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Ann Neurol. 2016 Oct;80(4):581-92. doi: 10.1002/ana.24758. Epub 2016 Aug 29.

A Novel Imaging Marker for Small Vessel Disease Based on Skeletonization of White Matter Tracts and Diffusion Histograms.

Author information

1
Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University LMU, Munich, Germany.
2
Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behavior, Department of Neurology, Nijmegen, the Netherlands.
3
Department of Neurology, Brain Center Rudolf Magnus, University Medical Center Utrecht, Utrecht, the Netherlands.
4
Department of Geriatrics, University Medical Center Utrecht, Utrecht, the Netherlands.
5
Department of Neurology, Medical University of Graz, Graz, Austria.
6
Université Paris Diderot, Sorbonne Paris Cité, UMR-S 1161 National Institute for Health and Medical Research (INSERM), Paris, France.
7
Departement Hospitalo-Universitaire NeuroVasc Sorbonne Paris Cité, Paris, France.
8
Department of Neurology, Lariboisière Hospital, Assistance Publique - Hôpitaux de Paris, Paris, France.
9
Institute of Clinical Radiology, Klinikum der Universität München, Ludwig-Maximilians-University LMU, Munich, Germany.
10
Munich Cluster for Systems Neurology (SyNergy), Munich, Germany.
11
German Center for Neurodegenerative Diseases (DZNE), Munich, Germany.
12
Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-University LMU, Munich, Germany. marco.duering@med.uni-muenchen.de.

Abstract

OBJECTIVE:

To establish a fully automated, robust imaging marker for cerebral small vessel disease (SVD) and related cognitive impairment that is easy to implement, reflects disease burden, and is strongly associated with processing speed, the predominantly affected cognitive domain in SVD.

METHODS:

We developed a novel magnetic resonance imaging marker based on diffusion tensor imaging, skeletonization of white matter tracts, and histogram analysis. The marker (peak width of skeletonized mean diffusivity [PSMD]) was assessed along with conventional SVD imaging markers. We first evaluated associations with processing speed in patients with genetically defined SVD (n = 113). Next, we validated our findings in independent samples of inherited SVD (n = 57), sporadic SVD (n = 444), and memory clinic patients with SVD (n = 105). The new marker was further applied to healthy controls (n = 241) and to patients with Alzheimer's disease (n = 153). We further conducted a longitudinal analysis and interscanner reproducibility study.

RESULTS:

PSMD was associated with processing speed in all study samples with SVD (p-values between 2.8 × 10(-3) and 1.8 × 10(-10) ). PSMD explained most of the variance in processing speed (R(2) ranging from 8.8% to 46%) and consistently outperformed conventional imaging markers (white matter hyperintensity volume, lacune volume, and brain volume) in multiple regression analyses. Increases in PSMD were linked to vascular but not to neurodegenerative disease. In longitudinal analysis, PSMD captured SVD progression better than other imaging markers.

INTERPRETATION:

PSMD is a new, fully automated, and robust imaging marker for SVD. PSMD can easily be applied to large samples and may be of great utility for both research studies and clinical use. Ann Neurol 2016;80:581-592.

PMID:
27518166
DOI:
10.1002/ana.24758
[Indexed for MEDLINE]

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