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, A., Arends, J., Abenavoli, E.M., Duke, S.A., Ferrara, D., Gruenert, S., Hacker, M., Hesse, S., Hofmann, L., Holm, S.H., Lund, T.B., Rullmann, M., Sandøe, P., Sciagra', R., Shiyam Sundar, L.K., Tönjes, A., Wirtz, H., Yu, J., Sabri, O., Beyer, T.. - 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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