Motor Cortical Activation Assessment in Progressive Multiple Sclerosis Patients Enrolled in Gait Rehabilitation: A Secondary Analysis of the RAGTIME Trial Assisted by Functional Near-Infrared Spectroscopy

Investigating cortical hypoxia in multiple sclerosis via time-domain near-infrared spectroscopy

OBJECTIVES

Hypoperfusion and tissue hypoxia have been implicated as contributory mechanisms in the neuropathology of multiple sclerosis (MS). Our objective has been to study cortical oxygenation in vivo in patients with MS and age-matched controls.

METHODS

A custom, multiwavelength time-domain near-infrared spectroscopy system was developed for assessing tissue hypoxia from the prefrontal cortex. A cross-sectional case-control study was undertaken assessing patients with secondary progressive MS (SPMS) and age-matched controls. Co-registered magnetic resonance imaging was used to verify the location from which near-infrared spectroscopy data were obtained through Monte Carlo simulations of photon propagation. Additional clinical assessments of MS disease severity were carried out by trained neurologists. Linear mixed effect models were used to compare cortical oxygenation between cases and controls, and against measures of MS severity.

RESULTS

Thirty-three patients with secondary progressive MS (median expanded disability status scale 6 [IQR: 5-6.5]; median age 53.0 [IQR: 49-58]) and 20 age-matched controls were recruited. Modeling of photon propagation confirmed spectroscopy data were obtained from the prefrontal cortex. Patients with SPMS had significantly lower cortical hemoglobin oxygenation compared with controls (-6.0% [95% CI: -10.0 to -1.9], P = 0.004). There were no significant associations between cortical oxygenation and MS severity.

INTERPRETATION

Using an advanced, multiwavelength time-domain near-infrared spectroscopy system, we demonstrate that patients with SPMS have lower cortical oxygenation compared with controls.

Traditional versus progressive robot-assisted gait training in people with multiple sclerosis and severe gait disability: study protocol for the PROGR-EX randomised controlled trial

Gait disorders are the most frequent symptoms associated to multiple sclerosis (MS). Robot-assisted gait training (RAGT) in people with MS (PwMS) has been proposed as a possible effective treatment option for severe motor disability without significant superiority when compared to intensive overground gait training (OGT). Furthermore, RAGT at high intensity may enhance fatigue and spasticity. This study aims to evaluate the effects of a low-intensity RAGT at progressively increasing intensity compared to conventional RAGT and OGT in PwMS and moderate to severe walking impairment. 24 PwMS will be recruited and assigned to one of the three treatment groups: low-intensity RAGT at progressively increasing intensity, conventional RAGT and OGT. All participants will receive 3-weekly treatment sessions of 3 hours each for 4 weeks. In the first 2 hours of treatment, all participants will receive a rehabilitation programme based on stretching exercises, muscle strengthening and educational interventions. During the last hour, subjects will undergo specific gait training according to the assignment group. Outcomes will be assessed before and after treatment and at 3-month follow-up. The primary outcome is walking speed. Secondary outcomes include mobility and balance, psychological measures, muscle oxygen consumption, electrical and haemodynamic brain activity, urinary biomarkers, usability, and acceptability of robotic devices for motor rehabilitation. The results of this study will provide a safe, affordable and non-operator-dependent, intervention for PwMS. Results in terms of functional, psychological, neurophysiological and biological outcomes will confirm our hypothesis. The study's trial registration number: NCT06381440.

Cortical Oxygenation during a Motor Task to Evaluate Recovery in Subacute Stroke Patients: A Study with Near-Infrared Spectroscopy

In subacute stroke patients we studied cortical oxygenation changes by near-infrared spectroscopy (NIRS) during a motor task performed with the hemiparetic arm (15 s of reaching and grasping, 45 s of rest, repeated 6 times). Twenty-three subjects were included at baseline, compared with six healthy subjects, and restudied after 6 weeks of rehabilitation. Motor/premotor cortical changes in oxyhemoglobin detected by NIRS were quantified as the area under the curve (AUC) for the total cortex (TOT-AUC) and for both affected (AFF-AUC) and unaffected hemispheres (UN-AUC). The ratio between AUC and the number of task repetitions performed identified the cortical metabolic cost (CMC) or the oxygenation increase for a single movement. Fugl−Meyer assessment of the upper extremity (FMA-UE) was also performed. At baseline, both total and hemispheric CMC were significantly higher in stroke patients than in healthy subjects and inversely correlated with FMA-UE. After rehabilitation, changes in total-CMC and unaffected-CMC, but not Affected-CMC, were inversely correlated with variations in the FMA-UE score. A value > 5000 a.u. for the ratio baseline TOT-CMC/days since stroke was associated with not reaching the clinically important difference for FMA-UE after rehabilitation. In subacute stroke the CMC, a biomarker assessed by NIRS during a motor task with the hemiparetic arm, may describe cortical time/treatment reorganization and favor patient selection for rehabilitation.

fNIRS-Based Upper Limb Motion Intention Recognition Using an Artificial Neural Network for Transhumeral Amputees

Prosthetic arms are designed to assist amputated individuals in the performance of the activities of daily life. Brain machine interfaces are currently employed to enhance the accuracy as well as number of control commands for upper limb prostheses. However, the motion prediction for prosthetic arms and the rehabilitation of amputees suffering from transhumeral amputations is limited. In this paper, functional near-infrared spectroscopy (fNIRS)-based approach for the recognition of human intention for six upper limb motions is proposed. The data were extracted from the study of fifteen healthy subjects and three transhumeral amputees for elbow extension, elbow flexion, wrist pronation, wrist supination, hand open, and hand close. The fNIRS signals were acquired from the motor cortex region of the brain by the commercial NIRSport device. The acquired data samples were filtered using finite impulse response (FIR) filter. Furthermore, signal mean, signal peak and minimum values were computed as feature set. An artificial neural network (ANN) was applied to these data samples. The results show the likelihood of classifying the six arm actions with an accuracy of 78%. The attained results have not yet been reported in any identical study. These achieved fNIRS results for intention detection are promising and suggest that they can be applied for the real-time control of the transhumeral prosthesis.