title: Body fat distribution as a risk factor for cerebrovascular disease: an MRI-based body fat quantification study.
abstract: BACKGROUND
  While adiposity is a well-established risk factor for cardiovascular disease, the association between adiposity and cerebrovascular disease is not entirely understood. For example, common methods to quantify body fat volume such as body mass index, waist circumference and waist-to-hip ratio are not suitable to identify the complex distribution patterns of body fat and its relation to cerebrovascular pathology. In view of a better understanding of the association between fat distribution and cerebrovascular disorders, the aim of the study was to perform measurements of body fat distribution patterns and body fat volumes in correlation to arteriosclerosis of the brain-feeding arteries and white matter lesion load (WMLL).
  
  
  METHODS
  In this study we performed a magnetic resonance imaging (MRI)-based volumetric differential analysis of subcutaneous and visceral body fat distribution in 25 patients with MRI-proven hyperacute ischemic stroke. For the measurement of adipose tissue volume and tissue distribution automatic labeling analysis software was used. A correlation analysis of MRI volumetric measurements of subcutaneous and visceral body fat, atherosclerotic plaque load of the brain-feeding arteries measured by computed tomography angiography, and WMLL measured by MRI volumetry of the whole brain was performed.
  
  
  RESULTS
  The normalized total abdominal adipose tissue and the normalized subcutaneous abdominal adipose tissue showed no significant correlation with either WMLL or total plaque volume. In contrast, the normalized visceral adipose tissue showed a significant correlation with WMLL volume. Visceral adipose tissue as a percentage of total adipose tissue showed a significant correlation with WMLL. In particular, the percentage of visceral adipose tissue rather than total body fat volume strongly correlated with atherosclerosis and ischemic cerebral lesions. Furthermore, the volume of both soft and calcified plaques correlated significantly with WMLL.
  
  
  CONCLUSIONS
  Our results contribute to existing studies about the association of different patterns of fat distribution with atherosclerosis of the brain-feeding arteries, in particular highlighting the importance of visceral adiposity as a risk factor for cerebrovascular disease. The percentage of visceral adipose tissue in total adipose tissue has the potential of a sensitive parameter and might become a relevant new epidemiological marker, showing highly significant correlations with well-established markers of cerebrovascular disease. In conclusion, the percentage of visceral adipose tissue by itself has to be regarded as a risk factor for both small vessel cerebrovascular disease and cerebral atherosclerosis of the large-to-medium-sized arteries.
authors.affiliation: Department of Neurology, University of Ulm, Ulm, Germany.
authors.forename: Hanna-Sofia
authors.initials: HS
authors.lastname: Karcher
authors.forename: Robert
authors.initials: R
authors.lastname: Holzwarth
authors.forename: Hans-Peter
authors.initials: HP
authors.lastname: Mueller
authors.forename: Albert C
authors.initials: AC
authors.lastname: Ludolph
authors.forename: Roman
authors.initials: R
authors.lastname: Huber
authors.forename: Jan
authors.initials: J
authors.lastname: Kassubek
authors.forename: Elmar H
authors.initials: EH
authors.lastname: Pinkhardt
mesh_terms: D050154:Adiposity; D000368:Aged; D002545:Brain Ischemia / Q000175:diagnosis / Q000209:etiology; D002533:Cerebral Angiography / Q000379:methods; D002536:Cerebral Arteries / Q000000981:diagnostic imaging / Q000473:pathology*; D002561:Cerebrovascular Disorders / Q000175:diagnosis* / Q000209:etiology / Q000473:pathology; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted; D050152:Intra-Abdominal Fat / Q000473:pathology*; D002537:Intracranial Arteriosclerosis / Q000175:diagnosis / Q000209:etiology; D056784:Leukoencephalopathies / Q000175:diagnosis / Q000209:etiology* / Q000473:pathology; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D011237:Predictive Value of Tests; D012307:Risk Factors; D012984:Software; D020521:Stroke / Q000175:diagnosis / Q000209:etiology; D050151:Subcutaneous Fat / Q000473:pathology*; D014057:Tomography, X-Ray Computed