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Updated: Oct 3, 2025
Heterogeneity Mapping of Protein Expression in Tumors using Quantitative Immunofluorescence
Published on: October 25, 2011
Prediction of Prostate Cancer Aggressiveness Using a Novel Multiparametric Magnetic Resonance Imaging Parameter:
Bedriye Koyuncu Sokmen1, Dogukan Sokmen2, Yusuf İlker Comez2
1Department of Radiology, Demiroglu Bilim University, Istanbul, Turkey.
Background And Aims:
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.
Material And Methods:
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 (ADCmean and ADCcv), Gleason score (GS), and risk classifications.
Results:
One hundred two patients were included in this study. Patients were evaluated as low-risk (group 1) (n = 35), moderate-risk (group 2) (n = 37), and high-risk (group 3) (n = 30). ADCmean values for all groups were significantly different (p < 0.0001). ADCcv 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 (p < 0.001). The multivariate analysis revealed that prostate-specific antigen, PI-RADS, ADCmean, and ADCcv values were predictive for tumor aggressiveness.
Conclusion:
ADCcv value as a tissue texture parameter can be used as a new biomarker to evaluate tumor aggressiveness in patients with PCa.
