Relationship between post-stroke trunk function and brain lesion locations: A support vector regression lesion-symptom mapping study
DOI:
https://doi.org/10.2340/jrm.v57.42782Keywords:
brain stroke, Trunk Control, mapping, neuroimaging, predictorAbstract
Objective: This study aimed to investigate the relationship between brain lesions and trunk function impairment in stroke patients.
Design: Retrospective cohort study.
Subjects/Patients: One hundred fifty-six first-time stroke patients admitted for rehabilitation between August 2021 and October 2023.
Methods: Trunk function was assessed using the Trunk Control Test. Brain lesions were detected using magnetic resonance imaging scans. Support vector regression lesion-symptom mapping was used to identify brain lesions associated with trunk function on admission and discharge, adjusted for lesion volume, age, and lower limb motor impairment.
Results: After adjusting for age, admission trunk function was linked to lesions in the right corticospinal tract, superior longitudinal fasciculus, superior thalamic radiation, and putamen. Further adjustment for lower limb motor impairment revealed associations not only with all aforementioned regions, but also with lesions in the right supplementary motor area and premotor cortex. For trunk function on discharge, no suprathreshold regions were found.
Conclusion: Early post-stroke trunk control impairment was associated with lesions in the right hemisphere, which is involved in motor function, motor control, and sensory integration. These findings provide insights into trunk dysfunction mechanisms, and suggest that targeted rehabilitation could improve trunk control and independence in daily activities for stroke patients.
Downloads
References
Lee KB, Lim SH, Kim KH, Kim KJ, Kim YR, Chang WN, et al. Six-month functional recovery of stroke patients: a multi-time-point study. Int J Rehabil Res 2015; 38: 173–180.
https://doi.org/10.1097/MRR.0000000000000108 DOI: https://doi.org/10.1097/MRR.0000000000000108
Thijs L, Voets E, Denissen S, Mehrholz J, Elsner B, Lemmens R, et al. Trunk training following stroke. Cochrane Database Syst Rev 2023; 3: CD013712.
https://doi.org/10.1002/14651858.CD013712.pub2 DOI: https://doi.org/10.1002/14651858.CD013712.pub2
Veerbeek JM, Van Wegen EE, Harmeling-Van der Wel BC, Kwakkel G, Investigators E. Is accurate prediction of gait in nonambulatory stroke patients possible within 72 hours poststroke? The EPOS study. Neurorehabil Neural Repair 2011; 25: 268–274.
https://doi.org/10.1177/1545968310384271 DOI: https://doi.org/10.1177/1545968310384271
Verheyden G, Nieuwboer A, De Wit L, Thijs V, Dobbelaere J, Devos H, et al. Time course of trunk, arm, leg, and functional recovery after ischemic stroke. Neurorehabil Neural Repair 2008; 22: 173–179.
https://doi.org/10.1177/1545968307305456 DOI: https://doi.org/10.1177/1545968307305456
Kafri M, Dickstein R. Activation of selected frontal trunk and extremities muscles during rolling from supine to side lying in healthy subjects and in post-stroke hemiparetic patients. NeuroRehabilitation 2005; 20: 125–131.
https://doi.org/10.3233/NRE-2005-20208 DOI: https://doi.org/10.3233/NRE-2005-20208
Tamaya VC, Wim S, Herssens N, Van de Walle P, Willem H, Steven T, et al. Trunk biomechanics during walking after sub-acute stroke and its relation to lower limb impairments. Clin Biomech (Bristol) 2020; 75: 105013.
https://doi.org/10.1016/j.clinbiomech.2020.105013 DOI: https://doi.org/10.1016/j.clinbiomech.2020.105013
Ryerson S, Byl NN, Brown DA, Wong RA, Hidler JM. Altered trunk position sense and its relation to balance functions in people post-stroke. J Neurol Phys Ther 2008; 32: 14–20.
https://doi.org/10.1097/NPT.0b013e3181660f0c DOI: https://doi.org/10.1097/NPT.0b013e3181660f0c
van Nes IJ, van der Linden S, Hendricks HT, van Kuijk AA, Rulkens M, Verhagen WI, et al. Is visuospatial hemineglect really a determinant of postural control following stroke? An acute-phase study. Neurorehabil Neural Repair 2009; 23: 609–614.
https://doi.org/10.1177/1545968308328731 DOI: https://doi.org/10.1177/1545968308328731
Moon HI, Lee HJ, Yoon SY. Lesion location associated with balance recovery and gait velocity change after rehabilitation in stroke patients. Neuroradiology 2017; 59: 609–618.
https://doi.org/10.1007/s00234-017-1840-0 DOI: https://doi.org/10.1007/s00234-017-1840-0
Handelzalts S, Melzer I, Soroker N. Analysis of brain lesion impact on balance and gait following stroke. Front Hum Neurosci 2019; 13: 149.
https://doi.org/10.3389/fnhum.2019.00149 DOI: https://doi.org/10.3389/fnhum.2019.00149
Lee KB, Hong BY, Kim JS, Sul B, Yoon SC, Ji EK, et al. Which brain lesions produce spasticity? An observational study on 45 stroke patients. PLoS One 2019; 14: e0210038.
https://doi.org/10.1371/journal.pone.0210038 DOI: https://doi.org/10.1371/journal.pone.0210038
DeMarco AT, Turkeltaub PE. A multivariate lesion symptom mapping toolbox and examination of lesion-volume biases and correction methods in lesion-symptom mapping. Hum Brain Mapp 2018; 39: 4169–4182.
https://doi.org/10.1002/hbm.24289 DOI: https://doi.org/10.1002/hbm.24289
Collin C, Wade D. Assessing motor impairment after stroke: a pilot reliability study. J Neurol Neurosurg Psychiatry 1990; 53: 576–579.
https://doi.org/10.1136/jnnp.53.7.576 DOI: https://doi.org/10.1136/jnnp.53.7.576
Fugl-Meyer AR, Jaasko L, Leyman I, Olsson S, Steglind S. The post-stroke hemiplegic patient. 1. A method for evaluation of physical performance. Scand J Rehabil Med 1975; 7: 13–31.
https://doi.org/10.2340/1650197771331 DOI: https://doi.org/10.2340/1650197771331
Nakazono T, Takahashi K, Suzuki Y, Mizuno K, Nomura Y, Hiraga Y, et al. Reliability and validity of Japanese version of Fugl-Meyer assessment for the lower extremities. Top Stroke Rehabil 2022; 29: 125–132.
https://doi.org/10.1080/10749357.2021.1899700 DOI: https://doi.org/10.1080/10749357.2021.1899700
Muir SW, Berg K, Chesworth B, Speechley M. Use of the Berg Balance Scale for predicting multiple falls in community-dwelling elderly people: a prospective study. Phys Ther 2008; 88: 449–459.
https://doi.org/10.2522/ptj.20070251 DOI: https://doi.org/10.2522/ptj.20070251
Ottenbacher KJ, Hsu Y, Granger CV, Fiedler RC. The reliability of the functional independence measure: a quantitative review. Arch Phys Med Rehabil 1996; 77: 1226–1232.
https://doi.org/10.1016/s0003-9993(96)90184-7 DOI: https://doi.org/10.1016/S0003-9993(96)90184-7
Chino N, Sonoda S, Domen K, Saitoh E, Kimura, A. Stroke Impairment Assessment Set (SIAS). Jpn J Rehabil Med 1996; 31: 119–125. DOI: https://doi.org/10.2490/jjrm1963.31.119
https://doi.org/10.1007/978-4-431-68461-9_3 DOI: https://doi.org/10.1007/978-4-431-68461-9_3
Zhang Y, Kimberg DY, Coslett HB, Schwartz MF, Wang Z. Multivariate lesion-symptom mapping using support vector regression. Hum Brain Mapp 2014; 35: 5861–5876.
https://doi.org/10.1002/hbm.22590 DOI: https://doi.org/10.1002/hbm.22590
Pustina D, Avants B, Faseyitan OK, Medaglia JD, Coslett HB. Improved accuracy of lesion to symptom mapping with multivariate sparse canonical correlations. Neuropsychologia 2018; 115: 154–166.
https://doi.org/10.1016/j.neuropsychologia.2017.08.027 DOI: https://doi.org/10.1016/j.neuropsychologia.2017.08.027
Bennett CM, Wolford GL, Miller MB. The principled control of false positives in neuroimaging. Soc Cogn Affect Neurosci 2009; 4: 417–422.
https://doi.org/10.1093/scan/nsp053 DOI: https://doi.org/10.1093/scan/nsp053
Mah YH, Husain M, Rees G, Nachev P. Human brain lesion-deficit inference remapped. Brain 2014; 137: 2522–2531.
https://doi.org/10.1093/brain/awu164 DOI: https://doi.org/10.1093/brain/awu164
Sperber C, Karnath HO. Impact of correction factors in human brain lesion-behavior inference. Hum Brain Mapp 2017; 38: 1692–1701.
https://doi.org/10.1002/hbm.23490 DOI: https://doi.org/10.1002/hbm.23490
Herbet G, Lafargue G, Duffau H. Rethinking voxel-wise lesion-deficit analysis: a new challenge for computational neuropsychology. Cortex 2015; 64: 413–416.
https://doi.org/10.1016/j.cortex.2014.10.021 DOI: https://doi.org/10.1016/j.cortex.2014.10.021
Foulon C, Cerliani L, Kinkingnehun S, Levy R, Rosso C, Urbanski M, et al. Advanced lesion symptom mapping analyses and implementation as BCBtoolkit. Gigascience 2018; 7: 1–17.
https://doi.org/10.1093/gigascience/giy004 DOI: https://doi.org/10.1093/gigascience/giy004
Thiebaut de Schotten M, Dell’Acqua F, Ratiu P, Leslie A, Howells H, Cabanis E, et al. From Phineas Gage and Monsieur Leborgne to H.M.: revisiting disconnection syndromes. Cereb Cortex 2015; 25: 4812–4827.
https://doi.org/10.1093/cercor/bhv173 DOI: https://doi.org/10.1093/cercor/bhv173
Thiebaut de Schotten M, Tomaiuolo F, Aiello M, Merola S, Silvetti M, Lecce F, et al. Damage to white matter pathways in subacute and chronic spatial neglect: a group study and 2 single-case studies with complete virtual “in vivo” tractography dissection. Cereb Cortex 2014; 24: 691–706.
https://doi.org/10.1093/cercor/bhs351 DOI: https://doi.org/10.1093/cercor/bhs351
Pellicciari L, Sodero A, Campagnini S, Guolo E, Basagni B, Castagnoli C, et al. Factors influencing trunk control recovery after intensive rehabilitation in post-stroke patients: a multicentre prospective study. Top Stroke Rehabil 2023; 30: 109–118.
https://doi.org/10.1080/10749357.2021.2016099 DOI: https://doi.org/10.1080/10749357.2021.2016099
Delibaş Kati Ş, Palaz EA, Güneş Gencer Y, Hekim HH, Temel Aksu N, Yaman A, et al. The effect of hemispheric lesion location on trunk control. Medicine (Baltimore). 2024; 103: e38589.
https://doi.org/10.1097/MD.0000000000038589 DOI: https://doi.org/10.1097/MD.0000000000038589
Strutton PH, Beith ID, Theodorou S, Catley M, McGregor AH, Davey NJ. Corticospinal activation of internal oblique muscles has a strong ipsilateral component and can be lateralised in man. Exp Brain Res 2004; 158: 474–479.
https://doi.org/10.1007/s00221-004-1939-5 DOI: https://doi.org/10.1007/s00221-004-1939-5
Janelle F, Iorio-Morin C, D’Amour S, Fortin D. Superior longitudinal fasciculus: a review of the anatomical descriptions with functional correlates. Front Neurol 2022; 13: 794618.
https://doi.org/10.3389/fneur.2022.794618 DOI: https://doi.org/10.3389/fneur.2022.794618
Parlatini V, Radua J, Dell’Acqua F, Leslie A, Simmons A, Murphy DG, et al. Functional segregation and integration within fronto-parietal networks. Neuroimage 2017; 146: 367–375.
https://doi.org/10.1016/j.neuroimage.2016.08.031 DOI: https://doi.org/10.1016/j.neuroimage.2016.08.031
Jacquemont T, Valabregue R, Daghsen L, Moulton E, Zavanone C, Lamy JC, et al. Association between superior longitudinal fasciculus, motor recovery, and motor outcome after stroke: a cohort study. Front Neurol 2023; 14: 1157625.
https://doi.org/10.3389/fneur.2023.1157625 DOI: https://doi.org/10.3389/fneur.2023.1157625
He BJ, Snyder AZ, Vincent JL, Epstein A, Shulman GL, Corbetta M. Breakdown of functional connectivity in frontoparietal networks underlies behavioral deficits in spatial neglect. Neuron 2007; 53: 905–918.
https://doi.org/10.1016/j.neuron.2007.02.013 DOI: https://doi.org/10.1016/j.neuron.2007.02.013
George K, Das JM. Neuroanatomy, thalamocortical radiations. StatPearls. In: StatPearls [Internet]. Treasure Island, FL: StatPearls Publishing; 2024 [cited 2024 Oct 8]. Available from: https://www.ncbi.nlm.nih.gov/books/NBK546699/
Takakusaki K. Functional neuroanatomy for posture and gait control. J Mov Disord 2017; 10: 1–17.
https://doi.org/10.14802/jmd.16062 DOI: https://doi.org/10.14802/jmd.16062
Leh SE, Ptito A, Chakravarty MM, Strafella AP. Fronto-striatal connections in the human brain: a probabilistic diffusion tractography study. Neurosci Lett 2007; 419: 113–118.
https://doi.org/10.1016/j.neulet.2007.04.049 DOI: https://doi.org/10.1016/j.neulet.2007.04.049
Lopez-Liria R, Vega-Tirado S, Valverde-Martinez MA, Calvache-Mateo A, Martinez-Martinez AM, Rocamora-Perez P. Efficacy of specific trunk exercises in the balance dysfunction of patients with Parkinson’s disease: a systematic review and meta-analysis. Sensors (Basel) 2023; 23:1817.
https://doi.org/10.3390/s23041817 DOI: https://doi.org/10.3390/s23041817
Mehanna R, Jankovic J. Movement disorders in cerebrovascular disease. Lancet Neurol 2013; 12: 597–608.
https://doi.org/10.1016/S1474-4422(13)70057-7 DOI: https://doi.org/10.1016/S1474-4422(13)70057-7
Sorrentino G, Sale P, Solaro C, Rabini A, Cerri CG, Ferriero G. Clinical measurement tools to assess trunk performance after stroke: a systematic review. Eur J Phys Rehabil Med 2018; 54: 772–784.
https://doi.org/10.23736/S1973-9087.18.05178-X DOI: https://doi.org/10.23736/S1973-9087.18.05178-X
Published
How to Cite
License
Copyright (c) 2025 Keita Nitto, Hiroaki Abe, Yuka Hashimoto, Yutaro Yabuki, Mayu Arai, Ryo Sato
This work is licensed under a Creative Commons Attribution 4.0 International License.
All digitalized JRM contents is available freely online. The Foundation for Rehabilitation Medicine owns the copyright for all material published until volume 40 (2008), as from volume 41 (2009) authors retain copyright to their work and as from volume 49 (2017) the journal has been published Open Access, under CC-BY-NC licences (unless otherwise specified). The CC-BY-NC licenses allow third parties to copy and redistribute the material in any medium or format and to remix, transform, and build upon the material for non-commercial purposes, provided proper attribution to the original work.
From 2024, articles are published under the CC-BY licence. This license permits sharing, adapting, and using the material for any purpose, including commercial use, with the condition of providing full attribution to the original publication.
