Related Experiment Video
Updated: Apr 18, 2026
A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Correlation of MRI-Derived Apparent Diffusion Coefficient (ADC) Values With Gleason Scores in Prostate Cancer and
Victoria Y Bird1,2, Krystina Masihy1, Juan Varela3
1Urology, National Medical Association and Research Group, Gainesville, USA.
Background:
Accurate characterization of prostate cancer (PCa) aggressiveness remains a clinical challenge. While multiparametric MRI (mpMRI) and Prostate Imaging Reporting and Data System (PI-RADS) scoring are widely used, their qualitative nature introduces inter-reader variability. Apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) may provide a more objective biomarker of tumor severity.
Methods:
We retrospectively analyzed 181 lesions from 101 patients with biopsy-proven PCa (2019-2025). The lowest or minimum ADC (ADCmin) value (µm2/s) was recorded for each lesion and correlated with Gleason scores: low-risk (3+3), intermediate-favorable (3+4), intermediate-unfavorable (4+3), and high-risk (≥4+4). Statistical analysis was performed using Welch's analysis of variance (ANOVA) with Games-Howell post hoc testing.
Results:
Mean ADC values showed a progressive decline with increasing Gleason category: 3+3 = 456.5 ± 191 µm2/s; 3+4 = 382.0 ± 188 µm2/s; 4+3 = 296.2 ± 130 µm2/s; ≥4+4 = 222.6 ± 134 µm2/s. Interquartile ranges (IQRs) similarly decreased across categories. Welch's ANOVA demonstrated significant overall group differences (F(3, 84.78) = 18.95, p < 0.001). Games-Howell post hoc tests revealed significantly lower ADC values in 4+3 and ≥4+4 compared with 3+3 (p < 0.001) and in ≥4+4 compared with 3+4 (p < 0.001).
Conclusion:
MRI-derived ADC values inversely correlate with Gleason scores, suggesting their potential as a non-invasive biomarker for PCa aggressiveness. Incorporating ADC values into clinical workflows may enhance biopsy targeting, risk stratification, and treatment planning.
