title: MRI biomarkers of vascular damage and atrophy predicting mortality in a memory clinic population.
abstract: OBJECTIVE
  MRI biomarkers play an important role in the diagnostic work-up of dementia, but their prognostic value is less well-understood. We investigated if simple MRI rating scales predict mortality in a memory clinic population.
  
  
  METHODS
  We included 1138 consecutive patients attending our memory clinic. Diagnostic categories were: subjective complaints (n=220), mild cognitive impairment (n=160), Alzheimer disease (n=357), vascular dementia (n=46), other dementia (n=136), and other diagnosis (n=219). Baseline MRIs were assessed using visual rating scales for medial temporal lobe atrophy (range, 0-4), global cortical atrophy (range, 0-3), and white matter hyperintensities (range, 0-3). Number of microbleeds and presence of infarcts were recorded. Cox-regression models were used to calculate the risk of mortality.
  
  
  RESULTS
  Mean follow-up duration was 2.6 (+/-1.9) years. In unadjusted models, all MRI markers except infarcts predicted mortality. After adjustment for age, sex, and diagnosis, white matter hyperintensities, and microbleeds predicted mortality (white matter hyperintensities: hazard ratio [HR], 1.2; 95% CI, 1.0-1.4; microbleeds: HR, 1.02 95% CI, 1.00-1.03; categorized: HR, 1.5; 95% CI, 1.1-2.0). The predictive effect of global cortical atrophy was restricted to younger subjects (HR, 1.7; 95% CI, 1.2-2.6). An interaction between microbleeds and global cortical atrophy indicated that mortality was especially high in patients with both microbleeds and global cortical atrophy.
  
  
  CONCLUSIONS
  Simple MRI biomarkers, in addition to their diagnostic use, have a prognostic value with respect to mortality in a memory clinic population. Microbleeds were the strongest predictor of mortality.
authors.affiliation: Department of Radiology and Alzheimer Center, VU University Medical Center, Amsterdam, The Netherlands. w.henneman@vumc.nl
authors.forename: Wouter J P
authors.initials: WJ
authors.lastname: Henneman
authors.forename: Jasper D
authors.initials: JD
authors.lastname: Sluimer
authors.forename: Charlotte
authors.initials: C
authors.lastname: Cordonnier
authors.forename: Merel M E
authors.initials: MM
authors.lastname: Baak
authors.forename: Philip
authors.initials: P
authors.lastname: Scheltens
authors.forename: Frederik
authors.initials: F
authors.lastname: Barkhof
authors.forename: Wiesje M
authors.initials: WM
authors.lastname: van der Flier
mesh_terms: D000367:Age Factors; D000368:Aged; D000544:Alzheimer Disease / Q000401:mortality / Q000473:pathology; D001284:Atrophy; D015415:Biomarkers; D001921:Brain / Q000473:pathology*; D002536:Cerebral Arteries / Q000473:pathology; D002543:Cerebral Hemorrhage / Q000401:mortality / Q000473:pathology; D002550:Cerebral Veins / Q000473:pathology; D002560:Cerebrovascular Circulation; D002561:Cerebrovascular Disorders / Q000401:mortality / Q000473:pathology*; D003072:Cognition Disorders / Q000401:mortality / Q000473:pathology; D003704:Dementia / Q000401:mortality* / Q000473:pathology*; D015140:Dementia, Vascular / Q000401:mortality / Q000473:pathology; D005260:Female; D006801:Humans; D053208:Kaplan-Meier Estimate; D008279:Magnetic Resonance Imaging; D008297:Male; D008569:Memory Disorders / Q000401:mortality* / Q000473:pathology*; D019636:Neurodegenerative Diseases / Q000401:mortality / Q000473:pathology; D011153:Population; D011379:Prognosis; D012044:Regression Analysis; D018570:Risk Assessment; D012737:Sex Factors
chemical_list: D015415:Biomarkers