A computational neurodegenerative disease progression score: Method and results with the Alzheimer's disease neuroimaging initiative cohort

NeuroImage

Volumn 63, Issue 3, 2012, Pages 1478-1486

  Jedynak, Bruno M ^a   Lang, Andrew ^a   Liu, Bo ^a   Katz, Elyse ^b   Zhang, Yanwei ^b   Wyman, Bradley T ^b   Raunig, David ^b,e   Jedynak, C Pierre ^c   Caffo, Brian ^d   Prince, Jerry L ^a  

^a Johns Hopkins University   (United States)

^b PFIZER INC   (United States)

^c Self   (France)

^d JOHNS HOPKINS BLOOMBERG SCHOOL OF PUBLIC HEALTH   (United States)

^e ICON Medical Imaging   (United States)

Author keywords

Alzheimer's disease; Biomarkers; Disease progression score; Neurodegenerative diseases

Indexed keywords

AMYLOID BETA PROTEIN; TAU PROTEIN;

ALZHEIMER DISEASE; ALZHEIMER DISEASE NEUROIMAGING INITIATIVE; ARTICLE; COMPUTER ANALYSIS; DATA BASE; DEGENERATIVE DISEASE; DISEASE COURSE; DISEASE PROGRESSION SCORE; FUNCTIONAL NEUROIMAGING; HIPPOCAMPUS; HUMAN; IMAGE PROCESSING; MATHEMATICAL ANALYSIS; METHODOLOGY; MILD COGNITIVE IMPAIRMENT; PRIORITY JOURNAL;

ALGORITHMS; ALZHEIMER DISEASE; BIOLOGICAL MARKERS; COHORT STUDIES; DISEASE PROGRESSION; HUMANS; NEURODEGENERATIVE DISEASES; SEVERITY OF ILLNESS INDEX;

EID: 84866163493     PISSN: 10538119     EISSN: 10959572     Source Type: Journal    
DOI: 10.1016/j.neuroimage.2012.07.059     Document Type: Article

References (38)

1. Ashford J., Shan M., Butler S., Rajasekar A., Schmitt F. Temporal quantification of Alzheimer's disease severity: 'Time Index' model. Dementia 1995, 6(5):269-280.
2. Bennett D.A., Schneider J.A., Arvanitakis Z., Kelly J.F., Aggarwal N.T., Shah R.C., Wilson R.S. Neuropathology of older persons without cognitive impairment from two community-based studies. Neurology 2006, 66(12):1837-1844.
3. Berg L., Miller J.P., Storandt M., Duchek J., Morris J.C., Rubin E.H., Burke W.J., Coben L.A. Mild senile dementia of the alzheimer type: 2. Longitudinal assessment. Ann. Neurol. 1988, 23(5):477-484.
4. Brooks D.J., Pavese N. Imaging biomarkers in Parkinson's disease. Progress in Neurobiology 2011, Aug. 10.1016/j.pneurobio.2011.08.009.
5. Brooks J., Kraemer H., Tanke E., Yesavage J. The methodology of studying decline in Alzheimer's disease. J. Am. Geriatr. Soc. 1993, 41(6):623-628.
6. Caroli A., Frisoni G., the Alzheimer's Disease Neuroimaging Initiative The dynamics of Alzheimer's disease biomarkers in the Alzheimer's disease neuroimaging initiative cohort. Neurobiol. Aging 2010, 31(8):1263-1274.
7. Carroll R., Fan J., Gijbels I., Wand M. Generalized partially linear single-index models. J. Am. Stat. Assoc. 1997, 92(438):477-489.
8. Duara R., Loewenstein D.A., Greig M.T., Potter E., Barker W., Raj A., Schinka J., Borenstein A., Schoenberg M., Wu Y., Banko J., Potter H. Pre-MCI and MCI: neuropsychological, clinical, and imaging features and progression rates. Am. J. Geriatr. Psychiatry 2011, 19(11):951-960.
9. 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 Neurol. 2007, 6(8):734-746.
10. Folstein M.F., Folstein S.E., McHugh P.R. "Mini-mental state": a practical method for grading the cognitive state of patients for the clinician. J. Psychiatr. Res. 1975, 12(3):189-198.
11. Fonteijn H.M.J., Clarkson M.J., Modat M., Barnes J., Lehmann M., Ourselin S., Fox N.C., Alexander D.C. An event-based disease progression model and its application to familial Alzheimer's disease. Vol. 6801 of Lecture Notes in Computer Science 2011, 748-759. Springer.
12. Hampel H., Burger K., Teipel S.J., Bokde A.L., Zetterberg H., Blennow K. Core candidate neurochemical and imaging biomarkers of Alzheimer's disease. Alzheimers Dement. 2008, 4(1):38-48.
13. Hardle W., Hall P., Ichimura H. Optimal smoothing in single-index models. Ann. Stat. 1993, 21(1):157-178.
14. Hayden M. Huntington's Chorea 1981, Springer-Verlag.
15. Hinrichs C., Singh V., Xu G., Johnson S.C. Predictive markers for AD in a multi-modality framework: an analysis of MCI progression in the ADNI population. NeuroImage 2011, 55(2):574-589.
16. Hughes C., Berg L., Danziger W., Coben L., Martin R. A new clinical scale for the staging of dementia. Br. J. Psychiatry 1982, 140:566-572.
17. Jack C.R., Knopman D.S., Jagust W.J., Shaw L.M., Aisen P.S., Weiner M.W., Petersen R.C., Trojanowski J.Q. Hypothetical model of dynamic biomarkers of the Alzheimer's pathological cascade. Lancet Neurol. 2010, 9(1):119-128.
18. Jack C.R.J., Vemuri P., Wiste H.J., Weigand S.D., Aisen P.S., Trojanowski J.Q., Shaw L.M., Bernstein M.A., Petersen R.C., Weiner M.W., Knopman D.S., for the Alzheimer's Disease Neuroimaging Initiative Evidence for ordering of alzheimer disease biomarkers. Arch. Neurol. 2011, 68(12):1526-1535.
19. Jicha G.A., Carr S.A. Conceptual evolution in Alzheimer's disease: implications for understanding the clinical phenotype of progressive neurodegenerative disease. J. Alzheimers Dis. 2010, 19(1):253-272.
20. Labbe A. ALS biomarkers study seeks 250 participants. MDA ALS News Magazine 2012, January.
21. Levenberg K. A method for the solution of certain non-linear problems in least squares. Q. Appl. Math. 1944, 2:164-168.
22. Martin L.J. Ch. Neurodegeneratives disorders of the human brain and spinal cord. Encyclopedia of the Human Brain 2002, vol. 3:441-463. Elsevier Science Academic press.
23. Mitnitski A., Graham J., Rockwood K. Modeling decline in Alzheimer's disease. Int. Psychogeriatr. 1999, 11(02):211-213.
24. Mosconi L., Brys M., Glodzik-Sobanska L., Santi S.D., Rusinek H., de Leon M.J. Early detection of Alzheimer's disease using neuroimaging. Exp. Gerontol. 2007, 42(1-2):129-138.
25. Mungas D., Reed B.R. Application of item response theory for development of a global functioning measure of dementia with linear measurement properties. Stat. Med. 2000, 19(11-12):1631-1644.
26. Qiu A., Younes L., Miller M.I., Csernansky J.G. Parallel transport in diffeomorphisms distinguishes time-dependent hippocampal surface atrophy in healthy aging and Alzheimer's disease. NeuroImage 2008, 40:68-76.
27. Richards F. A flexible growth function for emperical use. J. Exp. Bot. 1959, 10:290-300.
28. Rizk-Jackson A., Stoffers D., Sheldon S., Kuperman J.M., Dale A.M., Goldstein J., Corey-Bloom J., Poldrack R.A., Aron A.R. Evaluating imaging biomarkers for neurodegeneration in pre-symptomatic Huntington's disease using machine learning techniques. NeuroImage 2011, 56(2):788-796.
29. Sabuncu M.R., Desikan R.S., Sepulcre J., Yeo B.T.T., Liu H., Schmansky N.J., Reuter M., Weiner M.W., Buckner R.L., Sperling R.A., Fischl B., ADNI The dynamics of cortical and hippocampal atrophy in Alzheimer disease. Arch. Neurol. 2011, 68(8):1040-1048.
30. Shaw P.J. Molecular and cellular pathways of neurodegeneration in motor neurone disease. J. Neurol. Neurosurg. Psychiatry 2005, 76(8):1046-1057.
31. Sperling R.A., Aisen P.S., Beckett L.A., Bennett D.A., Craft S., Fagan A.M., Iwatsubo T., Jack C.R., Kaye J., Montine T.J., Park D.C., Reiman E.M., Rowe C.C., Siemers E., Stern Y., Yaffe K., Carrillo M.C., Thies B., Morrison-Bogorad M., Wagster M.V., Phelps C.H. Toward defining the preclinical stages of Alzheimer's disease: recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease. Alzheimers Dement. 2011, 7(3):280-292.
32. Stern R., Mohs R., Davidson M., Schmeidler J., Silverman J., Kramer-Ginsberg E., Searcey T., Bierer L., Davis K. A longitudinal study of Alzheimer's disease: measurement, rate, and predictors of cognitive deterioration. Am. J. Psychiatry 1994, 151(3):390-396.
33. Turner M.R., Kiernan M.C., Leigh P.N., Talbot K. Biomarkers in amyotrophic lateral sclerosis. Lancet Neurol. 2009, 8(1):94-109. (January).
34. Turner M.R., Grosskreutz J., Kassubek J., Abrahams S., Agosta F., Benatar M., Filippi M., Goldstein L.H., van den Heuvel M., Kalra S., Lul D., Mohammadi B. Towards a neuroimaging biomarker for amyotrophic lateral sclerosis. Lancet Neurol. 2011, 10(5):400-403. URL http://www.sciencedirect.com/science/article/pii/S1474442211700497.
35. Ververidis D., Van Gils M., Koikkalainen J., Lotjonen J. Feature selection and time regression software: application on predicting Alzheimer's disease progress. Proc. European Signal Processing Conference (EUSIPCO) 2010.
36. Walhovd K., Fjell A., Brewer J., McEvoy L., Fennema-Notestine C., Hagler D.J., Jennings R., Karow D., Dale A., the Alzheimer's Disease Neuroimaging Initiative Combining MR imaging, positron-emission tomography, and CSF biomarkers in the diagnosis and prognosis of Alzheimer disease. AJNR Am. J. Neuroradiol. 2010, 31(2):347-354.
37. Yang E., Farnum M., Lobanov V., Schultz T., Raghavan N., Samtani M.N., Novak G., Narayan V., DiBernardo A. Quantifying the pathophysiological timeline of Alzheimer's disease. J. Alzheimers Dis. 2011, 26(4):745-753.
38. Yang W., Lui R., Gao J., Chan T., Yau S., Sperling R., Huang X. Independent component analysis-based classification of Alzheimer's disease mri data. J. Alzheimers Dis. 2011, 24(4):775-783.