There is a critical need for new alternatives for screening and diagnosis of prostate cancer (PCa). Current methods for detecting and diagnosing prostate cancer (PCa), including serum PSA level, DRE (digital rectal exam), and TRUS-guided (transrectal ultrasound) random prostate biopsy are seriously flawed since they are unreliable and lead to procedures that often do not help and frequently harm patients, at high financial costs. MRI has potential to improve detection and management of PCa, due to its excellent soft tissue contrast and functional information. Nevertheless there is, as of yet, no MRI method that is adequate for routine screening or for guiding biopsies. To be clinically useful ?MRI must identify clinically significant cancers (Gleason 7 or higher) and distinguish them from normal prostate, benign changes, and Gleason 6 ?cancers?. In this resubmission, we propose to extend our previous work on hybrid multi-dimensional MRI (HM-MRI), based on the combination of T2-weighted and diffusion-weighted imaging. This approach is very different from conventional MRI measurements of T2 and ?apparent diffusion coefficient? (ADC). Conventional methods treat T2 and ADC as independent parameters. In contrast, HM-MRI measures the change in T2 as a function of ?b? value, and the change in ADC as a function of ?TE?. HM-MRI exploits the interdependence of T2 and ADC and distinct MR properties of prostate tissue components to increase diagnostic accuracy of PCa diagnosis. We will analyze HM-MRI data to extract volume fractions of the luminal, epithelial, and stromal compartments, and the ADC and T2 of each compartment in each image voxel. Volume fractions of these tissue compartments, when measured using quantitative histology, are known to provide high diagnostic accuracy. This proposal is significantly revised to respond to the previous review. We will test the hypotheses that: 1. HM-MRI data can identify clinically significant PCa, by non-invasively measuring epithelial, stromal, and luminal volume fractions, to provide information similar to quantitative histology. 2. In addition, HM-MRI provides the T2 and ADC of each compartment, and the volume and spatial distribution of these compartments. This information may increase diagnostic accuracy, and cannot be easily obtained from histology. As a result, HM-MRI combined with compartmental analysis can be used clinically to provide high diagnostic accuracy, and non-invasive assessment of PCa aggressiveness.
There is a critical need for new alternatives for screening and diagnosis of prostate cancer (PCa). MRI has potential to improve detection and management of PCa, due to its excellent soft tissue contrast and functional information, but no current clinical MRI method is adequate for routine screening. Here we propose to develop hybrid multi-dimensional MRI (HM-MRI), based on quantitative measurements of the interdependence of T2 and ADC, to significantly increase the accuracy of PCa diagnosis.
