title: Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.
abstract: The failure of current strategies to provide an explanation for controversial findings on the pattern of pathophysiological changes in Alzheimer's Disease (AD) motivates the necessity to develop new integrative approaches based on multi-modal neuroimaging data that captures various aspects of disease pathology. Previous studies using [18F]fluorodeoxyglucose positron emission tomography (FDG-PET) and structural magnetic resonance imaging (sMRI) report controversial results about time-line, spatial extent and magnitude of glucose hypometabolism and atrophy in AD that depend on clinical and demographic characteristics of the studied populations. Here, we provide and validate at a group level a generative anatomical model of glucose hypo-metabolism and atrophy progression in AD based on FDG-PET and sMRI data of 80 patients and 79 healthy controls to describe expected age and symptom severity related changes in AD relative to a baseline provided by healthy aging. We demonstrate a high level of anatomical accuracy for both modalities yielding strongly age- and symptom-severity- dependant glucose hypometabolism in temporal, parietal and precuneal regions and a more extensive network of atrophy in hippocampal, temporal, parietal, occipital and posterior caudate regions. The model suggests greater and more consistent changes in FDG-PET compared to sMRI at earlier and the inversion of this pattern at more advanced AD stages. Our model describes, integrates and predicts characteristic patterns of AD related pathology, uncontaminated by normal age effects, derived from multi-modal data. It further provides an integrative explanation for findings suggesting a dissociation between early- and late-onset AD. The generative model offers a basis for further development of individualized biomarkers allowing accurate early diagnosis and treatment evaluation.
authors.affiliation: LREN, Département des Neurosciences Cliniques, CHUV, Université de Lausanne, Lausanne, Switzerland. dukart@cbs.mpg.de
authors.forename: Juergen
authors.initials: J
authors.lastname: Dukart
authors.forename: Ferath
authors.initials: F
authors.lastname: Kherif
authors.forename: Karsten
authors.initials: K
authors.lastname: Mueller
authors.forename: Stanislaw
authors.initials: S
authors.lastname: Adaszewski
authors.forename: Matthias L
authors.initials: ML
authors.lastname: Schroeter
authors.forename: Richard S J
authors.initials: RS
authors.lastname: Frackowiak
authors.forename: Bogdan
authors.initials: B
authors.lastname: Draganski
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D000375:Aging; D000544:Alzheimer Disease / Q000175:diagnosis / Q000000981:diagnostic imaging*; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology; D016022:Case-Control Studies; D018450:Disease Progression; D005260:Female; D019788:Fluorodeoxyglucose F18 / Q000494:pharmacology*; D005947:Glucose / Q000378:metabolism; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D049268:Positron-Emission Tomography / Q000379:methods*; D019275:Radiopharmaceuticals / Q000494:pharmacology; D012984:Software
chemical_list: D019275:Radiopharmaceuticals; D019788:Fluorodeoxyglucose F18; D005947:Glucose