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Updated: Jul 12, 2026
Measuring the Carotid to Femoral Pulse Wave Velocity (Cf-PWV) to Evaluate Arterial Stiffness
Published on: May 3, 2018
Carotid stiffness quantified through shear wave elastography and pulse wave velocity by ultrafast ultrasound for
Xuehui Ma1, Zhengqiu Zhu1, Yinping Wang1
1Department of Ultrasound, Affiliated Hospital of Nanjing University of Chinese Medicine, Jiangsu Province Hospital of Chinese Medicine, Nanjing, China.
Background:
Carotid arterial stiffness is closely linked to cardiovascular (CV) events. Traditional evaluation methods have limitations in detecting early vascular lesions and do not adequately capture regional elastic changes. Real-time shear wave elastography (RT-SWE) can quantify local carotid stiffness, while ultrafast pulse wave velocity (ufPWV) provides regional stiffness assessment. However, the value of integrating these two modalities for improving CV risk assessment has not been established. Therefore, this study aimed to improve CV risk assessment by integrating RT-SWE and ufPWV carotid artery parameters.
Methods:
We divided 88 patients into control [no major cardiovascular risk factors (CVRFs); n=20] and CV risk groups (hypertension, diabetes, dyslipidemia, or smoking; n=68). Carotid intima-media thickness (cIMT), pulse wave velocity (PWV) at systole beginning (PWV-BS) and end (PWV-ES), and elastic moduli (Emean, Emax, Emin, Esd) were measured via ultrasound. Between-group comparisons, correlation analysis, analysis of covariance (ANCOVA) for age adjustment, univariate and multivariable logistic regression, and receiver operating characteristic (ROC) analysis were performed.
Results:
Carotid elasticity parameters in RT-SWE and ufPWV (PWV-BS, PWV-ES, Emax, and Esd) were age-related (r=0.245-0.338, P<0.05). PWV-ES, Emean, Emax, and Esd were significantly higher in the CV risk group (P<0.05), with Emean, Emax, and PWV-ES remaining significantly elevated after age adjustment using ANCOVA (P<0.05). Univariate analysis showed that PWV-ES, Emean, Emax, and Esd all predicted CV risk (all P<0.05). PWV-ES yielded the highest predictive efficacy, with an area under the curve (AUC) of 0.753. The combined model (PWV-ES + Emean + Emax) achieved an AUC of 0.863, significantly outperforming single-parameter models.
Conclusions:
Carotid elasticity measured by RT-SWE is closely associated with carotid stiffness measured by ufPWV. A combined model integrating RT-SWE and ufPWV provides a promising noninvasive approach for CV risk stratification. Notably, following age adjustment using ANCOVA, Emax (P=0.009), Emean (P=0.047), and PWV-ES (P=0.046) retained independent associations with CV risk, underscoring their incremental prognostic value beyond the effects of vascular aging.
