - Presidential Science Poster Session Showcase

3052 - Clinical Validation of Dose Regimen Generalized AI Prostate SBRT Plans: Dosimetric Comparison, Blinded Physician Review, and Deliverability Assessment

04:00pm - 05:00pm ET
Poster Hall - Exhibit Hall A
Screen: 19
POSTER

Presenter(s)

Nayoon Lee, BA - University of Pennsylvania, Philadelphia, PA

N. J. Lee1, A. Zhao1, L. Wang2, S. Philbrook1, W. R. Green1, E. Berlin1, J. Chojnowski1, M. Costea3, B. Ungun4, R. Vauclin4, E. Mengin4, N. Paragyos4, G. Temiz4, A. Chakrabarti5, and R. McBeth1; 1Department of Radiation Oncology, University of Pennsylvania, Philadelphia, PA, 2Department of Radiation Oncology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, 3TheraPanacea, Lyon, France, 4TheraPanacea, Paris, France, 5Philips Healthcare, Andover, MA

Purpose/Objective(s): To evaluate the clinical readiness of an AI-based automated planning system for prostate SBRT by comparing AI-generated plans against approved manual plans across dosimetric endpoints, blinded physician preference, and delivery quality assurance, while assessing generalization from the vendor-trained 36.25 Gy/5 regimen to the institutional 40 Gy/5 standard.

Materials/Methods: 23 prostate SBRT cases (40 Gy/5 fractions) were replanned with the AI system using identical CT and structure sets as approved clinical plans. Both plan sets were normalized to D95%=100%. The AI model was trained on 36.25 Gy/5 without institution-specific tuning. Target metrics included PTV D95%, D99%, and Paddick Conformity Index. OAR evaluation used an institutional SBRT constraint set; urethral structures were excluded from analysis given CT-only delineation and exclusion from model training. A blinded A/B preference test was conducted on 20 unique cases: urethral objectives were excluded from the evaluation scorecards, and plans were randomized as Plan A/B per-patient. Three physicians (a network attending, a faculty member, and a second-year resident) independently selected Prefer A, Prefer B, or No Preference. Five AI plans underwent patient-specific QA with gamma analysis at 2%/2mm criteria.

Results: AI plans met D95% in all cases with comparable conformality to manual plans. All AI plans used 2 arcs (vs 2–3 for manual), averaging 438 fewer MUs and <10-minute generation time. Excluding urethral structures, 99.2% of DVH objectives were met (390/393). In the blinded review (60 total evaluations), 42% were No Preference and 8% favored the AI plan (Table 1). When a preference was stated, manual plans were preferred 86%. Excluding urethra objectives, all AI plans were considered clinically acceptable by all reviewers. Dosimetrically, AI plans showed higher mid-dose rectal (D33% +149 cGy, D50% +131 cGy) and skin (+189 cGy) values on average, while meeting 99.2% of non-urethral constraints. Patient-specific QA demonstrated 100% gamma pass rates at 2%/2mm across all five plans tested (10/10 fields), with mean gamma values ranging from 0.15 to 0.24.

Conclusion: The AI-based automated planning system generated deliverable, clinically acceptable prostate SBRT plans with successful dose-regimen generalization and improved planning efficiency. Blinded physician review confirmed clinical equivalence for the majority of cases across non-urethral structures. Urethral sparing remains the primary limitation, attributable to CT-only delineation and exclusion from model training. These results support a path toward clinical implementation contingent on MR-informed urethral contouring and vendor optimization of urethral constraints.

Table 1: Blinded Physician Preference (20 Unique Patients)

Reviewer Prefer Manual Prefer AI No Preference
Network Attending 12 1 7
Faculty 2 0 18
PGY-2 Resident 16 4 0
Total (60 evaluations) 30 (50%) 5 (8%) 25 (42%)