Novel Diffusion-Weighted MRI for High-Grade Prostate Cancer Detection
Abstract
Our initial findings illustrate the potential of the stretched exponential model parameters to better characterize high-grade prostate cancer. Additional work is underway to establish the correspondence between the DDC and a-maps with histological sections of the entire prostate gland. Given the technical difficulty with comparison of radical prostatectomy histology with imaging, we have also introduced a method to evaluate the accuracy of our novel diffusion imaging with biopsy histology. Development of a non-invasive quantitative imaging biomarker for high grade PCa will be useful for improving biopsy yield and grade accuracy, accurately identifying men appropriate for surveillance versus curative therapy, and reduce biopsies needed.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 01, 2018
- Accession Number
- AD1095816
Entities
People
- Andre Kajdacsy-balla
- Brandon Caldwell
- Hong-Cai Zhou
- Meltem Uyanik
- Michael Abern
- Peter H Gann
- Richard Magin
- Virgilia Macias
Organizations
- University of Illinois at Chicago