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Introduction
Atherosclerosis (AS) is a key pathological basis underlying the initiation and progression of cardiovascular and cerebrovascular diseases [1]. Extensive research has demonstrated that proactive early intervention in AS can significantly reduce the risk of clinical cardiovascular [2] and stroke [3] events. However, early-stage AS primarily manifests through subtle pathophysiological changes, including an asymptomatic status and vascular endothelial cell dysfunction (ECD), rendering it highly covert and easily overlooked [1,4]. Carotid intima-media thickness (cIMT), a non-invasive ultrasonographic measurement, is widely recognized as an early vascular morphological indicator of AS [5] and has been shown to predict cardiovascular endpoints [6]. A comprehensive meta-analysis with a large sample (n=100,667) [7] demonstrated that increased cIMT is a definitive indicator of AS. Nevertheless, the association between progressive cIMT increase and the incidence of cardiovascular events remained inconclusive. In the MESA study, cIMT showed poor sensitivity for predicting cardiovascular events; moreover, after adjustment for traditional risk factors, cIMT was not an independent predictor of these events [8]. Given that AS is a lifelong and systemic condition [9], concerns about the reliability of cIMT in assessing early-stage AS have prompted a search for superior alternatives [10]. Nitroglycerin-mediated dilation can be used to evaluate vascular smooth muscle function but is invasive and not an established screening method for early atherogenesis [11].
Flow-mediated dilation (FMD) is an advanced ultrasound technique that non-invasively detects arterial dilation, reflecting the degree of vascular ECD [11,12]. Brachial artery wall dilation is accurately measured using M-mode ultrasonography following a brief (5-minute) forearm ligation and subsequent release during maximal refilling and resting after ischemia [11-13]. This index directly reflects the capacity of vascular endothelial cells to release vasoactive substances, such as nitric oxide; these compounds induce vasodilation in response to ischemic stress, thereby indicating the extent of ECD [14]. Numerous studies have confirmed that FMD is significantly associated with cardiovascular risk factors. It is considered a gold-standard method for accurately assessing the recovery of vascular endothelial function after treatment for AS, as well as for guiding clinical medication decisions and cardiovascular disease prognosis [15-18]. However, the measurement of FMD currently requires an external ultrasound sensor fixation device and highly precise timing equipment [19]. Additionally, the timing equipment necessitates an ultrasound machine with an extremely high frame-rate response speed, restricting this gold-standard technology primarily to laboratory and research settings. Thus, its widespread clinical application has been limited.
Vascular endothelial cells in the intima serve as the initial barrier between blood vessels and blood, acting as crucial microsecretory units and microeffectors [20]. High-resolution flow-mediated dilation (hrFMD) is an ultrasound technique utilizing a high-frequency commercial probe (24 MHz) with a rapid scanning response rate (>1,000 frames/s) that can clearly differentiate between the intima-media layers and the lumen [21]. This method enables large-scale, routine clinical evaluation of ECD using high-resolution commercial ultrasound devices. Nevertheless, the potential of this technology for assessing early AS progression in vivo and its clinical applicability require further investigation.
This study aimed to investigate the feasibility of hrFMD for assessing the extent of arterial ECD and evaluating early atherosclerotic risk in clinical practice.
Materials and Methods
Compliance with Ethical Standards
The study protocol was approved by the ethics committee of the Affiliated Hospital of Nanjing University of Chinese Medicine (2024NL-113-02), and the methods adhered to the Declaration of Helsinki. All participants provided written informed consent.
Patients
Two prospective patient cohorts were recruited. The first cohort was used to assess intra-operator hrFMD reproducibility and relative measurement variability (n=10), as well as inter-operator reproducibility between two hrFMD operators (X.M. and Z.Z., from January 2024 to April 2024; n=30). This cohort included 40 consecutive patients undergoing routine carotid ultrasound and hrFMD examinations.
The second cohort, recruited from May to December 2024, was used to assess the capability of hrFMD to assess the extent of arterial ECD and to evaluate early-stage AS in clinical practice. For this cohort, 89 non-smoking individuals who underwent comprehensive clinical and laboratory evaluations, carotid ultrasonography, and hrFMD assessments were consecutively recruited. The exclusion criteria were as follows: (1) a history of cardiovascular or stroke events within the past 6 months (n=3) or diabetes mellitus (n=3); (2) missing laboratory or imaging data (n=9); (3) unsuccessful hrFMD measurements due to excessive subcutaneous fat thickness (n=5), atrial fibrillation (n=1), or severe hypertension (blood pressure >200 mmHg; n=1); (4) chronic liver or kidney disease, autoimmune disease, or cancer (n=7); and (5) minors or pregnant women (n=0). Ultimately, 60 participants (67.4%) with complete data were included in the analysis (Fig. 1). Following the 2024 European Society of Cardiology (ESC) guidelines [22], participants with systolic blood pressure (SBP) <130 mmHg and diastolic blood pressure (DBP) <80 mmHg were assigned to the non-hypertensive (NHT) group (n=29), while those with SBP ≥130 mmHg and/or DBP ≥80 mmHg were included in the hypertensive (HT) group (n=31).
The cohort was subdivided into multiple subgroups to further analyze the feasibility of using hrFMD to assess ECD. Because the risk of AS and HT increases markedly after the age of 50 years [23], the population was subdivided by age into subgroups of <50 years (n=20) and ≥50 years (n=40). Patients were also subdivided based on the median cIMT into two groups: cIMT ≤0.64 mm (n=32) and cIMT >0.64 mm (n=28). A cardiovascular risk score was calculated for each participant using age, sex, smoking status, SBP, high-density lipoprotein (HDL) and total cholesterol (TC) levels, and diabetes, following the Framingham Risk Score (FRS) algorithm proposed by D'Agostino et al. [24]. Smoking and diabetes were defined according to the 2024 ESC guidelines for cardiovascular disease prevention [22]. Based on a 10-year risk percentage threshold derived from the FRS algorithm, patients were classified into two subgroups: FRS <10% (n=44) and FRS ≥10% (n=16).
All participants (n=60) underwent conventional ultrasound examination and hrFMD, performed by two operators (H.G. and P.D., with 10 and 15 years of ultrasonography experience). The hrFMD data (results and consensus) were independently reviewed frame by frame on the scanner by another experienced investigator (B.S., with 10 years of ultrasonography experience), who was blinded to patient group assignments and clinical outcomes.
cIMT Measurement and hrFMD Procedure
All ultrasound examinations were performed by specially trained sonographers following a standardized protocol [25]. An 8-24 MHz transducer (i24LX8), connected to an ultrasonographic system (Aplio i900, Canon Medical Systems, Tokyo, Japan), was used to acquire longitudinal arterial grayscale images. cIMT of the posterior wall of the bilateral carotid arteries was measured in the long-axis view, 1.5 cm proximal to the bifurcation of the common carotid artery, in plaque-free regions. Three successful assessments were recorded, and the patient’s cIMT value was calculated as the mean of the bilateral medians from these three measurements.
The hrFMD procedures aligned with expert consensus and evidence-based recommendations for FMD [11], except that cross-sectional rather than longitudinal images of the brachial artery were used. Cross-sectional imaging enables the placement of the M-mode ultrasonographic line at the center of the vessel, reducing major bias in diameter measurements compared with longitudinal imaging. Patient preparation before hrFMD measurement included a 12-hour fast and avoidance of caffeine, alcohol, high-fat foods, and vitamin C for 24 hours before the study [11]. The patient lay in the supine position during the measurement, with the right arm extended at approximately 80° from the torso (Fig. 2A). A rapid inflation cuff was positioned on the imaged arm, immediately adjacent to the distal end of the olecranon process, to induce forearm ischemia. An 8-24 MHz transducer (i24LX8) connected to the ultrasonographic system (Aplio i900, Canon Medical Systems) was used to image the brachial artery in the distal third of the upper arm, ensuring that the maximum lumen cross-section was clearly displayed in the cross-sectional view. M-mode imaging was employed to record the motion curves of the vessel’s anterior and posterior walls after 10 minutes of supine rest. Resting systolic (SDr) and diastolic (DDr) diameters of the brachial artery within one cardiac cycle were recorded (Fig. 2B). Subsequently, the cuff was inflated to 200 mmHg and kept inflated for 5 minutes. After cuff deflation, the systolic (SDx) and diastolic (DDx) diameters of the brachial artery were recorded at 30, 60, and 120 seconds using M-mode imaging. All measurements were performed three times in one cardiac cycle, and the median value was taken as the final measurement. Traditional expansion ratios (TER) during systole (TERS) and diastole (TERD), as well as the new expansion ratio (NER), were computed (Fig. 2C). TER was calculated using equations (1) and (2), as follows:
NER was calculated using Eq. (3):
In the above equations, r represents the resting state before cuff occlusion, and x represents 30, 60, or 120 seconds after cuff deflation.
Statistical Analysis
Statistical analysis was conducted using IBM SPSS Statistics for Windows, version 22.0 (IBM Corp., Armonk, NY, USA). Intra-operator reproducibility of hrFMD measurements in the first cohort was assessed using repeated-measures analysis of variance. Systolic diameter (SD) and diastolic diameter (DD) measurements were obtained three times from each of the 10 patients in the first cohort. If the Mauchly sphericity test indicated that the assumption of sphericity was violated, the P-value was corrected using the Greenhouse-Geisser method. Inter-operator reproducibility of hrFMD measurement was evaluated using Bland-Altman analysis (n=30) [26]. Categorical variables in the second cohort were compared using the chi-square test. Continuous variables were assessed for normality: normally distributed data were compared using the Student t-test, while non-normally distributed data were compared with the Mann-Whitney U test. Histograms and line charts were generated to compare NER and TER between groups. Univariable and multivariable analyses were employed to calculate crude and adjusted odds ratios (ORs), respectively, along with their 95% confidence intervals, to assess the predictive value of various parameters for AS risk in this cohort. The variables selected as candidate adjustments in the multivariable model represented major cardiovascular risk factors, including age, sex, body mass index (BMI), fasting blood glucose (FBG), HDL, low-density lipoprotein (LDL), triglyceride (TG), and TC. Statistical significance was set at P<0.05, two-tailed.
Results
Validation of the hrFMD Technique
Patients in the first cohort exhibited notable differences in SD and DD, as determined by repeated-measures analysis of variance (Mauchly sphericity test: all P<0.001; SD, P=0.604; DD, P=0.360; no correction required) (Fig. 3A, B). The inter-patient variations in SD (3.4-4.9 mm) and DD (3.1-4.6 mm) could not be solely attributed to measurement variability or instability (average variability: SD, 0.023±0.029 mm; DD, 0.033±0.050 mm). Furthermore, repeated measurements resulted in consistent SD and DD values (P=0.168 for SD; P=0.223 for DD; no correction required) (Fig. 3A, B). Bland-Altman analysis for inter-operator comparison revealed mean differences of 0.003 mm for SD and -0.020 mm for DD, with 95% limits of agreement of -0.137 to 0.144 mm and -0.150 to 0.110 mm, respectively (Fig. 3C, D). Inter-operator reproducibility for SD and DD measurements showed no significant deviations (Fig. 3C, D). These results indicated satisfactory intra- and inter-operator repeatability of hrFMD measurements.
Clinical Characteristics
The clinical characteristics of the second cohort (n=60) are summarized in Table 1.
The NHT (n=29) and HT (n=31) groups displayed no significant differences in age, sex, BMI, HDL, LDL, TG, TC, FBG, uric acid, serum creatinine, or hemoglobin (all P>0.05). However, compared to the NHT group, the HT group had significantly higher SBP, DBP, mean arterial pressure, and pulse pressure (all P≤0.004).
cIMT and hrFMD Measurements across Groups
Table 2 presents the hrFMD and cIMT measurements from the NHT and HT groups. No significant difference in cIMT was found between the two groups (P=0.091). Additionally, the groups were similar in NER30, NER120, TERS30, TERD30, TERD60, TERS120, and TERD120 (all P>0.05). However, NER60 (P=0.001) and TERS60 (P=0.001) were significantly higher in the NHT group compared to the HT group.
hrFMD Measurements in Relation to Age, cIMT, and SBP
Age is a key independent cardiovascular risk factor for AS assessment. NER60 exhibited a clear negative correlation with age (r=-0.603, P<0.001) (Fig. 4D). However, no significant correlation was found between TERS60 and age (r=0.013, P>0.05) (Fig. 4A). Increased cIMT is an indicator of arterial AS; NER60 was negatively correlated with cIMT (r=-0.328, P=0.011) (Fig. 4E), while no significant correlation was observed between TERS60 and cIMT (r=0.033, P>0.05) (Fig. 4B). Additionally, both TERS60 (r=-0.267, P=0.039) and NER60 (r=-0.277, P=0.032) displayed negative correlations with SBP (Fig. 4C, F).
Extent and Time Phase of NER across Subgroups
The two age subgroups differed significantly in NER30 (P=0.001) (Fig. 5A) and NER60 (P=0.001) (Fig. 5D), but not in NER120 (P=0.964) (Fig. 5G). Similarly, the two cIMT subgroups differed significantly in NER30 (P=0.003) (Fig. 5B) and NER60 (P=0.008) (Fig. 5E), but not in NER120 (P=0.676) (Fig. 5H). The FRS subgroups differed significantly in NER60 (P<0.001) (Fig. 5F), but not in NER30 (P=0.086) (Fig. 5C) or NER120 (P=0.361) (Fig. 5I).
Time-phase analysis in the NHT group indicated that vasodilation peaked within 30 seconds in five individuals (17.2%), within 60 seconds in 22 (75.8%), and within 120 seconds in two (6.8%) (Fig. 6A). In the HT group, vasodilation peaked within 30 seconds in two individuals (6.4%), within 60 seconds in 21 (67.7%), and within 120 seconds in eight (26%) (Fig. 6B).
hrFMD Measurements Predict Atherosclerotic Risk in HT Populations
Using the NHT group as a reference, the univariable analysis showed that NER60 (OR, 0.122; P=0.002) and TERS60 (OR, 0.079; P=0.004) were inversely associated with hypertension, which is linked to ECD and atherosclerotic risk (Table 3). A multivariable model adjusted for age, sex and BMI revealed that NER60 (OR, 0.041; P=0.001) and TERS60 (OR, 0.040, P=0.007) in the HT group were significant predictors of HT-characterized atherosclerotic risk (Table 3). After adjusting for age, sex, BMI, TG, TC, HDL, LDL, and FBG, NER60 (OR, 0.025; P=0.004) and TERS60 (OR, 0.051; P=0.014) remained associated with HT-characterized atherosclerotic risk in the HT group (Table 3).
Discussion
Endothelial cells are known to be impaired across various HT types and durations [27,28]. Using HT-characterized ECD, this study showed that the participants with HT had notably lower arterial vasodilatation, quantified by FMD indices, compared to the NHT group. To the authors’ knowledge, this is the first study assessing the feasibility of using hrFMD with a 24-MHz commercial ultrasound probe to investigate ECD in patients with HT, potentially enabling broader implementation of the FMD technique in routine clinical practice.
Additionally, the present results indicate that hrFMD can reflect ECD, with ORs ranging from 0.025 to 0.122, independently of age, sex, and major cardiovascular risk factors. Aging, the primary risk factor for atherogenesis, is associated with increased ECD and cardiovascular disease incidence [29]. This analysis demonstrated a marked negative correlation between age and NER60, but not between age and TERS60. Furthermore, subgroup analysis by age revealed notably lower NER values, especially NER60, in the older subgroup compared to the younger participants. These findings align with prior studies [29,30] showing a negative association between age and the FMD expansion ratio. Thus, hrFMD could represent a promising tool for assessing ECD in routine clinical practice using a commercial ultrasound device with a high-frequency probe.
A novel finding of this study was the dynamic change in arterial wall distensibility following cuff occlusion release, an aspect not previously demonstrated with conventional FMD [11-13]. The shift in peak distensibility timing confirmed ECD, analogous to diagnosing diabetes based on peak insulin secretion from pancreatic islet cells. Furthermore, the present results showed that 60 seconds post-deflation represented the best time point for assessing hrFMD and NER, as these measurements exhibited stronger correlations with traditional risk factors. The discrepancy may be due to differences in denominators between FMD and hrFMD algorithms. The traditional FMD algorithm uses the baseline diameter as the denominator at all time points, whereas the hrFMD algorithm corrects itself using parameters from the same time point, improving measurement repeatability and stability.
ECD leads to reduced nitric oxide synthesis, increased levels of inflammatory factors, and oxidative stress; these factors promote vessel wall inflammation and lipid deposition, cause cIMT thickening, and elevate the risk of clinical events [11,31]. This study revealed that hrFMD using the NER60 algorithm was negatively correlated with cIMT. Additionally, hrFMD values (NER30 and NER60) in the highc-IMT subgroup were significantly lower than those in the low-cIMT subgroup. This finding is consistent with previous observations [32] that FMD is associated with cIMT and that both parameters predict coronary artery disease. However, possibly due to differences in measurement methods, multiple studies have suggested the absence of a correlation between cIMT and FMD [33,34], which aligns with the present results obtained using the TERS60 and TERD60 algorithms. No significant difference in cIMT was found between the NHT and HT groups, with values falling within the normal range. Therefore, hrFMD, which indirectly reflects ECD, might be more sensitive than cIMT in assessing early AS risk.
The FRS, calculated using cardiovascular risk factors, is the first and most influential risk prediction model. It has been used to estimate 10-year cardiovascular risk in various risk populations [35]. Although the FRS has many advantages, it also has limitations. For example, it classifies asymptomatic middle-aged adults as low risk, even though nearly 60% of them have been found to have subclinical AS [36]. Moreover, the cardiovascular risk factors included in the FRS algorithm are not directly equivalent to true cardiovascular risk factors; rather, they require bridging parameters, such as plaque burden and ECD [37]. In this study, the high-FRS group exhibited a lower hrFMD expansion rate. The difference between low- and high-FRS groups was statistically significant when using the NER60 algorithm, aligning with studies by Sharad et al. [38] and Pastori et al. [35], which demonstrated a significant negative association between FRS and FMD. Moreover, the present study showed that, independently of major cardiovascular risk factors, hrFMD was a good predictor of atherosclerotic risk. This finding implies that routine clinical application of this approach could be used to conveniently assess ECD using hrFMD measurements, providing added value as a novel AS risk assessment system.
The present study had several limitations. First, the sample size was relatively small; therefore, these results should be validated in large-scale multicenter clinical trials. Second, although the study adjusted for common cardiometabolic variables (e.g., age and BMI), other key factors (e.g., antihypertensive or statin drug use, physical activity, and diet) were not included. These omissions could represent sources of residual confounding and may have led to biased results. Third, the observed reduction in hrFMD aligns with the expected decrease in arterial wall compliance in hypertension, attributed to the non-linear pressure-area relationship. This phenomenon was not assessed in the present feasibility study due to the limited sample size. Furthermore, the observed ECD may be due to both arterial wall pathology and reduced reserve in already dilated vessels among HT participants. Future large-scale, multicenter studies that normalize hrFMD by DBP could help disentangle the contributions of intrinsic wall stiffening from ECD in HT participants. Finally, this was a cross-sectional observational study. The inherent limitations of this design therefore preclude the use of its endpoints as a gold standard for assessing atherosclerotic risk [39]. ECD measured by this technique also reflects early-stage AS; thus, the technique is unsuitable for assessing ECD in terminal events.
NER60 obtained via hrFMD was significantly lower in the HT group than in the NHT group, suggesting its potential as a surrogate marker for impaired vascular reactivity related to hypertension. However, further validation against established physiological criteria is required to confirm the effectiveness of this value in directly detecting ECD.
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