Meta-analysis based SVM classification enables accurate detection of Alzheimer's disease across different clinical centers using FDG-PET and MRI

Psychiatry Research - Neuroimaging

Volumn 212, Issue 3, 2013, Pages 230-236

  Dukart, Juergen ^a,b,c   Mueller, Karsten ^a   Barthel, Henryk ^b   Villringer, Arno ^a,b   Sabri, Osama ^b   Schroeter, Matthias Leopold ^a,b  

^a MAX PLANCK INSTITUTE FOR HUMAN COGNITIVE AND BRAIN SCIENCES   (Germany)

^b UNIVERSITY OF LEIPZIG   (Germany)

^c LAUSANNE UNIVERSITY HOSPITAL   (Switzerland)

Author keywords

ADNI; Multicenter validation; Multimodal imaging; Support vector machine classification

Indexed keywords

FLUORODEOXYGLUCOSE F 18;

ADULT; ALZHEIMER DISEASE; ARTICLE; CLINICAL ARTICLE; CONTROLLED STUDY; DEMENTIA; DIAGNOSTIC ACCURACY; DISEASE CLASSIFICATION; FEMALE; HUMAN; MALE; META ANALYSIS; NUCLEAR MAGNETIC RESONANCE IMAGING; POSITRON EMISSION TOMOGRAPHY; PRIORITY JOURNAL; SUPPORT VECTOR MACHINE;

AGED; AGED, 80 AND OVER; ALZHEIMER DISEASE; FEMALE; HUMANS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED; MULTIMODAL IMAGING; NEUROIMAGING; POSITRON-EMISSION TOMOGRAPHY;

EID: 84878119051     PISSN: 09254927     EISSN: 18727506     Source Type: Journal    
DOI: 10.1016/j.pscychresns.2012.04.007     Document Type: Article

References (37)

1. Abdulkadir A., Mortamet B., Vemuri P., Jack C.R., Krueger G., Klöppel S., Initiative A.s.D.N. Effects of hardware heterogeneity on the performance of SVM Alzheimer's disease classifier. Neuroimage 2011, 58:785-792.
2. Ashburner J. A fast diffeomorphic image registration algorithm. Neuroimage 2007, 38:95-113.
3. Barthel H., Gertz H.J., Dresel S., Peters O., Bartenstein P., Buerger K., Hiemeyer F., Wittemer-Rump S.M., Seibyl J., Reininger C., Sabri O., Florbetaben Study Group Cerebral amyloid-Β PET with florbetaben (18F) in patients with Alzheimer's disease and healthy controls: a multicentre phase 2 diagnostic study. Lancet Neurology 2011, 10:424-435.
4. Buckner R.L., Snyder A.Z., Shannon B.J., LaRossa G., Sachs R., Fotenos A.F., Sheline Y.I., Klunk W.E., Mathis C.A., Morris J.C., Mintun M.A. Molecular, structural, and functional characterization of Alzheimer's disease: evidence for a relationship between default activity, amyloid, and memory. Journal of Neuroscience 2005, 25:7709-7717.
5. Chang, C.C., Lin, C.J., 2001. LIBSVM: a Library for Support Vector Machines. Software available at:. http://www.csie.ntu.edu.tw/cjlin/libsvm/.
6. Chaves R., Ramírez J., Górriz J.M., López M., Salas-Gonzalez D., Alvarez I., Segovia F. SVM-based computer-aided diagnosis of the Alzheimer's disease using t-test NMSE feature selection with feature correlation weighting. Neuroscience Letters 2009, 461:293-297.
7. Davatzikos C., Resnick S.M., Wu X., Parmpi P., Clark C.M. Individual patient diagnosis of AD and FTD via high-dimensional pattern classification of MRI. Neuroimage 2008, 41:1220-1227.
8. Diehl J., Grimmer T., Drzezga A., Riemenschneider M., Förstl H., Kurz A. Cerebral metabolic patterns at early stages of frontotemporal dementia and semantic dementia. A PET study. Neurobiology of Aging 2004, 25:1051-1056.
9. Diehl-Schmid J., Grimmer T., Drzezga A., Bornschein S., Riemenschneider M., Förstl H., Schwaiger M., Kurz A. Decline of cerebral glucose metabolism in frontotemporal dementia: a longitudinal 18F-FDG-PET-study. Neurobiology of Aging 2007, 28:42-50.
10. Dubois B., Feldman H.H., Jacova C., Dekosky S.T., Barberger-Gateau P., Cummings J., Delacourte A., Galasko D., Gauthier S., Jicha G., Meguro K., O'brien J., Pasquier F., Robert P., Rossor M., Salloway S., Stern Y., Visser P.J., Scheltens P. Research criteria for the diagnosis of Alzheimer's disease: revising the NINCDS-ADRDA criteria. Lancet Neurology 2007, 6:734-746.
11. Dukart J., Mueller K., Horstmann A., Vogt B., Frisch S., Barthel H., Becker G., Möller H.E., Villringer A., Sabri O., Schroeter M.L. Differential effects of global and cerebellar normalization on detection and differentiation of dementia in FDG-PET studies. Neuroimage 2010, 49:1490-1495.
12. Dukart J., Mueller K., Horstmann A., Barthel H., Möller H.E., Villringer A., Sabri O., Schroeter M.L. Combined evaluation of FDG-PET and MRI improves detection and differentiation of dementia. PLoSOne 2011, 6(3):e18111. 10.1371/journal.pone.0018111.
13. Edison P., Archer H.A., Hinz R., Hammers A., Pavese N., Tai Y.F., Hotton G., Cutler D., Fox N., Kennedy A., Rossor M., Brooks D.J. Amyloid, hypometabolism, and cognition in Alzheimer disease. An [11C]PIB and [18F]FDG PET study. Neurology 2007, 68:501-508.
14. Fung G., Stoeckel J. SVM feature selection for classification of SPECT images of Alzheimer's disease using spatial information. Knowledge and Information Systems 2007, 11:243-258.
15. Gerardin E., Chételat G., Chupin M., Cuingnet R., Desgranges B., Kim H.S., Niethammer M., Dubois B., Lehéricy S., Garnero L., Eustache F., Colliot O., Alzheimer's Disease Neuroimaging Initiative Multidimensional classification of hippocampal shape features discriminates Alzheimer's disease and mild cognitive impairment from normal aging. Neuroimage 2009, 47:1476-1486.
16. Habeck C., Foster N.L., Perneczky R., Kurz A., Alexopoulos P., Koeppe R.A., Drzezga A., Stern Y. Multivariate and univariate neuroimaging biomarkers of Alzheimer's disease. Neuroimage 2008, 40:1503-1515.
17. Habert M.O., Horn J.F., Sarazin M., Lotterie J.A., Puel M., Onen F., Zanca M., Portet F., Touchon J., Verny M., Mahieux F., Giron A., Fertil B., Dubois B. Brain perfusion SPECT with an automated quantitative tool can identify prodromal Alzheimer's disease among patients with mild cognitive impairment. Neurobiology of Aging 2009, 32(1):15-23.
18. Hinrichs C., Singh V., Mukherjee L., Xu G., Chung M.K., Johnson S.C., Initiative A.s.D.N. Spatially augmented LPboosting for AD classification with evaluations on the ADNI dataset. Neuroimage 2009, 48:138-149.
19. Hoffman J.M., Welsh-Bohmer K.A., Hanson M., Crain B., Hulette C., Earl N., Coleman R.E. FDG PET imaging in patients with pathologically verified dementia. Journal of Nuclear Medicine 2000, 41:1920-1928.
20. Horn J.F., Habert M.O., Kas A., Malek Z., Maksud P., Lacomblez L., Giron A., Fertil B. Differential automatic diagnosis between Alzheimer's disease and frontotemporal dementia based on perfusion SPECT images. Artificial Intelligence in Medicine 2009, 47:147-158.
21. Jack C.R., Lowe V.J., Senjem M.L., Weigand S.D., Kemp B.J., Shiung M.M., Knopman D.S., Boeve B.F., Klunk W.E., Mathis C.A., Petersen R.C. 11C PiB and structural MRI provide complementary information in imaging of Alzheimer's disease and amnestic mild cognitive impairment. Brain 2008, 131:665-680.
22. Jeong Y., Cho S.S., Park J.M., Kang S.J., Lee J.S., Kang E., Na D.L., Kim S.E. 18F-FDG PET findings in frontotemporal dementia: an SPM analysis of 29 patients. Journal of Nuclear Medicine 2005, 46:233-239.
23. Kipps C.M., Hodges J.R., Fryer T.D., Nestor P.J. Combined magnetic resonance imaging and positron emission tomography brain imaging in behavioural variant frontotemporal degeneration: refining the clinical phenotype. Brain 2009, 132:2566-2578.
24. Klöppel S., Stonnington C.M., Chu C., Draganski B., Scahill R.I., Rohrer J.D., Fos N.C., Jack C.R., Ashburner J., Frackowiak R.S. Automatic classification of MR scans in Alzheimer's disease. Brain 2007, 131:681-689.
25. McEvoy L.K., Fennema-Notestine C., Roddey J.C., Hagler D.J., Holland D., Karow D.S., Pung C.J., Brewer J.B., Dale A.M. Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment. Radiology 2009, 251:195-205. Initiative, A. s. D. N.
26. McKhann G., Drachman D., Folstein M., Katzman R., Price D., Stadlan E.M. Clinical diagnosis of Alzheimer's disease: report of the NINCDS-ADRDA Work Group under the auspices of Department of Health and Human Services Task Force on Alzheimer's Disease. Neurology 1984, 34:939-944.
27. Morris J.C. The Clinical Dementia Rating (CDR): current version and scoring rules. Neurology 1993, 43:2412-2414.
28. Neary D., Snowden J.S., Gustafson L., Passant U., Stuss D., Black S., Freedman M., Kertesz A., Robert P.H., Albert M., Boone K., Miller B.L., Cummings J., Benson D.F. Frontotemporal lobar degeneration: a consensus on clinical diagnostic criteria. Neurology 1998, 51:1546-1554.
29. Ramirez J., Gorriz J.M., Salas-Gonzales D., Romero A., Lopez M., Alvarez I., Gomez-Rio M. Computer-aided diagnosis of Alzheimer's type dementia combining support vector machines and discriminant set of features. Information Sciences 2009, 10.1016/j.ins.2009.05.012.
30. Rosen H.J., Gorno-Tempini M.L., Goldman W.P., Perry R.J., Schuff N., Weiner M., Feiwell R., Kramer J.H., Miller B.L. Patterns of brain atrophy in frontotemporal dementia and semantic dementia. Neurology 2002, 58:198-208.
31. Sabri O., Ringelstein E.B., Hellwig D., Schneider R., Schreckenberger M., Kaiser H.J., Mull M., Buell U. Neuropsychological impairment correlates with hypoperfusion and hypometabolism but not with severity of white matter lesions on MRI in patients with cerebral microangiopathy. Stroke 1999, 30:556-566.
32. Sabri O., Kendziorra K., Wolf H., Gertz H.J., Brust P. Acetylcholine receptors in dementia and mild cognitive impairment. European Journal of Nuclear Medicine and Molecular Imaging 2008, 35(Suppl. 1):30-45.
33. Schroeter M.L., Raczka K., Neumann J., Yves von Cramon D. Towards a nosology for frontotemporal lobar degenerations-a meta-analysis involving 267 subjects. Neuroimage 2007, 36:497-510.
34. Schroeter M.L., Raczka K., Neumann J., von Cramon D.Y. Neural networks in frontotemporal dementia-a meta-analysis. Neurobiology of Aging 2008, 29:418-426.
35. Schroeter M.L., Stein T., Maslowski N., Neumann J. Neural correlates of Alzheimer's disease and mild cognitive impairment: a systematic and quantitative meta-analysis involving 1351 patients. Neuroimage 2009, 47:1196-1206.
36. Schroeter M.L., Neumann J. Combined imaging markers dissociate Alzheimer's disease and frontotemporal lobar degeneration-an ALE meta-analysis. Frontiers in Aging Neuroscience 2011, 3:10.
37. Zhang D., Wang Y., Zhou L., Yuan H., Shen D. Multimodal classification of Alzheimer's disease and mild cognitive impairment. NeuroImage 2011, 55:856-867.