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Benign and Malignant Breast Lesions: Differentiation Using Microstructural Metrics Derived from Time-Dependent

Yun Su1,2, Ya Qiu3, Xingke Huang1,2

  • 1Department of Radiology, Sun Yat-Sen Memorial Hospital, Sun Yat-Sen University, No. 107 Yanjiang Road West, Guangzhou 510120, People's Republic of China.

Radiology. Imaging Cancer
|April 11, 2025
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Summary

Time-dependent diffusion MRI (Td-dMRI) shows promise for breast lesion diagnosis. Cell density from Td-dMRI better distinguishes malignant from benign breast tumors than conventional apparent diffusion coefficients (ADC).

Keywords:
BreastMR-Diffusion Weighted Imaging

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Area of Science:

  • Radiology and Imaging Science
  • Oncology Diagnostics
  • Biomedical Engineering

Background:

  • Distinguishing benign from malignant breast lesions is crucial for effective patient management.
  • Conventional diffusion-weighted imaging (DWI) provides apparent diffusion coefficients (ADCs) but can have limitations.
  • Advanced diffusion MRI techniques offer potential for improved diagnostic accuracy.

Purpose of the Study:

  • To evaluate the diagnostic performance of microstructural metrics from time-dependent diffusion MRI (Td-dMRI) in differentiating benign and malignant breast lesions.
  • To compare the diagnostic accuracy of Td-dMRI metrics with conventional ADC values.

Main Methods:

  • Prospective study (NCT05373628) involving 102 female participants with 105 breast lesions.
  • Acquisition of oscillating and pulsed gradient encoded Td-dMRI and conventional DWI data.
  • Analysis of Td-dMRI microstructural parameters (cell diameter, density, intracellular volume fraction) and ADC values, followed by receiver operating characteristic analysis.

Main Results:

  • Malignant lesions exhibited higher cell diameter, density, and intracellular volume fraction, and lower ADC compared to benign lesions (P < .001 to P = .001).
  • Cell density derived from Td-dMRI demonstrated the highest area under the receiver operating characteristic curve (0.93).
  • The diagnostic performance of cell density was significantly higher than that of ADC (P = .03).

Conclusions:

  • Cell density, a Td-dMRI microstructural metric, significantly outperforms conventional ADC in distinguishing benign from malignant breast lesions.
  • Td-dMRI offers a promising non-invasive tool for enhancing breast lesion characterization.
  • Further validation of Td-dMRI metrics may improve diagnostic workflows in breast imaging.