title: Multifractal analysis of deep white matter microstructural changes on MRI in relation to early-stage atherosclerosis.
abstract: Multifractal analysis based on generalized concepts of fractals has been applied to evaluate biological tissues composed of complex structures. This type of analysis can provide a precise quantitative description of a broad range of heterogeneous phenomena. Previously, we applied multifractal analysis to describe heterogeneity in white matter signal fluctuation on T2-weighted MR images as a new method of texture analysis and established Deltaalpha as the most suitable index for evaluating white matter structural complexity (Takahashi et al. J. Neurol. Sci., 2004; 225: 33-37). Considerable evidence suggests that pathophysiological processes occurring in deep white matter regions may be partly responsible for cognitive deterioration and dementia in elderly subjects. We carried out a multifractal analysis in a group of 36 healthy elderly subjects who showed no evidence of atherosclerotic risk factors to examine the microstructural changes of the deep white matter on T2-weighted MR images. We also performed conventional texture analysis, i.e., determined the standard deviation of signal intensity divided by mean signal intensity (SD/MSI) for comparison with multifractal analysis. Next, we examined the association between the findings of these two types of texture analysis and the ultrasonographically measured intima-media thickness (IMT) of the carotid arteries, a reliable indicator of early carotid atherosclerosis. The severity of carotid IMT was positively associated with Deltaalpha in the deep white matter region. In addition, this association remained significant after excluding 12 subjects with visually detectable deep white matter hyperintensities on MR images. However, there was no significant association between the severity of carotid IMT and SD/MSI. These results indicate the potential usefulness of applying multifractal analysis to conventional MR images as a new approach to detect the microstructural changes of apparently normal white matter during the early stages of atherosclerosis.
authors.affiliation: Department of Neuropsychiatry, Faculty of Medical Sciences, University of Fukui, 23-3 Shimoaizuki, Matsuoka-cho, Yoshida-gun, Fukui 910-1193, Japan.
authors.forename: Tetsuya
authors.initials: T
authors.lastname: Takahashi
authors.forename: Tetsuhito
authors.initials: T
authors.lastname: Murata
authors.forename: Kosuke
authors.initials: K
authors.lastname: Narita
authors.forename: Toshihiko
authors.initials: T
authors.lastname: Hamada
authors.forename: Hirotaka
authors.initials: H
authors.lastname: Kosaka
authors.forename: Masao
authors.initials: M
authors.lastname: Omori
authors.forename: Koichi
authors.initials: K
authors.lastname: Takahashi
authors.forename: Hirohiko
authors.initials: H
authors.lastname: Kimura
authors.forename: Haruyoshi
authors.initials: H
authors.lastname: Yoshida
authors.forename: Yuji
authors.initials: Y
authors.lastname: Wada
mesh_terms: D000368:Aged; D000465:Algorithms; D050197:Atherosclerosis / Q000473:pathology*; D001794:Blood Pressure / Q000502:physiology; D018660:Blood Pressure Monitoring, Ambulatory; D015992:Body Mass Index; D001921:Brain / Q000473:pathology* / Q000648:ultrastructure; D002339:Carotid Arteries / Q000000981:diagnostic imaging / Q000473:pathology; D002784:Cholesterol / Q000097:blood; D005260:Female; D017709:Fractals; D006801:Humans; D007091:Image Processing, Computer-Assisted; D016014:Linear Models; D008279:Magnetic Resonance Imaging; D008297:Male; D015203:Reproducibility of Results; D012307:Risk Factors; D014463:Ultrasonography
chemical_list: D002784:Cholesterol