A Translational Research Leveraging Diagnostic Accuracy of Innovations in MRI as a Model for Early Breast Cancer...

IntroductionBreast cancer remains a leading cause of cancer-related morbidity and mortality in sub-Saharan Africa, with Uganda experiencing a reported 5% annual increase in cases. Alarmingly, 87% of women in Uganda present with advanced-stage disease that is less responsive to treatment, contributing to the region's disproportionately low survival rate. Early breast cancer detection will be the fundamental intervention to reverse the mortality resulting from breast cancer in Uganda. This study aims to enhance breast cancer screening and early detection in Ugandan women who are at risk through innovative use of quantitative MRI to differentiate between benign and malignant breast lesions for women at risk.MethodsThe study prospectively recruited women at risk of breast cancer who underwent breast ultrafast DCE-MRI from July 2023 to April 2024. A 3.0-T MRI system with a16 channel breast dedicated coil was used with scan durations of up to 10 min. The T1 weighted pre-contrast, T1 weighted post-contrast, T1 weighted dynamic subtracted and Maximum Intensity projection (MIP) sequences were acquired and the histology blinded pharmacokinetic analysis for the breast lesion was done. The initial area under the curve in 30 s after contrast injection (iAUC30), MaxSlope, K^trans, BAT, and υ_e were calculated and used to assess the diagnostic performance.ResultsA total of 52 women were recruited and imaged and 36 lesions were found. Unlike the MaxSlope, K^trans, BAT and υ_e the iAUC30 values exhibited significant differences between benign and malignant lesions with a P-value <.005 and the area under the ROC curve (iAUC30) was 0.9147. The sensitivity, specificity, PPV and NPV of MRI using histology as the gold standard at 95% confidence interval were 70%, 100%, 100% and 73.9% respectively.ConclusionsAbbreviated DCE-MRI protocols with quantitative analysis can effectively differentiate malignant from benign breast lesions with improved compliance and can be adopted as a model of breast cancer screening and early detection for women at risk.