Early Detection of Breast Cancer and Recurrence Following Therapy With Magnetic Resonance Imaging and Spectroscopy

Abstract

The major hypothesis of this project is that use of a combination of MRI, MRI with contrast, magnetization transfer contrast and proton MR spectroscopy will lead to improved detection and characterization of breast cancer. At present mammography detects lesions which have about an 80% false positive rate for malignancy. There are strong preliminary indications that the combination of MRI with dynamic contrast uptake studies can both detect lesions and provide improved characterization over mammography. The addition of the metabolically based MRS parameters into an approach based on multivariate classification should improve the characterization even further. Technical progress has been made in three areas: improved spatial localization for MR spectroscopy, the development of multicoil spectral methods and the design and construction of a MR guided needle localization device. In the first year of this study, measurements have been obtained on: 18 patients undergoing breast- conserving surgery and definitive breast irradiation for treatment of early stage breast cancer; 19 patients undergoing breast biopsy for suspicious breast abnormalities, but without a confirmed diagnosis of malignancy; and 1 patient with locally advanced breast cancer. Breast cancer, Characterization, Recurrence, Response to therapy, Magnetic resonance

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Document Details

Document Type
Technical Report
Publication Date
Aug 19, 1994
Accession Number
ADA284901

Entities

People

  • Lawrence Solin
  • Robert E. Lenkinski

Organizations

  • University of Pennsylvania

Tags

DTIC Thesaurus Topics

  • Abnormalities
  • Acquisition
  • Biomedical Research
  • Breast Cancer
  • Cancer
  • Carcinoma
  • Classification
  • Detection
  • Diseases And Disorders
  • Health Services
  • Magnetic Resonance
  • Mammography
  • Materials
  • Neoplasms
  • Resonance
  • Spectroscopy
  • Therapy

Fields of Study

  • Medicine
  • Physics

Readers

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