Structural network connectivity and cognition in cerebral small vessel disease

Area of Science:

• Neuroimaging
• Neurology
• Cognitive Science

Background:

• Cerebral small vessel disease (SVD) is linked to cognitive impairment, but conventional MRI markers like white matter hyperintensities (WMH), lacunes, and microbleeds don't fully explain clinical variations.
• Existing MRI markers for SVD have limitations in accounting for the full spectrum of cognitive deficits observed in affected individuals.

Purpose of the Study:

• To investigate the relationship between conventional MRI markers of SVD, brain structural network efficiency, and cognitive performance in non-demented elderly individuals.
• To determine if network efficiency mediates the association between SVD markers and cognitive decline.

Main Methods:

• Structural connectivity networks were computed using diffusion tensor imaging and deterministic streamlining in 436 non-demented elderly participants with cerebral SVD.
• Multiple regression models were employed to assess the independent association of network efficiency with cognitive performance, controlling for SVD severity.

Main Results:

• Higher SVD severity (increased WMH, lacunes, microbleeds; decreased brain volume) correlated with reduced network density, connection strength, and overall network efficiency.
• Network efficiency remained significantly associated with cognitive index and psychomotor speed, independent of SVD MRI markers.
• Network efficiency mediated the relationship between SVD markers and cognitive performance.

Conclusions:

• Brain network inefficiency may be a key mechanism driving cognitive impairment associated with cerebral small vessel disease.
• Network analysis offers valuable insights into SVD-related cognitive impairment beyond traditional MRI markers, potentially serving as a novel disease marker.