Four-quadrant vector mapping of hybrid multidimensional MRI data for the diagnosis of prostate cancer

Purpose: The interpretation of prostate multiparametric magnetic resonance imaging (MRI) is subjective in nature, and there is large inter-observer variability among radiologists and up to 30% of clinically significant cancers are missed. This has motivated the development of new MRI techniques and sequences, especially quantitative approaches to improve prostate cancer diagnosis. Using hybrid multidimensional MRI, apparent diffusion coefficient (ADC) and T2 have been shown to change as a function of echo time (TE) and b-values, and that this dependence is different for cancer and benign tissue, which can be exploited for prostate cancer diagnosis. The purpose of this study is to investigate whether four-quadrant vector mapping of hybrid multidimensional MRI (HM-MRI) data can be used to diagnose prostate cancer (PCa) and determine cancer aggressiveness. Methods: Twenty-one patients with confirmed PCa underwent preoperative MRI prior to radical prostatectomy. Axial HM-MRI were acquired with all combinations of TE = 47, 75, 100 ms and b-values of 0, 750, 1500 s/mm(2), resulting in a 3 x 3 data matrix associated with each voxel. Prostate Quadrant (PQ) mapping analysis represents HM-MRI data for each voxel as a color-coded vector in the four-quadrant space of HM-MRI parameters (a 2D matrix of signal values for each combination of b-value and TE) with associated amplitude and angle information representing the change in T2 and ADC as a function of b-value and TE, respectively. Results: Cancers have a higher PQ4 (22.50% +/- 21.27%) and lower PQ2 (69.86% +/- 28.24%) compared to benign tissue: peripheral, transition, and central zone (PQ4 = 0.13% +/- 0.56%, 5.73% +/- 15.07%, 2.66% +/- 4.05%, and PQ2 = 98.51% +/- 3.05%, 86.18% +/- 21.75%, 93.38% +/- 9.88%, respectively). Cancers have a higher vector angle (206.5 +/- 41.8.) and amplitude (0.017 +/- 0.013) compared to benign tissue. PQ metrics showed moderate correlation with Gleason score (|rho| = 0.388-0.609), with more aggressive cancers being associated with increased PQ4 and angle and reduced PQ2 and amplitude. A combination of four-quadrant analysis metrics provided an area under the curve of 0.904 (p < 0.001) for the differentiation of prostate cancer from benign prostatic tissue. Conclusions: Four-quadrant vector mapping of HM-MRI data provides effective cancer markers, with cancers associated with high PQ4 and high vector angle and lower PQ2 and vector amplitude.