Non-Invasive Phosphorus-31 Magnetic Resonance Spectral Characterization of Breast Tissue Anomalies Using Pattern Recognition and Artificial Intelligence
Abstract
It is highly desirable to develop a non-invasive and pattern recognition technique that can detect and reliably interpret images or spectral data from small volumes of the breast. Due to the pervasive nature of breast cancer in society today, and the consequent need of a highly accurate, early diagnostic tool, this is a very timely proposal that could have a significant impact on women's health. Patient ROtating Delivery of Excitation Off-resonance (RODEO) MRI data has been obtained from Dr. Diana Lindquist at the University of Arkansas for Medical Sciences. These patients, which flagged suspicious regions in breast tissue, have undergone needle biopsies from these suspect regions for pathological examination. With the patient's permission, Dr. Lindquist obtained P-31 MR scans of the flagged suspect tissue and healthy tissue in the same session. Access to data from 6 patients were obtained and made available for analysis in this study. We proposed to use a combination of pattern recognition techniques, including Artificial Neural Networks (ANN), to develop in vivo methods that use breast P-31 MR scans (suspicious and nonsuspicious regions) to diagnose potential malignant tissue. The MR scan data will be paired with the known biopsy results to create a supervised training set. Unfortunately two events occurred to prevent us from completing this study [1-3].
Document Details
- Document Type
- Technical Report
- Publication Date
- Aug 01, 2006
- Accession Number
- ADA458441
Entities
People
- Dan Buzatu
- Diana Lindquist
- Jerry A. Darsey
- Ronald Walker
- Steven Harms
Organizations
- University of Arkansas at Little Rock