Structural or Functional Metrics to Assess Motor Impairment in Chronic Stroke?

HomeStrokeVol. 52, No. 1Structural or Functional Metrics to Assess Motor Impairment in Chronic Stroke? Free AccessEditorialPDF/EPUBAboutView PDFView EPUBSections ToolsAdd favoritesDownload citationsTrack citationsPermissions ShareShare onFacebookTwitterLinked InMendeleyReddit Jump toFree AccessEditorialPDF/EPUBStructural Assia Jaillard JaillardAssia Correspondence to: Jaillard, MD, PhD, SFR1 RMN Biomédicale et Neurosciences, Unité IRM 3 Tesla Recherche, CHU Grenoble Alpes, BP 217 - 38043 Cedex 9 France. Email E-mail Address: [email protected] IRMaGe, Inserm-US17 CNRS-UMS3552 UGA Alpes (CHUGA), Grenoble, France (A.J.). Université AGEIS, EA 7407, Pôle CHUGA, Search for more papers by this author Originally published15 Dec 2020https://doi.org/10.1161/STROKEAHA.120.032992Stroke. 2021;52:250–252This article is a commentary on the followingMultimodal Assessment of System Patients With Ischemic StrokeOther version(s) articleYou are viewing most recent version article. Previous versions: December 15, 2020: Ahead Print deficits following stroke leading cause long-term disability adults. Although advances management acute ischemic have improved patients’ outcome, few treatments available at chronic period stroke, neurorehabilitation remaining cornerstone motor impairment treatment.1 There evidence suggesting that correlated with structural and functional metrics provided set neurophysiological neuroimaging techniques2–5 may help clinicians improve impact attacking problem treatment from an original angle. Two types used. Macrostructural computed using lesion damaged corticospinal tract (CST) volumes obtained morphological tomography magnetic resonance imaging (MRI) images, whereas microstructural metrics, such as fractional anisotropy (FA), derived diffusion MRI assessing white matter tracts. The CST, also labeled pyramidal since CST fibers cross level medullar pyramids, main descending pathway. usual target studies aimed identifying upper limb function outcome.4 measures can be several techniques including transcranial stimulation (TMS), EEG, magnetoencephalography, near infrared spectroscopy, MRI. For instance, TMS, if applied over head region corresponding hand area primary cortex, elicit evoked potentials (MEPs) muscles contralateral limb. TMS used evaluate excitability ipsilesional (damaged) contralesional (nondamaged) cortices resting threshold.6,7See related article, p 241There debate among constellation approaches serve surrogates function.2,3,8A first question whether single measure predict function, fitting one size fits all concept? example, FA asymmetry measured internal capsule appears reliable metric explaining around half its variance.4,9 shown MEP parameters time testing, providing potential biomarkers, although some limitations might considered due methodological heterogeneity between studies.6,7,10 Conversely, multimodal based combination prediction accuracy.3,5,8An alternative perspective proposed Nazarova al11 report issue Stroke was develop sophisticated models combined modality performances small samples. This study 35 patients unilateral hemispheric who underwent clinical tests well assessment system tested would provide complementary redundant information outcome. authors corpus callosum, TMS-derived MEPs thresholds recorded 2 distinct (instead one) classify into categories assessed good, moderate, bad included Fréchet distance profiles. represents similarity curves accounting location order points along these (ie, profiles), so greater distance, damage.The results showed either (<0.75) (absence presence) were able differentiate good moderate paresis but not groups. In contrast, differed significantly three Moreover, correct classification each groups only combining CSTs. Regarding measures, there trend outcome when could elicited rather than MEPs. Of note, callosum did lead However, decreased group no MEPs.Overall, simple insufficient classification, line previous reports.3 Furthermore, their findings suggest better proxy function. need replicated larger samples, especially regarding relevance biomarkers paralleled other reports tracts walk recovery.12,13 Finally, benefit approach. appear counter-intuitive according view more, better, supposed information.5 Yet, another comparing has reported parameter (resting thresholds) predictor outcome.10How practice change knowing al,11 what issues remain addressed? Above all, mechanisms recovery investigated reduce fraction variance unexplained current new therapeutics postacute stroke. we face contradictory aims. On hand, extensive associated biological patient data way explore brain mechanisms, approach expansive, time-consuming, hardly simple. standardized implemented select responders guide individual management.A reconcile include sequence routine protocol performed subacute increase sample sizes, allowing validation different periods various demographics, factors, outcomes. Indeed, duration least 30 directions typically 6 minutes, which same 3-dimensional sequences. described lasting 1 hour, cannot administered protocol. A problematic severe yet population novel therapeutics, acquired almost patients. it should reminded task sequences offer advantage relative (3–15 minutes) limitations, state. appropriate exploring evidenced literature.2,14In conclusion, robust management, reliability contribution validated further studies.Sources FundingNone.DisclosuresNone.FootnotesThe opinions expressed necessarily those editors American Heart Association.For Disclosures, see page 251.Correspondence assia.[email protected]frReferences1. Albert SJ, Kesselring J. Neurorehabilitation.Brainin M., Heiss W-D, eds. Textbook Medicine. Cambridge University Press; 2010:283–306.Google Scholar2. Salvalaggio A, De Filippo Grazia M, Zorzi Thiebaut de Schotten Corbetta M. Post-stroke deficit indirect disconnection.Brain. 2020; 143:2173–2188. doi: 10.1093/brain/awaa156CrossrefMedlineGoogle Scholar3. Rosso C, Lamy JC. Prediction after stroke: being pragmatic innovative?Curr Opin Neurol. 33:482–487. 10.1097/WCO.0000000000000843Google Scholar4. Kumar P, Kathuria Nair Prasad K. tensor imaging: systematic review meta-analysis.J Stroke. 2016; 18:50–59. 10.5853/jos.2015.01186Google Scholar5. Stinear CM, Barber PA, Smale PR, Coxon JP, Fleming MK, Byblow WD. depends integrity.Brain. 2007; 130(pt 1):170–180. 10.1093/brain/awl333CrossrefMedlineGoogle Scholar6. Bembenek Kurczych K, Karli Nski Czlonkowska A. prognostic value motor-evoked − literature.Funct 2012; 27:79–84.MedlineGoogle Scholar7. Does threshold stroke?Front 2018; 9:1020. 10.3389/fneur.2018.01020Google Scholar8. Cunningham DA, Machado Janini D, Varnerin N, Bonnett Yue G, Jones S, Lowe Beall E, Sakaie al. inter-hemispheric imbalance noninvasive stroke.Arch Phys Med Rehabil. 2015; 96(4 Suppl):S94–103. 10.1016/j.apmr.2014.07.419Google Scholar9. Lindenberg R, Zhu LL, Rüber T, Schlaug G. Predicting imaging.Hum Brain Mapp. 33:1040–1051. 10.1002/hbm.21266CrossrefMedlineGoogle Scholar10. Kemlin Moulton JC, Houot Valabregue Leder Obadia MA, Meseguer Yger Brochard V, Elucidating correlates upper-limb poststroke impairment.Stroke. 2019; 50:3647–3649. 10.1161/STROKEAHA.119.027126LinkGoogle Scholar11. Kulikova Piradov Limonova AS, Dobrynina LA, Konovalov RN, Novikov Sehm B, Villringer Saltykova Multimodal imaging-transcranial stroke.Stroke. 52:241–249. 10.1161/STROKEAHA.119.028832Google Scholar12. Jang SH, Chang CH, Lee J, Kim CS, Seo Yeo SS. role corticoreticular pathway patients.Stroke. 2013; 44:1099–1104. 10.1161/STROKEAHA.111.000269LinkGoogle Scholar13. Soulard Huber Baillieul Thuriot Renard F, Aubert Broche Krainik Vuillerme A; ISIS-HERMES Group. integrity predicts walking recovery: stroke.Neurology. 94:e583–e593. 10.1212/WNL.0000000000008755Google Scholar14. Hannanu FF, Goundous I, Detante O, Naegele Spatiotemporal patterns sensorimotor fMRI activity influence longitudinal task-related study.Cortex. 129:80–98. 10.1016/j.cortex.2020.03.024Google Scholar Back top Next FiguresReferencesRelatedDetailsCited By Lohkamp Kiliaan Shenk Verweij V Wiesmann M (2021) Impact Voluntary Exercise Recovery, Frontiers Neuroscience, 10.3389/fnins.2021.695138, 15 Related articlesMultimodal StrokeMaria Nazarova, 2021;52:241-249 January 2021Vol Issue Advertisement Article InformationMetrics © 2020 Association, Inc.https://doi.org/10.1161/STROKEAHA.120.032992PMID: 33317413 publishedDecember Keywordspyramidal tractdiffusion MRImotor cortexEditorialsmagnetic imagingPDF download SubjectsIschemic StrokeMagnetic Resonance Imaging (MRI)NeurostimulationPrognosisQuality Outcomes