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Structural brain disconnectivity mapping of post-stroke fatigue
•We tested for associations between post stroke fatigue (PSF) and both lesion characteristics and brain structural disconnectome in 84 S patients.•Results provided no evidence supporting a simple association between PSF severity and lesion characteristics or disconnectivity.•PSF was strongly correla...
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Published in: | NeuroImage clinical 2021-01, Vol.30, p.102635-102635, Article 102635 |
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creator | Ulrichsen, Kristine M. Kolskår, Knut K. Richard, Geneviève Alnæs, Dag Dørum, Erlend S. Sanders, Anne-Marthe Tornås, Sveinung Sánchez, Jennifer Monereo Engvig, Andreas Ihle-Hansen, Hege de Schotten, Michel Thiebaut Nordvik, Jan E. Westlye, Lars T. |
description | •We tested for associations between post stroke fatigue (PSF) and both lesion characteristics and brain structural disconnectome in 84 S patients.•Results provided no evidence supporting a simple association between PSF severity and lesion characteristics or disconnectivity.•PSF was strongly correlated with depression.•Further studies including patients with more severe symptoms are needed to generalize the findings across a wider clinical spectrum.
Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remains unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a structural disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual structural brain disconnectome maps in 84 S survivors in the chronic phase (≥3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue among chronic stroke patients are not simply explained by lesion characteristics or the extent and distribution of structural brain disconnectome, and are discussed in light of methodological considerations. |
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Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remains unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a structural disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual structural brain disconnectome maps in 84 S survivors in the chronic phase (≥3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue among chronic stroke patients are not simply explained by lesion characteristics or the extent and distribution of structural brain disconnectome, and are discussed in light of methodological considerations.</description><identifier>ISSN: 2213-1582</identifier><identifier>EISSN: 2213-1582</identifier><identifier>DOI: 10.1016/j.nicl.2021.102635</identifier><identifier>PMID: 33799271</identifier><language>eng</language><publisher>Netherlands: Elsevier Inc</publisher><subject>Brain mapping ; Cognitive science ; Lesion ; MRI ; Post-stroke fatigue ; Regular ; Stroke ; Structural disconnectome</subject><ispartof>NeuroImage clinical, 2021-01, Vol.30, p.102635-102635, Article 102635</ispartof><rights>2021 The Author(s)</rights><rights>Copyright © 2021 The Author(s). Published by Elsevier Inc. All rights reserved.</rights><rights>info:eu-repo/semantics/openAccess</rights><rights>Distributed under a Creative Commons Attribution 4.0 International License</rights><rights>2021 The Author(s) 2021</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c579t-e6c2a673e6274e4097b9ceef831796de8e5719aa639f1a632d0bc67fca2214183</citedby><cites>FETCH-LOGICAL-c579t-e6c2a673e6274e4097b9ceef831796de8e5719aa639f1a632d0bc67fca2214183</cites><orcidid>0000-0003-0981-648X ; 0000-0002-2638-2452 ; 0000-0001-6475-2576 ; 0000-0002-0329-1814</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC8044723/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S2213158221000796$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,727,780,784,885,3549,26567,27924,27925,45780,53791,53793</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/33799271$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink><backlink>$$Uhttps://hal.science/hal-03370242$$DView record in HAL$$Hfree_for_read</backlink></links><search><creatorcontrib>Ulrichsen, Kristine M.</creatorcontrib><creatorcontrib>Kolskår, Knut K.</creatorcontrib><creatorcontrib>Richard, Geneviève</creatorcontrib><creatorcontrib>Alnæs, Dag</creatorcontrib><creatorcontrib>Dørum, Erlend S.</creatorcontrib><creatorcontrib>Sanders, Anne-Marthe</creatorcontrib><creatorcontrib>Tornås, Sveinung</creatorcontrib><creatorcontrib>Sánchez, Jennifer Monereo</creatorcontrib><creatorcontrib>Engvig, Andreas</creatorcontrib><creatorcontrib>Ihle-Hansen, Hege</creatorcontrib><creatorcontrib>de Schotten, Michel Thiebaut</creatorcontrib><creatorcontrib>Nordvik, Jan E.</creatorcontrib><creatorcontrib>Westlye, Lars T.</creatorcontrib><title>Structural brain disconnectivity mapping of post-stroke fatigue</title><title>NeuroImage clinical</title><addtitle>Neuroimage Clin</addtitle><description>•We tested for associations between post stroke fatigue (PSF) and both lesion characteristics and brain structural disconnectome in 84 S patients.•Results provided no evidence supporting a simple association between PSF severity and lesion characteristics or disconnectivity.•PSF was strongly correlated with depression.•Further studies including patients with more severe symptoms are needed to generalize the findings across a wider clinical spectrum.
Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remains unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a structural disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual structural brain disconnectome maps in 84 S survivors in the chronic phase (≥3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue among chronic stroke patients are not simply explained by lesion characteristics or the extent and distribution of structural brain disconnectome, and are discussed in light of methodological considerations.</description><subject>Brain mapping</subject><subject>Cognitive science</subject><subject>Lesion</subject><subject>MRI</subject><subject>Post-stroke fatigue</subject><subject>Regular</subject><subject>Stroke</subject><subject>Structural disconnectome</subject><issn>2213-1582</issn><issn>2213-1582</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2021</creationdate><recordtype>article</recordtype><sourceid>3HK</sourceid><sourceid>DOA</sourceid><recordid>eNp9UsFu1DAQjRCIVqU_wAFyhEMWe-zEiYSoqgraSitxAM6W44y3XnbtYDsr9e9xSFu1PeCDbY3fPM-8eUXxlpIVJbT5tF05q3crIEBzABpWvyiOASiraN3Cy0f3o-I0xi3JqyVENM3r4ogx0XUg6HFx9iOFSacpqF3ZB2VdOdiovXOokz3YdFvu1Thatym9KUcfUxVT8L-xNCrZzYRvildG7SKe3p0nxa9vX39eXFXr75fXF-frSteiSxU2GlQjGDYgOHLSib7TiKZlVHTNgC3WgnZKNawzNO8wkF43wmiV2-C0ZSfF9cI7eLWVY7B7FW6lV1b-C_iwkSqkrAhKwEEozXtEyjkI0zPDQBNG1ECZMpC5vixc49TvcdDoUm7_CenTF2dv5MYfZEs4F8AywceF4OZZ2tX5Ws4xkgUmwOFAM_b9gtXBxmSddD4oSUlbg2wFh7mcD3flBP9nwpjkPo8Adzvl0E9RQp3BWRJaZyjck_kYA5qH3ymRsy3kVs62kLMt5GKLnPTucbsPKfcmyIDPCwDzAA8Wg4zaotM42JBtkBW2_-P_C7t2xyw</recordid><startdate>20210101</startdate><enddate>20210101</enddate><creator>Ulrichsen, Kristine M.</creator><creator>Kolskår, Knut K.</creator><creator>Richard, Geneviève</creator><creator>Alnæs, Dag</creator><creator>Dørum, Erlend S.</creator><creator>Sanders, Anne-Marthe</creator><creator>Tornås, Sveinung</creator><creator>Sánchez, Jennifer Monereo</creator><creator>Engvig, Andreas</creator><creator>Ihle-Hansen, Hege</creator><creator>de Schotten, Michel Thiebaut</creator><creator>Nordvik, Jan E.</creator><creator>Westlye, Lars T.</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>3HK</scope><scope>1XC</scope><scope>5PM</scope><scope>DOA</scope><orcidid>https://orcid.org/0000-0003-0981-648X</orcidid><orcidid>https://orcid.org/0000-0002-2638-2452</orcidid><orcidid>https://orcid.org/0000-0001-6475-2576</orcidid><orcidid>https://orcid.org/0000-0002-0329-1814</orcidid></search><sort><creationdate>20210101</creationdate><title>Structural brain disconnectivity mapping of post-stroke fatigue</title><author>Ulrichsen, Kristine M. ; Kolskår, Knut K. ; Richard, Geneviève ; Alnæs, Dag ; Dørum, Erlend S. ; Sanders, Anne-Marthe ; Tornås, Sveinung ; Sánchez, Jennifer Monereo ; Engvig, Andreas ; Ihle-Hansen, Hege ; de Schotten, Michel Thiebaut ; Nordvik, Jan E. ; Westlye, Lars T.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c579t-e6c2a673e6274e4097b9ceef831796de8e5719aa639f1a632d0bc67fca2214183</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2021</creationdate><topic>Brain mapping</topic><topic>Cognitive science</topic><topic>Lesion</topic><topic>MRI</topic><topic>Post-stroke fatigue</topic><topic>Regular</topic><topic>Stroke</topic><topic>Structural disconnectome</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Ulrichsen, Kristine M.</creatorcontrib><creatorcontrib>Kolskår, Knut K.</creatorcontrib><creatorcontrib>Richard, Geneviève</creatorcontrib><creatorcontrib>Alnæs, Dag</creatorcontrib><creatorcontrib>Dørum, Erlend S.</creatorcontrib><creatorcontrib>Sanders, Anne-Marthe</creatorcontrib><creatorcontrib>Tornås, Sveinung</creatorcontrib><creatorcontrib>Sánchez, Jennifer Monereo</creatorcontrib><creatorcontrib>Engvig, Andreas</creatorcontrib><creatorcontrib>Ihle-Hansen, Hege</creatorcontrib><creatorcontrib>de Schotten, Michel Thiebaut</creatorcontrib><creatorcontrib>Nordvik, Jan E.</creatorcontrib><creatorcontrib>Westlye, Lars T.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>NORA - Norwegian Open Research Archives</collection><collection>Hyper Article en Ligne (HAL)</collection><collection>PubMed Central (Full Participant titles)</collection><collection>Directory of Open Access Journals</collection><jtitle>NeuroImage clinical</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Ulrichsen, Kristine M.</au><au>Kolskår, Knut K.</au><au>Richard, Geneviève</au><au>Alnæs, Dag</au><au>Dørum, Erlend S.</au><au>Sanders, Anne-Marthe</au><au>Tornås, Sveinung</au><au>Sánchez, Jennifer Monereo</au><au>Engvig, Andreas</au><au>Ihle-Hansen, Hege</au><au>de Schotten, Michel Thiebaut</au><au>Nordvik, Jan E.</au><au>Westlye, Lars T.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Structural brain disconnectivity mapping of post-stroke fatigue</atitle><jtitle>NeuroImage clinical</jtitle><addtitle>Neuroimage Clin</addtitle><date>2021-01-01</date><risdate>2021</risdate><volume>30</volume><spage>102635</spage><epage>102635</epage><pages>102635-102635</pages><artnum>102635</artnum><issn>2213-1582</issn><eissn>2213-1582</eissn><abstract>•We tested for associations between post stroke fatigue (PSF) and both lesion characteristics and brain structural disconnectome in 84 S patients.•Results provided no evidence supporting a simple association between PSF severity and lesion characteristics or disconnectivity.•PSF was strongly correlated with depression.•Further studies including patients with more severe symptoms are needed to generalize the findings across a wider clinical spectrum.
Stroke patients commonly suffer from post stroke fatigue (PSF). Despite a general consensus that brain perturbations constitute a precipitating event in the multifactorial etiology of PSF, the specific predictive value of conventional lesion characteristics such as size and localization remains unclear. The current study represents a novel approach to assess the neural correlates of PSF in chronic stroke patients. While previous research has focused primarily on lesion location or size, with mixed or inconclusive results, we targeted the extended structural network implicated by the lesion, and evaluated the added explanatory value of a structural disconnectivity approach with regards to the brain correlates of PSF. To this end, we estimated individual structural brain disconnectome maps in 84 S survivors in the chronic phase (≥3 months post stroke) using information about lesion location and normative white matter pathways obtained from 170 healthy individuals. PSF was measured by the Fatigue Severity Scale (FSS). Voxel wise analyses using non-parametric permutation-based inference were conducted on disconnectome maps to estimate regional effects of disconnectivity. Associations between PSF and global disconnectivity and clinical lesion characteristics were tested by linear models, and we estimated Bayes factor to quantify the evidence for the null and alternative hypotheses, respectively. The results revealed no significant associations between PSF and disconnectome measures or lesion characteristics, with moderate evidence in favor of the null hypothesis. These results suggest that symptoms of post-stroke fatigue among chronic stroke patients are not simply explained by lesion characteristics or the extent and distribution of structural brain disconnectome, and are discussed in light of methodological considerations.</abstract><cop>Netherlands</cop><pub>Elsevier Inc</pub><pmid>33799271</pmid><doi>10.1016/j.nicl.2021.102635</doi><tpages>1</tpages><orcidid>https://orcid.org/0000-0003-0981-648X</orcidid><orcidid>https://orcid.org/0000-0002-2638-2452</orcidid><orcidid>https://orcid.org/0000-0001-6475-2576</orcidid><orcidid>https://orcid.org/0000-0002-0329-1814</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Brain mapping Cognitive science Lesion MRI Post-stroke fatigue Regular Stroke Structural disconnectome |
title | Structural brain disconnectivity mapping of post-stroke fatigue |
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