Heliyon (Jan 2024)

Comparison of MUSE-DWI and conventional DWI in the application of invasive breast cancer and malignancy grade prediction: A comparative study

  • Weicheng Wang,
  • Bowen Dou,
  • Qi Wang,
  • Haogang Li,
  • Changshuai Li,
  • Wenjing Zhao,
  • Longjiang Fang,
  • Dmytro Pylypenko,
  • Yujing Chu

Journal volume & issue
Vol. 10, no. 2
p. e24379

Abstract

Read online

Objective: To compare MUSE-DWI with conventional DWI in assessing lesions of invasive breast cancer and evaluating the ADC values for preoperative histological grading. Methods: A retrospective analysis was conducted on 63 lesions confirmed as invasive breast cancer by surgical or biopsy pathology. Preoperatively, all patients underwent MUSE-DWI, conventional DWI, and dynamic contrast-enhanced (DCE) scans. Two radiologists with over 5 years of experience (intermediate and senior levels, respectively) subjectively evaluated the images for clarity, image artifacts, and distortion. Objective evaluation included signal-to-noise ratio (SNR) of lesions and fibrous tissue, as well as the ADC values of both imaging techniques. Due to the limited number of cases classified as grade I and the insignificant difference in disease-specific survival and recurrence scores between grades I and II tumors, grades I and II were grouped as low-grade, while grade III was classified as high-grade. Receiver operating characteristic (ROC) curves were used to evaluate the efficacy of ADC values in preoperatively predicting the grading of invasive breast cancer. Results: The SNR and subjective quality scores of MUSE-DWI images were significantly higher than those of conventional DWI (p < 0.05). For the same case, the ADC values of MUSE-DWI were lower than those of conventional DWI. The AUC values for predicting the grading of invasive breast cancer were 0.849 for MUSE-DWI and 0.801 for conventional DWI. Conclusion: Compared to conventional DWI, MUSE-DWI significantly reduces artifacts and distortions, greatly improving image quality. Moreover, MUSE-DWI demonstrates higher diagnostic efficacy for preoperative histological grading of invasive breast cancer.

Keywords