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Updated: Feb 7, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
Published on: March 21, 2025
Objective value on Apparent diffusion coefficient (ADC) map to categorize the intensity of diffusion-weighted imaging
Thais Caldara Mussi1, Tatiana Martins1,2, Adriano Tachibana1
1Hospital Israelita Albert Einstein, São Paulo, SP, Brasil.
Purpose:
To identify objective and subjective criteria on multiparametric prostate MRI that can be helpful for prostate cancer detection.
Materials And Methods:
Retrospective study, IRB approved, including 122 patients who had suspicious lesion on MRI and who underwent prostate biopsy with ultrasonography (US)/MRI imaging fusion. There were 60 patients with positive biopsies and 62 with negative biopsies. MRI of these patients were randomized and evaluated independently by two blinded radiologists. The following variables were analyzed in each lesion: morphology, contours, T2 signal, diffusion restriction (subjective impression and objective values), hyper-enhancement, contact with transition zone or prostatic contour, prostatic contour retraction, Likert and PIRADS classification.
Results:
Apparent diffusion coefficient (ADC) value was the best predictor of positivity for prostate cancer, with mean value of 1.08 (SD 0.20) and 1.09 mm2/sec (SD 0.24) on negative biopsies and 0.81 (SD 0.22) and 0.84 mm2/sec (SD 0.22) on positive biopsies for readers 1 and 2, respectively (p < 0.001 in both analysis). For the others categorical variables evaluated the best AUC for reader 1 was subjective intensity of diffusion restriction (AUC of 0.74) and for reader 2 was hyper-enhancement (AUC of 0.65), all inferior comparing to the value of ADC map. Interobserver agreement ranged from 0.13 to 0.75, poor in most measurements, and good or excellent (kappa > 0.6) only in lesion size and ADC values.
Conclusions:
Diffusion restriction with lower ADC-values is the best parameter to predict cancer on MRI prior to biopsy. Efforts to establish an ADC cutoff value would improve cancer detection, especially for less experience reader.
Insights
Lower apparent diffusion coefficient (ADC) values on multiparametric prostate MRI are the best indicator for prostate cancer detection. Establishing a specific ADC cutoff can enhance diagnostic accuracy, particularly for less experienced readers.
Area of Science:
- Radiology
- Oncology
- Medical Imaging
Background:
- Multiparametric prostate MRI (mpMRI) is crucial for prostate cancer detection.
- Identifying reliable imaging criteria is essential for accurate diagnosis.
- Objective and subjective parameters on mpMRI require further evaluation.
Purpose of the Study:
- To determine objective and subjective criteria on mpMRI for improved prostate cancer detection.
- To evaluate the diagnostic performance of various MRI parameters.
Main Methods:
- Retrospective study of 122 patients with suspicious MRI lesions undergoing biopsy.
- Two blinded radiologists independently assessed MRI variables including morphology, diffusion restriction (subjective and objective), and hyper-enhancement.
- Analysis included Likert and PI-RADS classification, with ultrasonography/MRI fusion for biopsy guidance.
Main Results:
- Apparent diffusion coefficient (ADC) values were the strongest predictor of prostate cancer (p < 0.001).
- Mean ADC values were significantly lower in positive biopsies (0.81-0.84 mm²/sec) compared to negative biopsies (1.08-1.09 mm²/sec).
- Interobserver agreement was poor for most variables, except for lesion size and ADC values (kappa > 0.6).
Conclusions:
- Lower ADC values indicating diffusion restriction are the most effective parameter for predicting prostate cancer on MRI.
- Establishing a definitive ADC cutoff value is recommended to enhance cancer detection rates.
- This is particularly beneficial for improving accuracy among less experienced radiologists.
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