Keywords:
Artificial Intelligence, Genital / Reproductive system male, Oncology, MR, MR-Diffusion/Perfusion, Biopsy, Computer Applications-Detection, diagnosis, Cancer
Authors:
N. Debs, A. Routier, B. Lorenzi, L. Wood, F. Nicolas, M.-M. Rohé
DOI:
10.26044/ecr2022/C-22165
Purpose
1) Prostate cancer (Pca) overview
- High prevalence: 2nd most common cancer in men [1]
- Diagnostic and treatment decision depend on:
- Level of Prostate Specific Antigen (PSA) from blood sample
- Identification of suspicious lesion using multimodal MRI and scoring from radiologist
- (If suspicion) Prostate biopsy to confirm clinically significant cancer (CSC) from uropathologist
2) Prostate cancer characterization:
- Histopathologic annotation obtained after biopsy or prostatectomy: Gleason score (GS), from Benign (< 6) to 10 [2]
- Lesion with score >= 7: CSC
- Reliable measure of cancer aggressiveness
- But not routinely determined (biopsy is invasive)
- Radiologic annotation based on multi- or bi-parametric MRI: score PIRADS v2.1, from 1 to 5 [3]
- Lesion with score >= 4: considered as CSC (hypothesis)
- Score obtention is less invasive
- Relatively reliable measure [4]
3) Contribution of this study
- State-of-the-art network for automatic systems for PCa detection/diagnosis: focus on GS annotated data [7-11]
- Aim of this study: showing the interest of PIRADS annotated data in addition to GS annotated data