论文标题
高分辨率宫颈听觉中的卷积复发性神经网络,食管上括约肌的开放分段
Upper Esophageal Sphincter Opening Segmentation with Convolutional Recurrent Neural Networks in High Resolution Cervical Auscultation
论文作者
论文摘要
上食道括约肌是通常观察到的吞咽过程的重要解剖学标志,这些过程通常通过对易于主观性和临床可行性问题的放射学检查进行运动学分析。上食管括约肌充当食道的门口,可以使摄入的材料从咽部到食管阶段过渡到吞咽的食管阶段,开放时间减少可以导致穿透/吸入和/或咽部残留物。因此,在这项研究中,我们考虑了一种非侵入性的高分辨率宫颈宫颈筛查工具,以近似上食管括约肌开放和闭合的人类评分。从116例患者中收集了燕子,并训练了一个深层神经网络,以产生遮罩,以划定上食管括约肌开放的持续时间。与人类评分相比,即使在独立的临床实验中对人类评分进行了测试,提出的方法达到了90 \%的精度和相似的灵敏度和特异性值。此外,预测的开口和闭合力矩令人惊讶地属于其人类额定级别的同类误差,这表明高分辨率宫颈听觉在取代基于电离的辐射评估吞咽运动学方面的临床意义。
Upper esophageal sphincter is an important anatomical landmark of the swallowing process commonly observed through the kinematic analysis of radiographic examinations that are vulnerable to subjectivity and clinical feasibility issues. Acting as the doorway of esophagus, upper esophageal sphincter allows the transition of ingested materials from pharyngeal into esophageal stages of swallowing and a reduced duration of opening can lead to penetration/aspiration and/or pharyngeal residue. Therefore, in this study we consider a non-invasive high resolution cervical auscultation-based screening tool to approximate the human ratings of upper esophageal sphincter opening and closure. Swallows were collected from 116 patients and a deep neural network was trained to produce a mask that demarcates the duration of upper esophageal sphincter opening. The proposed method achieved more than 90\% accuracy and similar values of sensitivity and specificity when compared to human ratings even when tested over swallows from an independent clinical experiment. Moreover, the predicted opening and closure moments surprisingly fell within an inter-human comparable error of their human rated counterparts which demonstrates the clinical significance of high resolution cervical auscultation in replacing ionizing radiation-based evaluation of swallowing kinematics.