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 - IMT Atlantique Accéder directement au contenu
Communication Dans Un Congrès SNMMI 2013 : Society of nuclear medicine and molecular imaging annual meeting Année : 2013

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.
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Dates et versions

hal-00936126 , version 1 (24-01-2014)

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  • HAL Id : hal-00936126 , version 1

Citer

David Groheux, Mathieu Hatt, Antoine Martineau, Dimitris Visvikis, Sylvie Giacchetti, et al.. 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. SNMMI 2013 : Society of nuclear medicine and molecular imaging annual meeting, Jun 2013, Vancouver, Canada. ⟨hal-00936126⟩
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