Novel Diffusion-Weighted MRI for High-Grade Prostate Cancer Detection

Abstract

Diffusion-weighted MRI with the calculated apparent diffusion coefficient (ADC) has been associated with prostate cancer (PCa) grade however there is opportunity to improve the accuracy. We therefore implemented a quantitative fractional order calculus (FROC) model for the first time for PCa detection. A retrospective cohort of 37 men undergoing MRI and confirmatory biopsy (n=31) and radical prostatectomy (n=6) were studied. The FROC model was compared to ADC and the stretched exponential model (SEM) of diffusion. FROC was found to have improved accuracy (AUC = 0.82) compared to ADC and to the clinical standard of care (PI-RADS, AUC = 0.74). Therefore, a prospective validation study of 50 men with no prior biopsy and suspected PCa was performed. A unique image acquisition protocol was designed and implemented for the study. The FROC model performed similarly as in the retrospective cohort and to ADC (both AUC = 0.80). FROC significantly outperformed PI-RADS (AUC = 0.63). We conclude that quantitative diffusion parameters improve PCa detection.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2021
Accession Number
AD1152630

Entities

People

  • Andre Kajdacsy-balla
  • Hong-Cai Zhou
  • Meltem Uyanik
  • Michael Abern
  • Peter H Gann
  • Richard Magin
  • Virgilia Macias

Organizations

  • University of Illinois at Chicago

Tags

DTIC Thesaurus Topics

  • Acquisition
  • Biomedical Research
  • Classification
  • Department Of Defense
  • Detection
  • Epidemiology
  • Health Services
  • Illinois
  • Image Processing
  • Information Science
  • Medical Personnel
  • Patient Care
  • Physicians
  • Predictive Modeling
  • Prostate Cancer
  • Public Health
  • Standards
  • Statistical Analysis
  • Universities

Fields of Study

  • Medicine

Readers

  • Medical Imaging.
  • Oncology and Biomarker-Based Cancer Detection.