title: Evaluation of age-related white matter changes using transcranial Doppler ultrasonography.
abstract: BACKGROUND
  Age-related white matter changes (WMC) increase risk of cognitive and functional decline. They are considered as target for preventive trials. However, using magnetic resonance imaging (MRI) to screen for subclinical WMC is not cost-effective. We explored the clinical utility of transcranial Doppler ultrasound (TCD) in the evaluation of WMC. We hypothesized that the pulsatility index (PI) of TCD correlates with severity of WMC.
  
  
  METHODS
  Among 100 stroke patients with WMC, we obtained the mean PI of middle cerebral artery (MCA) and vertebral basilar artery (VB). We investigated the association between PI and WMC volume. We also obtained PI of 50 subjects who had no WMC on MRI and explored the ability of PI values in differentiating subjects with and without WMC.
  
  
  RESULTS
  Multivariate linear regressions found that mean MCA PI and mean VB PI were independent predictors for total WMC volume (beta = .43, P < .001 and beta = .37, P < .001, respectively). Mean MCA PI significantly differentiated patients with WMC from those without WMC (area under curve [AUC] .85 [95% confidence interval .78-.91]) with an optimal cut-off value at 1.15 that yielded sensitivity and specificity of 73.7% and 82%, respectively. AUC for mean VB PI was .81 (95% confidence interval .74-.88) with cut-off value at 1.06 that yielded sensitivity and specificity of 70% and 75%, respectively.
  
  
  CONCLUSIONS
  PI correlates with volume of WMC. It may help to differentiate those with and without WMC in stroke patients. Further study evaluating the clinical utility of TCD in screening for subclinical WMC among community elderly is warranted.
authors.affiliation: Department of Medicine and Therapeutics, The Chinese University of Hong Kong, Shatin, Hong Kong Special Administrative Region, China.
authors.forename: Yun Yun
authors.initials: YY
authors.lastname: Xiong
authors.forename: Vincent
authors.initials: V
authors.lastname: Mok
authors.forename: Adrian
authors.initials: A
authors.lastname: Wong
authors.forename: Thomas
authors.initials: T
authors.lastname: Leung
authors.forename: Xiang Yan
authors.initials: XY
authors.lastname: Chen
authors.forename: Winnie C W
authors.initials: WC
authors.lastname: Chu
authors.forename: Yannie
authors.initials: Y
authors.lastname: Soo
authors.forename: Jian Hui
authors.initials: JH
authors.lastname: Fu
authors.forename: Ding
authors.initials: D
authors.lastname: Ding
authors.forename: Zhen
authors.initials: Z
authors.lastname: Hong
authors.forename: Ka Sing
authors.initials: KS
authors.lastname: Wong
mesh_terms: D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D005260:Female; D006723:Hong Kong; D006801:Humans; D008297:Male; D008875:Middle Aged; D009413:Nerve Fibers, Myelinated / Q000000981:diagnostic imaging*; D015995:Prevalence; D012307:Risk Factors; D020521:Stroke / Q000453:epidemiology* / Q000473:pathology*; D017585:Ultrasonography, Doppler, Transcranial / Q000706:statistics & numerical data*