White matter hyperintensity shape is associated with cognitive functioning – the SMART-MR study

Neurobiology of Aging, vol. 120, pp. 81–87

Abstract

White matter hyperintensity (WMH) shape has been associated with the severity of the underlying brain pathology, suggesting it is a potential neuroimaging marker of WMH impact on brain function. In 563 patients with vascular disease (58 ± 10 years), we examined the relationship between WMH volume, shape, and cognitive functioning. WMH volume and shape were automatically determined on 1.5T brain MRI data. Standardized linear regression analyses estimated the association between WMH volume and shape (concavity index, solidity, convexity, fractal dimension, and eccentricity) and memory and executive functioning, adjusted for age, sex, educational level, and reading ability. Larger WMH volumes were associated with lower executive functioning Z-scores (b (95%-CI): -0.09 (-0.17;-0.01)). Increased shape complexity of periventricular/confluent WMH associated with lower executive functioning (concavity index +1SD: -0.13 (-0.20;-0.06); solidity -1SD: -0.09 (-0.17;-0.02)) and lower memory function (fractal dimension +1SD: -0.10 (-0.18;-0.02)). Of note, the association between concavity index and executive functioning was independent of WMH volume (-0.12 (-0.19;-0.04)). Our results suggest that WMH shape contains additional information about WMH burden, not otherwise captured by WMH volume.

Authors 7

1. Maarten H.T. Zwartbol

   Utrecht University · University Medical Center Utrecht

   Affiliation as printed

   Department of Radiology, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands

2. Rashid Ghaznawi

   Utrecht University · University Medical Center Utrecht

   Affiliation as printed

   Department of Radiology, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands; Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands

   Department of Radiology, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands

   Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands

3. Myriam G. Jaarsma‐Coes Aachen Department of Radiology, Leiden University Medical Center

   Utrecht University · Leiden University Medical Center · University Medical Center Utrecht

   Affiliation as printed

   Department of Radiology, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands; Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands

   Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands

   Department of Radiology, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands

4. Hugo J. Kuijf

   Utrecht University · University Medical Center Utrecht

   Affiliation as printed

   Image Sciences Institute, University Medical Center Utrecht, Utrecht, the Netherlands

5. Jeroen Hendrikse

   Utrecht University · University Medical Center Utrecht

   Affiliation as printed

   Department of Radiology, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands

6. Jeroen de Bresser Aachen Department of Radiology, Leiden University Medical Center

   Leiden University Medical Center

   Affiliation as printed

   Department of Radiology, Leiden University Medical Center, Leiden, the Netherlands

7. Mirjam I. Geerlings corresponding

   Utrecht University · University Medical Center Utrecht

   Affiliation as printed

   Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands. Electronic address: m.geerlings@umcutrecht.nl

   Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht and Utrecht University, Utrecht, the Netherlands