Individualized rTMS Based on fNIRS to Spasticity

Overview

Stroke is of high morbidity and mortality, and surviving patients are often unable to take care of themselves because of severe motor dysfunction. The brain has plasticity, and makes adaptive changes after stroke, resulting in the reorganization and compensation of neural networks. However, the muscle tone of some patients will significantly increase during the recovery process, which affects the rehabilitation effect. Neuromodulation techniques such as repetitive transcranial magnetic stimulation (rTMS) have been widely used to promote brain network remodeling after stroke. The investigators attempted to evaluate the motor brain network characteristics of spastic patients by fNIRS, and used the most active brain regions as rTMS stimulation regions to evaluate the improvement effect of this individualized treatment on post-stroke spasticity.

Full Title of Study: “Effect of Individualized rTMS Based on fNIRS on the Upper Limb Spasticity After Stroke”

Study Type

  • Study Type: Interventional
  • Study Design
    • Allocation: Randomized
    • Intervention Model: Parallel Assignment
    • Primary Purpose: Treatment
    • Masking: Single (Outcomes Assessor)
  • Study Primary Completion Date: September 1, 2023

Interventions

  • Procedure: individual rTMS based on fNIRS
    • The rTMS parameters will be set according to fNIRS results.
  • Procedure: Traditional rTMS strategy
    • The low-frequency rTMS to contralesional M1 will always be used.

Arms, Groups and Cohorts

  • Experimental: Individualized rTMS based on fNIRS
    • Low-frequency rTMS will be given to the most active brain regions assessed by fNIRS.
  • Active Comparator: Traditional rTMS strategy
    • The control group will always be given low-frequency rTMS to contralesional M1

Clinical Trial Outcome Measures

Primary Measures

  • modified Ashworth scale
    • Time Frame: 1 month
    • The range is 0-Ⅳ level, the higher the level, the higher the spasticity.

Secondary Measures

  • Fugl-Meyer Assessment of upper limb motor function
    • Time Frame: 1 month
    • The score range is 0-66 points, the higher the score, the better the motor function of upper limb.
  • Barthel index
    • Time Frame: 1 month
    • The score range is 0-100 points, the higher the score, the better the activities of daily living.
  • average weighted clustering coefficient
    • Time Frame: 1 month
    • This is a brain network indicator based on graph theory. It is a measure of the local separation of the graph. The higher the average weighted clustering coefficient, the higher the degree of segregation of the brain network.
  • global efficiency
    • Time Frame: 1 month
    • This is a brain network indicator based on graph theory. It is a measure of the local integration of the graph. The higher the global efficiency, the stronger the ability of the network to transmit information.
  • inter-density
    • Time Frame: 1 month
    • It is a brain network indicator based on graph theory and is defined as the ratio of the actual number of connections among all possible connections between bilateral hemispheres.

Participating in This Clinical Trial

Inclusion Criteria

  • Aged 40-79 years; – Patients with first-onset stroke within 1 to 3 months after onset; – Consciousness, sitting balance level 1 or above, can cooperate with fNIRS assessment; – The patient or its authorized agent signs the informed consent form. Exclusion Criteria:

  • Previous seizures; – Suffered from mental illness such as depression, anxiety, mania, and schizophrenia before the stroke onset; – Patients with metal on the head, cochlear implants, intracranial infections, etc. who are not suitable for rTMS.

Gender Eligibility: All

Minimum Age: 40 Years

Maximum Age: 79 Years

Are Healthy Volunteers Accepted: Accepts Healthy Volunteers

Investigator Details

  • Lead Sponsor
    • First Affiliated Hospital Xi’an Jiaotong University
  • Provider of Information About this Clinical Study
    • Sponsor
  • Overall Contact(s)
    • Ziwen Yuan, MD, +8617502991129, yuanziwen@xjtufh.edu.cn

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