The elasticity of proximal large arteries is determined by a high elastin to collagen ratio, and the increase in arterial stiffness is mostly caused by the progressive elastic fiber degeneration (1, 2). The physical stiffening of arteries eventually increases the risk of cardiovascular (CV) disease, such as systolic hypertension, coronary artery disease, myocardial infarction and stroke (3–5). Aortic pulse wave velocity (PWV) has been considered as one of the most reliable clinical parameters for evaluating arterial stiffness, blood pressure, therapeutic efficacy and CV risk stratification in patients (6, 7). It depends not only on structural changes associated with the elastic modulus of the wall affecting wave propagation but also on aortic pressure, which has a strong direct relationship to stiffness (3).

The PWV is defined by the speed at which a forward pressure wave is transmitted from the aorta through the vascular tree. To estimate PWV (e.g., a few meters per second), the propagating distance and the time of the arterial waveform passing between the two sites are measured, and the carotid-femoral PWV is currently being regarded as the gold standard method (8–10). However, these systemic or regional PWV measurements cannot accurately assess biomechanical properties of vessel segments so that the invasive methods using a pressure catheter are still required for the assessment of local aortic compliance (11, 12). Therefore, several local based PWV measurement techniques have been introduced to noninvasively evaluate aortic segments along the arterial tree.

Cardiovascular magnetic resonance (CMR) based PWV assessment substantially reduces errors by using accurate aortic length and transit times between flow waves (13, 14). Doppler ultrasound or pulse wave imaging with electrocardiogram (ECG) synchronization allows the estimation of PWV values using the time delay between two close positions during a cardiac cycle along the vessels (15–17). However, these approaches suffer from a relatively low frame rate compared to PWV. To improve accuracy diminished by limited temporal resolution, a plane wave transmission based ultrafast PWV measurement method was recently proposed and it showed a real-time direct measurement of local PWV with high spatiotemporal resolution (18–21). With the advantages of simplicity and accessibility, it has been extensively studied for various clinical usages, such as carotid stiffness assessment (22–27).

From the previous studies, a local PWV measurement technique based on high spatiotemporal resolution is strongly required, and the ultrafast PWV measurement for aortic segments in human abdomen are still rarely studied due to low accessibility and technical limitations, such as a deep and wide field-of-view (FOV). Here, we propose a high spatiotemporal resolution aortic PWV measurement method based on wide FOV ultrafast curved array imaging (28) using diverging wave transmission (ufcPWV). In addition, a new aortic wall motion tracking algorithm based on adaptive reference frame update was also conducted to compensate errors from temporally accumulated out-of-plane motion. Using the proposed method, a feasibility study to investigate the correlation between PWV for abdominal aorta and a CV risk model was performed. The aortic central pressure waveform was simultaneously measured by the applanation tonometer, and a theoretical PWV based on Bramwell-Hill model (bhPWV) (29) was derived. The CV risk model was classified into three groups based on the Framingham risk score (FRS), which is one of the scoring systems used to estimate the 10-year CV risk (30), i.e., low-risk (<10%), intermediate-risk (10~20%) and high-risk (>20%). We hypothesized that aortic ufcPWV is associated with the Framingham risk model.

Pulse waves are propagated through arteries, and PWV is affected by the mechanical properties in the pathological process of arterial wall changes along the arterial system. Therefore, PWV is not constant and varies from one location to another since the geometrical and mechanical properties vary along the arterial tree, and there are differences between central elastic arteries and more peripheral, muscular arteries. For these reasons, the importance of measuring local PWV is increasing in contrast to measuring systemic PWV, which can only be estimated an averaged PWV. For example, aortic PWV, which is one of the most reliable clinical parameters for evaluating arterial stiffness, has been generally measured in two different sites (e.g., carotid and femoral arteries). The carotid-femoral PWV measurement is currently accepted as the gold-standard technique for arterial stiffness assessments. For carotid-femoral PWV measurements, several tonometry techniques based on pressure sensors with ECG gating (e.g., PulsePen, Complior and SphygmoCor) have been widely used in research and clinical settings (11). However, distance measurements of the pulse wave pathway are approximately estimated with the sensor location on the body surface, thus causing a crucial systemic error in the PWV measurements. To overcome this limitation, local PWV measurement methods through direct visualization of local vessels have been introduced based on ultrasound or MRI imaging techniques. The ultrasound technique allows the determination of the PWV by estimating the time delay between the diameter waveforms at two close positions in a local site, e.g., Doppler-derived PWV, flow-area method and pulse wave imaging (15–17, 38). The MRI-based PWV estimation uses the accurate and direct measurement of the path length of pulse waves between two imaging levels and provides aortic vascular parameters (aortic distensibility, aortic compliance, aortic elastic modulus and aortic stiffness index) (39, 40). These imaging-guided PWV measurements take advantage of the direct measurement for the pulse wave pathway and can avoid the systemic error induced by the coarse estimation of distance.

A major advantage of the local measurement of PWV is that a direct measurement of local vessels is strongly related to wall stiffness. In the early stage of arterial stiffness, the elastic properties are affected by locally scattered fibrous spots on the arterial wall, and the heterogeneous structure of arterial walls at different sites produces different functional properties between vessel segments. Regarding strongly localized wall heterogeneity, arterial wall mechanical properties can be dramatically altered within a small region (from a few millimeters to a few centimeters), e.g., abdominal aortic aneurysms or arterial plaques. However, the most current PWV measurements (e.g., carotid-femoral PWV) cannot assess biomechanical properties in local vessels, and they cannot directly evaluate the arterial stiffness of vessel segments due to the accessibility and the limited temporal resolution of the techniques. The temporal resolution (i.e., frame-rate) is the most significant technical factor in the PWV measurements. To properly snapshot the accelerated pulse wave (5~10 m/s), data acquisition rates must be increased relative to the PWV. However, the accuracy and reliability of the PWV measurement approaches usually suffer from an inherent technical tradeoff between spatial resolution (image quality) and temporal resolution (frame rate). Inaccurate measurements imposed by frame-rate limitations can increase errors as the PWV increases by arterial stiffening. Therefore, a high-frame-rate-based accurate PWV measurement technique is still required.

The FRS, which estimates the 10-year CV risk of an individual, is calculated based on a variety of risk factors such as age, smoking history, diabetes mellitus, systolic blood pressure, HDL-C concentration. The FRS is considered as a useful tool for quantitative assessment of the risk for CV disease in the general populations (30, 41–43) and it can be closely related to PWV since both FRS and PWV are widely used as surrogate markers to predict future CV disease by quantifying total CV risk. However, the correlation between FRS and PWV is rarely reported although it has potentials to develop into a more powerful biomarker for CV risk prediction (6, 44–46).

In this article, we investigated the association between the Framingham risk model classified with FRS and aortic PWV. To measure local PWV in a specific aortic segment (i.e., abdominal aorta) with high spatiotemporal resolution (>1 kHz), wide field-of-view ultrafast curved array imaging based PWV measurement method (ufcPWV) was proposed (Figure 1). In the result for the three risk groups (Figure 2), the ufcPWV showed a statistically significant difference between low- and intermediate-risk, and low- and high-risk groups, but there is no significant difference between intermediate- and high-risk groups. To compensate this factor, two evaluation groups consisting of the low- (FRS <10%) and the higher-risk group (FRS ≥ 10%) were additionally assessed, and it showed a highly significant difference in both bhPWV and ufcPWV (Figure 2). The additional analysis to investigate the direct correlation between FRS and ufcPWV was performed, and only the low- and the higher-risk groups showed a significant correlation with different increments of PWV (Figure 3). The direct association between FRS and aortic PWV should be more investigated with large populations.

The association between aortic PWV and systolic blood pressure among the clinical parameters (Table 1) was additionally evaluated since the systolic blood pressure is one of the mostly contributing factors to PWV (47). In the assessment for all subjects, the ufcPWV and systolic blood pressure showed a significant relationship, as illustrated in Figure 4A. However, in the analysis according to the CV risk model, only the intermediate and high-risk groups showed a significant association between the two parameters although the groups of the systolic blood pressure showed no significant differences (Table 1). It means that aortic PWV in higher risk group may be correlated with CV risk independently of the systolic blood pressure, but it should be investigated with more obvious control groups as well as large populations.

One of the limitations of this study is the lack of comparison with carotid-femoral PWV based on tonometry, which is the most validated technique to estimate arterial stiffness and correlated with CV risk (48). A validation study between carotid-femoral PWV and local ufcPWV may further improve an aortic PWV as a useful biomarker for predicting CV risk. The other limitation is that any tags for the same scanning site (i.e., abdominal aorta) were not utilized during examinations although patients in the supine position were basically scanned by experienced sonographers. In addition, there was no assessment of intra- and inter-observer variability in PWV measurements. A number of data sets in the intermediate- (n = 9) and the high-risk (n = 15) groups (Table 1) were excluded due to poor image quality or a history of CV disease. The main cause for the deterioration of image quality may be due to the degradation in receive beamforming since a thick layer of fat in obese patients incurs severe phase aberration. Furthermore, linear regression with r² < 0.5 was considered unreliable and the corresponding PWV estimate would be rejected.

For the future PWV measurements, relatively inexpensive techniques with fewer approximations, leading to an accurate evaluation, will be needed for the more efficient diagnostic tool in detecting CV diseases in early stages. In addition, highly accurate PWV measurements and direct arterial stiffness assessments may also improve the management of the process of CV risks or the monitoring of therapy in patients with conditions such as isolated systolic hypertension. In future work, aortic PWVs in different segmental regions (e.g., ascending aorta, arch of aorta and descending aorta) will be measured and evaluated in various clinical settings (e.g., atherosclerosis).

In this paper, a high-spatiotemporal resolution aortic PWV measurement method based on ultrafast curved array imaging (ufcPWV) was proposed and it showed the association with Framingham risk model. This feasibility study demonstrated that the ufcPWV measurement has the potential to be a new approach to overcome the limitations of conventional systemic measurement methods in the assessment of aortic stiffness.

The original contributions presented in the study are included in the article/supplementary material, further inquiries can be directed to the corresponding author.

The studies involving human participants were reviewed and approved by Institutional Review Board of the Clinical Trials Center of Yonsei University Health System (IRB number: 1-2019-0065). The patients/participants provided their written informed consent to participate in this study.

JK and KH performed the theoretical and experimental analyses and implementation of the in vivo study. JH and G-RH designed the clinical study protocol and obtained data from patients. G-RH and YY supervised the study. JK, G-RH, and YY wrote the manuscript. All authors contributed to the article and approved the submitted version.

This work was supported by the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIT) (NRF-2021R1A2C3006264) and the Korea Medical Device Development Fund grant funded by the Korea government (the Ministry of Science and ICT, the Ministry of Trade, Industry and Energy, the Ministry of Health & Welfare, and the Ministry of Food and Drug Safety) (Project Number: 202011A01).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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