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机械瓣膜状态和负荷的声学特性分析

Acoustic characterization of mechanical valve condition and loading.

作者信息

Eberhardt A C, Chassaing C E, Ward M A, Lewandowski S J

机构信息

Structural Acoustics, Inc., Raleigh, North Carolina 27612, USA.

出版信息

J Heart Valve Dis. 1995 Nov;4(6):649-58; discussion 658-9.

PMID:8611981
Abstract

Both closing dynamics and the mechanical condition of a Björk-Shiley Convexo-Concave (BSCC) valve are significant in assessing the risks of outlet strut fracture. Risk of fracture increases with the presence of a pre-existing fracture in one of the two strut legs and with magnitude and frequency of loading. Recent analyses of in vivo data collected in clinical studies, and in vitro data from a computer-controlled pulse duplicator, indicate that the condition of an outlet strut can be evaluated by non-invasive passive acoustic measurement. The technique utilizes heuristic methods to identify features in time and frequency in the closing sound of BSCC valves. Because of patient-to-patient and beat-to-beat variability in the waveforms of closing sounds, the sound of beats are cross-correlated to identify thirteen characteristic waveform groups that are independent of valve strut condition. The groups are used for subsequent acceptance of each closing event. For each group, a Mahalanobis distance technique is used to identify features in time and frequency that characterize the mechanical condition of the BSCC valve. A Volterra expansion is used to optimize the features. A similar approach, where strain gages supply the measured strut load, is used to identify features associated with valve closing load, and to predict outlet strut forces on a beat-for-beat basis in vitro and in sheep. The characterization is based on a set of acoustic recordings made on patients prior to explant of each valve. Analysis is made using blinded and leave-one-out methods, preventing overlap between the data used in training and that used in testing. Results have demonstrated a sensitivity and specificity to strut fracture of 100 percent on a group of 33 patients for whom gold standard data was available. Analysis of additional blinded data will be useful to further quantify the robustness of the detection method. The relative ease with which data can be collected, and the excellent results, indicate that the method may develop into a practical and effective screen for outlet strut condition.

摘要

在评估Björk-Shiley凸凹型(BSCC)瓣膜出口支柱骨折风险时,瓣膜的关闭动态及机械状况均具有重要意义。骨折风险会随着两个支柱腿之一预先存在骨折、负荷大小及频率的增加而升高。近期对临床研究收集的体内数据以及计算机控制脉冲复制器的体外数据进行的分析表明,出口支柱的状况可通过非侵入性被动声学测量来评估。该技术利用启发式方法识别BSCC瓣膜关闭声音在时间和频率上的特征。由于关闭声音波形在患者之间以及心搏之间存在变异性,因此对心搏声音进行互相关以识别与瓣膜支柱状况无关的13个特征波形组。这些组用于后续对每个关闭事件的验收。对于每组,使用马氏距离技术来识别表征BSCC瓣膜机械状况的时间和频率特征。使用沃尔泰拉展开来优化这些特征。一种类似的方法(使用应变片提供测量的支柱负荷)用于识别与瓣膜关闭负荷相关的特征,并在体外和绵羊体内逐搏预测出口支柱力。这种表征基于在每个瓣膜取出前对患者进行的一组声学记录。分析采用盲法和留一法,防止训练数据和测试数据之间出现重叠。结果表明,对于一组有金标准数据的33名患者,对支柱骨折的敏感性和特异性均为100%。对其他盲法数据的分析将有助于进一步量化检测方法的稳健性。数据收集的相对简便性以及出色的结果表明,该方法可能发展成为一种实用且有效的出口支柱状况筛查方法。

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