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Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...
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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
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MRI-Derived Body Composition and Breast Cancer Risk in Postmenopausal Women: UK Biobank Study.

Livingstone Aduse-Poku1, Lusine Yaghjyan1, Stephen E Kimmel1

  • 1Department of Epidemiology, College of Public Health & Health Professions & College of Medicine, University of Florida, 2004 Mowry Road, 2nd Floor, Gainesville, FL 32610, USA.

Cancers
|December 30, 2025
PubMed
Summary

Higher visceral adipose tissue (VAT) and muscle-fat infiltration (MFI) in postmenopausal women are linked to increased breast cancer risk. These body composition measures may improve risk prediction and prevention strategies.

Keywords:
UK biobankadipose tissuebreast cancermagnetic resonance imagingskeletal muscle

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Area of Science:

  • Oncology
  • Radiology
  • Epidemiology

Background:

  • Obesity is a known risk factor for breast cancer mortality in postmenopausal women.
  • Specific adipose tissue and skeletal muscle components linked to breast cancer risk require clarification.
  • This study investigates associations between MRI-assessed body composition and breast cancer risk.

Purpose of the Study:

  • To assess the relationship between magnetic resonance imaging (MRI)-measured adiposity and skeletal muscle mass with breast cancer risk in postmenopausal women.
  • To identify specific body composition metrics associated with increased breast cancer risk.
  • To explore potential improvements in breast cancer risk prediction using imaging-derived data.

Main Methods:

  • Analysis of data from 15,669 postmenopausal women in the UK Biobank with MRI body composition assessment.
  • Cox proportional-hazards regression used to estimate hazard ratios (HRs) for breast cancer risk, adjusting for confounders.
  • Restricted cubic splines employed to model nonlinear relationships between visceral adipose tissue (VAT), muscle-fat infiltration (MFI), and breast cancer risk.

Main Results:

  • Higher VAT levels were significantly associated with increased breast cancer risk (aHR = 1.24).
  • Elevated MFI was also linked to greater breast cancer risk (aHR = 1.53).
  • These associations remained significant after excluding early cancer diagnoses and showed a J-shaped relationship.

Conclusions:

  • Increased visceral adipose tissue (VAT) and muscle-fat infiltration (MFI) are associated with higher breast cancer risk in postmenopausal women.
  • MRI-derived body composition measures, specifically VAT and MFI, show potential for enhancing breast cancer risk prediction.
  • Findings suggest these imaging biomarkers could inform targeted prevention strategies for postmenopausal breast cancer.