Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.


Ressource 1Download: BIB_F1DBEC7E3B77.P001.pdf (9977.25 [Ko])
State: Public
Version: author
Serval ID
Article: article from journal or magazin.
Generative FDG-PET and MRI model of aging and disease progression in Alzheimer's disease.
PLOS Computational Biology
Dukart J., Kherif F., Mueller K., Adaszewski S., Schroeter M.L., Frackowiak R.S., Draganski B.
Working group(s)
Alzheimer's Disease Neuroimaging Initiative
Weiner M., Aisen P., Weiner M., Aisen P., Petersen R., Jack CR.<Suffix>Jr</Suffix> , Jagust W., Trojanowki JQ., Toga AW., Beckett L., Green RC., Saykin AJ., Morris J., Liu E., Green RC., Montine T., Petersen R., Aisen P., Gamst A., Thomas RG., Donohue M., Walter S., Gessert D., Sather T., Beckett L., Harvey D., Gamst A., Donohue M., Kornak J., Jack CR.<Suffix>Jr</Suffix> , Dale A., Bernstein M., Felmlee J., Fox N., Thompson P., Schuff N., DeCarli C., Jagust W., Bandy D., Koeppe RA., Foster N., Reiman EM., Chen K., Mathis C., Morris J., Cairns NJ., Taylor-Reinwald L., Trojanowki JQ., Shaw L., Lee VM., Korecka M., Toga AW., Crawford K., Neu S., Saykin AJ., Foroud TM., Potkin S., Shen L., Kachaturian Z., Frank R., Snyder PJ., Molchan S., Kaye J., Quinn J., Lind B., Dolen S., Schneider LS., Pawluczyk S., Spann BM., Brewer J., Vanderswag H., Heidebrink JL., Lord JL., Petersen R., Johnson K., Doody RS., Villanueva-Meyer J., Chowdhury M., Stern Y., Honig LS., Bell KL., Morris JC., Ances B., Carroll M., Leon S., Mintun MA., Schneider S., Marson D., Griffith R., Clark D., Grossman H., Mitsis E., Romirowsky A., deToledo-Morrell L., Shah RC., Duara R., Varon D., Roberts P., Albert M., Onyike C., Kielb S., Rusinek H., de Leon MJ. , Glodzik L., De Santi S., Doraiswamy P., Petrella JR., Coleman R., Arnold SE., Karlawish JH., Wolk D., Smith CD., Jicha G., Hardy P., Lopez OL., Oakley M., Simpson DM., Porsteinsson AP., Goldstein BS., Martin K., Makino KM., Ismail M., Brand C., Mulnard RA., Thai G., Mc-Adams-Ortiz C., Womack K., Mathews D., Quiceno M., Diaz-Arrastia R., King R., Weiner M., Martin-Cook K., DeVous M., Levey AI., Lah JJ., Cellar JS., Burns JM., Anderson HS., Swerdlow RH., Apostolova L., Lu PH., Bartzokis G., Silverman DH., Graff-Radford NR., Parfitt F., Johnson H., Farlow MR., Hake AM., Matthews BR., Herring S., van Dyck CH. , Carson RE., MacAvoy MG., Chertkow H., Bergman H., Hosein C., Black S., Stefanovic B., Caldwell C., Hsiung GY., Feldman H., Mudge B., Assaly M., Kertesz A., Rogers J., Trost D., Bernick C., Munic D., Kerwin D., Mesulam MM., Lipowski K., Wu CK., Johnson N., Sadowsky C., Martinez W., Villena T., Turner RS., Johnson K., Reynolds B., Sperling RA., Johnson KA., Marshall G., Frey M., Yesavage J., Taylor JL., Lane B., Rosen A., Tinklenberg J., Sabbagh M., Belden C., Jacobson S., Kowall N., Killiany R., Budson AE., Norbash A., Johnson PL., Obisesan TO., Wolday S., Bwayo SK., Lerner A., Hudson L., Ogrocki P., Fletcher E., Carmichael O., Olichney J., DeCarli C., Kittur S., Borrie M., Lee TY., Bartha R., Johnson S., Asthana S., Carlsson CM., Potkin SG., Preda A., Nguyen D., Tariot P., Fleisher A., Reeder S., Bates V., Capote H., Rainka M., Scharre DW., Kataki M., Zimmerman EA., Celmins D., Brown AD., Pearlson GD., Blank K., Anderson K., Saykin AJ., Santulli RB., Schwartz ES., Sink KM., Williamson JD., Garg P., Watkins F., Ott BR., Querfurth H., Tremont G., Salloway S., Malloy P., Correia S., Rosen HJ., Miller BL., Mintzer J., Longmire CF., Spicer K., Finger E., Rachinsky I., Rogers J., Kertesz A., Drost D.
1553-7358 (Electronic)
Publication state
Issued date
Publication types: Journal Article ; Research Support, N.I.H., Extramural ; Research Support, Non-U.S. Gov't Publication Status: ppublish
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.
Web of science
Open Access
Create date
05/06/2013 12:37
Last modification date
20/08/2019 17:19
Usage data