Magnetic Resonance Arterial Spin Tagging for Non-Invasive Pharmacokinetic Analysis of Breast Cancer

Abstract

This research project concerns the development of MRI arterial spin tagging to non-invasively measure breast tissue perfusion. The specific aims are to (1) refine arterial spin tagging pulse sequences, (2) develop automated data analysis software, and (3) compare the technique to first-pass contrast-enhanced MRI and biopsy. The scope of effort is mainly limited to technical developments. However, the project includes a performance comparison with first-pass, contrast-enhanced MRI in 60 patients. During the past year, the spin-tagging pulse sequences have been rewritten for a new, research-only, GE 1 .5T Horizon LX Echospeed CV/I MRI system at UC Davis. New image processing software, and software for statistical analysis of spin tagging and contrast enhanced dynamic scans, has been written. Prior software was enhanced for easier use by clinicians. Additional patient studies were not done, due to the loss of the co-investigator on the project, and to the lack of availability of an MRI system that could run the pulse sequences, for several months. As a result, the budget and schedule of the project was officially pushed back approximately six months, into the third year of the project, which was originally designed with very light project activity.

Open PDF

Document Details

Document Type
Technical Report
Publication Date
Oct 01, 1999
Accession Number
ADA386076

Entities

People

  • Michael Buonocore

Organizations

  • University of California

Tags

DTIC Thesaurus Topics

  • Breast Cancer
  • Computer Programming
  • Computer Programs
  • Computers
  • Contrast
  • Data Acquisition
  • Data Processing
  • Data Sets
  • High Resolution
  • Image Processing
  • Imaging Techniques
  • Magnetic Resonance
  • Materials
  • Neoplasms
  • Radio Frequency Pulses
  • Resonance
  • Statistical Analysis

Readers

  • Clinical Trial Research.
  • Geospatial Intelligence and Artificial Intelligence Analytics
  • Oncology and Biomarker-Based Cancer Detection.