Brachial artery wall shear stress as measured by ultrasound vector flow imaging for evaluating arteriovenous fistula stenosis in patients on hemodialysis

Introduction

An arteriovenous fistula (AVF) is the preferred vascular access for maintenance hemodialysis in patients with end-stage renal disease (ESRD) (1). Vascular remodeling of the AVF persists throughout maturation and clinical use (2,3). The frictional force exerted by blood flow (BF) on endothelial cells, known as wall shear stress (WSS), is a critical contributor to atherosclerosis and lumen stenosis (4-7). AVFs are frequently associated with unstable WSS, which can induce endothelial damage and trigger localized inflammatory responses, ultimately leading to AVF stenosis (8). Therefore, the early detection of AVF stenosis is of significant clinical importance.

Doppler ultrasound is the preferred technique for monitoring vascular access (9); however, it is angle-dependent and primarily applicable to laminar flow, resulting in substantial calculation errors (10). In contrast, ultrasound vector flow imaging (V-flow) leverages steered plane wave and interleaved focused wave transmissions (11,12). This technique estimates two-dimensional vector velocities at a high frame rate, enabling the measurement of velocity magnitude and direction near the vessel wall independent of beam angle. Consequently, WSS can be directly calculated within a region of interest at the vessel wall (13). Studies have shown that using vector velocity obtained through V-flow to calculate WSS results in significantly reduced error compared to conventional pulsed-wave Doppler, particularly under complex flow conditions (14). Previous research has demonstrated the feasibility of V-flow for assessing WSS in healthy adults (15) and in individuals with AVF (16).

Thus far, the bulk of research on AVF has focused on venous aspects, and there has been limited attention paid to the proximal arteries. The brachial artery, as the primary feeding vessel of AVF (17), exhibits hemodynamic parameters closely associated with AVF maturation and long-term patency (18,19). However, few studies have investigated the relationship between brachial artery WSS and AVF stenosis, and the clinical utility of V-flow-derived WSS remains insufficiently explored. Therefore, we sought to determine whether AVF stenosis could be assessed via the measurement of WSS in the ipsilateral brachial artery using V-flow imaging. We present this article in accordance with the STROBE reporting checklist (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2836/rc).

Methods

Study population and demographic characteristics

This observational cross-sectional study included 113 consecutive patients with ESRD undergoing hemodialysis via AVF between December 2024 and February 2025. The inclusion criteria were as follows: (I) age >18 years; (II) history of radial artery-cephalic vein end-to-side anastomosis with a functional AVF for >3 months post-creation; and (III) hemodialysis three times per week (4–6 hours per session). Relevant data were collected half an hour before the first dialysis session of the week. Meanwhile, the exclusion criteria were as follows: (I) left ventricular ejection fraction (LVEF) ≤50%; (II) inability to cooperate with examinations; (III) failure to obtain V-flow images and parameters due to poor acoustic windows, excessive depth, or patient body habitus; and (IV) any history of vascular access creation, percutaneous transluminal angioplasty (PTA), stenting, or other surgical/interventional procedures involving the contralateral upper limb.

The time elapsed between AVF creation and the ultrasound examination was recorded for all patients. The following data were recorded at enrollment: age, sex, body mass index (BMI), blood pressure, smoking history, AVF side (left or right arm), number of PTA procedures, dialysis duration, underlying diseases, and associated complications. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments and was approved by the Medical Ethics Committee of The People’s Hospital of Yubei District, Chongqing, China (approval No. 2024C06). Informed consent was obtained from all participants.

AVF ultrasound examination and data acquisition

Ultrasound examinations were performed with a Resona A20S ultrasound system (Mindray Bio-Medical Electronics Co., Ltd., Shenzhen, China) with a linear array probe (3.8–15.4 MHz).

In ultrasound imaging procedure, the brachial artery, radial artery, anastomotic site, and cephalic vein were examined with B-mode and color Doppler flow imaging. The Doppler angle was maintained at ≤60° to optimize signal intensity. Under pulsed-wave Doppler, BF, peak systolic velocity (PSV), diameter, and the resistive index (RI) were measured in the brachial artery approximately 3–4 cm proximal to the elbow crease. BF, was automatically calculated with the following formula: BF (mL/min) = time-averaged velocity (cm/s) × π × (D/2)² (cm²) × 60, where D is the vessel diameter. The inner diameter of the brachial artery was measured in axial B-mode images, with the intima-lumen interface serving as the reference. The RI was automatically calculated as follows: (PSV – EDV)/PSV, where EDV is the end-diastolic velocity. Meanwhile, the pulsatility index (PI) was calculated as follows: (PSV – EDV)/MV, where MV is the mean velocity.

V-flow protocol

V-flow acquisitions included plane wave imaging at three steering angles with a frame rate >40 Hz. The pulse repetition frequency (PRF) was automatically adjusted (typically by 1–5 kHz) to avoid aliasing, and the system’s center frequency was set to 7.5 MHz. Long-axis views of the brachial artery (approximately 3–4 cm from the elbow crease) were obtained, ensuring the vessel was horizontal and centered within the sampling box. Patients were instructed to avoid any body movement during the 1.5-second acquisition. V-flow dynamic images were stored for offline analysis.

Offline measurements of maximum wall shear stress (WSSmax), mean wall shear stress (WSSmean), and oscillatory shear index (OSI) were performed via the V-flow function on the ultrasound system. Six sample points were placed along the mid-portion of the brachial artery wall, the reference midline was overlaid on the intimal layer, and the correction line was aligned perpendicular to the vessel wall. This purpose of this was not to correct for Doppler angle dependency but rather to enable the system to extract appropriate velocity components for calculating the velocity gradient perpendicular to the vessel wall (du/dy) [du: the change in BF velocity (specifically the component parallel to the vessel wall) between two adjacent points; dy: the perpendicular distance from the vessel wall to the point where the velocity u is measured] (Figure 1). All V-flow acquisitions and offline measurements were performed by a single experienced radiologist with over 10 years of experience in vascular ultrasound and specific training in V-flow imaging who followed a standardized protocol to minimize variability. The average of the six points was used for final analysis. The WSS vector (τ) (20) was calculated as follows: τ = µ · (du/dy)|_{wall}, where µ is the blood viscosity (assumed constant at 0.004 Pa·s), and du/dy is the velocity gradient perpendicular to the wall. WSSmax and WSSmean values were determined throughout the cardiac cycle. The OSI was calculated as follows: OSI = 0.5 × (1 – (|∫WSS dt| / ∫|WSS| dt)).

Figure 1 Representative V‑flow images of the brachial artery. Six sampling points (labeled 1–6) are indicated with arrows and numbers along the arterial wall. Points 1–3 are located on the anterior wall (near the probe), and points 4–6 are located on the posterior wall (far from the probe). Arrow color and length denote flow velocity: red and longer arrows represent higher velocity, while green and shorter arrows indicate lower velocity. (A) V‑flow image from a patient in the arteriovenous fistula non-stenosis group, showing increased wall shear stress intensity (WSSmean =4.53 Pa). (B) V‑flow image from a patient in the arteriovenous fistula stenosis group, showing reduced wall shear stress intensity (WSSmean =1.26 Pa). (C) Corresponding WSSmean waveforms for both cases overlaid for direct comparison. OSI, oscillatory shear index; WSSmax, maximum wall shear stress; WSSmean, mean wall shear stress.

Group classification

Brachial artery parameters ipsilateral to the AVF constituted the study group, and the contralateral side served as the control. According to the Chinese expert consensus on ultrasound interventional therapy for hemodialysis vascular access (2024 edition) (21), patients were classified into the stenosis group if any one of the following criteria was met: (I) brachial artery BF <500 mL/min; (II) local venous diameter ≤1.7 or ≤2 mm with a stenotic segment length >20 mm; (III) arterial diameter ≤2.0 mm; (IV) PSV ratio (PSVR) of the vein >4 (PSVR=PSV at the stenosis/PSV 2 cm proximal to the stenosis.

Statistical analysis

Statistical analyses were performed with R software version 4.3.1 (The R Foundation for Statistical Computing, Vienna, Austria). The Shapiro-Wilk test was used to assess the normality of continuous variables. Normally distributed data are expressed as the mean ± standard deviation and were compared with t-tests; meanwhile, nonnormally distributed data are reported as the median with the first and third quartiles (Q1, Q3) and were compared with the Mann-Whitney U test. Categorical variables are described as numbers and percentages and were compared with Chi-squared or Fisher exact tests. Least absolute shrinkage and selection operator (LASSO) regression with 10-fold cross-validation was employed to select predictors of AVF dysfunction. The optimal penalty coefficient (λ) was determined according to the λ₁-SE criterion. Variables selected by LASSO were incorporated into a multivariate logistic regression model to create a combined diagnostic model. Receiver operating characteristic (ROC) curves were generated, and the area under the curve (AUC) was calculated. Decision curve analysis (DCA) was performed to evaluate clinical utility. Statistical significance was set at P<0.05. The correlation between WSSmean and ultrasonic parameters was analyzed via Spearman analysis and linear regression.

Results

Demographic characteristics

Initially, 119 individuals were enrolled in the study. Of these, one was excluded due to heart failure, one due to inability to cooperate with the examination, and four due to poor ultrasound image quality (Figure 2). A total of 113 patients (66 males and 47 females) were included, with a mean age of 57.7±13.1 years and a median age of 58.5 years. The median time since AVF creation was 24 (Q1, Q3: 12, 49.5) months. Forty-three patients (38%) were placed into the stenosis group. The baseline characteristics of patients are summarized in Table 1.

Figure 2 Flowchart of participant inclusion.

Comparison of flow parameters between the study and control groups

All brachial artery flow parameters differed significantly between the study (AVF side) and control groups (P<0.001). Inner diameter, PSV, BF, WSSmax, WSSmean, and their anterior/posterior wall components were higher in the study group, whereas OSI, RI, and PI were lower (Table 2).

Comparison between the stenosis and non-stenosis groups

Compared to the non-stenosis group, the stenosis group exhibited a significantly lower inner diameter, PSV, BF, WSSmax, and WSSmean (P<0.05). OSI did not differ significantly between groups (P>0.05; Table 3 and Figure 1). LASSO regression indicated that the three predictors of AVF dysfunction were inner diameter, RI, and WSSmean, with coefficients of –0.19, 0.38, and –0.25, respectively (Figure 3). A nomogram and decision curve were constructed based on the combined model (Figures 4,5). The AUC values for diameter, RI, WSSmean, and the combined model were 0.721, 0.728, 0.719, and 0.806, respectively (Figure 6). The combined model demonstrated the highest diagnostic performance (P<0.05). The combination model compared to any single parameter yielded the largest AUC of 0.806 (P<0.05).

Figure 3 Variable selection with LASSO regression. (A) The mean-squared error curve plotted against the log(Lambda) sequence. The left vertical dashed line indicates the lambda value (lambda.min) that gives the minimum mean cross-validated error. The right vertical dashed line (lambda.1se) represents the largest value of lambda such that the error is within one standard error of the minimum, which was used for our final, more parsimonious model. (B) The LASSO coefficient profiles of the candidate variables. The vertical dashed line is drawn at the value selected by 10-fold cross-validation (lambda.1se), where the optimal number of predictors (WSSmean, RI, diameter) is retained, and the coefficients of the other variables are shrunk to zero. LASSO, least absolute shrinkage and selection operator; RI, resistive index; WSSmean, mean wall shear stress.

Figure 4 Nomogram for predicting AVF stenosis based on diameter, RI, and WSSmean. Locate the patient’s brachial artery diameter on the ‘Diameter’ axis. Draw a vertical line upward to the ‘Points’ scale to obtain the corresponding points. Repeat for RI and WSSmean. Sum the points from all three variables to obtain the ‘Total points’. Locate the total points on the ‘Total points’ axis. Draw a vertical line downward to the ‘Probability of stenosis’ scale to read the patient’s predicted probability of AVF stenosis. AVF, arteriovenous fistula; RI, resistive index; WSSmean, mean wall shear stress.

Figure 5 Decision curve analysis of the combined model.

Figure 6 ROC curves of diameter, RI, WSSmean, and the combined model for diagnosing AVF stenosis. AUC, area under the curve; AVF, arteriovenous fistula; CI, confidence interval; FPR, false positive rate; RI, resistive index; ROC, receiver operating characteristic; TPR, true positive rate; WSSmean, mean wall shear stress.

Analysis of inter-variable correlations between the study groups

Correlation analysis revealed a weak positive correlation between PSV and WSSmean (r=0.291; P<0.01), with PSV accounting for only 8.5% of the variance in WSSmean (r²=0.085). WSSmean showed a weak positive correlation with BF (r=0.364; P<0.001), indicating that flow volume accounted for only 13.2% of WSS variance (Figure 7).

Figure 7 Analysis of inter-variable correlations between the study groups. PSV (A) and BF (B) were positively correlated with WSSmean. RI (C) was negatively correlated with WSSmean. There was no significant correlation between diameter and WSSmean (D). BF, blood flow; diameter, internal diameter of the brachial artery; PSV, peak systolic velocity; RI, resistance index; WSSmean, mean wall shear stress.

Discussion

This study demonstrates that hemodynamic parameters of the brachial artery, measured with V-flow and Doppler ultrasonography, are significantly altered in patients on hemodialysis with AVF stenosis. The principal finding is that lower WSSmean in the brachial artery was independently associated with downstream AVF stenosis. Furthermore, a diagnostic model combining diameter, RI, and WSSmean demonstrated superior performance as compared to any single parameter.

Vascular access is critical for effective dialysis. Inappropriate vascular remodeling leads to AVF stenosis and thrombosis, with a 2-year failure rate exceeding 50% (22,23). WSS, which is influenced by BF and blood viscosity (24,25), is a mechanical signal perceived by endothelial cells, triggering adaptive responses (26). V-flow has good reliability, as supported by studies confirming its high interobserver agreement in assessment of the peripheral arteries, especially those related to the carotid artery, which reduces measurement bias (27,28).

In our study, the WSSmean in the control group was median 0.52Pa, interquartile range (IQR) 0.36–0.70 Pa; consistent with values previously reported in healthy individuals (29). The slightly lower values in our cohort may reflect differences in study populations, as our controls were patients with ESRD without an ipsilateral AVF. Increased brachial artery diameter, BF, and WSS, along with a decreased RI and PI, indicate vascular remodeling in the AVF group. Following AVF creation, elevated WSS promotes endothelial nitric oxide release, vasodilation, and maintenance of high flow—a physiological compensatory state (26). He et al. (30) reported progressive increases in brachial artery WSS post-AVF creation, which is consistent with our findings.

No significant demographic differences were observed between the stenosis and non-stenosis groups, suggesting that hemodynamic factors may be more directly relevant to AVF stenosis. The OSI is a unitless value between 0 and 0.5. A value of 0 indicates that the BF at the measurement site remains unidirectional throughout the measurement period (16). In our study, the OSI did not differ between groups, possibly due to the unidirectional flow in AVF-side arteries, as reflected by near-zero OSI values. The lower WSS in the stenosis group aligns with Poiseuille’s law, which states that downstream stenosis increases resistance and reduces flow, thereby decreasing WSS (31). LASSO regression identified diameter, RI, and WSSmean as key predictors. Although brachial artery flow and RI are established indicators of AVF stenosis (21), they may remain normal in the early stages (32). Decreased arterial diameter is a morphological sign of stenosis but is difficult to detect early. Importantly, low WSS may both result from stenosis and promote endothelial dysfunction and intimal hyperplasia (33,34), suggesting a bidirectional relationship. Therefore, it is crucial to determine the specific threshold for protective high shear stress in order to establish and apply AFVs effectively. Our findings suggest that there is a significant association between reduced brachial artery WSS and the presence of AVF stenosis, consistent with the well-established pathophysiological role of low WSS in vascular remodeling described in previous experimental and clinical studies (35,36). WSSmean may be a more valuable parameter for the clinical evaluation of AVF stenosis than the RI or diameter. Additionally, previous studies have indicated that artery WSS can be used as an indicator of AVF stenosis (37).

There was a weak positive correlation between PSV and WSSmean (r²=0.085), as well as a modest association between WSSmean and BF (r²=0.132). This indicates that while PSV and BF reflect global flow velocity and overall conduit function, they cannot fully capture the complex near-wall hemodynamics that govern actual endothelial shear stress. The remaining variance may be attributed to factors such as flow pulsatility, variations in vessel diameter, and the shape of the velocity profile. These findings underscore the added value of V-flow in enabling direct quantification of WSS without a reliance on assumptions regarding the flow profile.

A pivotal finding is that the diagnostic performance of WSSmean (AUC 0.719) was comparable to those of conventional parameters, including diameter (0.721) and the RI (0.728), yet their integration into a combined model yielded substantially superior diagnostic value (0.806). The improvement in diagnostic performance from individual parameters (AUC 0.721) to the combined model (AUC 0.806) is not only statistically significant but also clinically meaningful. An AUC of 0.806 indicates good discriminatory ability, which in clinical practice translates to more accurate risk stratification. This significant enhancement suggests that AVF stenosis is a multifactorial process that manifests through concurrent changes in vascular morphology, downstream resistance, and local hemodynamic forces. From a clinical perspective, this finding supports a shift from a reliance on routine ultrasound to the adoption of a multiparametric assessment strategy for AVF surveillance. The developed nomogram (Figure 4), which visually integrates these three variables, offers a practical tool for clinicians to estimate the probability of stenosis. Furthermore, the DCA (Figure 5) confirmed that using this combined model for clinical decision-making provides a greater net benefit across a wide range of clinically reasonable risk thresholds. More specifically, this suggests that an intervention based on the model’s prediction could lead to better patient outcomes compared to one based on traditional single-parameter thresholds. Therefore, the integration of V-flow-derived WSSmean with conventional ultrasound parameters (diameter and RI) creates a synergistic effect, significantly improving the noninvasive identification of AVF stenosis and holding promise for enhancing the management of hemodialysis vascular access. It is important to note that the clinical application of V‑flow in hemodialysis AVFs is still in its early stages. Large‑scale, multicenter studies are needed to establish normative reference values for V‑flow-derived parameters. After validation, a practical, tiered surveillance protocol for integrating V-flow into clinical practice can be achieved. In this protocol, routine Doppler ultrasound would serves as the first-line screening tool, and V-flow would be selectively applied in patients with inconclusive findings, clinical suspicion of early stenosis, or high-risk profiles. The combined diagnostic model could then guide referral decisions for angiography, potentially reducing unnecessary invasive procedures while improving early detection. This selective, targeted approach optimizes resource utilization and ensures that V-flow is used in cases where it adds the greatest clinical value.

Several practical considerations must be acknowledged regarding the clinical adoption of V-flow. First, the technology currently requires high-end ultrasound platforms, which may limit immediate availability, particularly in community settings. However, as clinical evidence accumulates, broader dissemination is anticipated. Second, the additional examination time (approximately 5–8 minutes) and need for operator training represent incremental costs that must be weighed against the potential benefits of improved diagnostic accuracy and reduced angiography referrals. In our experience, the learning curve is reasonable for experienced vascular sonographers, with proficiency achievable after 10–15 supervised examinations. These benefits may offset costs by reducing unnecessary angiograms and preventing access failures.

Although our findings suggest an association between reduced WSS and AVF stenosis, establishing formal WSS-based grading criteria for dysfunction severity would require the completion of prospective studies that confirm the correlation between WSS and clinically meaningful outcomes (e.g., thrombosis, access abandonment) and validation via angiographic stenosis quantification. Future prospective studies should investigate whether declining WSSmean over time can predict the development of stenosis or access failure, as this could potentially enable the earlier detection of subclinical hemodynamic deterioration and guide preventive interventions.

Limitations

Several limitations of this study should be acknowledged. First, the single-center design may limit the generalizability of our findings to broader populations or clinical settings; therefore, multicenter studies with diverse patient cohorts are needed to validate the robustness and external applicability of our diagnostic model. Second, we captured hemodynamic parameters at a single time point, which precluded the assessment of causal relationships or predictive value over time. Future prospective cohort studies with longitudinal follow-up are necessary to determine whether reduced WSSmean precedes AVF stenosis development and to evaluate its value in predicting future stenotic events. Third, while we used the Chinese expert consensus criteria (2024 edition) as the reference standard for AVF stenosis, we acknowledge that digital subtraction angiography remains the definitive gold standard for anatomical assessment of vascular stenosis. The absence of angiographic confirmation might have introduced verification bias, and future studies should incorporate angiographic correlation in a subset of patients to further validate the diagnostic accuracy of V-flow-derived parameters. Fourth, our inclusion criteria were restricted to patients with radial artery-cephalic vein end-to-side anastomosis to ensure hemodynamic homogeneity, which could have introduced selection bias. Although this approach enhances internal validity, it may limit applicability to other AVF configurations (e.g., brachiocephalic or brachiobasilic fistulas). Despite these limitations, this study provides important preliminary evidence supporting the clinical utility of V-flow-derived WSS parameters for AVF stenosis assessment. These findings should be confirmed in larger, multicenter prospective studies with angiographic validation and long-term follow-up.

Conclusions

Reduced brachial artery WSS was found to be a key hemodynamic feature of AVF stenosis. A combined model incorporating WSS, the RI, and diameter outperformed individual parameters in diagnostic performance. These findings enhance our understanding of AVF pathophysiology and support the use of V-flow-derived WSS as a complementary tool for noninvasive AVF assessment. Future research should validate this model prospectively and explore its integration into clinical workflows to improve AVF longevity.

Acknowledgments

The authors thank their colleagues in the Nephrology Department and Ultrasound Department of The People’s Hospital of Yubei District, Chongqing, China for their help during the preparation of this manuscript.

Footnote

Reporting Checklist: The authors have completed the STROBE reporting checklist. Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2836/rc

Data Sharing Statement: Available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2836/dss

Funding: This work was supported by Yubei District Science and Health Joint Medical Research Project, Chongqing, China (No. 2025YBKW24), and by Yubei District People's Hospital Hospital-level Scientific Research Project (No. ybyk2025-24).

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://qims.amegroups.com/article/view/10.21037/qims-2025-1-2836/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. This study was conducted in accordance with the Declaration of Helsinki and its subsequent amendments. The study was approved by the Medical Ethics Committee of The People’s Hospital of Yubei District, Chongqing, China (approval No. 2024C06), and informed consent was obtained from all participants.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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