Our European consortium was awarded research funding from the EraPerMED consortium [14] (LuCaPET project, grant number ERAPerMed_324, “Clinical decision support for predicting cachexia in cancer patients using hybrid PET/CT imaging”) to study the effectiveness of 18F-fluorodeoxyglucose (FDG) imaging in combination with advanced artificial intelligence (AI) algorithms to study the evolution of inter-organ metabolic relations and from this to predict the onset of cancer-induced cachexia
"Metabolic fingerprints" of cachexia in lung cancer patients / Frille, Armin; Arends, Jann; Abenavoli, Elisabetta M; Duke, Shaul A; Ferrara, Daria; Gruenert, Stefan; Hacker, Marcus; Hesse, Swen; Hofmann, Lukas; Holm, Sune H; Lund, Thomas B; Rullmann, Michael; Sandøe, Peter; Sciagra', Roberto; Shiyam Sundar, Lalith Kumar; Tönjes, Anke; Wirtz, Hubert; Yu, Josef; Sabri, Osama; Beyer, Thomas. - In: EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING. - ISSN 1619-7089. - ELETTRONICO. - (2024), pp. 0-0. [10.1007/s00259-024-06689-8]
"Metabolic fingerprints" of cachexia in lung cancer patients
Abenavoli, Elisabetta M;Sciagra', Roberto;
2024
Abstract
Our European consortium was awarded research funding from the EraPerMED consortium [14] (LuCaPET project, grant number ERAPerMed_324, “Clinical decision support for predicting cachexia in cancer patients using hybrid PET/CT imaging”) to study the effectiveness of 18F-fluorodeoxyglucose (FDG) imaging in combination with advanced artificial intelligence (AI) algorithms to study the evolution of inter-organ metabolic relations and from this to predict the onset of cancer-induced cachexia
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