Relationship Between MRI-Based Perfusion Parameters and Ki-67 Expression in Breast Cancer: A Systematic Review and Meta-analysis

Abstract

The purpose of this systematic review and meta-analysis was to assess the quality and diagnostic accuracy of MRI-based radiomics methods for predicting Ki-67 expression in breast cancer. Methods: PubMed, Web of Science, and Embase were searched up until March 10, 2023. Studies that matched research questions and provided sufficient data for quantitative synthesis were included in the systematic review and meta-analysis, respectively. The predictive value of MRI-based radiomics for Ki-67 antigen in patients with breast cancer was assessed using pooled sensitivity (SEN), specificity, and area under the curve (AUC). Meta-regression was performed to explore the cause of heterogeneity. Different covariates were used for subgroup analysis. Results: 31 studies were included in the systematic review; among them, 21 reported sufficient data for meta-analysis. Kep and Ktrans was significantly different between lesions with high and low Ki-67 expression, but Ve was not. The pooled sensitivity, specificity, and AUC of MRI-based radiomics for predicting Ki-67 expression in training cohorts were 0.80 [95% CI, 0.73–0.86], 0.82 [95% CI, 0.78–0.86], and 0.88 [95%CI, 0.85–0.91], respectively. The corresponding values for validation cohorts were 0.81 [95% CI, 0.72–0.87], 0.73 [95% CI, 0.62–0.82], and 0.84 [95%CI, 0.80–0.87], respectively. No publication bias was found based on Deeks' funnel plot.