一种新的数值方法来解释超声造影剂测量门静脉压力的实验散射。

IF 1.7 4区 医学 Q3 ENGINEERING, BIOMEDICAL
Senthil Kumar Palani, Srinivasan Echchur Rangarajan, Arun K Thittai, Krishna Kumar Ramarathnam
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引用次数: 0

摘要

超声造影剂(UCAs)用于估计门静脉压力最近因其临床前景而受到关注,但声学振幅的变异性带来了挑战。uca含有微泡(直径1-10微米),了解它们的声学响应对于解决这种可变性至关重要。然而,目前文献中对影响微泡行为的因素的系统探索仍然有限。本文介绍了一种新的基于有限元分析的门户压力估算框架,弥补了关键的空白。该模型分两个阶段开发,首先捕获单个气泡对4 MHz 50 kPa声激励的次谐波响应,突出气泡大小对共振频率的影响。在第二阶段,将单泡响应扩展到分析微泡数量、大小和空间分布如何影响门户压力估计。本研究首次通过综合考虑这些变量阐明了压力测量中的实验散点,为基于uca的临床压力估计在门静脉和心脏压力评估等应用中提供了新的方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A novel numerical approach to elucidate experimental scatter in portal pressure measurement using ultrasound contrast agent.

The use of ultrasound contrast agents (UCAs) for estimating portal pressure has recently gained attention due to its clinical promise, yet variability in acoustic amplitude poses challenges. UCAs contain microbubbles (1-10 µm in diameter), and understanding their acoustic response is essential to address this variability. However, systematic exploration of factors influencing microbubble behavior remains limited in current literature. This paper introduces a novel finite element analysis-based framework for portal pressure estimation, bridging key gaps. Developed in two stages, the model first captures the subharmonic response of a single bubble to an acoustic excitation of 50 kPa at 4 MHz, highlighting the influence of bubble size on resonance frequency. In the second stage, single-bubble responses are extended to analyze how microbubble population, size, and spatial distribution affect portal pressure estimation. For the first time, this study elucidates the experimental scatter in pressure measurements through a comprehensive consideration of these variables, offering new directions for UCA-based clinical pressure estimation in applications such as portal and cardiac pressure assessment.

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来源期刊
CiteScore
3.60
自引率
5.60%
发文量
122
审稿时长
6 months
期刊介绍: The Journal of Engineering in Medicine is an interdisciplinary journal encompassing all aspects of engineering in medicine. The Journal is a vital tool for maintaining an understanding of the newest techniques and research in medical engineering.
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