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Updated: Oct 14, 2025

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
MRI grading for the prediction of prostate cancer aggressiveness
M Boschheidgen1, L Schimmöller2, C Arsov3
1Department of Diagnostic and Interventional Radiology, Medical Faculty, University Dusseldorf, Moorenstr. 5, 40225, Düsseldorf, Germany.
Objectives:
T o evaluate the value of multiparametric MRI (mpMRI) for the prediction of prostate cancer (PCA) aggressiveness.
Methods:
In this single center cohort study, consecutive patients with histologically confirmed PCA were retrospectively enrolled. Four different ISUP grade groups (1, 2, 3, 4-5) were defined and fifty patients per group were included. Several clinical (age, PSA, PSAD, percentage of PCA infiltration) and mpMRI parameters (ADC value, signal increase on high b-value images, diameter, extraprostatic extension [EPE], cross-zonal growth) were evaluated and correlated within the four groups. Based on combined descriptors, MRI grading groups (mG1-mG3) were defined to predict PCA aggressiveness.
Results:
In total, 200 patients (mean age 68 years, median PSA value 8.1 ng/ml) were analyzed. Between the four groups, statistically significant differences could be shown for age, PSA, PSAD, and for MRI parameters cross-zonal growth, high b-value signal increase, EPE, and ADC (p < 0.01). All examined parameters revealed a significant correlation with the histopathologic biopsy ISUP grade groups (p < 0.01), except PCA diameter (p = 0.09). A mixed linear model demonstrated the strongest prediction of the respective ISUP grade group for the MRI grading system (p < 0.01) compared to single parameters.
Conclusions:
MpMRI yields relevant pre-biopsy information about PCA aggressiveness. A combination of quantitative and qualitative parameters (MRI grading groups) provided the best prediction of the biopsy ISUP grade group and may improve clinical pathway and treatment planning, adding useful information beyond PI-RADS assessment category. Due to the high prevalence of higher grade PCA in patients within mG3, an early re-biopsy seems indicated in cases of negative or post-biopsy low-grade PCA.
Key Points:
• MpMRI yields relevant pre-biopsy information about prostate cancer aggressiveness. • MRI grading in addition to PI-RADS classification seems to be helpful for a size independent early prediction of clinically significant PCA. • MRI grading groups may help urologists in clinical pathway and treatment planning, especially when to consider an early re-biopsy.
Insights
Multiparametric MRI (mpMRI) provides valuable pre-biopsy information on prostate cancer (PCA) aggressiveness. Combining mpMRI parameters into an MRI grading system significantly improves the prediction of PCA aggressiveness compared to individual metrics.
Area of Science:
- Radiology
- Oncology
- Urology
Background:
- Prostate cancer (PCA) aggressiveness prediction is crucial for treatment planning.
- Multiparametric MRI (mpMRI) is increasingly used in PCA diagnosis.
Purpose of the Study:
- To evaluate the value of mpMRI in predicting prostate cancer aggressiveness.
- To develop and assess an MRI grading system for PCA aggressiveness.
Main Methods:
- Retrospective cohort study of 200 patients with histologically confirmed PCA.
- Evaluation of clinical and mpMRI parameters correlated with ISUP grade groups.
- Development of MRI grading groups (mG1-mG3) based on combined descriptors.
Main Results:
- mpMRI parameters (ADC, signal increase, EPE, cross-zonal growth) showed significant differences between ISUP grade groups.
- All evaluated parameters, except PCA diameter, correlated significantly with ISUP grade groups.
- The developed MRI grading system demonstrated the strongest prediction of ISUP grade groups.
Conclusions:
- mpMRI provides relevant pre-biopsy information on PCA aggressiveness.
- The MRI grading system, combining quantitative and qualitative parameters, offers superior prediction of PCA aggressiveness.
- This grading system can aid in clinical decision-making and treatment planning, potentially guiding early re-biopsy decisions.
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