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

• Published in: Annals of neurology Vol. 80; no. 4; pp. 581 - 592
• Main Authors: Baykara, Ebru, Gesierich, Benno, Adam, Ruth, Tuladhar, Anil Man, Biesbroek, J. Matthijs, Koek, Huiberdina L., Ropele, Stefan, Jouvent, Eric, Chabriat, Hugues, Ertl-Wagner, Birgit, Ewers, Michael, Schmidt, Reinhold, de Leeuw, Frank-Erik, Biessels, Geert Jan, Dichgans, Martin, Duering, Marco
• Format: Journal Article
• Language: English
• Published: United States Blackwell Publishing Ltd 01.10.2016; Wiley Subscription Services, Inc
• Subjects: Adult; Aged; Aged, 80 and over; Alzheimer Disease - diagnostic imaging; Biomarkers; Cerebral Small Vessel Diseases - complications; Cerebral Small Vessel Diseases - diagnostic imaging; Cognitive Dysfunction - diagnostic imaging; Cognitive Dysfunction - etiology; Cognitive Dysfunction - physiopathology; Diffusion Tensor Imaging - methods; Diffusion Tensor Imaging - standards; Female; Humans; Male; Middle Aged; Reproducibility of Results; White Matter - diagnostic imaging; Young Adult
• ISSN: 0364-5134; 1531-8249; 1531-8249
• DOI: 10.1002/ana.24758

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 (R2 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.