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
| Autor: | Groheux, David, Hatt, Mathieu, Martineau, Antoine, VISVIKIS, Dimitris, Giacchetti, Sylvie, De Cremoux, Patricia, Lehmann-Che, Jacqueline, Cheze-Le Rest, Catherine, HINDIE, Elif |
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| Přispěvatelé: | Optimisation Continue des Actions Thérapeutiques par l'Intégration d'Informations Multimodales, Université de Brest (UBO)-Télécom Bretagne-Centre Hospitalier Régional Universitaire de Brest (CHRU Brest)-Institut National de la Santé et de la Recherche Médicale (INSERM), Direction Scientifique (DS), Institut Mines-Télécom [Paris] (IMT)-Télécom Bretagne, Hopital Saint-Louis [AP-HP] (AP-HP), Assistance publique - Hôpitaux de Paris (AP-HP) (AP-HP), Centre Hospitalier Régional Universitaire de Brest (CHRU Brest), Service de médecine nucléaire [Bordeaux], CHU de Bordeaux Pellegrin [Bordeaux] |
| Jazyk: | angličtina |
| Rok vydání: | 2013 |
| Zdroj: | SNMMI 2013 : Society of nuclear medicine and molecular imaging annual meeting SNMMI 2013 : Society of nuclear medicine and molecular imaging annual meeting, Jun 2013, Vancouver, Canada |
| Popis: | International audience; 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 |
| Databáze: | OpenAIRE |
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