The role of whole-lesion apparent diffusion coefficient analysis for predicting outcomes of prostate cancer patients on active surveillance.

Abstract

To explore the role of whole-lesion apparent diffusion coefficient (ADC) analysis for predicting outcomes in prostate cancer patients on active surveillance. This study included 72 prostate cancer patients who underwent MRI-ultrasound fusion-targeted biopsy at the initiation of active surveillance, had a visible MRI lesion in the region of tumor on biopsy, and underwent 3T baseline and follow-up MRI examinations separated by at least one year. Thirty of the patients also underwent an additional MRI-ultrasound fusion-targeted biopsy after the follow-up MRI. Whole-lesion ADC metrics and lesion volumes were computed from 3D whole-lesion volumes-of-interest placed on lesions on the baseline and follow-up ADC maps. The percent change in lesion volume on the ADC map between the serial examinations was computed. Statistical analysis included unpaired t tests, ROC analysis, and Fisher's exact test. Baseline mean ADC, ADC0-10th-percentile, ADC10-25th-percentile, and ADC25-50th-percentile were all significantly lower in lesions exhibiting≥50% growth on the ADC map compared with remaining lesions (all P≤0.007), with strongest difference between lesions with and without≥50% growth observed for ADC0-10th-percentile (585±308 vs. 911±336; P=0.001). ADC0-10th-percentile achieved highest performance for predicting≥50% growth (AUC=0.754). Mean percent change in tumor volume on the ADC map was 62.3%±26.9% in patients with GS≥3+4 on follow-up biopsy compared with 3.6%±64.6% in remaining patients (P=0.050). Our preliminary results suggest a role for 3D whole-lesion ADC analysis in prostate cancer active surveillance.