Structural and microstructural brain changes predict impairment in daily functioning

American Journal of Medicine

Volumn 127, Issue 11, 2014, Pages 1089-1096.e2

  Verlinden, Vincentius J A ^a   Van Der Geest, Jos N ^a   De Groot, Marius ^a   Hofman, Albert ^a   Niessen, Wiro J ^a,b   Van Der Lugt, Aad ^a   Vernooij, Meike W ^a   Ikram, M Arfan ^a  

^a ERASMUS MEDICAL CENTER   (Netherlands)

^b DELFT UNIVERSITY OF TECHNOLOGY   (Netherlands)

Author keywords

Activities of daily living; Brain; DTI; Epidemiology; MRI

Indexed keywords

ANTIDIABETIC AGENT; ANTIHYPERTENSIVE AGENT;

ADULT; ARTICLE; BRAIN; BRAIN SIZE; DAILY LIFE ACTIVITY; FEMALE; FOLLOW UP; FOOD PROCESSING; FRACTIONAL ANISOTROPY; GRAY MATTER; HEALTH ASSESSMENT QUESTIONNAIRE; HIPPOCAMPUS; HUMAN; LAUNDRY; MAJOR CLINICAL STUDY; MALE; MINI MENTAL STATE EXAMINATION; NEUROIMAGING; NUCLEAR MAGNETIC RESONANCE IMAGING; SHOPPING; TRAVEL; WHITE MATTER; WHITE MATTER LESION; ATROPHY; DISABILITY; MIDDLE AGED; PATHOLOGY; STATISTICAL MODEL;

ACTIVITIES OF DAILY LIVING; ATROPHY; BRAIN; DISABILITY EVALUATION; FEMALE; FOLLOW-UP STUDIES; HUMANS; LINEAR MODELS; MAGNETIC RESONANCE IMAGING; MALE; MIDDLE AGED;

EID: 84912101016     PISSN: 00029343     EISSN: 15557162     Source Type: Journal    
DOI: 10.1016/j.amjmed.2014.06.037     Document Type: Article

References (34)

1. Luppa M, Luck T, Weyerer S, et al. Prediction of institutionalization in the elderly. A systematic review. Age Ageing. 2010;39(1):31-38.
2. Wang L, van Belle G, Kukull WB, Larson EB. Predictors of functional change: a longitudinal study of nondemented people aged 65 and older. J Am Geriatr Soc. 2002;50(9):1525-1534.
3. Bennett HP, Corbett AJ, Gaden S, et al. Subcortical vascular disease and functional decline: a 6-year predictor study. J Am Geriatr Soc. 2002;50(12):1969-1977.
4. Grigsby J, Kaye K, Baxter J, et al. Executive cognitive abilities and functional status among community-dwelling older persons in the San Luis Valley Health and Aging Study. J Am Geriatr Soc. 1998;46(5):590-596.
5. Tomaszewski Farias S, Cahn-Weiner DA, Harvey DJ, et al. Longitudinal changes in memory and executive functioning are associated with longitudinal change in instrumental activities of daily living in older adults. Clin Neuropsychol. 2009;23(3):446-461.
6. Prins ND, van Dijk EJ, den Heijer T, et al. Cerebral small-vessel disease and decline in information processing speed, executive function and memory. Brain. 2005;128(Pt 9):2034-2041.
7. Carmichael O, Schwarz C, Drucker D, et al. Longitudinal changes in white matter disease and cognition in the first year of the Alzheimer disease neuroimaging initiative. Arch Neurol. 2010;67(11):1370-1378.
8. Le Bihan D, Mangin JF, Poupon C, et al. Diffusion tensor imaging: concepts and applications. J Magn Reson Imaging. 2001;13(4):534-546.
9. Selnes P, Aarsland D, Bjornerud A, et al. Diffusion tensor imaging surpasses cerebrospinal fl uid as predictor of cognitive decline and medial temporal lobe atrophy in subjective cognitive impairment and mild cognitive impairment. J Alzheimers Dis. 2013;33(3):723-736.
10. Gold DA. An examination of instrumental activities of daily living assessment in older adults and mild cognitive impairment. J Clin Exp Neuropsychol. 2012;34(1):11-34.
11. Inzitari D, Pracucci G, Poggesi A, et al. Changes in white matter as determinant of global functional decline in older independent outpatients: three year follow-up of LADIS (leukoaraiosis and disability) study cohort. BMJ. 2009;339:b2477.
12. Inzitari D, Simoni M, Pracucci G, et al. Risk of rapid global functional decline in elderly patients with severe cerebral age-related white matter changes: the LADIS study. Arch Intern Med. 2007;167(1):81-88.
13. Rosano C, Kuller LH, Chung H, et al. Subclinical brain magnetic resonance imaging abnormalities predict physical functional decline in high-functioning older adults. J Am Geriatr Soc. 2005;53(4):649-654.
14. Hofman A, Darwish Murad S, van Duijn CM, et al. The Rotterdam Study: 2014 objectives and design update. Eur J Epidemiol. 2013;28(11):889-926.
15. Ikram MA, van der Lugt A, Niessen WJ, et al. The Rotterdam Scan Study: design and update up to 2012. Eur J Epidemiol. 2011;26(10):811-824.
16. de Boer R, Vrooman HA, van der Lijn F, et al. White matter lesion extension to automatic brain tissue segmentation on MRI. Neuroimage. 2009;45(4):1151-1161.
17. Vrooman HA, Cocosco CA, van der Lijn F, et al. Multi-spectral brain tissue segmentation using automatically trained k-Nearest-Neighbor classification. Neuroimage. 2007;37(1):71-81.
18. van der Lijn F, den Heijer T, Breteler MM, Niessen WJ. Hippocampus segmentation in MR images using atlas registration, voxel classification, and graph cuts. Neuroimage. 2008;43(4):708-720.
19. Vernooij MW, Ikram MA, Tanghe HL, et al. Incidental findings on brain MRI in the general population. N Engl J Med. 2007;357(18):1821-1828.
20. Poels MM, Vernooij MW, Ikram MA, et al. Prevalence and risk factors of cerebral microbleeds: an update of the Rotterdam scan study. Stroke. 2010;41(10 Suppl):S103-106.
21. Koppelmans V, Groot MD, de Ruiter MB, et al. Global and focal white matter integrity in breast cancer survivors 20 years after adjuvant chemotherapy. Hum Brain Mapp. 2014;35(3):889-899.
22. Leemans A, Jeurissen B, Sijbers J, Jones DK. ExploreDTI: a graphical toolbox for processing, analyzing, and visualizing diffusion MR data. Proceedings 17th Scientific Meeting International Society for Magnetic Resonance in Medicine. 2009:3537.
23. Greve DN, Fischl B. Accurate and robust brain image alignment using boundary-based registration. Neuroimage. 2009;48(1):63-72.
24. Jenkinson M, Bannister P, Brady M, Smith S. Improved optimization for the robust and accurate linear registration and motion correction of brain images. Neuroimage. 2002;17(2):825-841.
25. Fries JF, Spitz PW, Young DY. The dimensions of health outcomes: the health assessment questionnaire, disability and pain scales. J Rheumatol. 1982;9(5):789-793.
26. Bruce B, Fries JF. The Stanford Health Assessment Questionnaire: dimensions and practical applications. Health Qual Life Outcomes. 2003;1:20.
27. Lawton MP, Brody EM. Assessment of older people: self-maintaining and instrumental activities of daily living. Gerontologist. 1969;9(3):179-186.
28. Jefferson AL, Paul RH, Ozonoff A, Cohen RA. Evaluating elements of executive functioning as predictors of instrumental activities of daily living (IADLs). Arch Clin Neuropsychol. 2006;21(4):311-320.
29. Folstein MF, Folstein SE, McHugh PR. "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res. 1975;12(3):189-198.
30. Radloff LS. The CES-D Scale: a self-report depression scale for research in the general population. Appl Psychol Meas. 1977;1:385-401.
31. Vickers AJ, Altman DG. Statistics notes: analysing controlled trials with baseline and follow up measurements. BMJ. 2001;323(7321):1123-1124.
32. Cahn-Weiner DA, Farias ST, Julian L, et al. Cognitive and neuroimaging predictors of instrumental activities of daily living. J Int Neuropsychol Soc. 2007;13(5):747-757.
33. Godin O, Tzourio C, Maillard P, et al. Antihypertensive treatment and change in blood pressure are associated with the progression of white matter lesion volumes: the Three-City (3C)-Dijon Magnetic Resonance Imaging Study. Circulation. 2011;123(3):266-273.
34. Firbank MJ, Wiseman RM, Burton EJ, et al. Brain atrophy and white matter hyperintensity change in older adults and relationship to blood pressure. Brain atrophy, WMH change and blood pressure. J Neurol. 2007;254(6):713-721.