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Updated: Jun 21, 2026

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

Prostate Microstructure in Prostate Cancer Using 3-T MRI with Diffusion-Relaxation Correlation Spectrum Imaging:

Zhaohuan Zhang¹, Holden H Wu¹, Alan Priester¹

¹From the Department of Radiological Sciences, David Geffen School of Medicine (Z.Z., H.H.W., S.A.M., S.S., A.M.B., M.H., A.A., K.S., S.R., D.R.E.), Department of Bioengineering (Z.Z., H.H.W.), Department of Urology (A.P., R.E.R.), and Department of Pathology and Laboratory Medicine (C.M., A.E.S.), University of California, Los Angeles, 300 UCLA Medical Plaza, Suite B119, Los Angeles, CA 90095.

|June 10, 2020

Summary

This summary is machine-generated.

Diffusion-relaxation correlation spectrum imaging (DR-CSI) shows promise for prostate cancer (PCa) diagnosis. This study validated DR-CSI against histopathology, finding its signal components correlate with tissue microstructures and differ between PCa and benign tissues.

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A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

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Published on: March 21, 2025

Area of Science:

Radiology and Imaging Science
Oncology
Biomedical Engineering

Background:

Microstructural MRI holds potential for prostate cancer (PCa) diagnosis and characterization.
Validation of MRI techniques with histopathology is crucial but often lacking for PCa.
Diffusion-relaxation correlation spectrum imaging (DR-CSI) offers a novel approach to probe tissue microstructure.

Purpose of the Study:

To validate ex vivo DR-CSI for characterizing microstructural tissue compartments in prostate cancer specimens.
To compare DR-CSI findings with registered whole-mount digital histopathology (WMHP) as the reference standard.
To assess the correlation between DR-CSI spectral signal components and histological tissue fractions.

Main Methods:

Prospective study of men with PCa undergoing 3-T MRI and radical prostatectomy.
Ex vivo DR-CSI of fresh prostate specimens within patient-specific molds.
Coregistration of DR-CSI data with whole-mount digital histopathology slides for quantitative analysis of spectral signal and tissue fractions.

Main Results:

Three distinct DR-CSI spectral signal components (fA, fB, fC) were consistently identified.
DR-CSI components significantly correlated with epithelial, stromal, and luminal area fractions (Spearman coefficients: 0.74, 0.80, 0.67; all P < .001).
Prostate cancer tissues showed increased fA and epithelial fraction, and decreased fC and luminal fraction compared to benign tissues.

Conclusions:

DR-CSI signal components are validated as reliable indicators of microscopic tissue compartments in the prostate.
DR-CSI effectively differentiates between prostate cancer and benign prostate tissues based on microstructural characteristics.
This technique shows significant potential for improving the non-invasive diagnosis and characterization of prostate cancer.