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Magnetic Resonance Imaging01:24

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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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Differences in morphological features and minimum apparent diffusion coefficient values among breast cancer subtypes

Fumi Kato1, Kohsuke Kudo1, Hiroko Yamashita2

  • 1Department of Diagnostic and Interventional Radiology, Hokkaido University Hospital, N14, W5, Kita-ku, Sapporo 060-8648, Japan.

European Journal of Radiology
|January 3, 2016
PubMed
Summary

Breast cancer subtypes can be distinguished using imaging features like shape and minimum apparent diffusion coefficient (ADC) values. These characteristics, assessed via MRI, help differentiate between triple-negative, Luminal A, and Luminal B cancers.

Keywords:
Breast cancer subtypesDiffusion weighed imagingKi-67Magnetic resonance imaging

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Breast cancer comprises diverse subtypes with varying prognoses and treatment responses.
  • Accurate subtype classification is crucial for effective patient management and therapeutic strategies.
  • Magnetic Resonance Imaging (MRI) offers detailed morphological and functional information for breast lesion characterization.

Purpose of the Study:

  • To investigate the utility of morphological features and minimum apparent diffusion coefficient (ADC) values in differentiating breast cancer subtypes.
  • To compare imaging characteristics across different molecular subtypes of invasive breast carcinoma.

Main Methods:

  • A cohort of 98 invasive breast carcinomas from 93 patients undergoing breast MRI was analyzed.
  • Morphological features were assessed using the Breast Imaging Reporting and Data System (BIRADS-MRI).
  • Minimum ADC values were measured, and multivariate logistic regression was employed to identify distinguishing characteristics.

Main Results:

  • Oval/round morphology was significantly associated with triple-negative (TN) breast cancer (90.9% vs. 45.2%).
  • Luminal A cancers exhibited significantly less frequent rim enhancement (34.2% vs. 76.1%) and higher minimum ADC values (834×10(-6)mm(2)/s) compared to Luminal B (HER2-negative) cancers (748×10(-6)mm(2)/s).
  • Minimum ADC values differed significantly between TN-special type (997×10(-6)mm(2)/s) and TN-ductal carcinomas (702×10(-6)mm(2)/s).

Conclusions:

  • Morphological features and minimum ADC values derived from MRI are valuable for distinguishing between breast cancer subtypes.
  • These imaging biomarkers can aid in the non-invasive classification of breast cancer, potentially guiding treatment decisions.