Evaluation of Age‐Related White Matter Changes Using Transcranial Doppler Ultrasonography. Issue 1 (13th September 2011)

• Record Type: Journal Article
• Authors: Xiong, Yun Yun; Mok, Vincent; Wong, Adrian; Leung, Thomas; Chen, Xiang Yan; Chu, Winnie C.W.; Soo, Yannie; Fu, Jian Hui; Ding, Ding; Hong, Zhen; Wong, Ka Sing
• Is Part Of: Journal of neuroimaging. Volume 23:Issue 1(2013)
• Page Start: 53
• Page End: 57
• Publication Date: 2011-09-13
• Subjects: White matter changes -- pulsatility index -- transcranial Doppler; Diagnostic imaging -- Periodicals; Nervous system -- Diseases -- Diagnosis -- Periodicals; Imagerie pour le diagnostic -- Périodiques; Système nerveux -- Maladies -- Diagnostic -- Périodiques; Imagerie médicale; Neuroimagerie; Neurologie; Système nerveux; Périodique électronique (Descripteur de forme); Ressource Internet (Descripteur de forme); 616.804754
• DOI: 10.1111/j.1552-6569.2011.00649.x
• Languages: English
• ISSNs: 1051-2284

Abstract

Abstract : 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.