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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging
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Diffusion-weighted imaging (b value = 1500 s/mm(2)) is useful to decrease false-positive breast cancer cases due to

Miho Ochi1, Toshiro Kuroiwa, Shunya Sunami

  • 1Diagnostic Radiology Department, Iizuka Hospital, 3-83 Yoshio-machi, Iizuka, Fukuoka, 820-8505, Japan. mochih1@aih-net.com

Breast Cancer (Tokyo, Japan)
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PubMed
Summary

Adding apparent diffusion coefficient (ADC) values from diffusion-weighted imaging (DWI) to the Breast Imaging Reporting and Data System (BI-RADS) significantly improves diagnostic accuracy for differentiating malignant and benign breast lesions.

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Area of Science:

  • Radiology
  • Oncology
  • Medical Imaging

Background:

  • Breast magnetic resonance imaging (MRI) is crucial for lesion characterization.
  • Diffusion-weighted imaging (DWI) provides quantitative metrics like apparent diffusion coefficient (ADC) values.
  • The Breast Imaging Reporting and Data System (BI-RADS) is a standardized classification system for breast imaging findings.

Purpose of the Study:

  • To evaluate the utility of apparent diffusion coefficient (ADC) values in enhancing the diagnostic performance of the Breast Imaging Reporting and Data System (BI-RADS).
  • To compare the diagnostic accuracy of BI-RADS alone versus BI-RADS combined with ADC values for breast lesions.
  • To assess the effectiveness of ADC values in differentiating between benign and malignant breast lesions, particularly ductal carcinoma in situ (DCIS) and fibrocystic changes.

Main Methods:

  • Analysis of apparent diffusion coefficient (ADC) values from diffusion-weighted imaging (DWI) with a b value of 1500 s/mm(2) in 104 breast lesions with confirmed histology.
  • Comparison of mean ADC values between benign and malignant cases, and between specific lesion types like DCIS and fibrocystic changes.
  • Evaluation of diagnostic accuracy by comparing BI-RADS alone (categories 4a, 4b, 5) with BI-RADS augmented by ADC values.

Main Results:

  • Significant differences in mean ADC values were observed between malignant and benign breast lesions (p < 0.0001) and between DCIS and fibrocystic changes (p < 0.002).
  • The addition of ADC values to BI-RADS significantly increased positive predictive values compared to BI-RADS alone (81.3% vs. 70.5% overall; 64.3% vs. 40.9% for DCIS vs. fibrocystic changes).
  • Diagnostic accuracy was substantially improved by incorporating ADC values into the BI-RADS assessment.

Conclusions:

  • The integration of apparent diffusion coefficient (ADC) values derived from diffusion-weighted imaging (DWI) with the Breast Imaging Reporting and Data System (BI-RADS) offers a valuable enhancement for improving differential diagnostic accuracy.
  • This combined approach is particularly beneficial for distinguishing malignant tumors from benign lesions, especially in differentiating ductal carcinoma in situ (DCIS) from fibrocystic changes.
  • While effective for most distinctions, the addition of ADC values did not show significant differentiation between DCIS and ductal hyperplasia.