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基于非侵入性传感器的前后上位食管括约肌开口最大扩张估计。

Non-Invasive Sensor-Based Estimation of Anterior-Posterior Upper Esophageal Sphincter Opening Maximal Distension.

机构信息

Department of Biomedical EngineeringCairo University Giza 12613 Egypt.

Department of Electrical and Computer EngineeringSwanson School of EngineeringUniversity of Pittsburgh Pittsburgh PA 15260 USA.

出版信息

IEEE J Transl Eng Health Med. 2023 Feb 20;11:182-190. doi: 10.1109/JTEHM.2023.3246919. eCollection 2023.

Abstract

OBJECTIVE

Dysphagia management relies on the evaluation of the temporospatial kinematic events of swallowing performed in videofluoroscopy (VF) by trained clinicians. The upper esophageal sphincter (UES) opening distension represents one of the important kinematic events that contribute to healthy swallowing. Insufficient distension of UES opening can lead to an accumulation of pharyngeal residue and subsequent aspiration which in turn can lead to adverse outcomes such as pneumonia. VF is usually used for the temporal and spatial evaluation of the UES opening; however, VF is not available in all clinical settings and may be inappropriate or undesirable for some patients. High resolution cervical auscultation (HRCA) is a noninvasive technology that uses neck-attached sensors and machine learning to characterize swallowing physiology by analyzing the swallow-induced vibrations/sounds in the anterior neck region. We investigated the ability of HRCA to noninvasively estimate the maximal distension of anterior-posterior (A-P) UES opening as accurately as the measurements performed by human judges from VF images.

METHODS AND PROCEDURES

Trained judges performed the kinematic measurement of UES opening duration and A-P UES opening maximal distension on 434 swallows collected from 133 patients. We used a hybrid convolutional recurrent neural network supported by attention mechanisms which takes HRCA raw signals as input and estimates the value of the A-P UES opening maximal distension as output.

RESULTS

The proposed network estimated the A-P UES opening maximal distension with an absolute percentage error of 30% or less for more than 64.14% of the swallows in the dataset.

CONCLUSION

This study provides substantial evidence for the feasibility of using HRCA to estimate one of the key spatial kinematic measurements used for dysphagia characterization and management. Clinical and Translational Impact Statement: The findings in this study have a direct impact on dysphagia diagnosis and management through providing a non-invasive and cheap way to estimate one of the most important swallowing kinematics, the UES opening distension, that contributes to safe swallowing. This study, along with other studies that utilize HRCA for swallowing kinematic analysis, paves the way for developing a widely available and easy-to-use tool for dysphagia diagnosis and management.

摘要

目的

吞咽障碍的管理依赖于经过培训的临床医生在视频透视(VF)下对吞咽的时-空运动事件进行评估。UES 开口扩张代表有助于健康吞咽的重要运动事件之一。UES 开口扩张不足可导致咽残留物积聚,继而导致吸入,从而导致肺炎等不良后果。VF 通常用于 UES 开口的时-空评估;然而,并非所有临床环境都可提供 VF,并且对于某些患者来说,VF 可能不适当或不理想。高分辨率颈听诊(HRCA)是一种非侵入性技术,它使用颈部附着的传感器和机器学习通过分析前颈部区域的吞咽诱导振动/声音来表征吞咽生理学。我们研究了 HRCA 无创性估计 UES 前后(A-P)开口最大扩张的能力,其准确性与 VF 图像上由人类判断进行的测量相当。

方法和程序

经过培训的判断者对 133 名患者的 434 次吞咽进行了 UES 开口持续时间和 A-PUES 开口最大扩张的运动测量。我们使用了一种混合卷积递归神经网络,该网络由注意力机制支持,将 HRCA 原始信号作为输入,并估计 A-PUES 开口最大扩张的值作为输出。

结果

该网络对数据集内超过 64.14%的吞咽的 A-PUES 开口最大扩张的估计误差绝对值为 30%或更小。

结论

这项研究为使用 HRCA 估计用于吞咽障碍特征描述和管理的关键空间运动测量之一提供了实质性证据。临床和转化影响陈述:这项研究的发现通过提供一种非侵入性和廉价的方法来估计有助于安全吞咽的最重要的吞咽运动之一,UES 开口扩张,对吞咽障碍的诊断和管理有直接影响。这项研究与其他使用 HRCA 进行吞咽运动分析的研究一起,为开发一种广泛可用且易于使用的吞咽障碍诊断和管理工具铺平了道路。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/97b0/9976940/cc3a416d2c21/sejdi1abcde-3246919.jpg

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