The Association of Vascular Health With Cervical Paraspinal Muscle Atrophy and Disc Degeneration

Abstract

Study Design

Retrospective cross-sectional.

Objective

Degeneration of paraspinal muscles and intervertebral discs has been associated with adverse outcomes. While vascular influences on lumbar degeneration are known, cervical associations remain unclear. The objective is to evaluate the relationship between carotid artery stenosis (CAS) and cervical paraspinal muscle atrophy as well as its association with intervertebral disc integrity.

Methods

Patients undergoing primary cervical spine surgery (2009-2018) with cervical MRI and CTA ≤12 months apart were included. MRIs from C3-C7 quantified fatty infiltration (FI) and functional cross-sectional area (fCSA) in sternocleidomastoid (SCM), anterior group (AG), scalenus (SN), posteromedial (PM), posterolateral (PL), and trapezius (TP) groups. Disc degeneration was evaluated using the Disc Signal Intensity score. Maximum and mean CAS were measured on CTA.

Results

Sixty-five patients were included. In multivariable linear regression models, higher mean stenosis was significantly associated with increased FI in multiple muscle groups at C3, as well as the PM at C4 and SCM at C5 (P < 0.05), and with reduced fCSA in the PM and SCM at C4 (P < 0.05). Higher maximum stenosis was associated with increased FI in the SCM and TP at C3 and the PL at C4, along with reduced fCSA in the SCM at C4 (P < 0.05). No significant associations were observed with disc degeneration.

Conclusion

CAS was associated with cervical muscle atrophy, suggesting a potential link with vascular health. In contrast, disc degeneration showed no association with CAS, suggesting that muscle atrophy and disc degeneration may follow distinct pathways.

Keywords

carotid artery stenosis disc signal intensity cervical paraspinal muscle fat infiltration muscle atrophy

Introduction

Vascular health has increasingly been recognized as a key determinant of musculoskeletal integrity and spine function. Progressive arterial stiffening and atherosclerotic burden impair tissue perfusion and metabolic exchange, contributing to degenerative changes across multiple organ systems.^1-3 In the spine, degeneration of the paraspinal muscles, typically manifested as fatty infiltration (FI) and loss of functional cross-sectional area (fCSA),⁴ plays a key role in structural instability, chronic pain, disc degeneration and postoperative outcomes.^5-8

While the interplay between vascular disease and spinal degeneration has been explored in the lumbar region, particularly through associations between abdominal aortic calcification (AAC) and muscle atrophy,⁹ the cervical spine is largely uninvestigated. Cervical paraspinal muscles differ substantially in size, composition, and vascular supply, which may make them more susceptible to subtle vascular compromise, particularly in the presence of systemic vascular disease.^10-12 Previous research has linked cervical muscle quality to bone density, sagittal alignment, and surgical outcomes, yet the influence of vascular health remains unclear.^13-16

Computed tomography angiography (CTA) can reliably quantify carotid artery stenosis (CAS), a widely accepted marker of systemic atherosclerosis.^1,17-20 Because carotid arteries share regional and functional proximity to cervical musculature, CAS may serve as a useful surrogate marker of regional and systemic vascular health rather than a direct measure of muscle perfusion.^2,21,22 Using semi-automated CTA analysis combined with MRI-based muscle evaluation, this study investigates the association between CAS and cervical muscle composition across multiple levels (C3-C7) and muscle groups.

Beyond muscle degeneration, intervertebral disc health also plays a crucial role in cervical spine function.^23,24 Disc degeneration is a multifactorial process influenced by aging, mechanical loading, and systemic comorbidities, leading to progressive loss of hydration, proteoglycans, and endplate permeability.^25-27 To quantify disc integrity more objectively, the Disc Signal Intensity (DSI2) index was introduced as a validated MRI-based metric that normalizes the disc signal to cerebrospinal fluid, improving sensitivity over traditional qualitative systems such as the Pfirrmann grade.^28,29 This metric has shown a strong linear correlation with Pfirrmann grading and can detect early degenerative changes that might otherwise be overlooked by categorical systems.²⁸

By incorporating DSI2 with muscle parameters, this study examines whether vascular health contributes to intervertebral disc changes. Although discs are avascular and rely primarily on diffusion through the vertebral endplates, systemic vascular compromise can still influence disc degeneration indirectly through altered nutrient supply and metabolic dysregulation.^26,27,30,31 We hypothesize that CAS has stronger associations with muscle degeneration than with disc integrity, as disc degeneration is governed by more complex, multifactorial mechanisms that extend beyond vascular insufficiency alone.

Material and Methods

Study Design and Patient Population

This study was approved by our hospital’s institutional review board. Informed consent was waived by the IRB because of the retrospective nature of the study. This study follows the ethical principles of the Helsinki Declaration. We retrospectively reviewed preoperative cervical spine CTA studies performed at a single academic spine care institution from 2009 to 2018. All CTA examinations were obtained for clinical preoperative evaluation and were not performed for research purposes; imaging data were retrospectively analyzed for this study. The study included patients who had pre-operative cervical MRI and CTA obtained less than 1 year apart. We excluded patients: (1) with poor quality MRIs, (2) with poor quality CTAs, and (3) who were under the age of 18. Demographic information such as age, sex, and body mass index (BMI) was collected.

Muscle Measurements

Muscle measurements were conducted on T2-weighted axial MRIs, with the mid-vertebral body level designated as the measurement level from C3 to C7. This level was selected to optimize reproducibility, avoid disc and endplate signal contamination, and maintain consistency with prior cervical muscle morphometry studies. Muscles were categorized into 6 bilateral functional groups: (1) the sternocleidomastoid group (SCM), (2) the anterior group (longus colli and longus capitis), (3) the posteromedial group (PM) (including multifidus and rotatores), (4) the posterolateral group (PL) (spinalis cervicis, interspinalis cervicis, semispinalis capitis, levator scapulae, longissimus capitis, longissimus cervicis, spinalis capitis, splenius capitis, splenius cervicis, and semispinalis cervicis), (5) scalenus group (SN) and (6) the trapezius group (TP). Segmentation was performed using ITK-SNAP version 3.8.0 (Figure 1). Previously established and validated Matlab-based software was used to quantify muscle composition within each region of interest (ROI)^32-34 (Figure 2). The software calculated areas above and below a pixel intensity threshold, identifying muscle as functional cross-sectional area (fCSA) and fat as intramuscular fat (FAT). Total cross-sectional area (CSA) was defined as the sum of fCSA and FAT, and fatty infiltration (FI) was calculated as the ratio of FAT to CSA. Both software tools have been previously validated for cervical muscle assessment and demonstrate excellent intra- and inter-rater reliability.^13-15

Figure 1.

Axial MRI segmented image for 2 different patients at C3. Red: right sternocleidomastoid; green: left sternocleidomastoid; blue: right anterior muscle group; yellow: left anterior muscle group; beige: right posteromedial muscle group; orange: left posteromedial muscle group; cyan: right posterolateral muscle group; magenta: left posterolateral muscle group; light green: right trapezius; dark blue: left trapezius

Figure 2.

Matlab software calculated the area above and below a pixel intensity threshold within the respective region of interest (ROI). The area indicated in green is determined as fat infiltration within the muscle

DSI2 Measurements

DSI2 measurements were performed on midsagittal T2-weighted MRI images by determining the intensity within ROI. One ROI was set in the CSF, and 3 ROIs were set per disc at the anterior, middle, and posterior third. For the CSF ROI placement, the cistern in front of the medulla oblongata was selected (Figure 3). The diameters of the ROIs matched the heights of the discs between the upper and lower endplates at each position, and the endplates were excluded from ROIs. Discs with substantially decreased height that prohibited ROI selection were excluded. The mean of the 3 measurements per disc was then divided by that of the CSF to calculate the DSI2 score. A higher DSI2 score is indicative of less degeneration. This process was completed for the C1/C2 to C7/T1 discs. All DSI2 measurements were taken by a trained orthopedic spine surgery fellow with experience in MRI measurement techniques. This methodology has been previously validated both in the lumbar and in the cervical spine.^25,28

Figure 3.

Representative ROI measurements of the disc and CSF signal intensities on T2-weighted midsagittal MRI images. Illustrative images of ROI measurements of the disc and CSF signal intensities on T2-weighted midsagittal MRI. Disc signal intensities are measured 3 times at the C2/3 disc (arrowhead) and the ROI of CSF signal intensity measurement (arrow)

CTA Measurements

Carotid analysis was conducted on CTA images using previously validated semi-automated vessel analysis software (GE Advantage Workstation, Advanced Vessel Analysis, Version 4.2). This software has demonstrated excellent intra- and interobserver reproducibility in the measurement of CAS on CTA and has been shown to have a higher accuracy than seen with manual measurement.²² For each ICA, the software identified the narrowest luminal diameter (mm) and the reference luminal diameter in the distal ICA (mm), then calculated both the percentage of stenosis at the point of maximum narrowing and the mean percentage of stenosis along the vessel, normalized to the patient-specific internal carotid diameter (Figure 4A and B).

Figure 4.

Advanced Vessel Analysis software. A: Vessel selection starting in the common carotid artery. B: Stenosis automatic measurement in the internal carotid artery

Statistical Analysis

All continuous variables were first assessed for normal distribution by visualization. Spearman’s correlation coefficient was calculated for the correlation analysis between muscle parameters, DSI2 and CTA mean and maximum. Multivariable linear regression analysis was performed with adjustment for age, BMI and sex. Statistical analysis was performed by a biostatistician using R Statistical Software (version 4.2.2; The R Project for Statistical Computing). The Benjamini-Hochberg procedure was applied with adjusted P-values to control the false discovery rate in multiple comparisons. Statistical significance was set to P < 0.05.

Results

Our study identified 94 patients who met study inclusion criteria. Of these, 29 were excluded due to inadequate MRI/CTA quality for measurement evaluations. This left 65 consecutive patients (mean age: 67 years; 58% female) for analysis. The patient population was 88% Caucasian, with a median BMI of 26.5 kg/m². All patients were treated at a single academic spine center in the United States. Demographics, the median and interquartile range of muscle parameters, along with the mean ± SD of carotid analysis values, are summarized in Table 1.

Table 1.

Carotid and Muscle Measurements

Parameter	N (total = 65)
Demographics
Age, years	67.0 ± 14.3 years
Sex	58% female; 42% male
BMI, kg/m²	Median: 26.5 (21.1-31.3)
Race	88% Caucasian; 2% Asian, 2% Black; 3% Hispanic; 5% Other
Muscle measurements
C3
SCM group
fCSA (mm²)	291.70 (214.25 - 391.05)
FI (%)	7.03 (4.74 - 11.19)
Anterior group
fCSA (mm²)	85.55 (62.05 - 135.35)
FI (%)	4.85 (1.63 - 12.27)
Posterolateral group
fCSA (mm²)	832.85 (589.85 -1101.90)
FI (%)	25.41 (18.32 - 37.04)
Posteromedial group
fCSA (mm²)	76.08 (32.15 - 118.54)
FI (%)	44.48 (25.45 - 72.91)
Trapezius muscle
fCSA (mm²)	55.45 (35.75 - 88.85)
FI (%)	28.03 (19.98 - 36.89)
C4
SCM group
fCSA (mm²)	291.60 (230.85 - 421.25)
FI (%)	9.69 (6.30 - 16.05)
Anterior group
fCSA (mm²)	67.80 (44.58 - 91.95)
FI (%)	9.679 (6.23 - 17.08)
Posterolateral group
fCSA (mm²)	688.30 (528.90 - 952.35)
FI (%)	31.67 (28.35 - 40.20)
Posteromedial group
fCSA (mm²)	56.25 (39.08 - 90.80)
FI (%)	37.52 (30.56 - 53.43)
Trapezius muscle
fCSA (mm²)	74.45 (39.25 - 96.50)
FI (%)	39.87 (26.07 - 51.41)
SN
fCSA (mm²)	29.10 (12.70 - 51.60)
FI (%)	32.96 (23.59 - 51.93)
C5
SCM group
fCSA (mm²)	307.25 (257.70 - 448.58)
FI (%)	5.49 (2.67 - 10.13)
Anterior group
fCSA (mm²)	48.95 (35.94 - 67.81)
FI (%)	15.46 (9.08 - 26.44)
Posterolateral group
fCSA (mm²)	648.85 (512.50 - 862.10)
FI (%)	33.45 (29.16 - 41.08)
Posteromedial group
fCSA (mm²)	63.30 (47.20 - 89.93)
FI (%)	46.10 (37.52 - 54.04)
Trapezius muscle
fCSA (mm²)	95.55 (59.40 - 244.15)
FI (%)	31.03 (23.64 - 42.59)
Scalenus muscle
fCSA (mm²)	66.20 (38.18 - 87.83)
FI (%)	39.55 (30.91 - 49.33)
C6
SCM group
fCSA (mm²)	296.10 (231.48 - 363.38)
FI (%)	3.77 (1.88 - 9.51)
Anterior group
fCSA (mm²)	37.88 (28.58 - 54.33)
FI (%)	16.01 (8.73 - 28.45)
Posterolateral group
fCSA (mm²)	673.60 (544.98 - 885.25)
FI (%)	31.89 (25.37 - 36.89)
Posteromedial group
fCSA (mm²)	46.25 (28.05 - 71.98)
FI (%)	55.94 (39.17 - 65.94)
Trapezius muscle
fCSA (mm²)	292.95 (151.20 - 444.15)
FI (%)	23.37 (14.20 - 32.75)
Scalenus muscle
fCSA (mm²)	132.40 (85.40 - 213.10)
FI (%)	39.05 (31.44 - 50.16)
C7
Anterior group
fCSA (mm²)	50.28 (38.51 - 72.95)
FI (%)	9.96 (5.49 - 23.79)
Posterolateral group
fCSA (mm²)	651.08 (506.35 - 854.71)
FI (%)	32.27 (27.945 - 38.054)
Posteromedial group
fCSA (mm²)	29.80 (19.59 - 46.93)
FI (%)	60.77 (44.78 - 77.56)
Scalenus muscle
fCSA (mm²)	279.60 (209.65 - 390.99)
FI (%)	37.24 (27.31 - 48.51)
Mean stenosis (%)	38.82 (17.31)
Maximum stenosis (%)	48.02 (17.69)

SCM: Sternocleidomastoid; fCSA: Functional cross-sectional area; FI: Fat infiltration. Median (IQR) reported for muscle measurements and BMI. Mean +- SD reported for age and carotid analysis parameters.

Unadjusted Spearman correlation analyses demonstrated significant relationships between CAS and cervical muscle morphology, predominantly at the upper cervical levels (C3-C4) (Table 2). Higher mean and maximum CAS correlated with increased FI and reduced fCSA across multiple muscle groups. After Benjamini-Hochberg correction for multiple comparisons, statistically significant correlations (all P < 0.05) persisted primarily at the C3 and C4 levels.

Table 2.

Spearman Correlation Testing Results

Variables		Mean stenosis (%)			Maximum stenosis (%)
Variables		Rho	P value	BH adjusted P	Rho	P value	BH adjusted P
C3 muscles
SCM	FI	0.51	<0.001	0.001	0.49	<0.001	0.002
SCM	fCSA	−0.36	0.004	0.025	−0.40	<0.001	0.010
AG	FI	0.47	<0.001	0.003	0.47	<0.001	0.003
AG	fCSA	−0.16	0.217	0.367	−0.28	0.021	0.099
PL	FI	0.33	0.007	0.038	0.35	0.005	0.030
PL	fCSA	−0.34	0.005	0.031	−0.33	0.006	0.036
PM	FI	0.41	<0.001	0.008	0.45	<0.001	0.004
PM	fCSA	−0.28	0.023	0.100	−0.31	0.013	0.062
TP	FI	0.36	0.012	0.062	0.40	0.005	0.030
TP	fCSA	−0.21	0.156	0.300	−0.21	0.147	0.297
C4 muscles
SCM	FI	0.33	0.007	0.036	0.27	0.032	0.120
SCM	fCSA	−0.36	0.003	0.025	−0.43	<0.001	0.005
AG	FI	0.18	0.158	0.300	0.14	0.285	0.444
AG	fCSA	−0.18	0.163	0.306	−0.25	0.043	0.151
PL	FI	0.28	0.024	0.100	0.26	0.036	0.130
PL	fCSA	−0.18	0.141	0.297	−0.16	0.191	0.338
PM	FI	0.39	0.001	0.013	0.40	0.001	0.011
PM	fCSA	−0.43	<0.001	0.007	−0.38	0.002	0.017
TP	FI	0.06	0.669	0.765	0.12	0.364	0.526
TP	fCSA	−0.05	0.723	0.803	−0.09	0.502	0.627
SN	FI	0.17	0.202	0.352	0.26	0.047	0.151
SN	fCSA	−0.46	<0.001	0.005	−0.48	<0.001	0.004
C5 muscles
SCM	FI	0.21	0.100	0.261	0.18	0.155	0.300
SCM	fCSA	−0.28	0.024	0.100	−0.37	0.003	0.021
AG	FI	0.10	0.425	0.582	0.17	0.192	0.338
AG	fCSA	−0.24	0.057	0.167	−0.28	0.027	0.108
PL	FI	0.09	0.453	0.582	0.01	0.919	0.943
PL	fCSA	−0.21	0.088	0.241	−0.14	0.280	0.442
PM	FI	0.10	0.433	0.582	0.20	0.116	0.290
PM	fCSA	−0.19	0.135	0.297	−0.25	0.048	0.151
TP	FI	−0.02	0.866	0.920	−0.03	0.847	0.916
TP	fCSA	−0.05	0.709	0.802	−0.01	0.969	0.977
SN	FI	0.19	0.133	0.297	0.25	0.047	0.151
SN	fCSA	−0.09	0.484	0.611	−0.16	0.211	0.361
C6 muscles
SCM	FI	0.16	0.257	0.429	0.22	0.122	0.290
SCM	fCSA	−0.19	0.173	0.314	−0.22	0.119	0.290
AG	FI	0.11	0.404	0.577	0.14	0.273	0.442
AG	fCSA	−0.13	0.331	0.484	−0.19	0.146	0.297
PL	FI	0.25	0.051	0.154	0.25	0.047	0.151
PL	fCSA	−0.23	0.065	0.185	−0.18	0.166	0.306
PM	FI	0.10	0.455	0.582	0.19	0.132	0.297
PM	fCSA	−0.13	0.319	0.479	−0.18	0.148	0.297
TP	FI	0.09	0.533	0.646	0.07	0.651	0.752
TP	fCSA	−0.10	0.510	0.628	−0.07	0.633	0.748
SN	FI	0.10	0.456	0.582	0.13	0.292	0.449
SN	fCSA	−0.10	0.446	0.582	−0.14	0.267	0.439
C7 muscles
AG	FI	0.08	0.542	0.651	0.10	0.441	0.582
AG	fCSA	−0.02	0.884	0.922	−0.13	0.324	0.479
PL	FI	0.27	0.031	0.120	0.22	0.093	0.248
PL	fCSA	−0.25	0.049	0.151	−0.20	0.121	0.290
PM	FI	0.00	0.977	0.977	0.10	0.445	0.582
PM	fCSA	−0.19	0.142	0.297	−0.19	0.140	0.297
SN	FI	0.02	0.861	0.920	0.01	0.925	0.943
SN	fCSA	−0.08	0.513	0.628	−0.04	0.740	0.814
DSI2
C2-3		0.12	0.436	0.582	0.01	0.927	0.943
C3-4		0.12	0.439	0.582	0.06	0.720	0.803
C4-5		0.07	0.642	0.748	−0.02	0.879	0.922
C5-6		0.04	0.787	0.859	−0.07	0.641	0.748
C6-7		0.21	0.123	0.290	0.14	0.304	0.462
C7-T1		0.24	0.069	0.192	0.15	0.277	0.442

SCM: Sternocleidomastoid; AG: Anterior group; PL: Posterolateral group; PM: Posteromedial group; TP: Trapezius; SN: Scalenus; fCSA: Functional cross-sectional area; FI: Fat infiltration; DSI2: Disc Severity Index. Spearman’s rho, P-values, and Benjamini–Hochberg adjusted P-values are reported. Significant values (P < 0.05) are bolded.

For mean stenosis, significant positive correlations were observed with FI in the SCM, AG, PL, and PM at C3, and in the PM at C4, while negative correlations with fCSA were observed in select muscle groups at these same cervical levels. Maximum stenosis demonstrated a similar pattern, with significant positive correlations for FI in the SCM, AG, PL, and PM at C3 and in the PM at C4, as well as negative correlations with fCSA primarily involving the SCM and PM at C3 and C4. A single additional significant correlation was observed at C5, where higher maximum CAS correlated with reduced SCM fCSA. Complete Spearman correlation results are presented in Table 2.

Multivariable linear regression models adjusted for age, sex, and BMI demonstrated several associations between CAS and cervical muscle degeneration parameters, particularly at the C3 and C4 levels. The strongest effects were observed between mean stenosis and FI in the PM (95% CI 0.60 [0.25-0.94], P = 0.002), SCM (95% CI 0.18 [0.02-0.34], P = 0.027), and AG (95% CI 0.21 [0.03-0.38], P = 0.022) muscles at C3, and in the PM (95% CI 0.43 [0.13-0.73], P = 0.005) and TP (95% CI 0.45 [0.14-0.76], P = 0.006) muscles at C4. Negative β-coefficients were noted between CAS and fCSA in the SCM (95% CI -1.83 [−3.29 to −0.37], P = 0.016) and PL (95% CI -1.37 [−3.50 to 0.48], P = 0.48) at C3 as well as in the SCM (95% CI -2.28 [−3.92 to −0.64], P = 0.008) and PM (95% CI -0.79 [−1.37 to −0.22], P = 0.008) at C4. No statistically significant associations were observed between CAS (mean or maximum stenosis) and DSI2 values across cervical disc levels.

After Benjamini-Hochberg adjustment, formal statistical significance was attenuated, and no associations remained statistically significant at P < 0.05. However, multiple associations demonstrated consistent directionality with unadjusted and multivariable analyses, with several relationships remaining at trend-level significance (P < 0.20). These findings indicate a consistent pattern of association between vascular narrowing and muscle degeneration, although conservative multiple-testing correction and limited sample size may have reduced statistical power (Table 3).

Table 3.

Multivariable Linear Regression Results Adjusted for Age, Sex and BMI

Variables		Mean stenosis (%)			Maximum stenosis (%)
Variables		Estimate (CI)	P value	BH-adjusted P	Estimate (CI)	P value	BH-adjusted P
C3 muscles
SCM	FI	0.18 [0.08-0.27]	<0.001	0.065	0.14 [0.04-0.24]	0.005	0.089
SCM	fCSA	−1.57 [−3.34-0.19]	0.079	0.370	−1.83 [−3.50-−0.17]	0.032	0.225
AG	FI	0.21 [0.03-0.38]	0.022	0.200	0.17 [−0.00-0.34]	0.055	0.314
AG	fCSA	−0.39 [−0.96-0.19]	0.181	0.572	−0.54 [−1.08-−0.01]	0.047	0.298
PL	FI	0.22 [0.02-0.41]	0.031	0.225	0.17 [−0.02-0.36]	0.085	0.370
PL	fCSA	−1.37 [−5.23-2.49]	0.480	0.921	−0.73 [−4.45-2.98]	0.693	0.960
PM	FI	0.58 [0.21-0.94]	0.003	0.086	0.60 [0.25-0.94]	0.001	0.065
PM	fCSA	−0.53 [−1.35-0.30]	0.205	0.630	−0.68 [−1.46-0.10]	0.086	0.370
TP	FI	0.45 [0.14-0.76]	0.006	0.089	0.40 [0.12-0.68]	0.006	0.089
TP	fCSA	−0.23 [−1.10-0.64]	0.593	0.948	−0.29 [−1.06-0.48]	0.448	0.921
C4 muscles
SCM	FI	0.18 [0.02-0.34]	0.028	0.225	0.16 [−0.00-0.31]	0.050	0.301
SCM	fCSA	−2.12 [−3.85–-0.38]	0.018	0.181	−2.28 [−3.92-−0.64]	0.008	0.096
AG	FI	0.08 [−0.16-0.33]	0.497	0.921	0.06 [−0.18-0.29]	0.623	0.952
AG	fCSA	−0.29 [−0.81-0.23]	0.262	0.749	−0.35 [−0.84-0.14]	0.162	0.543
PL	FI	0.10 [−0.08-0.27]	0.271	0.755	0.06 [−0.11-0.23]	0.465	0.921
PL	fCSA	0.41 [−3.40-4.23]	0.830	0.990	0.90 [−2.75-4.55]	0.623	0.952
PM	FI	0.35 [0.13-0.57]	0.003	0.086	0.31 [0.10-0.53]	0.005	0.089
PM	fCSA	−0.79 [−1.37–-0.22]	0.008	0.096	−0.62 [−1.19-−0.06]	0.032	0.225
TP	FI	0.02 [−0.28-0.33]	0.871	0.990	0.03 [−0.26-0.32]	0.831	0.990
TP	fCSA	−0.60 [−1.92-0.72]	0.366	0.861	−0.72 [−1.98-0.54]	0.257	0.749
SN	FI	0.11 [−0.30-0.52]	0.589	0.948	0.23 [−0.15-0.61]	0.233	0.699
SN	fCSA	−0.64 [−1.30-0.02]	0.058	0.314	−0.54 [−1.17-0.09]	0.091	0.378
C5 muscles
SCM	FI	0.03 [−0.16-0.21]	0.776	0.990	0.02 [−0.15-0.19]	0.854	0.990
SCM	fCSA	−2.08 [−4.12-– 0.04]	0.046	0.298	−2.33 [−4.20-−0.46]	0.016	0.173
AG	FI	0.25 [−0.09-0.59]	0.144	0.540	0.26 [−0.06-0.59]	0.109	0.437
AG	fCSA	−0.22 [−0.65-0.22]	0.329	0.824	−0.16 [−0.58-0.26]	0.449	0.921
PL	FI	0.07 [−0.08-0.22]	0.349	0.837	0.03 [−0.12-0.17]	0.707	0.962
PL	fCSA	−0.67 [−4.02-2.67]	0.689	0.960	0.59 [−2.62-3.80]	0.713	0.962
PM	FI	0.06 [−0.18-0.30]	0.610	0.952	0.11 [−0.12-0.35]	0.324	0.824
PM	fCSA	−0.14 [−0.64-0.35]	0.556	0.948	−0.13 [−0.60-0.34]	0.583	0.948
TP	FI	−0.09 [−0.42-0.23]	0.567	0.948	−0.13 [−0.44-0.18]	0.401	0.907
TP	fCSA	0.02 [−2.90-2.94]	0.988	0.990	0.03 [−2.77-2.82]	0.985	0.990
SN	FI	0.06 [−0.20-0.32]	0.642	0.952	0.08 [−0.17-0.33]	0.522	0.943
SN	fCSA	0.06 [−0.91-1.04]	0.901	0.990	−0.19 [−1.13-0.74]	0.678	0.960
C6 muscles
SCM	FI	−0.01 [−0.25-0.22]	0.916	0.990	−0.02 [−0.25-0.21]	0.860	0.990
SCM	fCSA	−1.83 [−4.44-0.77]	0.163	0.543	−1.77 [−4.27-0.74]	0.161	0.543
AG	FI	0.12 [−0.22-0.46]	0.481	0.921	0.15 [−0.17-0.47]	0.341	0.835
AG	fCSA	−0.16 [−0.63-0.30]	0.481	0.921	−0.16 [−0.59-0.28]	0.475	0.921
PL	FI	0.11 [−0.01-0.23]	0.061	0.317	0.11 [−0.01-0.22]	0.067	0.336
PL	fCSA	−2.24 [−6.42-1.94]	0.287	0.783	−1.25 [−5.24-2.75]	0.534	0.943
PM	FI	−0.00 [−0.31-0.31]	0.983	0.990	0.07 [−0.23-0.36]	0.641	0.952
PM	fCSA	−0.21 [−0.96-0.53]	0.570	0.948	−0.34 [−1.05-0.36]	0.330	0.824
TP	FI	0.15 [−0.15-0.45]	0.308	0.820	0.10 [−0.19-0.39]	0.491	0.921
TP	fCSA	−0.39 [−4.17-3.40]	0.836	0.990	−0.36 [−4.04-3.33]	0.844	0.990
SN	FI	0.02 [−0.24-0.27]	0.903	0.990	0.02 [−0.23-0.26]	0.901	0.990
SN	fCSA	0.03 [−1.77-1.84]	0.970	0.990	−0.13 [−1.84-1.59]	0.883	0.990
C7 muscles
AG	FI	0.06 [−0.24-0.35]	0.694	0.960	0.05 [−0.23-0.33]	0.722	0.962
AG	fCSA	−0.02 [−0.42-0.38]	0.904	0.990	−0.13 [−0.50-0.25]	0.499	0.921
PL	FI	0.05 [−0.10-0.20]	0.495	0.921	0.03 [−0.11-0.17]	0.637	0.952
PL	fCSA	−1.40 [−4.56-1.76]	0.377	0.871	−0.07 [−3.09-2.95]	0.964	0.990
PM	FI	−0.11 [−0.45-0.24]	0.535	0.943	−0.01 [−0.34-0.31]	0.930	0.990
PM	fCSA	−0.08 [−0.46-0.30]	0.683	0.960	0.00 [−0.36-0.36]	0.990	0.990
SN	FI	−0.02 [−0.27-0.23]	0.856	0.990	−0.08 [−0.32-0.16]	0.490	0.921
SN	fCSA	0.41 [−1.67-2.48]	0.696	0.960	0.58 [−1.39-2.55]	0.557	0.948
DSI2
C2-3		0.00 [−0.00-0.00]	0.859	0.990	−0.00 [−0.00-0.00]	0.943	0.990
C3-4		0.00 [−0.00-0.00]	0.807	0.990	0.00 [−0.00-0.00]	0.945	0.990
C4-5		−0.00 [−0.00-0.00]	0.937	0.990	0.00 [−0.00-0.00]	0.882	0.990
C5-6		−0.00 [−0.00-0.00]	0.176	0.572	−0.00 [−0.00-0.00]	0.156	0.543
C6-7		−0.00 [−0.00-0.00]	0.080	0.370	−0.00 [−0.00-0.00]	0.140	0.540
C7-T1		−0.00 [−0.00-0.00]	0.791	0.990	−0.00 [−0.00-0.00]	0.736	0.971

SCM: Sternocleidomastoid; AG: Anterior group; PL: Posterolateral group; PM: Posteromedial group; TP: Trapezius; SN: Scalenus; fCSA: Functional cross-sectional area; FI: Fat infiltration; DSI2: Disc Severity Index. β estimates with 95% confidence intervals, P-values, and Benjamini–Hochberg adjusted P-values are reported. Significant values (P < 0.05) are bolded.

Discussion

This study demonstrates an association between CAS and cervical paraspinal muscle degeneration, highlighting the potential role of systemic vascular health in cervical musculoskeletal integrity. Higher mean and maximum CAS were associated with increased FI and reduced fCSA across several muscle groups, most prominently at the upper cervical levels. These findings support previous evidence linking AAC to lumbar paraspinal muscle degeneration and highlight carotid circulation as another vascular territory that may contribute to musculoskeletal decline in the cervical spine.

While both mean and maximum CAS correlated with muscle degeneration, mean stenosis appeared to better represent cumulative vascular burden. Unlike maximum stenosis, which reflects a single focal narrowing, mean stenosis quantifies the average luminal reduction along the arterial segment, providing an index of cumulative vascular burden.^35-40 The consistent association between higher mean stenosis and higher FI across multiple muscle groups supports the concept that sustained reductions in vascular supply may impair local metabolism and promote fatty replacement of cervical musculature.³⁵ Carotid stenosis, traditionally interpreted within a cardiovascular framework, may therefore also have implications for musculoskeletal integrity.

Previous studies have established associations between vascular calcification, muscle atrophy, and spinal degeneration, particularly in the lumbar region. AAC has been associated with low back pain, FI, reduced muscle quality, and worse postoperative outcomes,^41-43 as well as bone loss, vertebral fractures, and adjacent segment disease, highlighting the systemic consequences of vascular pathology on both bone and muscle health.^44,45 Thoracic and abdominal aortic calcifications also correlate with carotid atherosclerotic disease, reflecting a broader systemic interplay between vascular stiffening, calcification, and tissue degeneration.^46–48 Arterial stiffening reduces diastolic perfusion pressure and may impair microvascular circulation, limiting nutrient exchange and oxygen delivery to muscle tissue.^35,49,50 Considering CAS as a biomarker of overall vascular health, it is plausible that these pathophysiological mechanisms extend to the cervical region. The cervical musculature, with its smaller volume and higher oxidative demand, may therefore be particularly susceptible to the microcirculatory deficits and metabolic stress that accompany progressive atherosclerosis.

Beyond muscular degeneration, this study also explored the association between vascular health and intervertebral disc integrity. Intervertebral disc degeneration is a major contributor to neck pain and disability, and its progression can substantially affect quality of life and surgical outcomes.^23,24,51 The degenerative process is multifactorial, driven by aging, mechanical loading, inflammation, and systemic metabolic factors.^26,31 As the disc loses water and proteoglycans, its height, elasticity, and ability to absorb mechanical stress decline, predisposing to segmental instability, neural compression, and chronic pain syndromes.^27,52

To assess disc quality, we used the Disc Signal Intensity (DSI2) index, a quantitative MRI-based parameter that normalizes disc signal to cerebrospinal fluid. Originally introduced and validated by Tsuchiya et al, DSI2 has shown strong correlations with Pfirrmann grading in both the lumbar and cervical spine and provides greater sensitivity for detecting early degenerative changes.^25,28 Lumbar studies also demonstrated that DSI2 values correlate with patient-reported quality-of-life scores, highlighting its clinical value as an objective biomarker of disc health.²⁸

In our cohort, no significant correlations were observed between CAS and DSI2 values. In contrast to the muscular findings, this pattern suggests that muscle degeneration may be more directly tied to local perfusion deficits, whereas disc degeneration is driven by broader, multifactorial processes, including mechanical loading, systemic inflammation, and metabolic dysregulation rather than isolated perfusion compromise.^26,27,31 Skeletal muscle is directly perfused and highly responsive to microcirculatory changes, whereas the intervertebral disc is avascular and relies primarily on diffusion across the endplates for nutrient supply.^3,4,26 Consequently, moderate reductions in vascular flow, such as carotid stenosis, may exert minimal direct impact on disc homeostasis. Nonetheless, incorporating DSI2 into the analysis provides a valuable quantitative framework for assessing cervical disc quality and highlights how vascular, mechanical, and metabolic factors may contribute differently to tissue degeneration within the spine.

A major strength of this study lies in the integration of semi-automated CTA analysis and quantitative MRI parameters. The use of automated carotid stenosis quantification reduces observer variability and enables consistent evaluation of vascular burden. Similarly, the inclusion of objective muscle and disc metrics, FI, fCSA, and DSI2 enhances reproducibility and minimizes reliance on subjective visual grading systems.^17-20 Together, these methods provide a multimodal imaging approach for assessing vascular, muscular, and discal parameters within a unified analytic framework.

From a clinical perspective, these findings highlight the importance of considering vascular health as part of comprehensive spine evaluation. Carotid stenosis, traditionally viewed through a cerebrovascular lens, may serve as an imaging biomarker of systemic atherosclerotic burden and underlying muscle vulnerability. Identifying patients with concurrent vascular disease could help anticipate worse muscular quality and guide perioperative decision-making, particularly in complex cervical procedures where muscle integrity contributes to postoperative alignment and stability.^13-15,53,54 Moreover, incorporating vascular assessments into preoperative planning or longitudinal follow-up may allow for earlier identification of patients who could benefit from cardiovascular optimization, lifestyle modification, or targeted rehabilitation aimed at preserving muscle function.^3,43,55,56 While further research is needed to establish causality, the present study raises the possibility that maintaining vascular health may help preserve musculoskeletal integrity and potentially surgical outcomes.

Several limitations should be acknowledged. This was a retrospective, cross-sectional, single-center analysis with a relatively small sample size, limiting adjustment for a broader range of cardiovascular comorbidities that may influence muscle morphology. While we adjusted for key covariates such as age, sex, and BMI, the study design does not allow us to establish causality between CAS and cervical paraspinal muscle changes; our results indicate associations rather than direct effects. Clinical or patient-reported outcomes were not analyzed, as this study was primarily diagnostic and focused on imaging-based associations. However, previous literature has consistently demonstrated that both muscle atrophy and disc degeneration correlate strongly with pain, disability, and worse outcomes, supporting the clinical relevance of these degenerative changes even though they were not directly assessed in our cohort.^5,6,13,57-59 Vertebral artery stenosis was not evaluated because reliable measurement is technically challenging both manually, owing to the vessel’s small caliber, tortuosity, and high interobserver variability, and semi-automatically, as software packages provide inconsistent vessel tracking at that level.^60,61 Nonetheless, studies have shown a strong correlation between carotid and vertebral artery health, suggesting that our findings may reflect broader vascular status while using CAS as a reproducible and validated surrogate marker of overall vascular health.

Overall, our study highlights a novel association between CAS and cervical muscle atrophy, suggesting that vascular health may be an underrecognized factor influencing cervical muscles. Future prospective and longitudinal studies are warranted to clarify causality and determine whether improving vascular health can preserve muscle composition and mitigate degenerative spinal disease.

Conclusion

This study demonstrates an association between CAS and cervical paraspinal muscle degeneration, supporting a link between vascular health and muscle quality in the cervical spine. In contrast, no relationship was found between CAS and intervertebral disc integrity, suggesting that muscle and disc degeneration may follow distinct pathophysiological pathways. These findings highlight the role of vascular health as a potential contributing factor to musculoskeletal degeneration and emphasize the need for prospective studies to clarify causality and determine whether optimizing vascular status can help preserve muscle quality and spinal stability.

Footnotes

ORCID iDs

Bruno Verna

Ali E. Guven

Marco D. Burkhard

Julia Wimmer

Tom Folkerts

Andrew A. Sama

Alexander P. Hughes

Ethical Considerations

This study was approved by our hospital's institutional review board (IRB#2018-2300). Informed consent was waived by the IRB because of the retrospective nature of the study. This study follows the ethical principles of the Helsinki Declaration.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Declaration of Conflicting Interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data Availability Statement

The datasets generated and analyzed during the current study are not publicly available due to confidentiality restrictions but are available from the corresponding author on reasonable request.*

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