• Assessment of hypoxia and oxidative-related changes in a lung-derived brain metastasis model by [64Cu][Cu(ATSM)] PET and proteomic studies. Fantin J., Toutain J., Peres E., Bernay B., Mehani S., Helaine C., Bourgeois M., Brunaud C., Chazalviel L., Pontin J., Corroye Dumont A., Valable S., Chérel M., Bernaudin M. EJNMMI Res 2023; 13(1). https://doi.org/10.1186/s13550-023-01052-8

  • Graph-based multimodal multi-lesion DLBCL treatment response prediction from PET images. Thiery O, Rizkallah M, Bailly C, Bodet-Milin C, Itti E, Casasnovas RO, et al. arXiv; 2023. http://arxiv.org/abs/2310.16863

  • Performance of baseline FDG-PET/CT radiomics for prediction of bone marrow minimal residual disease status in the LyMa-101 trial. Bodet-Milin C, Morvant C, Carlier T, Frecon G, Tournilhac O, Safar V, et al. Sci Rep. 24 oct 2023;13(1):18177. https://doi.org/10.1038/s41598-023-45215-y

  • Hybrid simultaneous whole-body 2-[18F]FDG-PET/MRI imaging in newly diagnosed multiple myeloma: first diagnostic performance and clinical added value results. Jamet B, Carlier T, Bailly C, Bodet-Milin C, Monnet A, Frampas E, et al. Eur Radiol. sept 2023;33(9):6438 47. https://doi.org/10.1007/s00330-023-09593-1

  • Design of a generic method for single dual-tracer PET imaging acquisition in clinical routine. Taheri N, Le Crom B, Bouillot C, Chérel M, Costes N, Gouard S, et al. Phys Med Biol. 10 avr 2023;68(8). https://doi.org/10.1088/1361-6560/acc723

  • A Multicenter Study on Observed Discrepancies Between Vendor-Stated and PET-Measured 90Y Activities for Both Glass and Resin Microsphere Devices, Gnesin S, Mikell JK, Conti M, Prior JO, Carlier T, Lima TVM, et al. . J Nucl Med. mai 2023;64(5):825‑8. https://doi.org/10.2967/jnumed.122.264458

  • Preclinical Evaluation of a 64Cu-Based Theranostic Approach in a Murine Model of Multiple Myeloma, Métivier C, Le Saëc P, Gaschet J, Chauvet C, Marionneau-Lambot S, Hofgaard PO, et al., Pharmaceutics, 25 juin 2023;15(7):1817. https://doi.org/10.3390/pharmaceutics15071817

  • 18F-FDG-Based Radiomics and Machine Learning. Godefroy T, Frécon G, Asquier-Khati A, Mateus D, Lecomte R, Rizkallah M, et al., JACC: Cardiovascular Imaging. avr 2023;S1936878X23000931. https://doi.org/10.1016/j.jcmg.2023.01.020

  • 18FFDG-based radiomics and machine learning: a useful help for aortic prosthetic valve infective endocarditis diagnosis?, Thomas Godefroy, Gauthier Frécon, Antoine Asquier-Khati, Diana Mateus, Raphael Lecomte, Mira Rizkallah, Nicolas Piriou, Thomas Le Tourneau, David Boutoille, Thomas Eugene et Thomas Carlier, European Heart Journal, 43(Supplement 2):ehac544–318, 2022. http://dx.doi.org/10.1093/eurheartj/ehac544.318

  • FDG-PET/CT in Lymphoma: Where Do We Go Now?, Al Tabaa, Y ; Bailly, C ; Kanoun, S, Cancers (Basel), 2021, 13
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