The combination of FDG PET and dynamic contrast-enhanced MRI improves the prediction of disease-free survival in patients with advanced breast cancer after the first cycle of neoadjuvant chemotherapy

The aim of this study was to investigate the potential of FDG PET/CT and MRI in predicting disease-free survival (DFS) after neoadjuvant chemotherapy (NAC) and surgery in patients with advanced breast cancer. The analysis included 54 women with advanced breast cancer. All patients received three cycles of NAC, underwent curative surgery, and then received three cycles of additional chemotherapy. Before and after the first cycle of NAC, all patients underwent sequential PET/CT and MRI. All patients were analysed using a diverse range of parameters. including maximal standardized uptake value (SUV), percent change in SUV (ΔSUV), initial slope of the enhancement curve (MRslope), apparent diffusion coefficient (ADC), tumour size, change in MRslope (ΔMRslope), change in ADC (ΔADC), change in tumour size (Δsize) and other clinicopathological parameters. The relationships between covariates and DFS after surgery were analysed using the Kaplan-Meier method and the multivariate Cox proportional hazards model. Time-dependent receiver operating characteristic curves were used to determine the optimal cut-off values of imaging parameters for DFS. Of the 54 patients, 13 (24 %) experienced recurrence at a median follow-up of 38 months (range 25 - 45 months). Univariate and multivariate analyses showed that a lesser decline in SUV, a lesser decline in MRslope, a lesser increase in ADC, and ER negativity were significantly associated with a poorer DFS (P = 0.0006, ΔSUV threshold -41 %; P = 0.0016, ΔMRslope threshold -6 %; P = 0.011, ΔADC threshold 11 %; and P = 0.0086, ER status, respectively). Patients with a combination of ΔSUV >-41 % and ΔMRslope >-6 % showed a significantly higher recurrence rate (77.8 %) than the remaining of patients (13.3 %, P < 0.0001). Functional parameters of both FDG PET and MRI after the first cycle of NAC are useful for predicting DFS in patients with advanced breast cancer. This approach could lead to an improvement in patient care because ineffective NAC agents could be avoided and more aggressive therapy could be used in high-risk patients. (orig.)