Predictive value of preoperative [18F]FDG PET/CT imaging parameters for postoperative recurrence and metastasis in breast cancer patients
Abstract
Purpose To assess the predictive value of preoperative 2-deoxy-2-[¹8F]fluoro-D-glucose positron emission tomography/computed tomography ([18F]FDG PET/CT) imaging parameters in forecasting the recurrence and metastasis following surgery among individuals diagnosed with early-stage breast cancer. Methods A retrospective analysis was performed on 106 female patients with early-stage breast cancer (clinical TNM (cTNM) stage I–II, T1–2, N0–1, M0), all of whom underwent surgical procedures at our institution between January 2021 and December 2023. These individuals were divided into two groups: a non-recurrence group (n=57) and an recurrence/metastasis group (n=49), determined by whether recurrence or metastasis was observed within 24 months postoperatively. Preoperative imaging was carried out using a Discovery 710 scanner, and metabolic parameters were measured. Histological markers were assessed via immunohistochemistry. Results Significant differences were observed in lymphovascular invasion, Ki-67 expression, ER positivity, PR positivity, HER2 status, and TNBC subtype between the two groups. Among PET/CT parameters examined, it was observed that the recurrence/metastasis group exhibited significantly higher values for primary tumor (T) metabolic tumor volume (MTV), T total lesion glycolysis (TLG), axillary lymph nodes (N), maximum standardized uptake value (SUVmax), whole body (WB) MTV, and WB TLG. Multivariate logistic regression identified T MTV, T TLG, N SUVmax, WB MTV, and WB TLG as independent risk factors for recurrence and metastasis (all P<0.05). Receiver operating characteristic (ROC) analysis demonstrated that these parameters had good predictive performance, with combined ROC yielding an area under the curve of 0.805. Conclusion Preoperative [18F]FDG PET/CT imaging parameters may be valuable predictors of postoperative recurrence and metastasis in early-stage breast cancer patients. These findings highlight the potential utility of metabolic imaging in guiding personalized treatment strategies.