Quantitative parameters of magnetic resonance imaging of the brachial plexus in healthy adults and associated signs: a pilot cross-sectional study

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BACKGROUND

Nervous system disorders are a common group of diseases, more than half of which are attributable to peripheral nervous system disorders [1, 2]. Of particular concern are peripheral polyneuropathies in the working-age population, which are associated with a high risk of disability due to delayed diagnosis and therapy initiation [3]. The diagnostic gold standard for peripheral nervous system disorders is stimulation and needle electromyoneurography [4]. However, this method has several limitations, including operator dependence, low sensitivity in long-standing peripheral polyneuropathy with distal nerve atrophy, and the inability to assess surrounding neural and non-neural structures [4]. Ultrasonography is another widely used technique for diagnosing peripheral polyneuropathies. However, its application is limited by the depth of neural structures, inability to determine the primary type of nerve fiber damage, and operator dependence [5]. All of the above complicates the diagnosis of lesions affecting the proximal segments of the peripheral nervous system, particularly the brachial plexus [6].

Magnetic resonance imaging (MRI) is increasingly being used in the diagnosis of brachial plexus disorders, including traumatic injuries, neoplasms, compression syndromes, and peripheral polyneuropathies [7]. Its findings are incorporated as supportive diagnostic criteria for chronic inflammatory demyelinating polyneuropathy and multifocal motor neuropathy [8, 9]. However, abnormalities detected on conventional neurography sequences—such as increased nerve signal intensity on fluid-sensitive fat-suppressed sequences (STIR¹ T2 FatSat², T2 Dixon³) and thickening of plexus elements—are generally nonspecific and, in our experience, do not allow reliable differentiation among polyneuropathy subtypes. Moreover, in cases of bilateral symmetric involvement, even distinguishing abnormal changes from normal anatomy may be challenging. This limitation is primarily attributable to the anatomical variability of the brachial plexus in healthy individuals [10]. Furthermore, although a coronal diameter of 5 mm is commonly accepted as the threshold value for thickening of the anterior rami of spinal nerves [11], their thickness varies depending on the spinal level [12], further complicating objective assessment. Signal intensity on conventional MRI sequences is a relative measure and cannot be used for quantitative evaluation of the presence or severity of abnormal changes. Consequently, diagnostic accuracy in brachial plexus abnormalities, particularly in polyneuropathies and some other disorders, largely depends on the experience of the interpreting radiologist [13]. In this context, quantitative MRI techniques (specifically, T2 relaxometry and magnetization transfer imaging) appear promising for the assessment of the brachial plexus, as these methods provide absolute numerical parameters reflecting the macromolecular tissue structure. Their diagnostic utility has been demonstrated in studies of the brain [14, 15].

T2 relaxometry quantifies tissue relaxation properties, including the measured T2 relaxation time (T2app) and proton density (ρ). An increase in T2app is primarily associated with an increase in free protons, which may occur in endoneurial edema secondary to axonal injury [7], whereas the ρ parameter correlates with extracellular matrix microstructural alterations resulting from inflammatory changes and demyelination [16]. These parameters are therefore promising for determining the primary type of nerve fiber damage, which is essential for early diagnosis and timely initiation of treatment.

Magnetization transfer imaging is based on molecular exchange between the pools of bound and free water in tissues. During presaturation (the application of a preparatory off-resonance radiofrequency pulse to selectively suppress the bound water pool), the magnetization vector of free water is also reduced, which constitutes the magnetization transfer phenomenon [17]. In human tissues, this effect can be quantified using the magnetization transfer ratio (MTR); damage to the macromolecular pool of any origin leads to a decrease in this index [17]. Thus, in our view, MTR alone is unlikely to be sufficient for determining the primary type of nerve injury. However, it may be interpreted in combination with T2 relaxometry parameters to assess the presence and severity of tissue damage.

Studies of T2 relaxometry in the proximal elements of the brachial plexus have been reported only sporadically [18, 19], whereas investigations of MTR in the anterior rami of the spinal nerves forming the brachial plexus in healthy individuals, as well as comprehensive evaluation of these parameters, have not been previously performed. There are no standard MRI sequences for obtaining these data, and data processing algorithms remain undefined. Considering the substantial number of patients with peripheral nervous system disorders, particularly polyneuropathies [3], an additional tool for evaluating the brachial plexus appears promising for improving the accuracy and speed of primary and differential diagnosis of these conditions. Moreover, the relationship between quantitative MRI parameters of the brachial plexus and demographic variables (sex, age) as well as anthropometric characteristics (height, body weight, body mass index, nerve thickness) remains insufficiently studied. These parameters may vary considerably among patients with the same peripheral nervous system disorder (including the same polyneuropathy). Therefore, for a more objective interpretation of quantitative MRI measurements of the brachial plexus, it is relevant to investigate their associations with demographic and anthropometric factors.

AIM

To investigate the parameters of quantitative MRI of the brachial plexus elements in relation to laterality and level of spinal nerves and demographic and anthropometric characteristics in healthy adults.

METHODS

Study Design

A single-center, prospective, cross-sectional, non-comparative pilot study was conducted.

Study Setting

The study included individuals examined in the Department of Radiology of the Russian Center of Neurology and Neurosciences (Moscow) between April and September 2023.

Eligibility Criteria

Inclusion criteria:

• Age over 18 years;
• No clinical signs of brachial plexus involvement (pain or weakness in the upper limb and shoulder girdle);
• No history of brachial plexus abnormalities.

Non-inclusion criteria:

• Confirmed central nervous system disorders (including demyelinating, neoplastic, or neurodegenerative diseases);
• Absolute contraindications to MRI (MRI-incompatible hardware, cardiac pacemaker, non-removable hearing aid, etc.).

Exclusion criteria:

• Refusal to undergo MRI for any reason (e.g., claustrophobia);
• Considerable motion artifacts during image acquisition.

Magnetic Resonance Imaging Protocol

MRI was performed using a Magnetom Prisma® scanner (Siemens, Germany) with a magnetic field strength of 3.0 T. The scanning protocol included standard three-dimensional T2-weighted sequences (parameters: repetition time [TR] = 1500 ms; echo time [TE] = 135 ms; reconstructed voxel size = 0.4 × 0.4 × 0.8 mm; field of view [FOV] = 250 mm; number of slices = 192; acquisition time = 6 min 56 s), STIR¹ (parameters: TR = 3000 ms; TE = 281 ms; inversion time [TI] = 230 ms; reconstructed voxel size = 0.4 × 0.4 × 0.9 mm; FOV = 350 mm; number of slices = 144; acquisition time = 7 min 27 s), and coronal T1-weighted imaging (parameters: TR = 5.52 ms; TE₁ = 2.46 ms; TE₂ = 3.69 ms; voxel size = 1 × 1 × 1 mm; FOV = 380 mm; number of slices = 144; acquisition time = 5 min 58 s).

Given that no standard sequences are available for T2 relaxometry and magnetization transfer imaging, and considering the required temporal parameters (TR, TE) [20, 21], contrast parameters (fat suppression, presaturation pulse), and slice geometry (in-plane resolution, slice thickness) [6], the remaining parameters were optimized empirically through repeated scanning to achieve an optimal signal-to-noise ratio. The final axial acquisition parameters for the brachial plexus were as follows:

• T2 relaxometry (dual-echo T2 sequence): TR = 5570 ms; TE₁ = 9.1 ms; TE₂ = 72 ms; voxel size = 0.3 × 0.3 × 3 mm; number of slices = 45; interslice gap = 10%; frequency-selective fat suppression (FatSat) applied; acquisition time = 10 min 09 s;
• magnetization transfer imaging, T1 MT-on: TR = 33 ms; TE = 7 ms, with the addition of an off-resonance presaturation pulse; flip angle = 10°; voxel size = 0.3 × 0.3 × 3 mm; number of slices = 45; interslice gap = 10%; acquisition time = 4 min 51 s. T1 MT-off: identical parameters without the off-resonance presaturation pulse.

During scanning, a 64-channel combined head-and-neck radiofrequency coil was used in combination with a flexible 18-channel body coil positioned over the shoulder girdle and extended beneath the cervical coil as far as anatomically feasible.

Image Processing and Analysis

Image processing for quantitative MRI parameter assessment was performed using the MATLAB software package (MathWorks, United States), with a processing algorithm that included the following steps:

• Import of MRI findings in the Digital Imaging and Communications in Medicine (DICOM) format;
• Data conversion to the Neuroimaging Informatics Technology Initiative (NIfTI) format;
• Coregistration of the three imported sequences (T2dualecho, T1 MT-off, T1 MT-on);
• Calculation and generation of T2app, ρ, and MTR maps;
• Storage of the resulting data in the NIfTI format for subsequent export.

Parametric maps were calculated using the following formulas [20, 22]:

$T2app=\frac{T{E}_2-T{E}_1}{\ln \left(S\left(T{E}_1\right)/S\left(T{E}_2\right)\right)}$, (1)

where T2app is the measured T2 relaxation time; TE₁ and TE₂ are echo times; S(TE₁) and S(TE₂) are the signal intensities at echo times TE₁ and TE₂, respectively;

$\rho =\frac{S\left(T{E}_1\right)}{\exp \left(-T{E}_1/T2app\right)}$, (2)

where ρ is the proton density; TE₁ is echo time; S(TE₁) is the signal intensity at echo time TE₁;

$\rho =MTR=\frac{\left(S_0-S_1\right)}{S_0}\times 100$, (3)

where MTR is the magnetization transfer ratio; S₀ is the signal before magnetization transfer; S₁ is the signal after magnetization transfer.

The generated maps were imported into ITK-SNAP® (University of Pennsylvania, USA)⁴ for visualization. Using axial T2dualecho images as the anatomical reference with three-dimensional reconstruction to facilitate anatomical localization, a radiologist with 16 years of experience (including four years in peripheral nervous system imaging) manually delineated regions of interest within the anterior rami of the spinal nerves, from the fifth cervical (C5) to the first thoracic (T1) spinal nerves, 1–2 cm from the spinal ganglion (see Fig. 1). The extracted values were recorded for subsequent analysis. When the coefficient of variation (standard deviation) exceeded 30%, the measurement was considered unreliable and was excluded. Consequently, some data from the anterior rami of the T1 spinal nerves were excluded because their proximity to the lung apices and vascular structures made them particularly susceptible to artifacts caused by nonuniform fat suppression, vascular pulsation, and respiratory motion [6]. The thickness of the anterior rami from C5 to T1 was measured on standard three-dimensional STIR¹ images perpendicular to the corresponding nerve element, 1–2 cm from the spinal ganglion.

 

Fig. 1. Measurement of quantitative magnetic resonance imaging parameters (T2app, ρ, MTR) of the anterior rami of the C7 spinal nerves on both sides in a healthy 42-year-old male. Visualization was performed using ITK-SNAP® (University of Pennsylvania, USA). ρ, proton density; MTR, magnetization transfer ratio; T2app, measured T2 relaxation time.

 

Study Outcomes

The numerical values of T2app, ρ, and MTR were determined in the anterior rami of the spinal nerves forming the brachial plexus. Furthermore, the thickness of the anterior rami of the spinal nerves forming the brachial plexus was measured bilaterally. Associations between the quantitative MRI parameters and demographic (sex, age) and anthropometric variables (body weight, height, body mass index) were evaluated. The latter were recorded immediately before the MRI examination.

Ethics Approval

The study protocol was approved by the local Ethics Committee of the Russian Center of Neurology and Neurosciences (Minutes No. 1-3/22 of January 19, 2022). All potential participants provided written informed consent prior to enrollment.

Statistical Analysis

Sample size calculation: The samples size was not calculated previously. It was determined arbitrarily, given that it was a pilot study.

Statistical methods: Data analysis was performed using SPSS Statistics®, version 27 (IBM, USA). The distribution of quantitative variables (MRI parameters) was assessed using the Shapiro–Wilk test and visual inspection of histograms. For normally distributed data, the values are presented as M ± SD, where M is the mean and SD is the standard deviation. Given that demographic and anthropometric characteristics were measured once per participant, whereas MRI parameters were measured repeatedly (at different sides and spinal levels), generalized linear mixed models were applied to evaluate associations. The association between MRI parameters and the side of measurement was assessed separately for each spinal level using a paired t-test. The association between MRI parameters and the spinal level of measurement was assessed separately for each side using repeated measures analysis of variance (ANOVA). For MRI parameters that demonstrated associations with the investigated characteristics, multivariable analysis was performed using generalized linear mixed models, considering that demographic and anthropometric characteristics were assessed once per participant, whereas MRI parameters were measured repeatedly across each side and level. Differences and associations were considered significant at p <  0.05.

RESULTS

Study Participants

Twelve individuals were examined for inclusion in the study; one was excluded because of intermittent upper limb pain. Eleven participants provided written informed consent; one participant was subsequently withdrawn due to discomfort associated with prolonged positioning inside the MRI scanner. In total, 10 participants (6 men and 4 women) completed the study. The age ranged from 24 to 76 years (mean 43 years). The height ranged from 1.60 to 1.90 m (mean 1.73 m), body weight from 55 to 92 kg (mean 72 kg), and body mass index from 19.8 to 31.1 kg/m² (mean 24 kg/m²). Demographic and anthropometric characteristics of the healthy volunteers are presented in Table 1.

 

Table 1. Demographic and anthropometric characteristics of healthy volunteers
Participant	Sex	Age, years	Height, m	Body weight, kg	Body mass index, kg/m2
№ 1	Male	44	1.80	68	21.0
№ 2	Male	39	1.72	78	26.4
№ 3	Female	40	1.62	62	23.6
№ 4	Male	41	1.90	75	20.8
№ 5	Female	26	1.68	56	19.8
№ 6	Male	66	1.72	92	31.1
№ 7	Female	37	1.60	55	21.5
№ 8	Female	24	1.78	85	26.8
№ 9	Male	76	1.67	71	25.5
№ 10	Male	35	1.85	80	23.4

 

Primary Results

Given that the quantitative MRI parameters had a normal distribution (based on visual inspection of histograms and the Shapiro–Wilk test [p >  0.05]), they were described using the mean and standard deviation; the range of values was also reported (see Table 2).

 

Table 2. Descriptive statistics of quantitative magnetic resonance imaging parameters at different sides and levels
Measurement side	Measured T2 relaxation time, ms	Proton density	Magnetization transfer ratio	Thickness, mm
C5 spinal nerve, anterior ramus
Right	122.06 ± 27.51 (94.06–172.71)	457.38 ± 62.50 (379.63–602.57)	38.16 ± 6.03 (30.70–48.90)	3.24 ± 0.67 (2.38–4.60)
Left	119.94 ± 22.68 (89.83–171.97)	473.98 ± 76.77 (347.24–608.03)	39.74 ± 8.02 (31.46–58.37)	3.18 ± 0.71 (2.25–4.76)
C6 spinal nerve, anterior ramus
Right	134.65 ± 41.98 (100.22–234.73)	447.55 ± 49.04 (369.52–527.61)	41.04 ± 6.99 (29.90–48.33)	4.41 ± 0.43 (3.78–4.95)
Left	130.77 ± 29.60 (94.64–183.36)	445.60 ± 65.23 (333.53–550.69)	34.19 ± 6.76 (24.70–43.85)	4.22 ± 0.50 (3.18–4.84)
C7 spinal nerve, anterior ramus
Right	132.72 ± 32.49 (85.59–198.50)	457.64 ± 60.91 (362.77–557.97)	36.78 ± 7.25 (23.39–49.07)	4.86 ± 0.46 (3.88–5.45)
Left	150.25 ± 42.92 (105.40–263.71)	434.56 ± 59.23 (325.94–525.15)	33.30 ± 2.53 (29.26–36.62)	4.97 ± 0.49 (4.12–5.65)
C8 spinal nerve, anterior ramus
Right	141.05 ± 23.11 (101.41–185.02)	477.16 ± 66.89 (342.14–560.16)	39.31 ± 6.25 (31.20–48.85)	4.34 ± 0.39 (3.85–5.06)
Left	131.86 ± 16.62 (103.11–153.18)	449.33 ± 57.16 (346.74–550.05)	38.33 ± 5.76 (27.26–45.81)	4.26 ± 0.41 (3.68–5.04)
Th1 spinal nerve, anterior ramus
Right	147.06 ± 21.04 (121.16–172.80)	511.84 ± 80.90 (386.88–609.44)	38.11 ± 0.70 (37.25–38.73)	3.39 ± 0.61 (2.60–4.52)
Left	163.59 ± 20.20 (133.40–191.02)	471.69 ± 70.03 (366.00–579.58)	32.73 ± 6.37 (28.32–40.04)	3.59 ± 0.53 (2.82–4.36)
Note. Results are presented as M ± SD, where M is the arithmetic mean and SD is the standard deviation. Values in parentheses represent the minimum and maximum values.

 

An analysis of the associations between quantitative MRI parameters and anthropometric and demographic characteristics (see Table 3) revealed a significant relationship between T2app and age: with increasing age, T2app increased (regression coefficient B 1.062, 95% confidence interval [CI] 0.370–1.754; p = 0.003), and between T2app and height: with increasing height, T2app decreased (B −139.742, 95% CI −277.161 to −2.323; p = 0.046). Furthermore, there was a significant association between ρ and height: with increasing height, ρ decreased (B −433.907, 95% CI −613.204 to −254.611; p <  0.001). No significant associations were found between MTR or nerve thickness and the demographic or anthropometric characteristics.

 

Table 3. Correlations between quantitative magnetic resonance imaging parameters and anthropometric and demographic characteristics
Association with		Measured T2 relaxation time, ms	Proton density	Magnetization transfer ratio	Thickness, mm
Sex		р = 0.744	р = 0.332	р = 0.498	р = 0.293
Age		р = 0.003	р = 0.301	р = 0.908	р = 0.437
Height		р = 0.046	р <  0.001	р = 0.940	р = 0.466
Body weight		р = 0.698	р = 0.276	р = 0.845	р = 0.553
Body mass index		р = 0.409	р = 0.564	р = 0.835	р = 0.862
Level	C5	р = 0.798	р = 0.232	р = 0.691	р = 0.612
	C6	р = 0.535	р = 0.143	р = 0.171	р = 0.129
	C7	р = 0.078	р = 0.078	р = 0.270	р = 0.431
	C8	р = 0.204	р < 0.001	р = 0.986	р = 0.540
	Th1	р = 0.179	р = 0.076	р = 0.611	р = 0.127
Side	Right	р = 0.496	р = 0.401	р = 0.451	р <  0.001
	Left	р = 0.002	р = 0.525	р = 0.540	p <  0.001
Note. C5–C8, anterior rami of the C5–C8 cervical spinal nerves; Th1, anterior ramus of the first thoracic spinal nerve.

 

When evaluating the associations between quantitative MRI parameters and the side of measurement (see Table 3), significant right–left differences were detected for ρ at the level of the anterior rami of the eighth cervical (C8) spinal nerves, with higher values on the right than on the left (477.16 ± 66.89 vs. 449.33 ± 57.16, mean difference [MD] 27.83, 95% CI 15.57–40.09; p <  0.001). No significant associations were found between T2app, MTR, or thickness and the side of measurement at any level.

An analysis of the associations between quantitative MRI parameters and the level of measurement (see Table 3) demonstrated a significant relationship between the level and the thickness of the anterior rami on both the right and left sides (p <  0.001 for both; see Table 2). Moreover, post hoc pairwise comparisons between levels were performed (with Bonferroni correction for multiple comparisons). They showed that, on the right side, significant differences in the thickness of the anterior rami were observed between C5 and C6 spinal nerves (adjusted significance level [padj] 0.001), C5 and C7 (padj 0.001), C5 and C8 (padj 0.007), and C7 and C8 (padj 0.020), as well as between Th1 and C6 spinal nerves (padj < 0.001), Th1 and C7 (padj < 0.001), and Th1 and C8 (padj 0.001). On the left side, significant differences were observed between C5 and C6 spinal nerves (padj 0.003), C5 and C7 (padj < 0.001), C5 and C8 (padj 0.010), C6 and C7 (padj 0.009), and C7 and C8 (padj 0.030), as well as between Th1 and C7 spinal nerves (padj < 0.001) and Th1 and C8 (padj 0.003). Thus, a gradient in the thickness of the anterior rami of the spinal nerves forming the brachial plexus was identified, with maximum thickness at the level of the anterior rami of the C7 spinal nerves bilaterally, with an increase from C5 to C7, followed by a progressive decrease at the C8 and Th1 levels.

Furthermore, there was a significant association between the level and T2app on the left side (p = 0.002; see Table 2), with the lowest values at the level of the C5 spinal nerve. Post hoc pairwise comparisons showed significant differences between the C5 and C7 levels (padj 0.030) and between the C5 and Th1 spinal nerves (padj 0.010). No significant associations between ρ or MTR and the measurement level were identified on either side.

Thus, no significant associations of MTR with demographic or anthropometric characteristics, nor with measurement level or side, were found. For the thickness of the anterior rami, a significant association was detected only with one of the studied parameters—the measurement level. Therefore, a multivariable analysis of MRI quantitative parameters was not performed.

In contrast, for the other MRI parameters, significant associations were identified with several of the investigated characteristics: with height and measurement side for ρ and with age, height, and measurement level for T2app. This justified a multivariable analysis to assess the combined effects of all characteristics associated with these quantitative MRI parameters. The quantitative MRI parameter under investigation (ρ or T2app) was used as the dependent variable, and all variables that demonstrated significant associations with it were included as fixed factors.

According to the multivariable analysis, even after adjustment for measurement side, the significant effect of height on ρ was preserved. Lower ρ values were observed in taller participants (B −434.348 [95% CI −611.546 to −257.150]; p <  0.001). The effect of measurement side in this model was not significant (p = 0.157).

Furthermore, based on the multivariable analysis, even after adjustment for measurement level, significant effects of both height and age on T2app were preserved. T2app values were lower in younger participants (B 0.908 [95% CI 0.343–1.474]; p = 0.002) and in taller participants (B −111.767 [95% CI −205.520 to −18.013]; p = 0.020). The effect of measurement level in this model also remained significant (p = 0.001).

Thus, the results suggest an influence of age and height on T2app, as well as an influence of height on ρ.

DISCUSSION

Summary of Primary Results

This work is the first comprehensive pilot study on T2 relaxometry and MTR parameters in elements of the brachial plexus and their associations with demographic and anthropometric characteristics. The analysis revealed associations of T2app with age and height and of ρ with height. The most important finding of this study is the observed direct association between T2app and age.

Discussion of Primary Results

According to the scientific data search, studies on T2 mapping of the brachial plexus are scarce [18, 19], with healthy volunteer groups consisting of 10 and 5 participants, respectively. Rosmalen et al. [18] also conducted a correlation analysis and identified an association of these parameters with age, which is consistent with our findings. The findings of studies on T2app of brain tissue likewise align with our data. Specifically, an increase in T2app with age has been reported in multiple brain regions, except for the putamen and ventral pons [23]. Moreover, T2app increases with the amount of free water, which occurs naturally when axonal density decreases and the myelin sheath thins with age. This, in turn, leads to a decrease in macromolecular content and an increase in free water, as well as a reduction in their mutual interactions [24]. Kumar et al. [23] demonstrated sex-related differences in brain T2app, which the authors attributed to differential deposition of paramagnetic substances in participants of different sexes. No such differences were observed in the present study, which may be attributed both to the absence of paramagnetic substance deposition in peripheral nerves under normal conditions and to the small number of examined volunteers.

The observed inverse associations of T2app and ρ with height are unlikely to have a true biological basis; therefore, the identified trends require further investigation in larger cohorts.

In a study of peripheral nerves of the limbs (sciatic, tibial, median, radial, and ulnar nerves), an analysis of the relationships between T2 relaxometry parameters and age, height, body weight, and body mass index [25] revealed no significant associations of T2app with these variables when all nerves were analyzed collectively. However, ρ demonstrated an inverse correlation with body weight and body mass index, whereas in our study it was not significant, likely due to the smaller sample size, requiring validation in larger populations. In nerve-specific analyses, a significant inverse correlation between ρ and age was observed only at the sciatic nerve level [25], which is inconsistent with our findings and may be attributable to differences in imaging sequences, measurement locations, or random error, as this was the only significant association among the entire series of observations.

In the anterior rami at the C5 spinal nerve level on the left, T2app differed from the corresponding values at the other levels. True anatomical and morphological differences among the anterior rami of the spinal nerves appear unlikely. It is possible that the magic angle effect, which causes the T2 signal to increase when a structure makes a more acute angle relative to the magnetic field lines, is at work in this case, which may indeed occur in the anterior rami of the C5 spinal nerves. Similar correlations between nerve orientation and T2app were described by Campbell et al. [26] in their study of upper limb nerves. In the present study, no dedicated assessment of the deviation angle of the anterior rami relative to the B₀ magnetic field lines was performed, warranting further investigation.

The absence of significant associations between MTR and demographic or anthropometric parameters in the present study is consistent with the findings of J. Kollmer et al. [27], who likewise reported no differences in MTR depending on the measurement level and no associations with sex, body weight, height, or body mass index in the nerves of the lower extremities. However, when MTR values of the sciatic and tibial nerves were pooled across all measurement levels, significant differences were observed between older and younger participants. Nevertheless, when these groups were compared separately by location, the differences were not significant [27]. Thus, the data obtained for peripheral nerves of the lower extremities fully align with our findings.

The identified thickness gradient of the anterior rami forming the brachial plexus confirms previously reported anatomical and surgical data [10, 12], although such measurements have not previously been obtained using MRI. The discovery that the anterior ramus of the C7 spinal nerve has the greatest thickness looks plausible, given that it independently forms a separate trunk; its width exceeded 5 mm in some participants. In our opinion, these findings—specifically, the presence or absence of nerve element thickness gradients—should be considered when evaluating the brachial plexus in patients.

Study Limitations

The main limitation of this study is the small sample size (n = 10), which is primarily related to its pilot nature. One limitation of the analysis is the potentially low statistical power resulting from the small sample size and the low sensitivity of complex methods. Therefore, the findings require further validation in larger cohorts before they can be applied in patients with brachial plexus abnormalities.

CONCLUSION

The findings indicate that age and height must be considered in future studies of quantitative MRI parameters in both healthy individuals and patients with various brachial plexus abnormalities. Furthermore, when measuring the thickness of the anterior rami of the brachial plexus using standard MRI sequences, it is advisable to consider not only the absolute size of the nerve elements but also to assess the preservation of their thickness gradient.

ADDITIONAL INFORMATION

Author contributions: S.N. Morozova: conceptualization, investigation, data curation, visualization, writing—original draft; V.V. Sinkova: investigation; V.A. Orlov, S.I. Kartashov: software, data curation; S.S. Khanina, A.A. Poyda: software, data curation, validation; D.A. Grishina: investigation, writing—review & editing; N.A. Suponeva, M.V. Krotenkova: writing—review & editing, supervision, project administration. All the authors approved the version of the manuscript to be published and agreed to be accountable for all aspects of the work, ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Ethics approval: The study protocol was approved by the local Ethics Committee of the Russian Center of Neurology and Neurosciences (Minutes No. 1-3/22, dated January 19, 2022). All eligible participants provided written informed consent to participate in the study.

Funding sources: The definition of the aim and development of the study design, examination of healthy volunteers, distribution of neuroimaging data, labeling of processed images and recording of parameters, statistical processing of the obtained quantitative data were carried out within the framework of the state assignment of the Federal State Budgetary Scientific Institution "Russian Center for Neurology and Neurosciences" on the topic "Recovery and adaptation of patients with damage to the nervous system: modern possibilities for studying mechanisms, practice-oriented approaches" (EGISU: No. 122041800162-9). The development of a data processing algorithm and a program for obtaining quantitative MRI parameters, and the processing of experimental neuroimaging data were carried out within the framework of the state assignment of the National Research Center "Kurchatov Institute" on the topic "Fundamental interdisciplinary research in the field of creating nature-like technologies" (EGISU: 123061500011-0).

Disclosure of interests: The authors have no relationships, activities, or interests for the last three years related to for-profit or not-for-profit third parties whose interests may be affected by the content of the article.

Statement of originality: No previously obtained or published material (text, images, or data) was used in this study or article.

Data availability statement: The editorial policy regarding data sharing does not apply to this work.

Generative AI: No generative artificial intelligence technologies were used to prepare this article.

Provenance and peer-review: This article was submitted unsolicited and reviewed following the standard procedure. The peer review process involved two external reviewers and a member of the Editorial Board.

 

¹ Short TI inversion recovery (STIR) is a magnetic resonance imaging sequence with fat signal suppression achieved by applying an inversion pulse with a short inversion time.

² T2-weighted with fat saturation (T2 FatSat) is a T2-weighted sequence with fat signal suppression using frequency-selective saturation.

³ T2-weighted Dixon method (T2 Dixon) is a technique based on the difference in resonance frequency between water and fat.

⁴ ITK-SNAP visualization software [Internet]. In: ITK-SNAP, 2020–2024. Available at: https://www.itksnap.org. Accessed on: June 14, 2024.

About the authors

Sofya N. Morozova

Russian Center of Neurology and Neurosciences

Author for correspondence.
Email: morozova@neurology.ru
ORCID iD: 0000-0002-9093-344X
SPIN-code: 2434-7827

MD, Cand. Sci. (Medicine)

Russian Federation, Moscow

Viktoriya V. Sinkova

Russian Center of Neurology and Neurosciences

Email: 000564321@mail.ru
ORCID iD: 0000-0003-2285-2725
SPIN-code: 2949-2821

MD

Russian Federation, Moscow

Vyacheslav A. Orlov

National Research Center “Kurchatov Institute”

Email: orlov_va@nrcki.ru
ORCID iD: 0000-0002-4840-4499
SPIN-code: 5167-6342

Cand. Sci. (Physics and Mathematics)

Russian Federation, Moscow

Sergey I. Kartashov

National Research Center “Kurchatov Institute”

Email: mail@kartashovs.ru
ORCID iD: 0000-0002-0181-3391
SPIN-code: 1508-9120
Russian Federation, Moscow

Alexey A. Poyda

National Research Center “Kurchatov Institute”

Email: Poyda_AA@nrcki.ru
ORCID iD: 0000-0002-7660-6215
SPIN-code: 6870-2764

Cand. Sci. (Physics and Mathematics)

Russian Federation, Moscow

Sandaara S. Khanina

Moscow Institute of Physics and Technology

Email: sandaara.khan@mail.ru
ORCID iD: 0009-0002-7136-3434
SPIN-code: 2452-3210
Russian Federation, Dolgoprudny

Darya A. Grishina

Russian Center of Neurology and Neurosciences

Email: dgrishina82@gmail.com
ORCID iD: 0000-0002-7924-3405
SPIN-code: 6577-1799

MD, Dr. Sci. (Medicine)

Russian Federation, Moscow

Natalia A. Suponeva

Russian Center of Neurology and Neurosciences

Email: nasu2709@mail.ru
ORCID iD: 0000-0003-3956-6362
SPIN-code: 3223-6006

MD, Dr. Sci. (Medicine), Professor, Corresponding member of the Russian Academy of Sciences

Russian Federation, Moscow

Marina V. Krotenkova

Russian Center of Neurology and Neurosciences

Email: krotenkova_mrt@mail.ru
ORCID iD: 0000-0003-3820-4554
SPIN-code: 9663-8828

MD, Dr. Sci. (Medicine)

Russian Federation, Moscow

References

Supplementary files