AIM: To determine the use of early and final treatment F-FDG PET/CT in the prediction of response to neoadjuvant chemotherapy (NAC) and its role in the prognosis of patients with locally advanced breast cancer (LABC). METHODS: One hundred thirty-two patients underwent a baseline FDG PET/CT (PET-1) after the second course of chemotherapy (PET-2) and after the last course (PET-3). Breast tumors were categorized into molecular phenotypes and risk categories according to the biological prognostic factors obtained by immunohistochemistry. PET/CT scans were semiquantitatively evaluated, obtaining the Δ% SUV1-2 and SUV1-3 in primary tumor and axillary lymph nodes to establish response groups attending to EORTC criteria. Moreover, a binary assessment was obtained classifying the studies as positive or negative. Histopathological response was obtained in breast and lymph node specimens. Overall survival (OS) and disease-free survival (DFS) were obtained after the follow-up. ROC analysis was performed to determine a cutoff value of Δ% SUV1-2 and SUV1-3 for the prediction of response and prognosis. Relations between phenotypes, metabolic behavior, final histopathological response, OS, and DFS were evaluated. RESULTS: In binary analysis, only PET-3 was able to predict histopathological response in lymph nodes. The cutoff values of %Δ SUV1-2 and %Δ SUV1-3 with the best sensitivity and specificity in the prediction of response in breast tumor were 62% (Se: 70% and Sp: 69%) and 84% (Se: 70% and Sp: 88%). A %ΔSUV1-3 of 74% in breast tumor was a predictor of DFS (AUC = 0.647; P = 0.037, Se: 52% and Sp: 66%). Kaplan-Meier analysis revealed significant relations between the binary lymph node assessment of PET-3 with OS (P = 0.016, χ = 5.78) and DFS (P = 0.003, χ = 9.10). CONCLUSIONS: End-of-treatment F-FDG PET/CT was a predictor of lymph node response and prognosis. Most of metabolic response variables related to histopathological response showed association with the prognosis.
AIM: To determine the use of early and final treatment F-FDG PET/CT in the prediction of response to neoadjuvant chemotherapy (NAC) and its role in the prognosis of patients with locally advanced breast cancer (LABC). METHODS: One hundred thirty-two patients underwent a baseline FDG PET/CT (PET-1) after the second course of chemotherapy (PET-2) and after the last course (PET-3). Breast tumors were categorized into molecular phenotypes and risk categories according to the biological prognostic factors obtained by immunohistochemistry. PET/CT scans were semiquantitatively evaluated, obtaining the Δ% SUV1-2 and SUV1-3 in primary tumor and axillary lymph nodes to establish response groups attending to EORTC criteria. Moreover, a binary assessment was obtained classifying the studies as positive or negative. Histopathological response was obtained in breast and lymph node specimens. Overall survival (OS) and disease-free survival (DFS) were obtained after the follow-up. ROC analysis was performed to determine a cutoff value of Δ% SUV1-2 and SUV1-3 for the prediction of response and prognosis. Relations between phenotypes, metabolic behavior, final histopathological response, OS, and DFS were evaluated. RESULTS: In binary analysis, only PET-3 was able to predict histopathological response in lymph nodes. The cutoff values of %Δ SUV1-2 and %Δ SUV1-3 with the best sensitivity and specificity in the prediction of response in breast tumor were 62% (Se: 70% and Sp: 69%) and 84% (Se: 70% and Sp: 88%). A %ΔSUV1-3 of 74% in breast tumor was a predictor of DFS (AUC = 0.647; P = 0.037, Se: 52% and Sp: 66%). Kaplan-Meier analysis revealed significant relations between the binary lymph node assessment of PET-3 with OS (P = 0.016, χ = 5.78) and DFS (P = 0.003, χ = 9.10). CONCLUSIONS: End-of-treatment F-FDG PET/CT was a predictor of lymph node response and prognosis. Most of metabolic response variables related to histopathological response showed association with the prognosis.
Authors: Mette S van Ramshorst; Suzana C Teixeira; Bas B Koolen; Kenneth E Pengel; Kenneth G Gilhuijs; Jelle Wesseling; Sjoerd Rodenhuis; Renato A Valdés Olmos; Emiel J Rutgers; Wouter V Vogel; Gabe S Sonke; Marie-Jeanne T Vrancken Peeters Journal: Cancer Imaging Date: 2017-05-25 Impact factor: 3.909