Early prediction of response to neoadjuvant chemoterapy in luminal breast cancer using total lesion glycolysis measured on 18F-FDG PET images : a prospective validation stud
Résumé
Objectives: Luminal A and B breast tumors are characterized by variable and mostly limited response to neoadjuvant chemotherapy (NAC). We prospectively investigated the value of several 18F-FDG PET image-derived parameters for early prediction. Prediction based on PET was also compared to that obtained by clinical, histological and molecular markers. Methods: 64 luminal breast cancer patients were included and underwent 18F-FDG PET scans at baseline and before the third cycle of chemotherapy. Surgery was performed after 8 cycles of NAC and pathological response was assessed using the Sataloff scale. SUVmax and TLG image-derived parameters were extracted from PET images. The accuracy of image-derived parameters (delta between the two PET scans) or molecular markers such as progesterone or luminal status in identifying responders was assessed through receiver operating characteristic (ROC) analysis. Results: There were 27 responders and 37 non-responders. The best accuracy was obtained using {Delta}TLG, with an area under the ROC curve (AUC) of 0.81 (vs. 0.73, 0.71 and 0.63 for SUVmax, luminal status, and progesterone status, respectively). Median {Delta}TLG was -49±31% in non-responders (vs. -73±25% for responders; p<0.0001). {Delta}TLG had a sensitivity of 89% and a specificity of 74% in identifying non-responders. Conclusions: When they respond to neoadjuvant treatment, luminal tumors present more pronounced partial shrinkage at early evaluation. {Delta}TLG seems to be more adapted for early prediction than {Delta}SUVmax and also a more powerful predictor than biological parameters.