Frontiers in Neurology (Sep 2019)

Rich-Club Organization: An Important Determinant of Functional Outcome After Acute Ischemic Stroke

  • Markus D. Schirmer,
  • Markus D. Schirmer,
  • Markus D. Schirmer,
  • Sofia Ira Ktena,
  • Marco J. Nardin,
  • Kathleen L. Donahue,
  • Anne-Katrin Giese,
  • Mark R. Etherton,
  • Ona Wu,
  • Natalia S. Rost

DOI
https://doi.org/10.3389/fneur.2019.00956
Journal volume & issue
Vol. 10

Abstract

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Objective: To determine whether the rich-club organization, essential for information transport in the human connectome, is an important biomarker of functional outcome after acute ischemic stroke (AIS).Methods: Consecutive AIS patients (N = 344) with acute brain magnetic resonance imaging (MRI) (<48 h) were eligible for this study. Each patient underwent a clinical MRI protocol, which included diffusion weighted imaging (DWI). All DWIs were registered to a template on which rich-club regions have been defined. Using manual outlines of stroke lesions, we automatically counted the number of affected rich-club regions and assessed its effect on the National Institute of Health Stroke Scale (NIHSS) and modified Rankin Scale (mRS; obtained at 90 days post-stroke) scores through ordinal regression.Results: Of 344 patients (median age 65, inter-quartile range 54–76 years) with a median DWI lesion volume (DWIv) of 3cc, 64% were male. We established that an increase in number of rich-club regions affected by a stroke increases the odds of poor stroke outcome, measured by NIHSS (OR: 1.77, 95%CI 1.41–2.21) and mRS (OR: 1.38, 95%CI 1.11–1.73). Additionally, we demonstrated that the OR exceeds traditional markers, such as DWIv (ORNIHSS 1.08, 95%CI 1.06–1.11; ORmRS 1.05, 95%CI 1.03–1.07) and age (ORNIHSS 1.03, 95%CI 1.01–1.05; ORmRS 1.05, 95%CI 1.03–1.07).Conclusion: In this proof-of-concept study, the number of rich-club nodes affected by a stroke lesion presents a translational biomarker of stroke outcome, which can be readily assessed using standard clinical AIS imaging protocols and considered in functional outcome prediction models beyond traditional factors.

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