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Ultrafast ultrasound shear wave elastography: a novel approach for assessing myocardial stiffening in congenital aortic stenosis.

📚 期刊: Open heart 📅 发表: 0000-00-00 🔬 PMID: 42320977 🔗 DOI: 10.1136/openhrt-2026-004146 👁️ 浏览: 3

👤 作者: Zwaan RR, Keuning ZA, Loff Barreto B, Bowen DJ, van Dalen BM, Hirsch A, Roos-Hesselink JW, Vos HJ, van den Bosch AE

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📝 摘要

BACKGROUND: Congenital aortic stenosis (ConAoS) accounts for approximately 4%-8% of all congenital heart diseases. Chronic pressure overload may result in myocardial stiffening, leading to impaired cardiac filling, reduced contractility and ultimately contributing to the onset of symptomatic heart failure. Shear wave elastography (SWE), using high-frame-rate echocardiography, allows visualisation of myocardial shear waves. By measuring shear wave propagation velocity (SWV), this technique may enable non-invasive assessment of myocardial stiffness. This study aimed to explore the feasibility of SWE in adults with ConAoS and to compare SWV with healthy volunteers (HVs). METHODS: In 68 adult patients with ConAoS-including 17 patients after aortic valve replacement (AVR)-and 19 HVs, high-frame-rate recordings were acquired in the parasternal long-axis view. Custom software was used to measure SWV by manually placing M-mode lines through the interventricular septum after aortic valve closure. RESULTS: SWE feasibility was 73% in ConAoS patients with a native aortic valve (NV), 53% post-AVR and 100% in HVs. Median SWV was 4.7 m/s (3.2-5.5) in NV patients, 3.7 m/s (3.1-5.4) post-AVR and 3.4 m/s (3.0-4.4) in HVs (p=0.200). Patients with moderate-to-severe ConAoS demonstrated higher SWV compared with HVs (4.7 m/s (3.4-5.6) vs 3.4 m/s (3.0-4.4); p=0.035). CONCLUSIONS: SWE is feasible in the majority of ConAoS patients. Higher SWV in moderate-to-severe ConAoS patients, despite preserved diastolic function in most cases, may reflect early myocardial mechanical alterations and provide a promising non-invasive marker for myocardial stiffening. Further technical optimisation and cross-platform validation are essential for clinical translation.
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