Center for Neurological Imaging

Multimodal MRI Approach to Investigate the Development of Brain Damage in Age-related Small Vessel Disease 

Context

Cerebral small vessel disease (SVD) is the most common vascular cause of dementia worldwide (Wardlaw et al., 2013), and represents a major determinant of cognitive and physical disability in the aging population (Guttmann et al., 2000; Pantoni, 2010). Several studies, including our own reports (Kaplan et al., 2009; Moscufo et al., 2011, 2012; Papp et al., 2014; Wakefield et al., 2010; White et al., 2011; Wolfson et al., 2013), supported the association between the characteristic focal white matter lesions associated with cerebral SVD and decline in cognitive and motor abilities. Since white matter lesions are considered irreversible, there is a critical need of indicators that reflect earlier events in the pathogenesis of brain lesions underlying cognitive and mobility decline, to enable interventions designed to prevent these disabling sequelae before irreversible brain damage occurs. Previous studies showed that white matter lesions are preceded by more subtle and diffused changes to the white matter, which can be detected through perfusion and diffusion MRI (Bernbaum et al., 2015; de Groot et al., 2013; Maillard et al., 2011; Promjunyakul et al., 2016; Promjunyakul et al., 2015). However, the chain of perfusion and diffusion abnormalities leading to clinically relevant white matter damage has yet to be established. Our hypothesis is that perfusion abnormalities precedes the development of diffusion abnormalities, which precede focal white matter lesions underlying functional decline in cognitive and motor performance. To test this hypothesis we will investigate the spatial and temporal relationships between perfusion changes, diffusion abnormalities, and white matter lesions, as well as their association with cognitive and motor performance.


Objective

To investigate the mechanisms leading to brain damage associated with cerebral small vessel disease. The ultimate goal of this project is to develop a new biomarker to be used for risk assessment and prevention of disability in subjects at risk for cognitive and mobility impairment.


Methodology

We propose a secondary analysis of existing multimodal longitudinal data (R01 – AG022092), including perfusion, diffusion and structural MRI acquired over four years at three time points (baseline, 2-year, and 4-year follow-up) (see Moscufo et al., 2011 for details). Image analyses for this project include:

  • Implementation of existing co-registration methodologies to improve alignment of different MRI modalities (e.g., diffusion, perfusion imaging);
  • Processing and analysis of dynamic susceptibility contrast-enhanced (DSC) perfusion images using an innovative analysis framework that provides indices of capillary perfusion (Jespersen & Østergaard, 2012; Mouridsen, Hansen, Østergaard, & Jespersen, 2014);
  • Analysis of perfusion changes in the context of diffusion abnormalities and expansion of WMH using region-of-interest and voxel-wise approaches.


Profile

  • Image processing background (ITK, VTK)
  • Programming skills in Matlab


Contact

Researchers

 Address

    1249 Boylston St, Boston 02215, Massachusetts, USA


References

  1. Jespersen, S. N., & Østergaard, L. (2012). The roles of cerebral blood flow, capillary transit time heterogeneity, and oxygen tension in brain oxygenation and metabolism. Journal of Cerebral Blood Flow & Metabolism, 32(2), 264–277.
  2. Moscufo, N., Guttmann, C. R. G., Meier, D., Csapo, I., Hildenbrand, P. G., Healy, B. C., Wolfson, L. (2011). Brain regional lesion burden and impaired mobility in the elderly. Neurobiology of Aging, 32(4), 646–54.
  3. Mouridsen, K., Hansen, M. B., Østergaard, L., & Jespersen, S. N. (2014). Reliable estimation of capillary transit time distributions using DSC-MRI. Journal of Cerebral Blood Flow & Metabolism, 34(9), 1511–1521.
  4. Pantoni, L. (2010). Cerebral small vessel disease: from pathogenesis and clinical characteristics to therapeutic challenges. Lancet Neurology, 9(7), 689–701.
  5. Promjunyakul, N.-O., Lahna, D. L., Kaye, J. A., Dodge, H. H., Erten-Lyons, D., Rooney, W. D., & Silbert, L. C. (2016). Comparison of cerebral blood flow and structural penumbras in relation to white matter hyperintensities: A multi-modal magnetic resonance imaging study. Journal of Cerebral Blood Flow and Metabolism : Official Journal of the International Society of Cerebral Blood Flow and Metabolism.
  6. Wardlaw, J. M., Smith, E. E., Biessels, G. J., Cordonnier, C., Fazekas, F., Frayne, R., Dichgans, M. (2013). Neuroimaging standards for research into small vessel disease and its contribution to ageing and neurodegeneration. Lancet Neurology, 12(8), 822–38.

See also: Project