title: Quantitative MRI findings and cognitive impairment among community dwelling elderly subjects.
abstract: OBJECTIVE
  To study the factors which influence cognitive impairment among elderly subjects living in a local community, based on both MRI and clinical findings, to further elucidate the causes of dementia, and also to help develop strategies for its prevention.
  
  
  METHODS
  Cranial MRI and other medical examinations were performed on non-demented elderly subjects who resided in one rural community. A total of 254 subjects aged from 60 to 91 years of age, with a mean age of 73.9 (SD 6.8) were examined. The mini mental state examination (MMSE) was used to identify cognitive impairment. White matter lesions and cerebral atrophy on MR images were measured quantitatively. A multivariate analysis was also performed with the existence of cognitive impairment as the dependent variable, and the MRI findings and clinical observations were used as the independent variables.
  
  
  RESULTS
  Cognitive impairment was present in 46 subjects (18.1%). They were older, had a lower educational level, and more frequent hypertension compared with those without cognitive impairment. The packed cell volume was lower in the impaired group. In addition, their MRI findings showed significantly larger quantities of white matter lesions and cerebral atrophy, as well as more infarcts. A logistic regression analysis demonstrated a significant relation among such factors as white matter lesions (odds ratio (OR) 1.575, 95% confidence interval (95% CI) 1.123-2.208), cerebral atrophy (OR 0.761, 95%CI 0.587-0.987), and lower education (OR 0.682, 95%CI 0.544-0.855) for subjects with a cognitive impairment.
  
  
  CONCLUSIONS
  White matter lesions and cerebral atrophy are factors which induce a cognitive impairment in community dwelling elderly subjects without dementia. It is important to carefully watch for any abnormalities in these factors, and to perform cohort studies to check for the above risk factors, to both prevent and make an early diagnosis of dementia.
authors.affiliation: Department of Neuropsychiatry, Faculty of Medicine, Kyushu University Hospital, Maidashi, Fukuoka 812-8582, Japan. kogah@npsych.med.kyushu-u.ac.jp
authors.forename: H
authors.initials: H
authors.lastname: Koga
authors.forename: T
authors.initials: T
authors.lastname: Yuzuriha
authors.forename: H
authors.initials: H
authors.lastname: Yao
authors.forename: K
authors.initials: K
authors.lastname: Endo
authors.forename: S
authors.initials: S
authors.lastname: Hiejima
authors.forename: Y
authors.initials: Y
authors.lastname: Takashima
authors.forename: F
authors.initials: F
authors.lastname: Sadanaga
authors.forename: T
authors.initials: T
authors.lastname: Matsumoto
authors.forename: A
authors.initials: A
authors.lastname: Uchino
authors.forename: K
authors.initials: K
authors.lastname: Ogomori
authors.forename: A
authors.initials: A
authors.lastname: Ichimiya
authors.forename: H
authors.initials: H
authors.lastname: Uchimura
authors.forename: N
authors.initials: N
authors.lastname: Tashiro
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D001284:Atrophy; D001921:Brain / Q000473:pathology*; D003072:Cognition Disorders / Q000209:etiology / Q000473:pathology*; D003430:Cross-Sectional Studies; D004522:Educational Status; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D012424:Rural Population