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

Br J Radiol. 2023 Nov;96(1151):20220951. doi: 10.1259/bjr.20220951. Epub 2023 Jul 10.

Abstract

Objective: This study aimed to compare the image quality and diagnostic performance of computed diffusion-weighted imaging (DWI) with low-apparent diffusion coefficient (ADC)-pixel cut-off technique (cDWI cut-off) and actual measured DWI (mDWI).

Methods: Eighty-seven consecutive patients with malignant breast lesions and 72 with negative breast lesions who underwent breast MRI were retrospectively evaluated. Computed DWI with high b-values of 800, 1200, and 1500 s/mm2 and ADC cut-off thresholds of none, 0, 0.3, and 0.6 (×10-3 mm2/s) were generated from DWI with two b-values (0 and 800 s/mm2). To identify the optimal conditions, two radiologists evaluated the fat suppression and lesion reduction failure using a cut-off technique. The contrast between breast cancer and glandular tissue was evaluated using region of interest analysis. Three other board-certified radiologists independently assessed the optimised cDWI cut-off and mDWI data sets. Diagnostic performance was evaluated using receiver operating characteristic (ROC) analysis.

Results: When an ADC cut-off threshold of 0.3 or 0.6 (× 10-3 mm2/s) was applied, fat suppression improved significantly (p < .05). The contrast of the cDWI cut-off with a b-value of 1200 or 1500 s/mm2 was better than the mDWI (p < .01). The ROC area under the curve for breast cancer detection was 0.837 for the mDWI and 0.909 for the cDWI cut-off (p < .01).

Conclusion: The cDWI cut-off provided better diagnostic performance than mDWI for breast cancer detection.

Advances in knowledge: Using the low-ADC-pixel cut-off technique, computed DWI can improve diagnostic performance by increasing contrast and eliminating un-suppressed fat signals.

MeSH terms

  • Breast / diagnostic imaging
  • Breast / pathology
  • Breast Neoplasms* / pathology
  • Diffusion Magnetic Resonance Imaging / methods
  • Female
  • Humans
  • Retrospective Studies
  • Sensitivity and Specificity