Prediction of Prostate Cancer Aggressiveness Using a Novel Multiparametric Magnetic Resonance Imaging Parameter: Tumor Heterogeneity Index

Abstract

<b><i>Background and Aims:</i></b> The aim of this study was to evaluate if the tumor heterogeneity index can predict the aggressiveness of prostate cancer (PCa) in patients diagnosed by magnetic resonance imaging (MRI) fusion biopsy. <b><i>Material and Methods:</i></b> Patients who underwent MRI fusion prostatic biopsy between July 2019 and December 2020 were retrospectively reviewed. Tumor heterogeneity index (coefficient of variation [CV]) and PI-RADS v2.1 scoring were analyzed by using multiparametric MRI. The patients were divided into 3 groups according to the risk classification, and the correlation between tumor heterogeneity index and PCa aggressiveness was studied by using apparent diffusion coefficient (ADC_mean and ADC_cv), Gleason score (GS), and risk classifications. <b><i>Results:</i></b> One hundred two patients were included in this study. Patients were evaluated as low-risk (group 1) (<i>n</i> = 35), moderate-risk (group 2) (<i>n</i> = 37), and high-risk (group 3) (<i>n</i> = 30). ADC_mean values for all groups were significantly different (<i>p</i> &#x3c; 0.0001). ADC_cv tumor heterogeneity index values were higher in group 2 and group 3 by the score increases in subgroups according to GS, while being higher than group 1 (<i>p</i> &#x3c; 0.001). The multivariate analysis revealed that prostate-specific antigen, PI-RADS, ADC_mean, and ADC_cv values were predictive for tumor aggressiveness. <b><i>Conclusion:</i></b> ADC_cv value as a tissue texture parameter can be used as a new biomarker to evaluate tumor aggressiveness in patients with PCa.