Comparison of changes in dynamic contrast-enhanced magnetic resonance imaging and flourine-18 fluorodeoxyglucose...

This study aimed to compare the value of differences (Δ) in parameters obtained via both dynamic contrast-enhanced (DCE) magnetic resonance imaging (MRI) and flourine-18 fluorodeoxyglucose positron emission tomography/computed tomography (¹⁸F-FDG PET/CT) between baseline and post-neoadjuvant therapy in predicting the pathological response to neoadjuvant therapy in breast cancer.

A total of 109 patients who underwent both baseline and post-neoadjuvant therapy DCE-MRI and ¹⁸F-FDG PET/CT examinations were retrospectively analyzed. The DCE-MRI parameters and ¹⁸F-FDG PET/CT parameters [metabolic tumor volume (MTV), standardized uptake value (SUV)_max, SUV_mean, and total lesion glycolysis] were recorded at both time points. Additionally, the Δs between these parameters were calculated. Postsurgical pathology reports were documented, and the patients were subsequently categorized into two groups: those exhibiting pathologic complete response (pCR) and those exhibiting partial response. Parameters from DCE-MRI and ¹⁸F-FDG PET/CT were compared to determine which predicted pathological response to neoadjuvant therapy more effectively.

Patients with partial response demonstrated a higher rate of histologic grade 3 than those with pCR (P = 0.030). The only DCE-MRI parameter to indicate a significant difference between the two groups (P = 0.024) was the Δ(%)wash-out rate. Among the baseline parameters, only MTV successfully predicted pathological response (P = 0.033). The only post-neoadjuvant therapy parameter to be predictive of pathological response (P = 0.003) was SUV_mean. In receiver operating characteristic analysis, ΔSUV_mean emerged as the most significant parameter for predicting pathological response, followed by post-neoadjuvant SUV_mean [area under the curve: 0.724 (95% confidence interval: 0.630-0.805) and 0.673 (0.577-0.760), respectively].

The Δ¹⁸F-FDG PET/CT parameters are better than ΔDCE-MRI in predicting pathologic response to neoadjuvant therapy. Among these parameters, ΔSUV_mean is the most successful.

Neoadjuvant chemotherapy (NAC) response is one of the most important criteria in breast cancer prognosis. The two most important imaging modalities in breast cancer diagnosis and follow-up protocols are MRI and ¹⁸F-FDG PET/CT. However, it is not clear which of these two modalities is more successful in predicting the difference in treatment response between baseline and post-NAC.