Improved Assessments of Breast Cancer Therapies with DCE-MRI

Abstract

14. ABSTRACT Dynamic Contrast Enhancement MRI (DCE MRI) has been used in clinical and pre-clinical trials of anti-angiogenic breast cancer therapies, but its high variability severely reduces the value of this imaging modality to asses the early response to anti-angiogenic therapies in an individual patient. Since the start of this grant we have developed a new pharmacokinetic model for DCE-MRI that removes the effect of hematocrit and blood flow on relative measurement of tumor permeability. The only inputs required by this model are the concentration of two tracers in the tumor vasculature as a function of time. This is an improvement over previous reference-region models that require estimates of the tissue permeability and distribution to volume of one of the agents in addition to the absolute concentration of both agents. An important assumption in this model is that both tracers are detected simultaneously within the tissue of interest; in order to accomplish such task we designed and synthesized a new series of 19F-MRI contrast agents that can be selectively detected within the same region of interest. We also optimized our 19F-DCE-MRI protocol to obtain images of 19F contrast agents with the same temporal resolutions than standard 1H-DCE-MRI. Finally, we were also able to collect 19F images one of the agents in a mouse model of breast cancer with high temporal resolution for such studies.

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Document Details

Document Type
Technical Report
Publication Date
Apr 01, 2011
Accession Number
ADA546733

Entities

People

  • Julio C. Cardenas

Organizations

  • University of Arizona

Tags

DTIC Thesaurus Topics

  • Arteries
  • Biomedical Research
  • Blood
  • Blood Flow
  • Breast Cancer
  • Cancer
  • Chemistry
  • Contrast
  • Crown Ethers
  • Frequency
  • Hematocrit
  • Magnetic Resonance
  • Magnetic Resonance Imaging
  • Measurement
  • Neoplasms
  • Permeability
  • Standards

Fields of Study

  • Medicine

Readers

  • Computational Modeling and Simulation
  • Medical Imaging.
  • Oncology (Cancer Research).