MScope: A Reliable Battery for Functional Status Assessment in Multiple Sclerosis

Abstract

Multiple sclerosis (MS) is a neurodegenerative disease that often leads to severe disability. Although exercise, particularly strength training, improves health outcomes in MS, no standardized, reliable tool exists for functional assessment to inform tailored exercise prescriptions and patients’ categorization. This study aimed to validate the reliability of the MScope battery, a comprehensive tool incorporating structural, functional, and neuromuscular assessments to objectively evaluate patients with MS. A reproducibility study was conducted with 40 MS patients who completed the MScope battery twice, 72 h apart. Tests included structural (muscle thickness of the vastus lateralis and rectus femoris), functional (sit-to-stand, timed up-and-go, 10 m and six-minute walking test), and neuromuscular tests (isometric strength during the squat and leg extension exercises and handgrip strength). Intraclass correlation coefficients (ICCs), Bland–Altman plots, and the coefficient of variation (CV) were used to evaluate intra- and inter-day reliability. The MScope battery showed high intra- and inter-day reliability, with ICC values ranging from 0.79 to 0.99. Muscle thickness measurements, along with handgrip strength, demonstrated excellent reliability (ICC > 0.9, CV < 5%). Functional tests, including the timed up-and-go, 10 m walk, and sit-to-stand variations, maintained consistent scores (ICC > 0.85, CV < 10%). The six-minute walking test exhibited excellent inter-day reliability (ICC = 0.94, CV < 4%). Neuromuscular assessments showed strong reliability with minor day-to-day variability (ICC = 0.75–0.95, CV < 8%). The battery’s overall consistency supports its use as a reliable tool for assessing functional status in MS patients.

1. Introduction

Multiple sclerosis (MS) is a chronic disorder that affects the central nervous system. MS is the leading cause of non-traumatic disability in young adults in Europe and North America, and it affects more than 2.5 million people worldwide [1]. The etiology of MS remains uncertain; however, the most widely accepted hypothesis is a neurophysiopathological mechanism that combines immune dysfunction, neuroinflammation, and neurodegeneration [2]. Symptoms of MS include cognitive impairment, sensory and motor deficits, spasticity, fatigue, and disturbances in balance and coordination. Therefore, functional capacity declines, quality of life reduces, and the risk of falls and injuries increases [3]. Notwithstanding the favorable prognosis associated with high-efficacy treatments and early diagnosis, MS persists, causing disability across all clinical forms in which it manifests. Consequently, there is a pressing need to develop more effective tools to combat this disease [4].

Physical exercise has emerged as a non-pharmacological adjuvant therapy that allows patients with MS (PwMS) to improve both their physical and psychological health [5]. The evidence indicates that strength training increases muscle mass [3], improves balance and gait [6], reduces fatigue [7], and even promotes neuroplasticity in PwMS [8]. Furthermore, the effects of strength training have been shown to be more pronounced than those of other exercise-based strategies such as moderate-intensity aerobic exercise [3]. Recently, a neuroprotective effect of high-intensity strength training has been demonstrated [9], with a reduction in the serum concentration of neurofilaments (a neuronal cytoskeletal protein considered a biomarker of axonal damage) [10]. Collectively, these findings indicate that physical exercise may enhance functional capacity, autonomy, and quality of life in PwMS [9].

However, prescribing physical exercise effectively requires assessments to classify and identify a patient’s health status, ultimately enabling personalized training [3]. Despite this need, no standardized battery of tests or scientific consensus currently exists to provide a functional assessment framework that supports effective exercise prescription, patient categorization, or tracking of MS progression. A review of the literature reveals numerous disparate functional assessment tests, with only a few, such as the two-minute walking test [11,12], the six-minute walking test (6MWT) [13,14,15], the sit-to-stand test, both the 60 s (60STST) and five-repetition (5RSTST) versions [7,11,12,16], the timed 25-foot walk (T25FW) [12,17], and the stair climbing test [7,11,12,14], being commonly used. Moreover, only a limited number of tests, such as the timed up-and-go (TUG) [18] and 5RSTST [19,20,21], have been validated through studies assessing their reliability and validity specifically in patients with MS or similar neurological conditions like stroke or Parkinson’s disease. Therefore, it is necessary to propose a battery of homogeneous structural, neuromuscular, and functional assessment tests for PwMS.

Similarly, throughout the scientific literature, the classification of the health status of PwMS is often based on questionnaires that assess the level of disability. One example is the expanded disability status scale (EDSS), whose scores can vary owing to the complex scoring rules and subjectivity inherent in neurological examination [7,22,23]. An additional example is the assessment of gait patterns, for which a 12-item self-report scale (multiple sclerosis walking scale, MSWS-12) is frequently employed [12,17,22]. Frailty significantly contributes to cognitive and physical decline, driving neurodegeneration. Its assessment often relies on subjective questionnaires lacking objective quantitative data. An objective method is needed to evaluate pathology severity and motor pattern alterations without requiring specialized professionals, laboratories, or equipment. Such a method should also enable functional status categorization, providing a comprehensive health assessment for PwMS. Therefore, the aim of this study was to propose and analyze the reliability of a battery of structural, neuromuscular, and functional tests to obtain an objective assessment and categorization of PwMS. The hypothesis of this study was that the proposed battery would facilitate reliable and reproducible assessments of functional performance, neuromuscular capacity, and muscle mass.

2. Materials and Methods

2.1. Study Design

A longitudinal reproducibility study was conducted. Forty-six PwMS voluntarily participated in this study. They were invited to attend to the laboratory on two occasions separated by 72 h. As shown in Figure 1, during each visit, at least two measurements were taken for each of the following tests: muscle thickness of the vastus lateralis (VL) and rectus femoris (RF) of both legs, handgrip strength of the dominant hand, 60STST, average power of the 5RSTST, timed up-and-go test (TUG), 10 m walking speed test (10MWT), and maximal voluntary isometric strength in squat (MVIC_SQ) and leg extension (MVIC_LEXT) exercises. Furthermore, each visit included a maximum effort test known as the 6MWT. This study was conducted in accordance with the Declaration of Helsinki to ensure ethical research practices and approved by the Ethics Committee of the University Clinical Hospital of Valladolid (PI-GR-23-3292). All the participants provided written informed consent to participate.

2.2. Participants

Forty-six PwMS (45.1 ± 9.0 years, 156.8 ± 31.0 cm, and 75.1 ± 15.7 kg) volunteered in this study (see Supplementary File S1). The following criteria were used to determine which patients would be included in the study: The diagnosis of multiple sclerosis was made in accordance with the criteria set by Thompson et al. [24] (dissemination in space, dissemination in time, use of oligoclonal bands, and exclusion of alternative diagnosis); patients were required to be at least 18 years of age; the degree of disability was evaluated using the Expanded Disability Status Scale (EDSS), with a maximum score of 5; patients were deemed to be in a state of clinical stability, having exhibited no MS relapses over the preceding six months; it was required that no changes in disease-modifying treatment had been made in the previous six months, or that the patients were not undergoing any treatment; in order to be eligible for inclusion in the study, patients must have undergone an MRI scan within the past year, and the results must demonstrate the absence of inflammatory activity, as evidenced by the absence of new T2 lesions or gadolinium-enhancing lesions; the provision of informed consent in writing is a prerequisite for participation. The exclusion criteria for this study were as follows: patients who reported a moderate or higher level of physical activity according to the International Physical Activity Questionnaire (IPAQ-2018), patients who were pregnant or breastfeeding, and the presence of other diagnosed concomitant conditions that would limit physical exercise. In the event of disease relapse during the assessment period, continued participation in the study was subject to individual consideration. All participants completed both measurement sessions.

Before data collection, an a priori power analysis was conducted to determine the optimal sample size for the reproducibility study. The analysis aimed to achieve a statistical power of 0.95 (95%) with a significance level (α) of 0.05, ensuring robust results. The calculation assumed a minimum expected Spearman correlation coefficient (rs) of 0.31 between measurements [18], which corresponds to an effect size (dz) of 0.65. To perform this analysis, we used the statistical software G*Power (G*Power 3.1.9.2, Heinrich Heine University Dusseldorf, Dusseldorf, Germany; http://www.gpower.hhu.de/ (accessed on 1 November 2024)). Based on these parameters, a minimum sample size of 33 participants was required to achieve sufficient statistical power and precision to evaluate the reliability of the measurements. The selected sample size of 46 participants exceeds this minimum requirement, further strengthening the study’s ability to detect meaningful relationships between variables while maintaining statistical rigor.

2.3. Procedures

2.3.1. Muscle Mass Assessments

The study employed a quantitative approach to evaluate the muscle architecture and dimensions using a Samsung HS30 ultrasound device (Samsung Healthcare Global, Gangwon, Republic of Korea). The investigation focused on the thickness of the VL and RF muscles in both legs. The same investigator assessed muscle thickness from images obtained in vivo at rest using B-mode ultrasound (HS30, Samsung Healthcare Global, Gangwon, Republic of Korea), with a 40 mm, 3–12 MHz, linear-array probe. In this study, resting ultrasound images were taken at 50% on the line from the anterior spina iliaca superior to the superior part of the patella for the RF, and at 2/3 on the line from the anterior spina iliaca superior to the lateral side of the patella for the VL. The participant was resting supine on an examination bed with the knee in semi-flexion, supporting the popliteal region on a 15 cm-diameter foam roller (i.e., 25° knee flexion) [25]. The probe was positioned longitudinally along the midsagittal axis of the VL and carefully aligned with the fascicle plane to facilitate visualization of the fascicles on the ultrasound screen. The investigator applied minimal pressure when positioning the transducer on the skin to avoid undue discomfort to the subject. The muscle thicknesses of the VL and RF were determined by measuring the distance between the superficial and deep aponeuroses at the center of the acquired image [26]. For both assessments, three images were acquired and stored for subsequent offline analysis using the ImageJ 1.42q software (National Institutes of Health, Bethesda, MD, USA).

2.3.2. Functional Capacity Assessments

Functional capacity was assessed through the TUG test, 5RSTST, and 60STST. The TUG test was conducted following the method described by Karlon et al. [27]. It began with participants seated on a standard-height chair (45 cm), with their back touching the backrest and arms resting on the armrests. Participants were instructed to stand, walk 3 m, turn around, return to the chair, and sit down again. Timing started as they began to stand up and stopped once they sat back down. Three trials were conducted with 30 s of rest between each attempt, and the time taken to complete the test was recorded for each trial.

Following the TUG test, the 5RSTST was conducted on three occasions 30 s apart, where participants were instructed to perform 5 repetitions of standing up and sitting down as fast as possible. Each execution was recorded laterally using a mobile phone (iPhone 12, Apple Inc., Cupertino, CA, USA), and the PowerFrail app (GENUD, Toledo, Spain) was employed to measure the average power generated per repetition [28]. The app was set to mark the start of movement and the end of the final (fifth) repetition, alongside the total number of repetitions.

After one minute of rest, the 60STST was performed following Bohannon’s guidelines [29] using the 45 cm standard chair previously described. Participants were instructed to sit with their feet flat on the ground and then stand fully, extending knees and hips, and sit again with arms crossed over their chest, repeating as quickly as possible for 60 s. The total number of completed STST repetitions was recorded. As the 60STST test is maximal, only two trials were performed with two minutes rest between attempts.

Finally, the 6MWT was conducted to evaluate cardiorespiratory fitness [15]. This test involves covering the maximum possible distance within a six-minute period along a 50 m straight, obstacle-free path with no incline. Distance indicators were placed at 10 m intervals to assist patients in tracking their progress. Throughout the test, patients walked back and forth, turning around a marker at each end of the 50 m path. They were encouraged to maintain a brisk pace, with periodic reminders of the remaining time. If patients experienced fatigue, they were allowed to slow down or stop, and rest as needed. Chairs were provided at 10 m intervals along the course to enable patients to sit if necessary, and they could also lean against the wall. Assistive devices, such as crutches, were permitted for those requiring support for ambulation. Given its potentially exhaustive nature, it was performed only once per laboratory visit to ensure patient safety and to prevent fatigue. Participants wore their usual footwear and any necessary assistive devices.

2.3.3. Neuromuscular Assessments

Five minutes after completing the 60STST, maximal voluntary isometric contraction (MVIC) was assessed during the isometric squat (MVIC_SQ) and leg extension (MVIC_LEXT) exercises, both at bilateral and unilateral exercise variants. The isometric squat was performed with patients positioned on a dual force plate system (Hawkin Dynamics, Westbrook, ME, USA) and their knees bent at a 100° knee flexion to assess both bilateral (GRF) and unilateral (GRF_R and GRF_L) peak isometric ground reaction force [9]. A harness secured participants to the system via a cable, enabling height adjustments tailored to each patient. Additionally, a force sensor (Chronojump, Barcelona, Spain) that sampled data at 80 Hz was included in the chain that secured the harness to the ground to assess the MVIC_SQ. Data collected included bilateral ground reaction peak force, ground reaction peak force for each leg, and peak force at the chain level.

For the leg extension test, participants were seated on a locked leg extension machine fitted with a portable force sensor (Chronojump, Barcelona, Spain). This force sensor was attached at one end to the device and the other end connected to a chain linked to a padded anklet, which provided mechanical stability while minimizing joint movement, ensuring proper isometric testing [30]. The chain length was adjusted based on each participant’s anthropometric measurements to create mechanical stability and a comfortable knee angle of 90° [9]. Knee flexion was measured before each trial with a handheld goniometer (Nexgen Ergonomics, Point Claire, QC, Canada). The leg extension was performed bilaterally and unilaterally for both limbs. For both the squat and leg extension exercises, patients were instructed to exert maximal force as quickly as possible and hold the contraction for 5 s. Each test included two attempts with a 2 min rest interval.

In addition to the previous measurements, upon arrival at the laboratory, handgrip strength for all patients was recorded using a Jamar Smart Hand dynamometer (JAMAR^® Sammons Preston Inc., Bolingbrook, IL, USA). This assessment was conducted with the patient seated in a chair, with shoulder and forearm in a neutral position, and the elbow flexed at 90° [31]. Each participant performed two maximum handgrip strength attempts only with the dominant hand, each lasting three seconds, with a 30 s rest interval between repetitions. The peak force developed during each attempt was recorded for subsequent analysis.

2.4. Statistical Analysis

Statistical analysis was conducted using IBM SPSS Statistics v.26.0 for Windows (SPSS Inc., Chicago, IL, USA) and GraphPad Prism v.8.0 for Windows (GraphPad Software Inc., Boston, MA, USA). Descriptive statistics for the quantitative variables were calculated as means and standard deviations. Given the sample size, the Shapiro–Wilk test was used to assess the normality of the data. Statistical significance was set at a p-value ≤ 0.05.

2.4.1. Intra-Day Reproducibility

To assess the intra-day reproducibility for the various tests used, the intraclass correlation coefficient (ICC; random effects, single measure, absolute agreement), and 95% confidence interval (CI) were calculated for the collected measures. ICC values below 0.5 were deemed indicative of poor reproducibility, while values between 0.4 and 0.59 were considered sufficient, those between 0.5 and 0.75 were regarded as moderate, and values above 0.75 were classified as excellent reproducibility [32]. The analysis was conducted at two time points, designated Day 1 and Day 2, with a three-to-four-day interval between them. To assess the degree of variability, the coefficient of variation (CV), defined as the ratio of the standard deviation (SD) to the mean [CV = (SD/mean) × 100], was calculated for each subject and expressed as the mean value for each day. CV values below 10 were considered as very good reliability, between 10 and 20 as good, between 20 and 30 as acceptable, and values above 30 as unacceptable [33].

2.4.2. Inter-Day Reproducibility

To assess test–retest reproducibility, the ICC (random effects, multiple measures, absolute agreement) and its 95% CI were calculated comparing the Day 1 and Day 2 measurements. The mean values for handgrip, muscle thickness of VL (VL_R and VL_L) and RF (RF_R and RF_L), and the TUG test were calculated, as were the peak values for the 60STST, 5RSTST, unilateral MVIC during the squat exercise (MVIC_SQ), peak isometric ground reaction force (GRF), GRF_R, GRF_L, MVIC_LEXT, unilateral MVIC during the leg extension exercise (UMVIC_{LEXT_R} and UMVIC_{LEXT_L}), and the 10MWT. The 6MWT was assessed on a single occasion at each visit, and these data were used in the inter-day repeatability analysis. To ascertain whether there were statistically significant changes between Day 1 and Day 2 for the measured variables, Student’s t-test for paired samples or its non-parametric alternative (Wilcoxon signed-rank test) was employed if any data distributions were non-normal. Furthermore, Bland–Altman plots were analyzed using the Jamovi software package (The Jamovi Project, v.1.6.23.0; downloadable at https://www.jamovi.org (accessed on 1 November 2024)) to illustrate the discrepancies between the measurements and the mean of those measurements. The limits of agreement (LoAs) were derived from the 95% CI of the difference and bias (mean difference). The association between the difference and the magnitude of the measurement (i.e., heteroscedasticity) was examined by regression analysis, entering the difference between Day 1 and Day 2 measurements. To assess the degree of variability between days, the CV was calculated using the mean values of each subject on each day and the SD between these two measurements was determined.

3. Results

3.1. Intra-Day Reproducibility

Table 1. Intra-day reproducibility of the different evaluated tests.

Visit	Test	Measures			ICC (95% CI)	CV (%)
		1	2	3
Day 1	Handgrip (kg)	28.40 ± 10.6	29.0 ± 9.4	-	0.965 (0.936–0.980)	7.3
	VLR muscle thickness (cm)	1.82 ± 0.4	1.83 ± 0.4	1.83 ± 0.4	0.978 (0.964–0.987)	3.4
	VLL muscle thickness (cm)	1.83 ± 0.4	1.83 ± 0.4	1.82 ± 0.4	0.995 (0.995–0.997)	2.4
	RFR muscle thickness (cm)	1.88 ± 0.4	1.88 ± 0.4	1.89 ± 0.4	0.994 (0.990–0.997)	2.5
	RFL muscle thickness (cm)	1.85 ± 0.4	1.86 ± 0.4	1.86 ± 0.4	0.996 (0.994–0.999)	1.8
	TUG test (s)	6.28 ± 1.4	6.09 ± 1.2	5.94 ± 1.2	0.984 (0.974–0.991)	4.4
	60STST (n)	32.13 ± 9.4	32.22 ± 9.7	-	0.971 (0.947–0.984)	4.6
	5RSTST (w/kg)	2.97 ± 0.9	3.15 ± 0.9	-	0.968 (0.942–0.9802)	6.8
	MVICSQ (N)	476.59 ± 218.3	504.98 ± 194.6	-	0.912 (0.840–0.951)	13.2
	GRF (N)	1189.49 ± 271.8	1103.64 ± 280.2	-	0.935 (0.882–0.964)	6.2
	GRFR (N)	596.64 ± 153.2	551.51 ± 149.6	-	0.922 (0.859–0.957)	7.3
	GRFL (N)	588.20 ± 127.8	550.47 ± 136.9	-	0.935 (0.881–0.964)	6.2
	MVICLEXT (N)	302.48 ± 174.1	315.36 ± 168.6	-	0.983 (0.969–0.991)	8.1
	UMVICLEXT_R (N)	93.68 ± 75.5	105.66 ± 90.1	-	0.970 (0.946–0.983)	11.5
	UMVICLEXT_L (N)	111.64 ± 91.0	109.84 ± 93.2	-	0.975 (0.955–0.986)	12.6
	10MWT (s)	5.27 ± 0.9	5.09 ± 1.0	5.00 ± 0.8	0.957 (0.930–0.975)	3.2
Day 2	Handgrip (kg)	30.71 ± 9.8	31.17 ± 10.20	-	0.984 (0.970–0.991)	4.4
	VLR muscle thickness (cm)	1.89 ± 0.4	1.89 ± 0.4	1.89 ± 0.4	0.995 (0.992–0.997)	2.1
	VLL muscle thickness (cm)	1.85 ± 0.4	1.86 ± 0.4	1.86 ± 0.4	0.996 (0.994–0.998)	1.9
	RFR muscle thickness (cm)	1.95 ± 0.4	1.94 ± 0.4	1.96 ± 0.4	0.994 (0.991–0.997)	2.0
	RFL muscle thickness (cm)	1.92 ± 0.4	1.91 ± 0.4	1.91 ± 0.4	0.998 (0.996–0.999)	1.5
	TUG test (s)	5.55 ± 1.0	5.40 ± 0.9	5.30 ± 0.8	0.975 (0.959–0.986)	3.8
	60STST (n)	37.49 ± 10.4	36.60 ± 10.8	-	0.971 (0.946–0.984)	5.0
	5STST (w/kg)	3.78 ± 0.9	3.91 ± 1.0	-	0.979 (0.960–0.988)	4.0
	MVICSQ (N)	556.75 ± 226.3	572.43 ± 238.7	-	0.970 (0.945–0.984)	8.5
	GRF (N)	1241.25 ± 283.0	1178.98 ± 273.5	-	0.988 (0.977–0.993)	3.4
	GRFR (N)	623.61 ± 157.4	593.82 ± 153.3	-	0.989 (0.980–0.994)	3.8
	GRFL (N)	617.64 ± 132.5	585.07 ± 126.0	-	0.981 (0.965–0.990)	4.0
	MVICLEXT (N)	332.25 ± 166.6	327.71 ± 186.8	-	0.980 (0.964–0.989)	10.3
	UMVICLEXT_R (N)	102.35 ± 97.9	97.60 ± 89.8	-	0.972 (0.948–0.985)	12.8
	UMVICLEXT_L (N)	103.42 ± 90.3	106.28 ± 92.7	-	0.984 (0.971–0.991)	11.4
	10MWT (s)	4.97 ± 0.8	4.83 ± 0.8	4.78 ± 0.7	0.982 (0.970–0.990)	3.4

Abbreviations: 5RSTST, five-repetitions sit-to-stand test; 10MWT, ten-meter walking test; 60STST, 60 s sit-to-stand test; cm, centimeters; CI, confidence interval; CV, coefficient of variation; ICC, intraclass correlation coefficient; GRF, peak isometric ground reaction force; GRF_L, unilateral left peak isometric ground reaction force; GRF_R, unilateral right peak isometric ground reaction force; kg, kilograms; MVIC_LEXT, maximal voluntary isometric contraction during the leg extension exercise; MVIC_SQ, maximal voluntary isometric contraction during the squat exercise; N, newtons; n, number; RF_L, left rectus femoris; RF_R, right rectus femoris; s, seconds; TUG test, timed up-and-go test; UMVIC_{LEXT_L}, unilateral left leg extension maximal voluntary isometric contraction; UMVIC_{LEXT_R}, unilateral right leg extension maximal voluntary isometric contraction; VL_L, left vastus lateralis; VL_R, right vastus lateralis; w/kg, watts per kilogram of body weight.

presents the results of the intra-day repeatability analysis for each of the evaluated tests. It can be observed that all tests demonstrate an excellent level of agreement (Cronbach’s alpha > 0.7), with a p-value of less than 0.001 in all cases. All data showed a normal distribution except for TUG, 5RSTS, MVIC_SQ, GRF, GRF_{_R}, and 10MWT.

3.2. Inter-Day Reproducibility

Statistical analysis of the data from the measured variables revealed significant differences in handgrip variables (in terms of both average and maximum values), the TUG test, 60STST, 5STST, GRF, 10MWT, and 6MWT (

Table 2. Inter-day repeatability of the different evaluated tests.

Tests	Measures		RMs p-Value	ICC (95% CI)	%CV
	Day 1	Day 2
Handgrip (kg)	26.84 ± 6.2	28.18 ± 5.9	0.031	0.817 (0.648–0.905)	9.2
VLR muscle thickness (cm)	1.82 ± 0.4	1.88 ± 0.4	0.032	0.933 (0.875–0.964)	6.2
VLL muscle thickness (cm)	1.81 ± 0.4	1.85± 0.4	0.130	0.958 (0.920–0.978)	4.8
RFR muscle thickness (cm)	1.88 ± 0.4	1.94 ± 0.4	0.033	0.933 (0.874–0.964)	5.5
RFL muscle thickness (cm)	1.85 ± 0.4	1.88 ± 0.4	0.028 *	0.973 (0.948–0.986)	3.2
TUG test (s)	5.80 ± 0.9	5.24 ± 0.7	<0.001	0.866 (0.752–0.927)	8.6
60STST (n)	33.49 ± 10.0	38.17 ± 10.0	<0.001	0.937 (0.884–0.966)	10.8
5RSTST (w/kg)	3.26 ± 0.9	3.96 ± 1.0	<0.001 *	0.832 (0.690–0.909)	17.8
MVICSQ (N)	541.79 ± 213.0	593.18 ± 229.0	0.014 *	0.775 (0.587–0.877)	17.0
GRF (N)	1196.72 ± 276.6	1248.35 ± 282.4	0.102 *	0.882 (0.682–0.907)	9.6
GRFR (N)	604.49 ± 152.0	628.70 ± 156.7	0.136 *	0.850 (0.723–0.919)	9.6
GRFL (N)	592.47 ± 130.0	621.77 ± 132.2	0.082	0.797 (0.625–0.890)	10.2
MVICLEXT (N)	327.87 ± 183.9	349.23 ± 178.9	0.067	0.955 (0.917–0.975)	17.1
UMVICLEXT_R (N)	109.51 ± 92.3	108.8 ± 99.9	0.922	0.932 (0.875–0.963)	25.9
UMVICLEXT_L (N)	122.14 ± 96.4	122.68 ± 94.6	0.288	0.897 (0.812–0.944)	26.9
10MWT (s)	5.11 ± 0.9	4.86 ± 0.8	<0.001 *	0.933 (0.875–0.964)	4.9
6MWT (m)	621.51 ± 87.3	644.40 ± 84.8	0.002	0.929 (0.866–0.962)	4.2

Statistically significant changes between days were assessed using the Student’s t-test for paired samples unless specified.* Wilcoxon signed-rank test was employed if any data distributions were non-normal. Abbreviations: 5RSTST, five-repetitions sit-to-stand test; 10MWT, ten-meter walking test; 60STST, 60 s sit-to-stand test; cm, centimeters; CI, confidence interval; CV, coefficient of variation; ICC, intraclass correlation coefficient; GRF, peak isometric ground reaction force; GRF_L, unilateral left peak isometric ground reaction force; GRF_R, unilateral right peak isometric ground reaction force; kg, kilograms; MVIC_LEXT, maximal voluntary isometric contraction during the leg extension exercise; MVIC_SQ, maximal voluntary isometric contraction during the squat exercise; N, newtons; n, number; RF_L, left rectus femoris; RF_R, right rectus femoris; s, seconds; RMs, repeated measures; TUG test, timed up-and-go test; UMVIC_{LEXT_L}, unilateral left leg extension maximal voluntary isometric contraction; UMVIC_{LEXT_R}, unilateral right leg extension maximal voluntary isometric contraction; VL_L, left vastus lateralis; VL_R, right vastus lateralis; w/kg, watts per kilogram of body weight.

). However, all measures demonstrated excellent repeatability (Cronbach’s alpha > 0.7). It is important to note that the presence of significant differences in the measurements is not indicative of the degree of reproducibility, as one case evaluates the differences between measurements in absolute terms, whereas the other assesses the internal ability to classify patients.

The Bland–Altman plots for the muscle mass, functional capacity, and neuromuscular assessments are shown in Figure 2, Figure 3, and Figure 4, respectively. All structural (Figure 2) and neuromuscular (Figure 4) data did not show significant differences; however, all the functional tests showed significant differences (Figure 3) (TUG: t = 8.6, p < 0.001; 60STS: t = 8.1, p < 0.001; 5RSTS: t = 6.2, p < 0.001; 10MWT: t = 3.8, p < 0.001; 6MWT: t = 3.3, p = 0.02). Heteroscedasticity was not presented in the results (see Supplementary File S2) except for TUG, MVIC_SQ, and UMVIC_{LEXT_L}.

4. Discussion

This study aimed to evaluate the reliability and validity of a battery of tests (MScope battery) designed to assess functional capacity in PwMS. The reliability of the test battery was confirmed by high ICC values, indicating a high degree of consistency in the measurements. All the analyzed structural, functional, and neuromuscular variables demonstrated excellent intra-day reliability, with ICC values exceeding 0.92. These high values showed that the tests yielded consistent results on the same day. Moreover, most tests exhibited good-to-excellent test–retest reliability, with ICC values ranging from 0.775 to 0.973, indicating consistent results across different assessment sessions. However, significant differences between sessions were observed in functional tests, likely due to factors such as task familiarization or sensitivity to minor changes in functional capacity, while structural and neuromuscular assessments showed greater stability. This reproducibility, coupled with the exploratory factor analysis supporting the construct validity, underscores the robustness of the battery. Thus, this is the first study to propose a reliable and valid set of functional, structural, and neuromuscular tests to comprehensively assess functional status in PwMS.

Functional assessments included the TUG test, 5RSTST, 60STST, 10MWT, and 6MWT. These tests are frequently used to assess various aspects of functional capacity, including balance, lower limb strength, and walking endurance. The intra-day reliability, defined as the consistency of measurements taken on the same day, was excellent (ICC > 0.9) for all functional assessments, except for the 6MWT, for which intra-day reliability was not assessed as it was performed only once per laboratory visit due to its potentially exhaustive nature. These findings indicate that the tests are relatively free from measurement errors when administered multiple times within a short period, even though participants were unfamiliarized with testing protocols. However, despite good-to-excellent test–retest reproducibility for functional outcomes, the agreement between measurements obtained on different days demonstrated greater variability, showing significant differences between measurements on Day 1 and 2 for all the functional tests (Table 2, Figure 3). This variability may be attributed to learning effects or daily fluctuations in participant motivation [28]. However, despite the observed differences in variability between the two measurements, only the TUG test demonstrated significant heteroscedasticity (Supplementary File S2). This finding suggests that discrepancies tend to increase or decrease based on the magnitude of the variable, which should be considered when interpreting the results.

Previous studies have also reported a high level of reliability of the TUG test in PwMS. For example, Sebastião et al. [18] found an ICC of 0.93 in their investigation of the validity of the TUG test in relation to the MSWS-12. Furthermore, the favorable test–retest reproducibility shown in our study, with an ICC of 0.866, is consistent with previous findings reporting ICCs of 0.97 and 0.91 [34,35]. This highlights the utility of the TUG test as an effective measure for assessing functional capacity across various conditions in PwMS [34,35], and as a valid tool for assessing fall risk [36]. Similarly, the sit-to-stand test has been widely employed in its various forms in patients with MS across scientific literature [16]. The reliability and validity of the 5RSTST have recently been confirmed, demonstrating high reliability (ICC = 0.99) and excellent intra- and inter-rater reliability for assessing muscle strength when administered remotely in MS [20]. Moreover, similar studies on patients with neurodegenerative diseases have yielded comparable findings regarding the intra-day reliability and test–retest reproducibility of the 5RSTST. For example, Mong et al. [21] reported intra-day ICCs between 0.97 and 0.99 in individuals with Parkinson’s disease, while Duncan et al. [19] reported test–retest reproducibility between 0.76 and 0.98 in stroke patients. Differences between our results and previous studies could be due to our method of calculation. Instead of simply recording the time taken to complete five repetitions [20], as is common in earlier studies, we implemented a more precise approach that incorporates each patient’s anthropometric characteristics to calculate average power output during the test [28]. This algorithm, based on the mean time to complete the five repetitions, may slightly influence the results, and explain the observation of only low reproducibility in our study, despite the test demonstrating high intra- and inter-day ICCs (Table 1 and Table 2). Regarding the 60STST, there is no previous scientific evidence available on the reliability of this test in PwMS. However, the reliability of the same test with a duration of 30 seconds, rather than 60 seconds, has been analyzed in PwMS, demonstrating an ICC of 0.983 [37]. This finding aligns well with our results and supports the 60STST as a valid, feasible, and reliable tool for assessing functional capacity and muscular endurance in PwMS.

On the other hand, as gait speed has been associated with quality of life in patients with MS and has been widely assessed through the MSWS-12 test, it is one of the most commonly measured indicators for categorizing frailty levels in this population [38]. Among the tests frequently used for this purpose is the T25FW (i.e., 7.6 m distance), which has shown excellent test–retest reliability (ICC = 0.98) [39], establishing associations between increases in walking time and factors such as age, disability, disease type, and disease duration [39]. However, this study is the first to analyze the reliability of the 10MWT in PwMS, showing similar results with the timed 25-foot walking test. In addition, it demonstrates similarly high reproducibility and strong validity, with results aligning closely with those observed in patients with other neurological conditions, such as Parkinson’s disease (ICC = 0.92) [40], or in healthy older adults (ICC = 0.98) [41]. Hence, the 10MWT has significant utility for PwMS, as it provides a simple, yet effective measure to assess functional mobility, balance, and gait, allowing clinicians to monitor disease progression and adjust rehabilitation protocols accordingly [38].

Regarding the 6MWT, previous studies demonstrated excellent reliability (ICC = 0.95) in PwMS, positioning this test as a valid approach to estimate functional capacity and cardiovascular fitness [34,42,43]. Our study found a similarly high reliability (ICC = 0.94), further supporting its applicability in this population. Including the 6MWT in our battery of tests allows us to assess a critical aspect of functional mobility, as it correlates with daily life activity levels and can effectively gauge changes over time or in response to interventions [44]. However, a limitation of our study was the inability to evaluate intra-day reliability due to the potentially exhaustive nature of the 6MWT, as it was performed only once per laboratory visit to prevent potential fatigue in participants. It is important to note that, despite the acceptable reliability of the data, statistically significant differences were observed between the mean results of the two test days for the TUG test, 60STST, 10MWT, and 6MWT. These findings may be attributed to a possible lack of familiarity with the tests, which could have contributed to the significant differences found between the measurements taken on different days for certain tests. However, it is also essential to consider that other factors may have contributed to these differences. These may include the natural variability in biological measurements, changes in environmental factors, and neuromuscular fatigue that patients may experience after their first laboratory visit.

The neuromuscular evaluations conducted as part of this study encompassed a range of assessments, including handgrip strength, isometric peak force during the squat exercise (measured with a dual force plate system and a force sensor), and isometric peak force during unilateral and bilateral knee extension exercise (measured with a force sensor). Neuromuscular evaluations demonstrated excellent intra-day reliability, with ICC values exceeding 0.75 (ranging from 0.912 to 0.989) for both measurements. This high level of consistency indicates that these measures are reliable for assessing neuromuscular function of the lower limbs and demonstrated strong consistency within the same day. Regarding the test–retest reliability, the results were generally good to excellent. The ICCs for the majority of the variables ranged from 0.797 to 0.955, indicating a reasonable degree of consistency between the testing sessions (see Table 2). This finding supports the stability of neuromuscular measures over time, with non-significant differences in the Bland–Altman test. However, the heteroscedasticity analysis (Supplementary File S2) revealed significant differences between measurements 1 and 2 for the MVIC_SQ and UMVIC_{LEXT_L} variables, suggesting that variability in these measurements may be influenced by the magnitude of the recorded values. This should be considered when interpreting the reliability of these assessments, although this may be explained by fatigue induced by the maximum isometric tests performed only 72 h apart. Although neuromuscular capacity assessments have been frequently included in various intervention studies with MS patients, commonly through measurements such as one-repetition maximum (1-RM), maximal concentric isokinetic torque, mechanical power across different loads, or MVIC, the simplest approach for generally untrained MS patients remains assessing isometric strength at a specific joint angle. However, only one study has specifically examined the reliability of MVIC measurements in the leg extension exercise at 90° knee flexion, demonstrating high repeatability (ICC = 0.973) and a minimum detectable change of 13.2 kg [45]. Furthermore, the study reported a strong correlation between MVIC and 1-RM (R² = 0.804) with a 13% absolute percentage error in predicting 1-RM based on MVIC [45]. This reliability was consistent across MS types and independent of neurological disability scores [45]. Notably, our study results align with these findings and with prior studies conducted in different populations that have investigated the reliability of similar assessments. For example, Blazevich et al. [46] reported high reliability (ICC = 0.97) for isometric squat tests in healthy adults. However, the handgrip strength test remains the most commonly administered strength assessment for patients with neurological disorders such as MS [47]. In the case of PwMS, it has proven to be a reliable measure, with reliability estimates of 0.98 for MVIC and 0.84 for time to fatigue [47]. These findings align closely with the results observed in our study. These studies, in conjunction with others focusing on handgrip strength, indicate that these assessments can be reliable tools for evaluating muscle function in diverse populations, including healthy individuals and those with specific health conditions, such as MS [48]. However, similarly to MVIC_SQ and UMVIC_{LEXT_L}, handgrip strength demonstrated statistically significant inter-day differences, being the only neuromuscular variable to show such significant variations (Figure 4). Nevertheless, no significant differences were observed in heteroscedasticity tests (Supplementary File S2), and although the bias identified in the Bland–Altman analysis was statistically significant, it is not clinically relevant (1.34 kg). The observed variability in these neuromuscular tests may be attributed to learning effects given the absence of familiarization with the tests. Alternatively, it may be attributed to daily fluctuations such as fatigue and motivation, which are specific characteristics of the MS population. Additionally, slight variations in the technique may also influence force production. It is worth noting that, although the test battery includes the measurement of both GRF and MVIC in the squat exercise, GRF can be measured for each leg individually, enabling reliable asymmetry analysis without requiring a separate unilateral test for each leg. A unilateral test, while validated [49], demands higher balance and may require extensive familiarization, potentially reducing its reliability. However, GRF measurement requires complex and less-accessible equipment. Therefore, measuring GRF is not essential for future test application, as inter-leg asymmetry can also be assessed using a unilateral leg extension exercise, which is safer and simpler for PwMS. Future research should focus on the reliability of unilateral strength assessments in PwMS, particularly about measuring inter-limb asymmetries. Evaluating asymmetrical force output may provide valuable insights into neuromuscular dysfunctions and compensatory strategies within this population [3]. As inter-limb strength disparities are associated with increased injury risk and reduced functional capacity, understanding the reliability of unilateral strength measures could enhance the utility of these tests in both clinical and research settings [50]. Furthermore, establishing robust protocols for assessing unilateral strength could aid in developing targeted rehabilitation strategies that address specific functional deficits in PwMS.

The use of ultrasound imaging as a structural assessment tool for PwMS has recently been proposed by Maroto-Izquierdo et al. [9], offering a practical alternative to MRI or DXA for regularly monitoring muscle health. This method is promising for tracking sarcopenia, a concern in MS due to inactivity, neurogenic atrophy, and metabolic changes [51,52]. Muscle thickness and cross-sectional area measurements obtained via ultrasound serve as reliable indicators of muscle mass and functional decline [52,53]. Reviews have shown ultrasound’s reliability in muscle size assessment across various health conditions, especially in the VL and RF muscles with ICCs ranging from 0.72 to 1.00 in older adults [53]. Similarly, Lesinski et al. [54] reported excellent inter- and intra-rater reliabilities for muscle thickness in younger populations (ICCs: 0.91–0.99), supporting ultrasound’s applicability across different age groups. In this study, the muscle thickness of the VL and RF was assessed through ultrasound in MS patients, marking the first analysis of its reliability within this population. The results showed excellent intra-day reliability (ICCs: 0.978–0.998), indicating minimal measurement error, and strong test–retest reliability (ICCs: 0.933–0.973). This positions ultrasound as a robust tool for tracking muscle health, especially important for PwMS facing sarcopenia and dynapenia as contributing factors to frailty.

The primary limitation of this study lies in the narrow disability range of the participants, as all patients presented with relatively low levels of disability (EDSS score < 4). This restricts the applicability of our findings to patients with moderate-to-severe disability levels. Additionally, this study included only 13% male participants, which, while reflective of the higher prevalence of MS in women, limits the generalizability of our findings to male patients. Future studies should aim to include a more balanced gender representation. Another limitation was the short interval of 72 h between the two assessment sessions. This time frame may not have been sufficient to mitigate the effects of fatigue, which is particularly prevalent in this population. Moreover, fatigue was not specifically controlled or measured, which could influence the results. Future studies should consider incorporating longer recovery periods and explicitly monitoring fatigue to minimize its impact on the reliability of the assessments. Another notable limitation is the lack of familiarization trials, which might impact not only the reproducibility but also the variability and heteroscedasticity of results. However, the decision to forego familiarization reflects real-world clinical contexts, where PwMS are typically not familiarized with assessment protocols prior to testing. While most functional tests included in this study do not require familiarization, future research could compare reliability outcomes between familiarized and non-familiarized groups to evaluate potential benefits, particularly in functional and isometric strength tests. Although the MScope test battery has demonstrated high reproducibility, further validation against gold-standard tests—such as isokinetic assessments for strength and gas analysis for cardiorespiratory capacity—would provide a more robust validation framework. Additionally, applying this battery to a broader sample of MS patients would facilitate the creation of a more extensive database, potentially supporting the classification of frailty levels based on structural, functional, and neuromuscular parameters. This, in turn, could guide the development of individualized treatment plans aimed at slowing neurodegeneration and enhancing quality of life in MS patients.

5. Conclusions

This study aimed to evaluate the reliability and validity of the MScope test battery, designed to comprehensively assess functional, structural, and neuromuscular capacity in PwMS. The findings confirm the robustness of this tool, as evidenced by high intra- and inter-day reliability across all measured variables, with ICC values exceeding 0.92 for most tests, indicating consistent performance within and across assessment sessions. However, significant differences were observed in functional tests between sessions, highlighting the sensitivity of these tests to subtle changes in capacity and the potential influence of learning effects. Notably, only the TUG test showed significant heteroscedasticity, although the observed bias was minimal and unlikely to be clinically relevant.

Neuromuscular and structural evaluations demonstrated strong reliability and minimal variability, with non-significant differences in Bland–Altman and heteroscedasticity analyses, reinforcing their stability for clinical and research applications. Additionally, ultrasound-based muscle thickness measurements showed excellent intra-day and test–retest reliability, supporting the use of ultrasound as a practical and accessible method for monitoring muscle health, particularly in populations at risk of sarcopenia and dynapenia such as PwMS.

Future research should address the current limitations by including patients with a broader range of disabilities, achieving balanced gender representation, and incorporating familiarization trials to minimize potential learning effects. In summary, the MScope test battery provides a reliable and valid tool for evaluating functional, structural, and neuromuscular parameters in PwMS. Its application can enhance clinical assessment, guide personalized rehabilitation protocols, and contribute to advancing the understanding of neuromuscular function and frailty in PwMS.