Frontoparietal structural network disconnections correlate with outcome after a severe stroke
crossref(2024)
Abstract
Structural disconnectome analyses have provided valuable insights into how a stroke lesion results in widespread network disturbances and how these relate to deficits, recovery patterns, and outcome. Previous analyses have primarily focused on patients with relatively mild to moderate deficits. However, outcomes vary among survivors of severe strokes, and the mechanisms of recovery remain poorly understood. This study assesses the association between lesion-induced network disconnection and outcome after severe stroke. Thirty-eight ischaemic stroke patients underwent MRI brain imaging early after stroke and longitudinal clinical follow-up. Lesion information was integrated with normative connectome data to infer individual disconnectome profiles on a localized regional and region-to-region pathway level. Ordinal logistic regressions were computed to link disconnectome information to the modified Rankin Scale after 3-6 months. Disconnections of ipsilesional frontal, parietal and temporal cortical brain areas were significantly associated with a worse motor outcome after a severe stroke, adjusted for the initial deficit, lesion volume, and age. The analysis of the underlying pathways mediating this association revealed location specific results: For frontal, prefrontal and temporal brain areas, the association was primarily driven by relatively sparse intrahemispheric disconnections. In contrast, the ipsilesional primary motor cortex, the dorsal premotor cortex, and various parietal brain regions showed a remarkable involvement of either frontoparietal intrahemispheric or additionally interhemispheric disconnections. These results indicate that localized disconnection of multiple regions embedded in the structural frontoparietal network correlates with worse outcome after severe stroke. Specifically, primary motor and parietal cortices might gain a particular importance as they structurally link frontoparietal networks of both hemispheres. These data shed novel light on the significance of distinct brain networks for recovery after severe stroke.
### Competing Interest Statement
The authors have declared no competing interest.
### Funding Statement
This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) SFB 936 178316478, projects C1 to C.G., C2 to G.T. and SFB TRR169 project A3 with the National Science Foundation of China (NSFC) in project Crossmodal Learning to C.G., and the Else Kroener-Fresenius-Stiftung (2016\_A214 to R.S.). R.S. and C.U.C. are supported by an Else Kroener Exzellenzstipendium from the Else Kroener-Fresenius-Stiftung (2020\_EKES.16 to R.S., 2018_EKES.04 to C.U.C.). F.Q. is supported by the Gemeinnuetzige Hertie-Stiftung (Hertie Network of Excellence in Clinical Neuroscience).
### Author Declarations
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The details of the IRB/oversight body that provided approval or exemption for the research described are given below:
The original studies which were the base for this secondary analysis were conducted in line with the ethical declaration of Helsinki and were granted permission by the ethics committee of the Chamber of Physicians Hamburg. All participants or their legal guardian provided informed consent.
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