# Ultrasound Shear Wave Velocity of Peripheral Nerves: A Possible Non-Invasive Biomarker for Demyelinating Neuropathies

Ricardo Andrade, Antoine Nordez, Armelle Magot, Laura Couloume, Jean-philippe Plançon, Jean-Baptiste Quillard, Robert Ware, Michel Coppieters, Yann Péréon, François Hug

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## To cite this version:

Ricardo Andrade, Antoine Nordez, Armelle Magot, Laura Couloume, Jean-philippe Plançon, et al. Ultrasound Shear Wave Velocity of Peripheral Nerves: A Possible Non-Invasive Biomarker for Demyelinating Neuropathies. Journal of the Peripheral Nervous System, 2025, 30 (2), 10.1111/jns.70015. hal-05022768

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Submitted on 10 Feb 2026

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# Ultrasound Shear Wave Velocity of Peripheral Nerves: A Possible Non-Invasive Biomarker for Demyelinating Neuropathies

Ricardo J. Andrade<fnref n="1" />,² ID | Antoine Nordez<fnref n="1" />,³ ID | Armelle Magot⁴ | Laura Couloume⁴ | Jean-Philippe Plançon⁵ | Jean-Baptiste Quillard<fnref n="1" /> | Robert S. Ware⁶ ID | Michel W. Coppieters²,⁷ ID | Yann Péréon⁴ ID | François Hug<fnref n="1" />,³,⁸ ID

**Correspondence:** Ricardo J. Andrade (ricardo.andrade@univ-nantes.fr) | Antoine Nordez (antoine.nordez@univ-nantes.fr)

## ABSTRACT

**Background and Aims:** Repeated cycles of demyelination and remyelination alter nerve tissue composition, likely affecting its material properties, including stiffness. Using ultrasound shear wave elastography (SWE), we assessed nerve shear wave velocity (SWV), a surrogate measure of stiffness, to determine its potential as a biomarker for demyelinating neuropathies, including chronic inflammatory demyelinating polyneuropathy, Charcot-Marie-Tooth type 1A, and anti-myelin-associated glycoprotein neuropathy.

**Methods:** This cross-sectional study compared nerve SWV between 20 patients with demyelinating neuropathies (60.2 ± 13.1 years) and 16 age-matched controls (56.8 ± 10.8 years). Each participant underwent bilateral SWE of the proximal and distal segments of four peripheral nerves in the upper (median, ulnar and radial) and lower (sciatic-tibial) limbs. Measurements were conducted in different limb positions to mimic two nerve tensile states, yielding a total of 32 nerve stiffness measurements per participant. Conventional nerve cross-sectional area was further evaluated for each nerve and location.

**Results:** Individuals with demyelinating polyneuropathy exhibited increased nerve SWV compared to age-matched controls (mean difference = 0.7 m/s, 95%CI [0.5 to 0.9]; *p* < 0.0001). This difference was observed across all nerves and regions, with the largest difference noted in the tibial. Axial nerve tension amplified these differences. Additionally, moderate to high negative correlations were observed between motor nerve conduction and nerve SWV.

**Interpretation:** This study identifies significant neuropathy-associated alterations in peripheral nerve elasticity. Our findings suggest that nerve stiffness could be a promising biomarker for demyelinating neuropathies, and provide a basis for the development of standardized peripheral nerve SWE protocols.

## 1 | Introduction

Disease monitoring of demyelinating polyneuropathies relies on the clinical presentation and electrophysiological signs of

demyelination or nerve conduction blocks [1–4]. Despite the fact that nerve conduction studies remain the gold standard in the objective monitoring of demyelinating polyneuropathies, this method lacks sensitivity to detect action potentials from

<footnote n="1">¹Nantes Université, Movement - Interactions - Performance, MIP, UR 4334, Nantes, France | ²School of Health Sciences and Social Work, Griffith University, Brisbane and Gold Coast, Australia | ³Institut Universitaire de France (IUF), Paris, France | ⁴CHU Nantes, Centre de référence Pour les Maladies Neuromusculaires AOC, Filnemus, Euro-NMD, Hôtel-Dieu, Nantes, France | ⁵Association Française Contre les Neuropathies Périphériques, La Baule-Escoublac, France | ⁶Griffith Biostatistics Unit, Griffith University, Brisbane, Australia | ⁷Department of Human Movement Sciences, Faculty of Behavioural and Movement Sciences, Vrije Universiteit Amsterdam, Amsterdam, the Netherlands | ⁸Université Côte d'Azur, LAMHESS, Nice, France</footnote>
small-diameter sensory nerves [5] and is limited to distal nerves that are often severely damaged and unexcitable [6].

Among biomedical imaging techniques, ultrasound B-mode imaging has rapidly become an important adjunct method in the evaluation of peripheral nerve disorders [7] to assess nerve cross-sectional area and abnormalities of nerve and fascicle echogenicity [8, 9]. While these measures provide clinical information about a nerve's (macro)structural integrity, ultrasound B-mode may only convey limited information about nerve morphology and textural properties [10–12] due to its high dependence on operator experience and system settings. The emerging ultrasound shear wave elastography (SWE) allows non-invasive quantification of soft-tissue elasticity from the characteristics of shear wave propagation through the medium [13]. The shear wave velocity (SWV) of peripheral nerves, a surrogate measure of stiffness [14], has recently been used to characterize the mechanical properties of peripheral nerve disorders, such as focal [15, 16] and polyneuropathies [17]. These preliminary studies have demonstrated the potential clinical relevance of SWE for neuropathies [18] that cause alterations in nerve mechanical properties [19–21], with the majority reporting increased nerve stiffness regardless of etiology [18]. However, no prior studies have examined the applicability of SWE to evaluate peripheral nerve elastic properties in rare demyelinating, inherited, or acquired, polyneuropathies. Demyelinating neuropathies are characterized by pathological changes resulting from demyelination and remyelination. These changes are marked by significant ultrastructural abnormalities and altered nerve tissue composition [6, 22], which may result in altered nerve stiffness.

This study aimed to assess the differences in peripheral nerve SWV, as measured by SWE, between patients with demyelinating polyneuropathies, acquired and inherited, and healthy age-matched controls. We hypothesized that typical demyelinating polyneuropathies (i.e., Chronic Inflammatory Demyelinating Polyneuropathy (CIDP), Charcot-Marie-Tooth type 1A (CMT1a), and anti-myelin-associated glycoprotein (anti-MAG) neuropathy) would increase nerve SWV compared to healthy age-matched controls. Because nerve SWV is also sensitive to mechanical loads imposed upon the neural structure by joint positional changes [23–26] and exhibits spatial variations [27], we further examined whether the polyneuropathy-associated changes in nerve SWV differ between nerves (median vs. ulnar vs. radial vs. sciatic/tibial), nerve region (proximal vs. distal), and nerve tensile loading state (resting length vs. tensioned). Understanding the interaction between these factors is a critical step toward the development of standardized SWE scanning protocols for evaluating peripheral nerve disorders [28]. Lastly, we further characterized the cross-sectional areas of peripheral nerves using high-resolution B-mode ultrasound imaging, as commonly performed in clinical neuromuscular ultrasound.

# 2 | Methods

## 2.1 | Participants

For both the patient and healthy age-matched control groups, the inclusion criteria to participate in this study included men or women aged 18 years or older. Patients met the inclusion

criteria for the demyelinating polyneuropathy group if they had a confirmed clinical diagnosis of CIDP (diagnosis of definite CIDP, typical or atypical, in accordance with the guidelines of the European Federation of Neurological Societies guidelines), CMT1a (with a proven genetically *PMP22* duplication and a Medical Research Council (MRC) score for muscle strength <3 in at least one muscle group) and/or anti-MAG neuropathy (fulfilling the international criteria for the diagnosis immunoglobulin M (IgM) monoclonal gammopathy, with anti-MAG antibodies). Individuals were excluded from the healthy comparison group if they had a history of peripheral nerve disorders, diabetes, neuromuscular disease, or received neurotoxic chemotherapy.

## 2.2 | Standard Protocol Approvals, Registrations and Patient Consents

The study participants were recruited from two sources. Patients were recruited from the Centre de Référence Maladies Neuromusculaires AOC at Nantes University Hospital, which specializes in the diagnosis and treatment of neuromuscular disorders. Healthy individuals were recruited from various sources, including working environments and the local community. The study was approved by the Institutional Ethics Review Board (CPP-MIP-011). Prior to testing, written informed consent was obtained from all participants.

## 2.3 | Ultrasound Shear Wave Elastography

Nerve SWV was assessed using SWE. All ultrasound scans were performed bilaterally (left and right side) in a randomized order. Four different peripheral nerves (median, ulnar, radial, and sciatic/tibial) were scanned at two different scanning sites/regions (proximal and distal) and two different levels of tensile loads (resting length and tensioned). The full ultrasound scanning protocol lasted ~60 min.

Participants were instructed to lie on their back on an examination plinth for the peripheral nerve scans of the upper extremities (median, ulnar, and radial). The shoulder of the tested upper limb was positioned in 90° abduction. The arm, forearm, and wrist were supported on a separate table placed by the side of the examination plinth. A custom splint was employed to maintain the wrist and fingers in a neutral position (approximately 0°). The forearm was maintained in neutral pronosupination during the examination. A polypropylene pegboard was placed on top of the examination table and used to support the upper limb while stabilizing the position of the main joints, including the shoulder, elbow, and wrist. Two elbow positions were tested: 90° flexion and 180° extension. Elbow extension significantly increased the tensile load placed upon both the median and radial nerves while unloading the ulnar nerve [24, 29]. We then classified nerve tensile load in resting length vs. tensioned accordingly. All nerves were scanned at two nerve regions: proximal (arm) and distal (forearm). Briefly, the upper-arm length was measured as the distance between the lateral epicondyle of the elbow and the acromion at the shoulder, and the forearm length was defined as the distance between the radial styloid process at the wrist and the olecranon with the elbow flexed at
<table><caption>**TABLE 1** | Characteristics of the patient with demyelinating neuropathy and healthy age-matched controls.</caption><thead><tr><th></th><th>Healthy aged-matched controls (N=16, 6 women)</th><th>Demyelinating polyneuropathy (N=20, 9 women)</th><th>p</th></tr></thead><tbody><tr><td>Age (yrs)</td><td>56.8 ± 10.8</td><td>60.2 ± 13.1</td><td>0.41</td></tr><tr><td>Weight (kg)</td><td>69.6 ± 11.0</td><td>73.7 ± 11.9</td><td>0.30</td></tr><tr><td>Height (cm)</td><td>170.7 ± 7.2</td><td>170.2 ± 7.8</td><td>0.85</td></tr><tr><td>BMI (kg/m²)</td><td>23.8 ± 2.6</td><td>25.4 ± 2.9</td><td><strong>0.09</strong></td></tr></tbody></table>

Note: Data are shown as mean ± SD. p < 0.05 significant difference.
Abbreviation: BMI, body mass index.

90°. All nerves were then scanned at 1/3 of the arm (proximal) and forearm (distal) lengths from the elbow joint.

For the scans in the lower extremities, the participants were instructed to lie prone on the examination plinth. The sciatic/tibial nerve was scanned in two regions: proximal (thigh: sciatic) and distal (ankle: tibial). The proximal region was scanned at the mid-distance between the point where the sciatic nerve bifurcates into tibial and common fibular branches and the mid-point between the ischial tuberosity and the greater trochanter. The tibial nerve was scanned near the ankle joint, at 10% of the straight distance from the medial malleolus to the medial femoral condyle. For the assessment of the sciatic/tibial nerve, the participant's hip joint was passively positioned in a neutral position and their ankle was passively secured at 90° over the edge of the examination plinth. Scans were performed at two nerve tensile load states by altering the knee angle [26]: knee flexed at 90° (resting length) and knee fully extended (tensioned).

Skin marks were used to identify all scanning regions prior to measurements. A linear array transducer (L15-4 MHz for upper limb nerves; L10-2 MHz for lower limb nerves; Tours, France) coupled to an ultrasound scanner (Aixplorer, version 6.1; Supersonic Imagine, Aix-en-Provence, France) was used for all scans. SWE scans were performed in MSK pre-set, with the following settings: penetration mode, 100% opacity, no temporal smoothing (persistence=OFF), and intermediate spatial smoothing—5/9. All scans were performed with minimal transducer pressure. The maps of the SWV were obtained at 1 sample/s with a spatial resolution of 1 × 1 mm.

For each location, peripheral nerves were first identified in the resting length condition. A B-mode image was acquired in transverse view for each nerve and nerve region. These images were used to measure the nerve cross-sectional area. Then, the transducer was rotated 90° into the longitudinal plane and aligned with the direction of nerve fibers for SWE purposes. For each nerve region, the center of the transducer was aligned with the skin marks. The SWV map was placed over the nerve of interest and its location remained unchanged during the duration of each measurement clip. The size of the SWE map was defined as the largest size allowed by the scanner. A 10-s SWE clip (1 Hz) was obtained for each nerve, region, tension level, and side (i.e.,

<table><caption>**TABLE 2** | Clinical features and nerve conduction tests for the demyelinating polyneuropathy group.</caption><thead><tr><th colspan="2">Clinical features, n (%)</th></tr></thead><tbody><tr><td>Distal symmetric</td><td>9/20 (45)</td></tr><tr><td>Proximal and distal symmetric</td><td>8/20 (40)</td></tr><tr><td>Distal asymmetric</td><td>3/20 (15)</td></tr><tr><td>Sensory dominant</td><td>7/20 (35)</td></tr><tr><td>Sensorimotor</td><td>12/20 (60)</td></tr><tr><td>Motor dominant</td><td>1/20 (5)</td></tr><tr><td>MRC sum-score</td><td>54.1 ± 5.2</td></tr><tr><td colspan="2">Nerve conduction study</td></tr><tr><td>Median MNCV (m/s)*</td><td>29.3 ± 12.3</td></tr><tr><td>Median CMAP (mV)*</td><td>3.7 ± 2.5</td></tr><tr><td>Ulnar MNCV (m/s)#</td><td>34.6 ± 15.4</td></tr><tr><td>Ulnar CMAP (mV)#</td><td>4.7 ± 3.1</td></tr><tr><td>Radial MNCV (m/s)$</td><td>25.9 ± 13.4</td></tr><tr><td>Radial CMAP (mV)$</td><td>3.0 ± 1.9</td></tr></tbody></table>

Note: Data are shown as mean ± SD.
Abbreviations: CMAP, compound muscle action potential (mV); MNCV, motor nerve conduction velocity (m/s).

*A total of 19 (out of 20) patients were evaluated. Data from 19 median distal nerves were analyzed. One patient with CMT1a did not attend nerve conduction tests. The median nerve of 3 patients (all with anti-MAG neuropathy) was completely unexcitable at least in one testing site and omitted from the correlation analyses.

†A total of 19 (out of 20) patients were evaluated. Data from 19 ulnar distal nerves were analyzed. One patient with CMT1a did not attend nerve conduction tests. Four ulnar nerves (patients with anti-MAG neuropathy) were completely unexcitable at least in one testing site and omitted from the correlation analyses.

§A total of 15 (out of 20) patients were evaluated. Data from 15 radial proximal nerves were analyzed. One patient with CMT1a did not attend nerve conduction tests. The four patients with CIDP did not perform electrodiagnostic tests on the radial nerve. The radial nerve of 6 patients (all anti-MAG neuropathy) was completely unexcitable at least in one testing site and omitted from the correlation analyses.

32 measurements per participant). After recording one clip, the transducer was then moved to the next nerve/region, and the procedure for data acquisition was repeated. To account for the viscoelastic properties of biological soft tissues, SWE measurements were delayed for a minimum of 2 min after positioning the participant's limb in the testing position. This protocol was implemented to mitigate the viscoelastic stress relaxation, which can occur as a result of static stretching, particularly at the onset of tension application [30]. Our pilot data indicate that there were no temporal changes in SWE measurements observed after 2 min. Intra-observer reliability for peripheral nerve SWE has been shown to be very good to excellent in the examination of both healthy and pathological nerves [17, 18, 28]. Data from our group have demonstrated very good intra-observer reliability, with ICCs ranging from 0.92 to 0.99 [95% confidence interval (95% CI) ranging from 0.72 and 1] and a coefficient of variation smaller than 8.1% [26].

Shear wave propagation in thin and stiff media can experience successive reflections at the boundaries of the medium. This phenomenon, known as guided wave propagation, has been
demonstrated in tendons and can affect the relationship between shear modulus and SWV [31]. For peripheral nerves, which are less stiff than tendons, the impact of guided wave propagation is expected to be smaller. However, we chose to report our main outcome variable in terms of SWV rather than shear modulus or Young's modulus [28]. In addition, to account for the possible guided wave phenomena, we quantified the nerve thickness for each nerve SWE measurement and used it as a covariate in our statistical models. To acquire these measurements, we used simultaneous real-time SWE and B-mode ultrasound imaging views. The SWE window was used to calculate SWV, while the B-mode window was used to identify the region of interest (ROI) for SWE images and measure nerve thickness. Participants were instructed to remain relaxed during the scans to ensure that their upper and lower limb muscles were in a passive state.

## 2.4 | Neurophysiologic Studies

To explore the association between nerve SWV and nerve function, we employed standard clinical nerve conduction studies from routine patient examination. Motor nerve conduction

velocity (MNCV; m/s) and compound muscle action potential (CMAP; mV) of the median distal, ulnar distal, and radial proximal nerve segments were measured using the Dantec Keypoint system (Natus, Middleton, USA) in accordance with the guidelines from the American Academy of Neurology and American Association of Electrodiagnostic Medicine [32]. To eliminate any bias, the electrodiagnostic studies were conducted independently by two trained investigators (Y.P. and A.M.) who were blind to the ultrasonography scans.

## 2.5 | Data Processing

All data were analyzed offline using custom Matlab (Version 18; The MathWorks Inc., Natick, MA, USA) scripts. SWE clips were exported in MP4 format and converted (1 Hz) into JPEG images. Then, peripheral nerve ROIs were manually traced (image-by-image) on the adjacent B-mode window. ROIs were defined as the largest nerve area within the nerve hyperechoic boundaries (epineurium). Based on the scanner's scale (ranging from 0 to 18.3 m/s), SWV values were obtained for each pixel within the SWE map and averaged within each ROI to obtain

<figure><img src="image_3.png" /><figcaption>**FIGURE 1** | Example of shear wave elastography maps (including a B-mode window) scanned at the proximal region of the median nerve in a patient with CMT1a (left panel) and in an age-matched healthy control (right panel). Upper and bottom panels illustrate median nerve scans at resting and tension conditions, respectively.</figcaption></figure>
a representative SWV value (m/s) per frame. The mean SWV was then calculated by averaging over consecutive frames (total of ~10s) and used for statistical analysis. All SWE data were visually inspected for the occurrence of artifacts and significant void areas. In addition, nerve thickness was measured in the longitudinal view of each nerve B-mode image as the average of six manually placed straight-line measurements, drawn perpendicular to the nerve's main axis, between the superficial and deep hyperechoic epineural boundaries. These boundaries were placed immediately adjacent to the intraneural compartment, which excluded the epineural thickness from the measurement. The nerve cross-sectional area was measured three times on the same image and calculated as the area inside the hyperechoic rim of the epineurium using the tracing method. The average was used for further analysis.

## 2.6 | Statistical Analysis

All analyses were implemented in RStudio (v1.4.1103). Differences in age, weight, height, and BMI between testing groups were analyzed using unpaired t-tests. Values are reported as mean ± standard deviation. Then, linear mixed-effect models were implemented to investigate the associations between demyelinating polyneuropathy and age-associated alterations on nerve SWV and nerve cross-sectional area. We used the “lme4” package with the Kenward-Roger method to estimate F and p-values. For each analysis, we considered all the data points, including bilateral measurements per participant, instead of averaging the values per participant. We used the Akaike Information Criterion (AIC) and the Schwarz Bayesian Criterion (BIC) to select the covariance matrix with the best fit. The structure exhibiting the smallest AIC and BIC values was

then chosen. The first linear mixed effects model was used to assess the effects of demyelinating polyneuropathy (groups: demyelinating polyneuropathy, healthy age-matched controls), nerve region (proximal, distal), tension level (resting, tension), and nerve (median, radial, ulnar, sciatic/tibial) on the peripheral nerve SWV. In addition to the fixed effects, the model was implemented with participants as a random factor effect and side (left, right) nested with the participant to account for the influence of the correlation between repeated observations in each participant [33]. We first fitted a model adjusting for the covariates nerve thickness and sex as fixed effects due to their possible influence on nerve SWV [28, 31, 34]. However, based on our model-fit criteria, both thickness and sex were removed from the variance-covariance structure. The second model was implemented to compare the nerve cross-sectional area between experimental groups, nerve region, and nerve, with the participant as a random factor nested with side. This model was initially adjusted for the covariate sex. Here, the best model fit excluded both side and sex from the model structure. For all models, normality assumptions were visually confirmed by analysis of the histogram of residuals, Q-Q Plot, and the residual-predicted scatterplot. When appropriate, we performed multiple comparisons (post hoc analysis) using the “emmeans” package. P-values were adjusted using the Tukey HSD. The effect sizes derived from the F ratios were calculated with the partial omega-squared (ω [2]). The estimated marginal mean difference (MD) and 95% CI were determined. Data are presented as MD [95% CI]. Statistical significance was defined as *p* < 0.05. The associations between MNCV and SWV were explored for the median distal, ulnar distal, and radial proximal segments using Pearson's correlation coefficient. Similar tests were used to investigate the associations between CMAPs and nerve stiffness in the same segments.

<figure><img src="image_4.png" /><figcaption>**FIGURE 2** | Differences in nerve cross-sectional area (mm²) between demyelinating neuropathy and healthy age-matched controls per nerve (median, radial, sciatic/tibial, and ulnar) and nerve region (distal, proximal). For the sciatic/tibial nerve tract, the proximal nerve region refers to measurements performed in the sciatic nerve, while the distal region corresponds to measurements performed in the tibial nerve. Each dot represents a single data point/participant, colored by group (demyelinating polyneuropathy: Light blue; healthy age-matched controls: Light pink). There are two data points for each participant as ultrasound shear wave elastography scans were performed bilaterally. Mean ± SD are shown for each nerve and offset to the left to facilitate data visualization. *Denotes statistical difference, *p* < 0.05.</figcaption></figure>
Twenty patients with rare demyelinating neuropathies (4 CIPD, 9 anti-MAG, 7 CMT1a; 60.2 ± 13.1 years, 9 women), sixteen age-matched healthy controls (56.8 ± 10.8 years, 6 women) volunteered to participate in this study (Table 1). Clinical features of the demyelinating polyneuropathy group are shown in Table 2.

The mixed model analysis of nerve SWV was performed on all available data (1152 data points). All nerves and nerve regions were successfully scanned except for one sciatic nerve in a patient with demyelinating polyneuropathy (i.e., CIDP), which exhibited substantial void areas within the SWE map due to its deep location (> 4 cm). SWV data (i.e., 4 data points) were not imputed for the sciatic nerve at both tensile states (resting, tension) and side (left, right) conditions of this participant. Figure 1 illustrates the differences in SWE maps of a median nerve (proximal region) between a patient with CMT1a and a healthy age-matched control.

## 3.1 | Effects of Demyelinating Polyneuropathies on Nerve Cross-Sectional Area

The classically measured mean cross-sectional area was significantly different between groups ($F=39.5; p<0.0001; \omega^2=0.5$), with patients with demyelinating polyneuropathy having significantly greater nerve cross-sectional areas than healthy age-matched controls (MD=12.5 mm² 95% CI [8.5 to 16.6]; $p<0.0001$). Furthermore, a Group\*Region\*Nerve interaction ($F=3.2; p=0.023; \omega^2=0.5$; Figure 2) was observed. Post hoc tests revealed that the demyelinating polyneuropathy-associated changes in nerve cross-sectional area were similar across all scanned peripheral nerves and nerve regions (MD<sub>Polyneuropathy—Healthy Controls</sub> ranged between 7.6 mm² and 43.0 mm²; all $p \le 0.01$).

## 3.2 | Effects of Demyelinating Polyneuropathies on Nerve Shear Wave Velocity

Average shear wave velocities for each nerve, region, and tensile state are detailed in Table 3 for both the polyneuropathy and healthy control groups. Mean SWV differed significantly between groups ($F=33.7; p<0.0001; \omega^2=0.5$), with patients with demyelinating polyneuropathy having significantly greater nerve SWV than healthy age-matched controls (MD=0.7 m/s, 95% CI [0.5 to 0.9]). We did not observe a significant Group\*Nerve\*Region\*Tension interaction ($F=0.08; p=0.972$), Group\*Nerve\*Tension interaction ($F=0.7; p=0.528$) or Group\*Tension\*Region interaction ($F=0.01; p=0.911$), suggesting that polyneuropathy-associated differences were not influenced by the combined effects of nerve tension, region, and nerve being tested.

There was a significant Group\*Region\*Nerve interaction ($F=3.2; p=0.02; \omega^2=0.006$; Figure 3). Post hoc comparisons revealed that mean SWV was significantly greater in patients with demyelinating neuropathy compared to healthy age-matched controls for all scanned nerves and nerve regions (MD<sub>Polyneuropathy—Healthy Controls</sub> ranged between 0.5 m/s and

<table><caption>**TABLE 3** | Averaged shear wave velocities across peripheral nerves, nerve regions and tension states: Measurements for both left and right nerves included, with detailed shear wave velocity data for each neuropathy subtype.</caption><thead><tr><th rowspan="3">Region</th><th rowspan="3">NERVE</th><th colspan="10">Shear wave velocity (m/s)</th></tr><tr><th colspan="5">Distal</th><th colspan="5">Proximal</th></tr><tr><th>Median</th><th>Resting</th><th>Tension</th><th>Radial</th><th>Resting</th><th>Tension</th><th>Ulnar</th><th>Median</th><th>Resting</th><th>Tension</th><th>Radial</th><th>Resting</th><th>Tension</th><th>Ulnar</th></tr></thead><tbody><tr><td rowspan="2">Tension</td><td>Healthy</td><td>3.2 ± 0.5</td><td>6.1 ± 1.0</td><td>3.0 ± 0.7</td><td>5.0 ± 1.1</td><td>3.1 ± 0.5</td><td>3.8 ± 0.5</td><td>3.3 ± 0.4</td><td>3.9 ± 0.7</td><td>3.3 ± 0.6</td><td>7.3 ± 1.4</td><td>3.0 ± 0.6</td><td>5.0 ± 0.9</td><td>2.2 ± 0.3</td><td>3.1 ± 0.5</td><td>3.6 ± 0.8</td><td>4.7 ± 0.8</td></tr><tr><td>aged-matched controls (n=16)</td><td>3.5 ± 0.6</td><td>6.9 ± 1.0</td><td>3.8 ± 1.1</td><td>5.9 ± 1.3</td><td>4.0 ± 1.0</td><td>5.3 ± 1.3</td><td>3.7 ± 0.7</td><td>4.5 ± 1.1</td><td>3.9 ± 0.8</td><td>8.3 ± 1.5</td><td>3.5 ± 0.9</td><td>5.6 ± 0.9</td><td>2.7 ± 0.7</td><td>4.0 ± 1.0</td><td>4.2 ± 1.0</td><td>5.6 ± 1.6</td></tr><tr><td rowspan="2">Tension</td><td>Demyelinating polyneuropathy (n=20)</td><td>3.2 ± 0.6</td><td>7.0 ± 1.1</td><td>3.7 ± 0.7</td><td>5.7 ± 1.1</td><td>3.5 ± 0.6</td><td>4.7 ± 1.0</td><td>3.4 ± 0.5</td><td>4.3 ± 0.9</td><td>3.8 ± 0.7</td><td>8.0 ± 1.5</td><td>3.0 ± 0.5</td><td>5.8 ± 0.7</td><td>2.8 ± 0.9</td><td>4.2 ± 1.2</td><td>3.9 ± 0.9</td><td>5.4 ± 1.4</td></tr><tr><td>Anti-MAG (n=9)</td><td>3.3 ± 0.5</td><td>7.1 ± 0.8</td><td>3.8 ± 1.3</td><td>6.6 ± 1.2</td><td>3.8 ± 0.4</td><td>5.5 ± 1.7</td><td>3.4 ± 0.5</td><td>4.3 ± 1.4</td><td>4.0 ± 0.9</td><td>9.5 ± 1.1</td><td>4.1 ± 1.2</td><td>5.7 ± 0.8</td><td>2.9 ± 0.4</td><td>4.2 ± 0.6</td><td>4.4 ± 1.5</td><td>6.0 ± 0.8</td></tr><tr><td rowspan="2">Tension</td><td>CMT1a (n=7)</td><td>3.9 ± 0.5</td><td>6.6 ± 0.8</td><td>4.0 ± 1.3</td><td>5.7 ± 1.7</td><td>4.8 ± 1.1</td><td>5.9 ± 1.1</td><td>4.1 ± 0.7</td><td>5.0 ± 1.0</td><td>4.1 ± 0.9</td><td>8.2 ± 1.4</td><td>3.8 ± 0.8</td><td>5.2 ± 1.1</td><td>2.6 ± 0.5</td><td>3.8 ± 0.9</td><td>4.4 ± 0.8</td><td>5.6 ± 2.1</td></tr></tbody></table>

Abbreviations: Anti-MAG, Anti-myelin associated glycoprotein; CIDP, Chronic inflammatory demyelinating polyradiculoneuropathy; CMT, Charcot–Marie-Tooth; Data are shown as mean ± SD.

*For the sciatic/tibial nerve tract, the proximal nerve region refers to measurements performed in the sciatic nerve, while the distal region corresponds to measurements performed in the tibial nerve.
1.2 m/s; all *p* < 0.006). The highest magnitude difference across all nerves and nerve regions was observed in the tibial nerve (1.2 m/s), suggesting distal-to-proximal mechanical changes.

Lastly, we found a Group*Tension interaction* (*F*=10.9; *p*=0.001; *ω*²=0.009) indicating that the magnitude of differences between both groups was greater under axial tension (*MD*<sub>Polyneuropathy—Healthy Controls</sub>=0.9; *p*<0.0001) than in the unloaded condition (*MD*<sub>Polyneuropathy—Healthy Controls</sub>=0.6; *p*=0.0002).

## 3.3 | Associations Between Nerve Shear Wave Velocity and Nerve Conduction Studies

Overall, we observed moderate to high negative correlations between nerve SWV, measured using SWE, and both MNCV and CMAPs, as assessed by nerve conduction studies, for the median, ulnar, and radial nerves (Figure 4). Significant correlations were noted for all nerves, except for the relationship between CMAP and SWV in the radial nerve.

## 4 | Discussion

Peripheral nerve SWE is a novel and rapidly developing field. It has shown promise as an adjunct diagnostic test and as a potential measure of treatment response in peripheral nerve disorders, such as diabetic polyneuropathy [17] and carpal tunnel syndrome [15], with high diagnostic sensitivity and specificity [18]. Using SWE to quantify nerve SWV, we showed that demyelinating peripheral nerves are stiffer than those from healthy age-matched individuals. Our comprehensive characterization of peripheral nerve elasticity as a function of disease, nerve, nerve region, and nerve tensile state provides a basis for the

development of standardized SWE protocols in demyelinating polyneuropathies.

Demyelinating peripheral nerves are exposed to repeated demyelination and abortive attempts at remyelination, resulting in ‘onion bulb’ formations [6, 35]. This pathological hallmark of demyelinating polyneuropathies (including CMT1a, anti-MAG neuropathy and CIDP) constitutes of multiple concentric layers of Schwann cells and basement membranes surrounding the axons [6, 36]. Other histological features of demyelinating nerves include derived products associated with nerve degeneration, such as an abundance of myxoid and amorphous material [22], and increased number of collagen fibers [22, 37]. Together, these marked histopathologic features cause nerve hypertrophy or enlargement [9] and are likely to dictate the nerve elastic properties. Indeed, our results showed that nerve SWV is increased for all demyelinating peripheral nerves and nerve regions with the highest magnitude difference being observed in the tibial nerve near the ankle joint. This not only shows that demyelinating peripheral nerves exhibit increased stiffness, but also suggests a length-dependent disease pattern, characterized by a distal-to-proximal progression, for the neuropathy-associated changes in the nerve’s elasticity. This is further supported by the observation that most patients in the demyelinating polyneuropathy group presented with classic, length-dependent forms of CMT1a (n=7) [38] and anti-MAG demyelinating neuropathies (n=9) [39], while only four participants displayed a non-length-dependent neuropathy (CIDP, n=4). Finally, while we found significant neuropathy-associated changes in nerve stiffness for both tensile states, the magnitude of these changes was greater for the tension state. This indicates that early and subtle changes in nerve elasticity may be better detected under axial nerve tensile loads. Paradoxically, nerve tensioning can also be a confounding variable as it is highly sensitive to positional changes [24, 27].

<figure><img src="image_5.png" /><figcaption>**FIGURE 3** | Differences in nerve shear wave velocity (m/s) between demyelinating neuropathy and healthy age-matched controls per nerve region (distal, proximal) and nerve (median, radial, sciatic/tibial, and ulnar). For the sciatic/tibial nerve tract, the proximal nerve region refers to measurements performed in the sciatic nerve, while the distal region corresponds to measurements performed in the tibial nerve. Each dot represents a single data point, colored by tension level (resting: Blue; tensioned: Red). For each participant, there are two data points as shear wave elastography scans were performed bilaterally. Mean ± SD are shown and offset to the left to facilitate data visualization. *Denotes statistical difference, *p* < 0.05.</figcaption></figure>
A

<figure><img src="image_6.png" /></figure>

R = -0.724
p-value = 0.00153

<figure><img src="image_7.png" /></figure>

R = -0.57
p-value = 0.0264

<figure><img src="image_8.png" /></figure>

R = -0.735
p-value = 0.0241

B

<figure><img src="image_9.png" /></figure>

R = -0.581
p-value = 0.0182

<figure><img src="image_10.png" /></figure>

R = -0.632
p-value = 0.0114

<figure><img src="image_11.png" /></figure>

R = -0.511
p-value = 0.16

Neuropathy ● anti-MAG ● CIDP ● CMT1a

**FIGURE 4** | Associations between nerve shear wave velocity (m/s) and routine clinical electrodiagnostic tests for the demyelinating neuropathy group. (A) Correlation between the nerve shear wave velocity (m/s) and nerve motor conduction velocities (m/s) for median, ulnar, and radial nerves; (B) Correlation between the nerve shear wave velocity (m/s) and CMAP (mV) for median, ulnar, and radial nerves. CMAP: Compound muscle action potential.

Our results demonstrate that both nerve size, as measured by cross-sectional area, and nerve elasticity, as measured by SWV, undergo significant changes in response to demyelinating neuropathy across various nerves and regions. Notably, these changes were consistently observed in the same nerves and regions (Figures 2 and 3). However, the correlation between nerve cross-sectional area and SWV across all data was weak (r = -0.215; *p* < 0.001; Figure 5). This suggests that nerve cross-sectional area and SWV may represent distinct and independent parameters in nerve evaluation, which is logical from a mechanical perspective, as geometry and elastic modulus pertain to different and independent properties. Evaluating nerve elasticity may be particularly valuable for assessing neuropathies that do not lead to noticeable nerve enlargement or swelling, such as some axonal neuropathies [40]. Further studies are required to explore the potential application of SWE in these forms of neuropathies.

Our findings also suggest an overall trend toward an association between nerve electrophysiological function and its mechanical

properties as estimated by nerve SWV (Figure 4). However, it is important to note that the sample size for electrodiagnostic tests was small and the interpretation of such preliminary results should be made with caution. While nerve mechanical properties may be related to nerve electrophysiological function [41, 42], further studies with larger sample sizes are needed to confirm this possible association and to investigate these correlations in more detail.

We acknowledge the following limitations. First, this is a preliminary study of a relatively small cohort of patients (n = 20) with rare demyelinating acquired and inherited polyneuropathies, not powered to provide validated biomarkers or statistical correlation with clinical measures. Larger-scale longitudinal studies could serve as future steps to better evaluate the utility of SWE. Second, owing to its cross-sectional design, our study was conducted on a series of patients with different forms of demyelinating polyneuropathy, whose clinical characteristics, such as severity, chronicity, and ongoing therapies, may differ. Third, we scanned three different forms of polyneuropathies. Despite
Cross-sectional area vs. Shear wave velocity

<figure><img src="image_12.png" /><figcaption>**FIGURE 5** | Associations between nerve shear wave velocity (m/s) and cross-sectional area (mm²) for all nerves and nerve regions at resting tensile state. Data from both left and right sides were included in the Pearson correlation analysis (r).</figcaption></figure>

<figure><img src="image_13.png" /><figcaption>**FIGURE 6** | Individual nerve shear wave velocity raw data per form of polyneuropathy, nerve region, and nerve. For the sciatic/tibial nerve tract, the proximal nerve region refers to measurements performed in the sciatic nerve, while the distal region corresponds to measurements performed in the tibial nerve. Both levels of nerve tension are also represented. Individual groups are illustrated by color. CMT1a: Charcot-Marie-Tooth type 1A; CIDP: Chronic Inflammatory Demyelinating Polyneuropathy.</figcaption></figure>

their being all demyelinating, they do not present the same pathophysiology and histopathologic characteristics. This may lead to neuropathy-specific changes in nerve properties, including stiffness. We did not perform statistical subgroup analysis due to the small number of participants for each type of neuropathy. Individual raw data showing nerve shear wave velocities as a function of neuropathy type are available in Figure 6. From

visual inspection, it is challenging to discern a distinct pattern for each pathology. Further research with a larger patient population is needed to verify these findings. In addition, the nerve dimensions and stiffness measurements presented in this study did not account for epineural thickness, which is likely affected by neuropathy-associated tissue remodeling. Lastly, peripheral nerve SWE scans were limited to proximal and distal peripheral
nerve regions in both upper and lower limbs. Scanning pure
sensory segments (e.g., sural nerve) and regions closer to the
spine (e.g., lumbosacral plexus) would provide a more detailed
mechanistic understanding of elasticity-associated changes in
demyelinating neuropathies.

5 | Conclusion

SWE has shown great promise in the field of neuropathies. The development of non-invasive biomarkers with longitudinal sensitivity and applicability in multi-center trials is essential to better evaluate peripheral nerve disease progression and the effectiveness of new therapeutic strategies. In this study, we demonstrated the potential of nerve SWV, a surrogate measure of nerve stiffness, as a possible non-invasive mechanical biomarker for the monitoring of demyelinating acquired or inherited polyneuropathies. Our preliminary results warrant further large-scale and prospective studies to validate the utility of nerve SWV as a disease biomarker in demyelinating neuropathies. In addition, future clinical research should consider the impact of nerve location and positional nerve stiffness on the accuracy of nerve SWV measurements. Lastly, emerging angle-resolved shear wave methods hold promise for further improving the mechanical characterization of peripheral nerves and may provide novel mechanical-based indicators of tissue health, such as tensile elasticity, anisotropy, and nonlinear shear elasticity [43–45].

Author Contributions

Conception and design of the study: R.J.A., A.N., A.M., J.P.P., Y.P., F.H.
Acquisition and analysis of data: R.J.A., A.N., A.M., L.C., J.B.Q., R.S.W.,
M.W.C., Y.P., F.H. Drafting a significant portion of the manuscript or
figures: R.J.A., A.N., M.W.C., Y.P., F.H.

Acknowledgments

This study was supported by the Région des Pays de la Loire (QUETE
project, no. 2015-09035) and the Nantes Université (Interdisciplinary
program). R.J.A. was supported by a Griffith University Postdoctoral
Fellowship (GUPF) and AFM-Téléthon (Grant ID#28643).

Conflicts of Interest

The authors declare no conflicts of interest.

**Data Availability Statement**

The data that support the findings of this study are available from the
corresponding author upon reasonable request.

References

1. Joint Task Force of the E, the PNS, "European Federation of Neurological Societies/Peripheral Nerve Society Guideline on Management of Paraproteinemic Demyelinating Neuropathies. Report of a Joint Task Force of the European Federation of Neurological Societies and the Peripheral Nerve Society—First Revision," *Journal of the Peripheral Nervous System* 15, no. 3 (2010): 185–195, https://doi.org/10.1111/j.1529-8027.2010.00278.x.

2. Joint Task Force of the E, the PNS, "European Federation of Neurological Societies/Peripheral Nerve Society Guideline on Management of Chronic Inflammatory Demyelinating Polyradiculoneuropathy: Report

of a Joint Task Force of the European Federation of Neurological Societies and the Peripheral Nerve Society—First Revision,” *Journal of the Peripheral Nervous System* 15, no. 1 (2010): 1–9, https://doi.org/10.1111/j.1529-8027.2010.00245.x.

3. Joint Task Force of the E, the PNS, “European Federation of Neurological Societies/Peripheral Nerve Society Guideline on Management of Multifocal Motor Neuropathy. Report of a Joint Task Force of the European Federation of Neurological Societies and the Peripheral Nerve Society—First Revision,” *Journal of the Peripheral Nervous System* 15, no. 4 (2010): 295–301, https://doi.org/10.1111/j.1529-8027.2010.00290.x.

4. P. Y. Van den Bergh, R. D. Hadden, P. Bouche, et al., "European Federation of Neurological Societies/Peripheral Nerve Society Guideline on Management of Chronic Inflammatory Demyelinating Polyradiculoneuropathy: Report of a Joint Task Force of the European Federation of Neurological Societies and the Peripheral Nerve Society - First Revision," *European Journal of Neurology* 17, no. 3 (2010): 356–363, https://doi.org/10.1111/j.1468-1331.2009.02930.x.

5. J. C. Arezzo and E. Zotova, "Electrophysiologic Measures of Diabetic Neuropathy: Mechanism and Meaning," *International Review of Neurobiology* 50 (2002): 229–255, https://doi.org/10.1016/s0074-7742(02)50079-9.

6. N. Latov, "Diagnosis and Treatment of Chronic Acquired Demyelinating Polyneuropathies," *Nature Reviews. Neurology* 10, no. 8 (2014): 435–446, https://doi.org/10.1038/nrneurol.2014.117.

7. J. A. Telleman, I. J. Herraets, H. S. Goedee, J. T. van Asseldonk, and L. H. Visser, "Ultrasound Scanning in the Diagnosis of Peripheral Neuropathies," *Practical Neurology* 21, no. 3 (2021): 186–195, https://doi.org/10.1136/practneurol-2020-002645.

8. R. Gasparotti, L. Padua, C. Briani, and G. Lauria, "New Technologies for the Assessment of Neuropathies," *Nature Reviews. Neurology* 13, no. 4 (2017): 203–216, https://doi.org/10.1038/nrneurol.2017.31.

9. A. Di Pasquale, S. Morino, S. Loreti, E. Bucci, N. Vanacore, and G. Antonini, “Peripheral Nerve Ultrasound Changes in CIDP and Correlations With Nerve Conduction Velocity,” *Neurology* 84, no. 8 (2015): 803–809, https://doi.org/10.1212/WNL.0000000000001291.

10. E. Gallardo, Y. Noto, and N. G. Simon, "Ultrasound in the Diagnosis of Peripheral Neuropathy: Structure Meets Function in the Neuromuscular Clinic," *Journal of Neurology, Neurosurgery, and Psychiatry* 86, no. 10 (2015): 1066–1074, https://doi.org/10.1136/jnnp-2014-309599.

11. C. Moschovos, G. Tsivgoulis, A. Ghika, et al., “Image Analysis Can Reliably Quantify Median Nerve Echogenicity and Texture Changes in Patients With Carpal Tunnel Syndrome,” *Clinical Neurophysiology* 149 (2023): 61–69, https://doi.org/10.1016/j.clinph.2023.02.171.

12. F. Schreiber, C. Garz, H. J. Heinze, S. Petri. S. Vielhaber, and S. Schreiber, “Textural Markers of Ultrasonographic Nerve Alterations in Amyotrophic Lateral Sclerosis,” *Muscle & Nerve* 62, no. 5 (2020): 601–610, https://doi.org/10.1002/mus.27043.

13. J. L. Gennisson, T. Deffieux, M. Fink, and M. Tanter, "Ultrasound Elastography: Principles and Techniques," *Diagnostic and Interventional Imaging* 94, no. 5 (2013): 487–495, https://doi.org/10.1016/j.diii.2013.01.022.

14. V. Schrier, J. Lin, A. Gregory, et al., "Shear Wave Elastography of the Median Nerve: A Mechanical Study," *Muscle & Nerve* 61, no. 6 (2020): 826-833, https://doi.org/10.1002/mus.26863.

15. F. Kantarci, F. E. Ustabasioglu, S. Delil, et al., "Median Nerve Stiffness Measurement by Shear Wave Elastography: A Potential Sonographic Method in the Diagnosis of Carpal Tunnel Syndrome," *European Radiology* 24, no. 2 (2014): 434–440, https://doi.org/10.1007/s00330-013-3023-7.

16. T. Neto, S. R. Freitas, R. J. Andrade, et al., "Noninvasive Measurement of Sciatic Nerve Stiffness in Patients With Chronic Low Back Related Leg Pain Using Shear Wave Elastography," *Journal of Ultrasound in Medicine* 38, no. 1 (2019): 157–164, https://doi.org/10.1002/jum.14679.
17. A. S. Dikici, F. E. Ustabasioglu, S. Delil, et al., "Evaluation of the Tibial Nerve With Shear-Wave Elastography: A Potential Sonographic Method for the Diagnosis of Diabetic Peripheral Neuropathy," *Radiology* 282, no. 2 (2017): 160135, https://doi.org/10.1148/radiol.2016160135.

18. T. C. Wee and N. G. Simon, "Ultrasound Elastography for the Evaluation of Peripheral Nerves: A Systematic Review," *Muscle & Nerve* 60, no. 5 (2019): 501-512, https://doi.org/10.1002/mus.26624.

19. B. G. Bober and S. B. Shah, "Paclitaxel Alters Sensory Nerve Biomechanical Properties," *Journal of Biomechanics* 48, no. 13 (2015): 3559-3567, https://doi.org/10.1016/j.jbiomech.2015.07.020.

20. B. E. Layton, A. M. Sastry, H. Wang, et al., "Differences Between Collagen Morphologies, Properties and Distribution in Diabetic and Normal Biobreeding and Sprague-Dawley Rat Sciatic Nerves," *Journal of Biomechanics* 37, no. 6 (2004): 879-888, https://doi.org/10.1016/j.jbiomech.2003.11.008.

21. Y. Zhu, Z. Jin, Y. Luo, et al., "Evaluation of the Crushed Sciatic Nerve and Denervated Muscle With Multimodality Ultrasound Techniques: An Animal Study," *Ultrasound in Medicine & Biology* 46, no. 2 (2020): 377-392, https://doi.org/10.1016/j.ultrasmedbio.2019.10.004.

22. M. Matsuda, S. Ikeda, S. Sakurai, A. Nezu, N. Yanagisawa, and T. Inuzuka, "Hypertrophic Neuritis due to Chronic Inflammatory Demyelinating Polyradiculoneuropathy (CIDP): A Postmortem Pathological Study," *Muscle & Nerve* 19, no. 2 (1996): 163-169.

23. R. J. Andrade, S. R. Freitas, F. Hug, et al., "The Potential Role of Sciatic Nerve Stiffness in the Limitation of Maximal Ankle Range of Motion," *Scientific Reports* 8, no. 1 (2018): 14532, https://doi.org/10.1038/s41598-018-32873-6.

24. C. L. Rugel, C. K. Franz, and S. S. M. Lee, "Influence of Limb Position on Assessment of Nerve Mechanical Properties by Using Shear Wave Ultrasound Elastography," *Muscle & Nerve* 61, no. 5 (2020): 616-622, https://doi.org/10.1002/mus.26842.

25. J. Greening and A. Dilley, "Posture-Induced Changes in Peripheral Nerve Stiffness Measured by Ultrasound Shear-Wave Elastography," *Muscle & Nerve* 55, no. 2 (2017): 213-222, https://doi.org/10.1002/mus.25245.

26. R. J. Andrade, A. Nordez, F. Hug, et al., "Non-invasive Assessment of Sciatic Nerve Stiffness During Human Ankle Motion Using Ultrasound Shear Wave Elastography," *Journal of Biomechanics* 49, no. 3 (2016): 326-331, https://doi.org/10.1016/j.jbiomech.2015.12.017.

27. R. J. Andrade, S. R. Freitas, F. Hug, M. W. Coppieters, E. SierralSilvestre, and A. Nordez, "Spatial Variation in Mechanical Properties Along the Sciatic and Tibial Nerves: An Ultrasound Shear Wave Elastography Study," *Journal of Biomechanics* 136 (2022): 111075, https://doi.org/10.1016/j.jbiomech.2022.111075.

28. T. Neto, J. Johannsson, and R. J. Andrade, "Using Ultrasound Shear Wave Elastography to Characterize Peripheral Nerve Mechanics: A Systematic Review on the Normative Reference Values in Healthy Individuals," *Ultrasonography* 43, no. 3 (2024): 169-178, https://doi.org/10.14366/usg.23211.

29. J. J. Manvell, N. Manvell, S. J. Snodgrass, and S. A. Reid, "Improving the Radial Nerve Neurodynamic Test: An Observation of Tension of the Radial, Median and Ulnar Nerves During Upper Limb Positioning," *Manual Therapy* 20, no. 6 (2015): 790-796, https://doi.org/10.1016/j.math.2015.03.007.

30. S. R. Freitas, R. J. Andrade, L. Larcoupaille, P. Mil-homens, and A. Nordez, "Muscle and Joint Responses During and After Static Stretching Performed at Different Intensities," *European Journal of Applied Physiology* 115, no. 6 (2015): 1263-1272, https://doi.org/10.1007/s00421-015-3104-1.

31. J. Brum, M. Bernal, J. L. Gennisson, and M. Tanter, "In Vivo Evaluation of the Elastic Anisotropy of the Human Achilles Tendon Using Shear Wave Dispersion Analysis," *Physics in Medicine and Biology* 59, no. 3 (2014): 505-523, https://doi.org/10.1088/0031-9155/59/3/505.

32. J. D. England, G. S. Gronseth, G. Franklin, et al., "Distal Symmetric Polyneuropathy: A Definition for Clinical Research: Report of the American Academy of Neurology, the American Association of Electrodiagnostic Medicine, and the American Academy of Physical Medicine and Rehabilitation," *Neurology* 64, no. 2 (2005): 199-207, https://doi.org/10.1212/01.WNL.0000149522.32823.EA.

33. M. E. Heroux, "Analyzing Dependent Data as if Independent Biases Effect Size Estimates and Increases the Risk of False-Positive Findings," *Journal of Applied Physiology* 130, no. 3 (2021): 675-676, https://doi.org/10.1152/japplphysiol.01024.2020.

34. X. Tang, B. Zhu, M. Tian, et al., "Preliminary Study on the Influencing Factors of Shear Wave Elastography for Peripheral Nerves in Healthy Population," *Scientific Reports* 11, no. 1 (2021): 5582, https://doi.org/10.1038/s41598-021-84900-8.

35. J. A. Tracy, P. J. Dyck, C. J. Klein, J. K. Engelstad, J. E. Meyer, and P. J. B. Dyck, "Onion-Bulb Patterns Predict Acquired or Inherited Demyelinating Polyneuropathy," *Muscle & Nerve* 59, no. 6 (2019): 665-670, https://doi.org/10.1002/mus.26452.

36. A. A. Carvalho, A. Vital, X. Ferrer, et al., "Charcot-Marie-Tooth Disease Type 1A: Clinicopathological Correlations in 24 Patients," *Journal of the Peripheral Nervous System* 10, no. 1 (2005): 85-92, https://doi.org/10.1111/j.1085-9489.2005.10112.x.

37. R. N. Auer, R. B. Bell, and M. A. Lee, "Neuropathy With Onion Bulb Formations and Pure Motor Manifestations," *Canadian Journal of Neurological Sciences* 16, no. 2 (1989): 194-197, https://doi.org/10.1017/s0317167100028894.

38. K. M. Krajewski, R. A. Lewis, and D. R. Fuerst, "Neurological Dysfunction and Axonal Degeneration in Charcot-Marie-Tooth Disease Type 1A," *Brain* 123, no. 7 (2000): 1516-1527, https://doi.org/10.1093/brain/123.7.1516.

39. A. J. Steck, "Anti-MAG Neuropathy: From Biology to Clinical Management," *Journal of Neuroimmunology* 361 (2021): 577725, https://doi.org/10.1016/j.jneuroim.2021.577725.

40. A. Grimm, B. Heiling, U. Schumacher, O. W. Witte, and H. Axer, "Ultrasound Differentiation of Axonal and Demyelinating Neuropathies," *Muscle & Nerve* 50, no. 6 (2014): 976-983, https://doi.org/10.1002/mus.24238.

41. T. Heimburg and A. D. Jackson, "On Soliton Propagation in Biomembranes and Nerves," *Proceedings of the National Academy of Sciences of the United States of America* 102, no. 28 (2005): 9790-9795, https://doi.org/10.1073/pnas.0503823102.

42. A. Jerusalem, Z. Al-Rekabi, H. Chen, et al., "Electrophysiological-Mechanical Coupling in the Neuronal Membrane and Its Role in Ultrasound Neuromodulation and General Anaesthesia," *Acta Biomaterialia* 97 (2019): 116-140, https://doi.org/10.1016/j.actbio.2019.07.041.

43. H. H. P. Ngo, R. J. Andrade, J. Lancelot, et al., "Unravelling Anisotropic Nonlinear Shear Elasticity in Muscles: Towards a Non-invasive Assessment of Stress in Living Organisms," *Journal of the Mechanical Behavior of Biomedical Materials* 150 (2024): 106325, https://doi.org/10.1016/j.jmbbm.2023.106325.

44. H. H. Ngo, R. Andrade, J. Brum, et al., "In Plane Quantification of In Vivo Muscle Elastic Anisotropy Factor by Steered Ultrasound Pushing Beams," *Physics in Medicine and Biology* 69, no. 4 (2024): 45013, https://doi.org/10.1088/1361-6560/ad21a0.

45. R. J. Andrade, A. Racapé, M. Hernández-Secorún, et al., "Simultaneous Measurement of Tensile and Shear Elasticity and Anisotropy in Human Skeletal Muscle Tissue Using Steered Ultrasound Shear Waves," *AMI: Acta Biomaterialia* 2025 (2025), https://doi.org/10.2139/ssrn.5109332.