Hybrid multidimensional MRI (HM-MRI) uses standard measures, such as T1, T2, and apparent diffusion coefficient (ADC) values, and analyzes how they react to changes in sequence parameters including echo time (TE), repetition time (TR), and b-values. By doing so, clinicians can evaluate tissue characteristics and structure associated with prostate cancer.
In this study, 21 patients with confirmed cases of prostate cancer underwent preoperative 3-tesla MRI. Axial images using HM-MRI were acquired with specific TE and b-values to create an array of data associated with each voxel.
In addition, volumes of three tissue components -- the stroma, epithelium, and lumen -- were calculated by fitting the hybrid data to a three-compartment signal model, with distinct ADC and T2 values associated with each compartment.
In doing so, HM-MRI data showed significantly increased fractional volumes of epithelium and reduced lumen, stroma, ADC, and T2 values, compared with normal tissue. The elevated fractional volumes of the prostatic lumen, stroma, and epithelium signal are significant indications of cancer, the authors noted.
"Prostate tissue composition estimated noninvasively using HM-MRI has better diagnostic accuracy of detecting prostate cancer and determining the aggressiveness of cancer compared to conventional T2 and ADC values," study co-author Aritrick Chatterjee, PhD, from the department of radiology at the University of Chicago, told AuntMinnie.com.
These parameters can be measured noninvasively using HM-MRI, he said, adding that the "novel quantitative parameters have the potential to improve prostate cancer diagnosis and determine the aggressiveness of prostate cancer."
