Quantitative Measures by Dedicated Breast PET and MRI for Early Prediction of Response to Neoadjuvant Chemotherapy

Abstract

The objective of this project is to combine imaging metrics from dedicated breast positron emission tomography (dbPET) and magnetic resonance imaging (MRI) with machine learning to produce diagnostic models to inform early redirection of treatment for non-responding patients, and to forego additional treatment for responding patients, sparing them from unnecessary toxic therapy.

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Document Details

Document Type
Technical Report
Publication Date
Oct 01, 2020
Accession Number
AD1129282

Entities

People

  • Ella F Jones

Organizations

  • University of California Regents

Tags

Communities of Interest

  • Biomedical

DTIC Thesaurus Topics

  • Biomedical Research
  • Breast Cancer
  • California
  • Chemotherapy
  • Computational Science
  • Computer Programming
  • Computer Vision
  • Image Processing
  • Machine Learning
  • Magnetic Resonance
  • Magnetic Resonance Imaging
  • Mathematical Models
  • Medical Personnel
  • Models
  • Neoplasms
  • Nuclear Medicine
  • Positron Emission Tomography
  • Positron Emissions
  • Positrons
  • Predictive Modeling
  • Resonance
  • Therapy

Fields of Study

  • Medicine
  • Physics

Readers

  • Medical Imaging.
  • Oncology
  • Systems Analysis and Design

Technology Areas

  • AI & ML