Fusion US/MRI prostate biopsy using a computer aided diagnostic (CAD) system.

Area of Science:

• Urology
• Medical Imaging
• Oncology

Background:

• Prostate cancer (PCa) diagnosis relies on accurate biopsy.
• Fusion prostate biopsy (FPB) integrates MRI with ultrasound for targeted biopsies.
• Computer-aided diagnosis (CAD) systems aim to enhance lesion detection in medical imaging.

Purpose of the Study:

• To evaluate the impact of CAD on prostate cancer detection rates during FPB.
• To compare PCa detection with and without CAD assistance in a prospective study.
• To identify predictors of PCa detection in FPB procedures.

Main Methods:

• Two prospective transperineal FPB series were analyzed: one with CAD assistance and one without.
• PCa detection rates were compared using per-patient and per-target analyses.
• Statistical tests (χ², Mann-Whitney) and regression analyses were employed to assess significance and identify predictors.

Main Results:

• Overall PCa and clinically significant (cs) PCa detection rates showed no significant difference with CAD in per-patient analysis.
• CAD-assisted biopsy demonstrated a significantly higher positive predictive value (PPV) for any PCa in per-target analysis (58% vs. 37.8%).
• PI-RADS Score was the sole independent predictor for any and csPCa detection. In subgroup analysis, CAD significantly improved csPCa detection in anterior/transitional zone lesions (54.5% vs. 11.1%).

Conclusions:

• CAD assistance for FPB may improve the detection of clinically significant prostate cancer in anterior/transitional zone lesions.
• Enhanced lesion identification and contouring by CAD could contribute to improved diagnostic performance in specific scenarios.
• PI-RADS score remains a critical factor in predicting PCa detection during FPB.