Identification of prostate cancer using multiparametric MR imaging characteristics of prostate tissues referenced to whole mount histopathology.

In this study, the objective was to characterize the MR signatures of the various benign prostate tissues and to differentiate them from cancer. Data was from seventy prostate cancer patients who underwent multiparametric MRI (mpMRI) and subsequent prostatectomy. The scans included T2-weighted imaging (T2W), diffusion weighted imaging, dynamic contrast-enhanced MRI (DCE MRI), and MR spectroscopic imaging. Histopathology tissue information was translated to MRI images. The mpMRI parameters were characterized separately per zone and by tissue type. The tissues were ordered according to trends in tissue parameter means. The peripheral zone tissue order was cystic atrophy, high grade prostatic intraepithelial neoplasia (HGPIN), normal, atrophy, inflammation, and cancer. Decreasing values for tissue order were exhibited by ADC (1.8 10-3 mm2/s to 1.2 10-3 mm2/s) and T2W intensity (3447 to 2576). Increasing values occurred for DCE MRI peak (143% to 157%), DCE MRI slope (101%/min to 169%/min), fractional anisotropy (FA) (0.16 to 0.19), choline (7.2 to 12.2), and choline / (creatine + citrate) (0.3 to 0.9). The transition zone tissue order was cystic atrophy, mixed benign prostatic hyperplasia (BPH), normal, atrophy, inflammation, stroma, anterior fibromuscular stroma, and cancer. Decreasing values occurred for ADC (1.6 10-3 mm2/s to 1.1 10-3 mm2/s) and T2W intensity (2863 to 2001). Increasing values occurred for DCE MRI peak (143% to 150%), DCE MRI slope (101%/min to 137%/min), FA (0.18 to 0.25), choline (7.9 to 11.7), and choline / (creatine + citrate) (0.2 to 0.6). Logistic regression was used to create parameter model fits to differentiate cancer from benign prostate tissues. The fits achieved AUCs ≥0.91. This study quantified the mpMRI characteristics of benign prostate tissues and demonstrated the capability of mpMRI to discriminate among benign as well as cancer tissues, potentially aiding future discrimination of cancer from benign confounders.

Magnetic resonance imaging. 2021 Oct 16 [Epub ahead of print]

Matthew Gibbons, Olga Starobinets, Jeffry P Simko, John Kurhanewicz, Peter R Carroll, Susan M Noworolski

Deparment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, USA. Electronic address: ., Deparment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, USA., Department of Urology, University of California, 550 16th Street, San Francisco, CA, USA; Department of Pathology, University of California, 1825 4th Street, San Francisco, CA, USA. Electronic address: ., Deparment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, USA; Department of Urology, University of California, 550 16th Street, San Francisco, CA, USA. Electronic address: ., Department of Urology, University of California, 550 16th Street, San Francisco, CA, USA. Electronic address: ., Deparment of Radiology and Biomedical Imaging, University of California, 185 Berry Street, San Francisco, CA, USA. Electronic address: .

email news signup