Goal: Use multiparametric MRI and basic clinical variables (age, PSA, PSA density, prostate volume) to estimate the probability of clinically significant prostate cancer (csPCa) and recommend whether biopsy is warranted, before histopathological confirmation is available.

Input modalities

  • Multiparametric MRI (T1w, ADC maps, DWI)
  • Clinical variables: age, PSA, PSA density, prostate volume

Output required

  • Probability of csPCa
  • Binary biopsy recommendation (yes / no)
  • Structured reasoning trace referencing PI-RADS scores, lesion characteristics, zonal anatomy, and capsular contact

Ground truth: Histopathology-confirmed csPCa (ISUP Grade Group >= 2); negative cases confirmed by longitudinal PSA follow-up.

Dataset

Split Cases Notes
Training 75 Radboudumc; real-world class distribution
Validation 75 Radboudumc; up to 5 submissions allowed
Test 250 100 cases from Karolinska Institute (external); 1 submission allowed

Input data (precomputed): Precomputed MRI features as .h5 files + clinical variables as .csv. Raw images are not provided for inference.

Expected output per case: JSON file (~5 KB) containing the probability score and structured reasoning trace.

Primary metric: AUROC

Provided tool: Validated MRI prostate zone segmentation