128 Chapter 5 36. Golla, S.S., et al., Quantification of tau load using [18 F] AV1451 PET. Molecular imaging and biology, 2017. 19(6): p. 963-971. 37. Rask, T., et al., PVElab: Software for correction of functional images for partial volume errors. Neuroimage, 2004. 22. 38. Golla, S.S., et al., Partial volume correction of brain PET studies using iterative deconvolution in combination with HYPR denoising. EJNMMI research, 2017. 7(1): p. 1-12. 39. Cysouw, M., et al., Partial-volume correction in dynamic PET-CT: effect on tumor kinetic parameter estimation and validation of simplified metrics. EJNMMI research, 2019. 9(1): p. 1-11. 40. Groot, C., et al., Differential effects of cognitive reserve and brain reserve on cognition in Alzheimer disease. Neurology, 2018. 90(2): p. e149-e156. 41. Folstein, M.F., S.E. Folstein, and P.R. McHugh, “Mini-mental state”: a practical method for grading the cognitive state of patients for the clinician. Journal of psychiatric research, 1975. 12(3): p. 189-198. 42. Rubin, D.B., Multiple imputation for nonresponse in surveys. Vol. 81. 2004: John Wiley & Sons. 43. Von Hippel, P.T., How many imputations do you need? A two-stage calculation using a quadratic rule. Sociological Methods & Research, 2020. 49(3): p. 699-718. 44. Selvin, S., Statistical analysis of epidemiologic data. 2004: Oxford University Press. 45. Benjamini, Y. and Y. Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal statistical society: series B (Methodological), 1995. 57(1): p. 289-300. 46. Lehmann, M., et al., Diverging patterns of amyloid deposition and hypometabolism in clinical variants of probable Alzheimer’s disease. Brain, 2013. 136(3): p. 844-858. 47. Chan, D., et al., Change in rates of cerebral atrophy over time in early-onset Alzheimer’s disease: longitudinal MRI study. The Lancet, 2003. 362(9390): p. 1121-1122. 48. Möller, C., et al., Different patterns of gray matter atrophy in early-and late-onset Alzheimer’s disease. Neurobiology of aging, 2013. 34(8): p. 2014-2022. 49. Lehmann, M., et al., Loss of functional connectivity is greater outside the default mode network in nonfamilial early-onset Alzheimer’s disease variants. Neurobiology of aging, 2015. 36(10): p. 2678-2686. 50. De Waal, H., et al., EEG abnormalities in early and late onset Alzheimer’s disease: understanding heterogeneity. Journal of Neurology, Neurosurgery & Psychiatry, 2011. 82(1): p. 67-71. 51. De Waal, H., et al., Young Alzheimer patients show distinct regional changes of oscillatory brain dynamics. Neurobiology of aging, 2012. 33(5): p. 1008. e25-1008. e31. 52. Iaccarino, L., et al., Spatial Relationships between molecular pathology and neurodegeneration in the Alzheimer’s disease continuum. Cerebral Cortex, 2021. 31(1): p. 1-14. 53. Schöll, M., et al., Distinct 18F-AV-1451 tau PET retention patterns in early-and late-onset Alzheimer’s disease. Brain, 2017. 140(9): p. 2286-2294. 54. Cavedo, E., et al., Medial temporal atrophy in early and late-onset Alzheimer’s disease. Neurobiology of aging, 2014. 35(9): p. 2004-2012.
RkJQdWJsaXNoZXIy MjY0ODMw