Can diffusion-weighted MR imaging and contrast-enhanced MR imaging precisely evaluate and predict pathological response to neoadjuvant chemotherapy in patients with breast cancer?

Clinical evidence regarding the value of MRI for therapy responses assessment in breast cancer is increasing. The objective of this study is to compare the diagnostic capability of diffusion-weighted MR imaging (DW-MRI) and contrast-enhanced MR imaging (CE-MRI) to evaluate and predict pathological response in breast cancer patients receiving neoadjuvant chemotherapy (NAC). We performed a meta-analysis of all available studies of the diagnostic performance of DW-MRI or CE-MRI to evaluate and predict pathological response to NAC in patients with breast cancer. We determined sensitivities and specificities across studies, calculated positive and negative likelihood ratios (LR+ and LR-), diagnostic odds ratio (DOR) and constructed summary receiver operating characteristic curves using hierarchical regression models. Methodological quality was assessed by QUADAS tool. Thirty-four studies met the inclusion criteria and involved 1,932 pathologically confirmed patients in total. Methodological quality was relatively high. DW-MRI sensitivity was 0.93 (95 % CI 0.82-0.97) and specificity was 0.82 (95 % CI 0.70-0.90). Overall LR+ was 5.09 (95 % CI 3.09-8.38), LR- was 0.09 (95 % CI 0.04-0.22), and DOR was 55.59 (95 % CI 21.80-141.80). CE-MRI sensitivity was 0.68 (95 % CI 0.57-0.77) and specificity was 0.91 (95 % CI 0.87-0.94). Overall LR+ was 7.48 (95 % CI 5.29-10.57), LR- was 0.36 (95 % CI 0.27-0.48), and DOR was 20.98 (95 % CI 13.24-33.24). Our study confirms that DW-MRI is a high sensitive and CE-MRI is a high specific modality in predicting pathological response to NAC in breast cancer patients. The combined use of DW-MRI and CE-MRI has the potential to improve the diagnostic performance in monitoring NAC. Further large prospective studies are warranted to assess the actual value of this combination in breast cancer preoperative treatment screening.