Pilot Study of the Use of Hybrid Multidimensional T2-Weighted Imaging-DWI for the Diagnosis of Prostate Cancer and Evaluation of Gleason Score.

The objective of our study was to evaluate the role of a hybrid T2-weighted imaging-DWI sequence for prostate cancer diagnosis and differentiation of aggressive prostate cancer from nonaggressive prostate cancer.

Twenty-one patients with prostate cancer who underwent preoperative 3-T MRI and prostatectomy were included in this study. Patients underwent a hybrid T2-weighted imaging-DWI examination consisting of DW images acquired with TEs of 47, 75, and 100 ms and b values of 0 and 750 s/mm(2). The apparent diffusion coefficient (ADC) and T2 were calculated for cancer and normal prostate ROIs at each TE and b value. Changes in ADC and T2 as a function of increasing the TE and b value, respectively, were analyzed. A new metric termed "PQ4" was defined as the percentage of voxels within an ROI that has increasing T2 with increasing b value and has decreasing ADC with increasing TE.

ADC values were significantly higher in normal ROIs than in cancer ROIs at all TEs (p < 0.0001). With increasing TE, the mean ADC increased 3% in cancer ROIs and increased 12% in normal ROIs. T2 was significantly higher in normal ROIs than in cancer ROIs at both b values (p ≤ 0.0002). The mean T2 decreased with increasing b value in cancer ROIs (ΔT2 = -17 ms) and normal ROIs (ΔT2 = -52 ms). PQ4 clearly differentiated normal ROIs from prostate cancer ROIs (p = 0.0004) and showed significant correlation with Gleason score (ρ = 0.508, p < 0.0001).

Hybrid MRI measures the response of ADC and T2 to changing TEs and b values, respectively. This approach shows promise for detecting prostate cancer and determining its aggressiveness noninvasively.

AJR. American journal of roentgenology. 2016 Jun 28 [Epub ahead of print]

Meredith Sadinski, Gregory Karczmar, Yahui Peng, Shiyang Wang, Yulei Jiang, Milica Medved, Ambereen Yousuf, Tatjana Antic, Aytekin Oto

1 Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637., 1 Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637., 2 School of Electronic and Information Engineering, Beijing Jiaotong University, Beijing, China., 1 Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637., 1 Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637., 1 Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637., 1 Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637., 3 Department of Pathology, University of Chicago, Chicago, IL., 1 Department of Radiology, University of Chicago, 5841 S Maryland Ave, MC 2026, Chicago, IL 60637.