A Verger1,2, M Doyen1,2, J Y Campion3,4, Eric Guedj5,6,7. 1. Department of Nuclear Medicine and Nancyclotep Imaging Platform, Université de Lorraine, 54000, Nancy, France. 2. IADI, INSERM U1254, Université de Lorraine, 54000, Nancy, France. 3. CNRS, Ecole Centrale de Marseille, UMR 7249, Institut Fresnel, Aix-Marseille Université, Marseille, France. 4. CERIMED, Aix-Marseille University, Marseille, France. 5. CNRS, Ecole Centrale de Marseille, UMR 7249, Institut Fresnel, Aix-Marseille Université, Marseille, France. eric.guedj@ap-hm.fr. 6. CERIMED, Aix-Marseille University, Marseille, France. eric.guedj@ap-hm.fr. 7. Department of Nuclear Medicine, Assistance Publique Hôpitaux de Marseille, Timone University Hospital, Marseille, France. eric.guedj@ap-hm.fr.
Abstract
BACKGROUND: The objective of the study is to define the most appropriate region for intensity normalization in brain 18FDG PET semi-quantitative analysis. The best option could be based on previous absolute quantification studies, which showed that the metabolic changes related to ageing affect the quasi-totality of brain regions in healthy subjects. Consequently, brain metabolic changes related to ageing were evaluated in two populations of healthy controls who underwent conventional (n = 56) or digital (n = 78) 18FDG PET/CT. The median correlation coefficients between age and the metabolism of each 120 atlas brain region were reported for 120 distinct intensity normalizations (according to the 120 regions). SPM linear regression analyses with age were performed on most significant normalizations (FWE, p < 0.05). RESULTS: The cerebellum and pons were the two sole regions showing median coefficients of correlation with age less than - 0.5. With SPM, the intensity normalization by the pons provided at least 1.7- and 2.5-fold more significant cluster volumes than other normalizations for conventional and digital PET, respectively. CONCLUSIONS: The pons is the most appropriate area for brain 18FDG PET intensity normalization for examining the metabolic changes through ageing.
BACKGROUND: The objective of the study is to define the most appropriate region for intensity normalization in brain 18FDG PET semi-quantitative analysis. The best option could be based on previous absolute quantification studies, which showed that the metabolic changes related to ageing affect the quasi-totality of brain regions in healthy subjects. Consequently, brain metabolic changes related to ageing were evaluated in two populations of healthy controls who underwent conventional (n = 56) or digital (n = 78) 18FDG PET/CT. The median correlation coefficients between age and the metabolism of each 120 atlas brain region were reported for 120 distinct intensity normalizations (according to the 120 regions). SPM linear regression analyses with age were performed on most significant normalizations (FWE, p < 0.05). RESULTS: The cerebellum and pons were the two sole regions showing median coefficients of correlation with age less than - 0.5. With SPM, the intensity normalization by the pons provided at least 1.7- and 2.5-fold more significant cluster volumes than other normalizations for conventional and digital PET, respectively. CONCLUSIONS: The pons is the most appropriate area for brain 18FDG PET intensity normalization for examining the metabolic changes through ageing.
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