The pons as reference region for intensity normalization in semi-quantitative analysis of brain 18FDG PET: application to metabolic changes related to ageing in conventional and digital control databases - Université de Lorraine Access content directly
Journal Articles EJNMMI Research Year : 2021

The pons as reference region for intensity normalization in semi-quantitative analysis of brain 18FDG PET: application to metabolic changes related to ageing in conventional and digital control databases

Abstract

Abstract Background The objective of the study is to define the most appropriate region for intensity normalization in brain 18 FDG 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) 18 FDG 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 18 FDG PET intensity normalization for examining the metabolic changes through ageing.
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Dates and versions

hal-03268289 , version 1 (23-06-2021)

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A. Verger, M. Doyen, J. y Campion, Eric Guedj. The pons as reference region for intensity normalization in semi-quantitative analysis of brain 18FDG PET: application to metabolic changes related to ageing in conventional and digital control databases. EJNMMI Research, 2021, 11 (1), pp.31. ⟨10.1186/s13550-021-00771-0⟩. ⟨hal-03268289⟩
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