BACKGROUND: The objective of this prospective study was to evaluate the ability of (18)F-fluorodeoxyglucose ((18)F-FDG) positron emission tomography/computed tomography (PET/CT) to predict chemosensitivity in patients with estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative breast cancer. METHODS: Sixty-four consecutive patients underwent (18)F-FDG PET/CT scanning at baseline and after the second course of neoadjuvant chemotherapy (NAC). The evolution (Δ) between the 2 scans of image parameters (maximum standardized uptake value [SUV(max)], SUV(mean), metabolic tumor volume, and total lesion glycolysis [TLG]) was measured. Correlations between early changes in PET-derived parameters and pathologic response observed in surgical specimens after the completion of 8 courses of NAC were estimated with Mann-Whitney U tests. Response prediction on the basis of clinical data, histologic type, or molecular markers also was assessed (Fisher exact test). Receiver operating characteristic (ROC) analysis was used to compare the area under the curve (AUC) of each parameter. RESULTS: The best prediction of chemosensitivity was obtained with ΔTLG (-49% ± 31% in nonresponders vs -73% ± 25% in responders; P < .0001). Among the biologic parameters, only negative progesterone receptor status (57% responders vs 31% nonresponders; P = .04) and luminal B subtype (63% responders vs 22% nonresponders; P = .02) were predictive of a pathologic response. ROC analysis resulted in an AUC of 0.81, 0.73, 0.71, and 0.63 for ΔTLG, ΔSUV(max), luminal subtype, and progesterone receptor status, respectively. CONCLUSIONS: When patients responded to NAC, the majority of ER-positive/HER2 negative tumors exhibited partial tumor shrinkage; and the PET parameters that combined volume and activity measurements, such as TLG, offered better accuracy for early prediction than the SUV(max). Negative progesterone receptor status and luminal B subtype had weaker predictive power than PET-derived parameters.
BACKGROUND: The objective of this prospective study was to evaluate the ability of (18)F-fluorodeoxyglucose ((18)F-FDG) positron emission tomography/computed tomography (PET/CT) to predict chemosensitivity in patients with estrogen receptor (ER)-positive/human epidermal growth factor receptor 2 (HER2)-negative breast cancer. METHODS: Sixty-four consecutive patients underwent (18)F-FDG PET/CT scanning at baseline and after the second course of neoadjuvant chemotherapy (NAC). The evolution (Δ) between the 2 scans of image parameters (maximum standardized uptake value [SUV(max)], SUV(mean), metabolic tumor volume, and total lesion glycolysis [TLG]) was measured. Correlations between early changes in PET-derived parameters and pathologic response observed in surgical specimens after the completion of 8 courses of NAC were estimated with Mann-Whitney U tests. Response prediction on the basis of clinical data, histologic type, or molecular markers also was assessed (Fisher exact test). Receiver operating characteristic (ROC) analysis was used to compare the area under the curve (AUC) of each parameter. RESULTS: The best prediction of chemosensitivity was obtained with ΔTLG (-49% ± 31% in nonresponders vs -73% ± 25% in responders; P < .0001). Among the biologic parameters, only negative progesterone receptor status (57% responders vs 31% nonresponders; P = .04) and luminal B subtype (63% responders vs 22% nonresponders; P = .02) were predictive of a pathologic response. ROC analysis resulted in an AUC of 0.81, 0.73, 0.71, and 0.63 for ΔTLG, ΔSUV(max), luminal subtype, and progesterone receptor status, respectively. CONCLUSIONS: When patients responded to NAC, the majority of ER-positive/HER2 negative tumors exhibited partial tumor shrinkage; and the PET parameters that combined volume and activity measurements, such as TLG, offered better accuracy for early prediction than the SUV(max). Negative progesterone receptor status and luminal B subtype had weaker predictive power than PET-derived parameters.
Authors: Charles Lemarignier; Antoine Martineau; Luis Teixeira; Laetitia Vercellino; Marc Espié; Pascal Merlet; David Groheux Journal: Eur J Nucl Med Mol Imaging Date: 2017-02-10 Impact factor: 9.236