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Tracking the Mammary Architectural Features and Detecting Breast Cancer with Magnetic Resonance Diffusion Tensor Imaging

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Computed diffusion-weighted imaging with a low-apparent diffusion coefficient-pixel cut-off technique for breast

Toshiki Kazama¹, Taro Takahara², Jun Endo¹

¹Department of Diagnostic Radiology, Tokai University School of Medicine, Isehara, Japan.

The British Journal of Radiology

|July 2, 2023

Summary

Computed diffusion-weighted imaging (cDWI) with a low apparent diffusion coefficient (ADC) pixel cut-off technique significantly improves breast cancer detection compared to measured DWI (mDWI). This method enhances image quality by increasing contrast and reducing fat signals, leading to better diagnostic performance.

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Area of Science:

Radiology
Medical Imaging
Oncology

Background:

Diffusion-weighted imaging (DWI) is crucial for breast MRI, but image quality can be affected by artifacts like fat suppression failure.
Computed DWI (cDWI) with an apparent diffusion coefficient (ADC) pixel cut-off technique offers a potential method to improve DWI quality and diagnostic accuracy.

Purpose of the Study:

To compare the image quality and diagnostic performance of cDWI with a low-ADC-pixel cut-off technique against measured DWI (mDWI).
To evaluate the effectiveness of cDWI in improving contrast and reducing artifacts for breast cancer detection.

Main Methods:

Retrospective analysis of 87 malignant and 72 benign breast lesions from breast MRI examinations.
Generation of cDWI using high b-values (800, 1200, 1500 s/mm²) and various ADC cut-off thresholds (0-0.6 ×10⁻³ mm²/s) from standard DWI (b-values 0 and 800 s/mm²).
Radiologist assessment of fat suppression, lesion visibility, contrast enhancement, and diagnostic performance using ROC analysis.

Main Results:

Applying ADC cut-off thresholds of 0.3 or 0.6 (×10⁻³ mm²/s) significantly improved fat suppression (p < .05).
cDWI with b-values of 1200 or 1500 s/mm² demonstrated superior contrast compared to mDWI (p < .01).
The area under the ROC curve for breast cancer detection was significantly higher for cDWI (0.909) than for mDWI (0.837) (p < .01).

Conclusions:

The cDWI with a low-ADC-pixel cut-off technique offers superior diagnostic performance for breast cancer detection compared to mDWI.
This technique enhances image quality by improving contrast and effectively eliminating un-suppressed fat signals, thereby increasing diagnostic accuracy.