Comparison of changes in dynamic contrast-enhanced magnetic resonance imaging and flourine-18 fluorodeoxyglucose positron emission tomography/computed tomography parameters from baseline to post-neoadjuvant therapy in predicting pathological response in breast cancer.

Abstract

Purpose: 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.

Methods: 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.

Results: 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].

Conclusion: 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.

Clinical significance: 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.