Comparing the Performances of Magnetic Resonance Imaging Size vs Pharmacokinetic Parameters to Predict Response to Neoadjuvant Chemotherapy and Survival in Patients With Breast Cancer

Purpose To compare the value of dynamic contrast-enhanced magnetic resonance imaging-pharmacokinetic (PK) parameters vs tumor volume in predicting breast cancer neoadjuvant chemotherapy response (NACR) and patient survival. Subjects and Methods Sixty-six patients with locally advanced breast cancer who underwent breast MRI monitoring of NACR were retrospectively analyzed. We compared baseline transfer constant ( K trans ), reflux rate contrast ( k ep ), and extracellular extravascular volume fraction ( v e ) with the same parameters obtained at early postchemotherapy MRI, and examined model-independent changes in time-intensity curves (maximum slope, contrast enhancement ratio, and IAUC90). Tumor size changes (tumor volume, single dimension, and Response Evaluation Criteria in Solid Tumors [RECIST]) were also analyzed. The Spearman correlation test was used to assess the association between size and PK parameters, and regression analysis to assess the association with 5-year disease-free survival. Results Higher v e values at baseline were associated with greater decreases in tumor size ( P = 0.008). Changes in K trans and IAUC90 were the strongest predictors of NACR. Changes in IAUC90 ( P = 0.04) and RECIST ( P = 0.003) were independently associated with pathologic response. The only parameter significantly associated with 5-year survival was change in RECIST ( P = 0.001). However, there was a trend toward statistical significance for changes in v e and K trans , with greater changes associated with longer survival. Conclusion Changes in PK and dynamic contrast-enhanced magnetic resonance imaging kinetic parameters may have a role in predicting NACR in breast tumors. Although changes in K trans and IAUC90 are helpful in predicting NACR, they do not show significant association with survival. Early RECIST size change measured by MRI remains the strongest predictor of overall patient survival.