应用下腔静脉半自动边缘追踪超声心动图多参数法评估右心房压力的准确性：心血管疾病患者的初步研究。
Accuracy of right atrial pressure estimation using a multi-parameter approach derived from inferior vena cava semi-automated edge-tracking echocardiography: a pilot study in patients with cardiovascular disorders.
机构信息
Cardiothoracic Department, Division of Cardiology and Postgraduate School in Cardiovascular Sciences, University of Trieste, Trieste, Italy.
Mathematical Biology and Physiology, Department of Electronics and Telecommunications, Politecnico di Torino, Turin, Italy.
出版信息
Int J Cardiovasc Imaging. 2020 Jul;36(7):1213-1225. doi: 10.1007/s10554-020-01814-8. Epub 2020 Mar 19.
The echocardiographic estimation of right atrial pressure (RAP) is based on the size and inspiratory collapse of the inferior vena cava (IVC). However, this method has proven to have limits of reliability. The aim of this study is to assess feasibility and accuracy of a new semi-automated approach to estimate RAP. Standard acquired echocardiographic images were processed with a semi-automated technique. Indexes related to the collapsibility of the vessel during inspiration (Caval Index, CI) and new indexes of pulsatility, obtained considering only the stimulation due to either respiration (Respiratory Caval Index, RCI) or heartbeats (Cardiac Caval Index, CCI) were derived. Binary Tree Models (BTM) were then developed to estimate either 3 or 5 RAP classes (BTM3 and BTM5) using indexes estimated by the semi-automated technique. These BTMs were compared with two standard estimation (SE) echocardiographic methods, indicated as A and B, distinguishing among 3 and 5 RAP classes, respectively. Direct RAP measurements obtained during a right heart catheterization (RHC) were used as reference. 62 consecutive 'all-comers' patients that had a RHC were enrolled; 13 patients were excluded for technical reasons. Therefore 49 patients were included in this study (mean age 62.2 ± 15.2 years, 75.5% pulmonary hypertension, 34.7% severe left ventricular dysfunction and 51% right ventricular dysfunction). The SE methods showed poor accuracy for RAP estimation (method A: misclassification error, ME = 51%, R = 0.22; method B: ME = 69%, R = 0.26). Instead, the new semi-automated methods BTM3 and BTM5 have higher accuracy (ME = 14%, R = 0.47 and ME = 22%, R = 0.61, respectively). In conclusion, a multi-parametric approach using IVC indexes extracted by the semi-automated approach is a promising tool for a more accurate estimation of RAP.
超声心动图估计右心房压（RAP）基于下腔静脉（IVC）的大小和吸气塌陷。然而，这种方法已被证明存在可靠性限制。本研究旨在评估一种新的半自动方法估计 RAP 的可行性和准确性。使用半自动技术处理标准采集的超声心动图图像。在吸气过程中考虑到血管塌陷的相关指数（Caval Index，CI）和新的脉动指数，仅考虑呼吸（Respiratory Caval Index，RCI）或心跳（Cardiac Caval Index，CCI）引起的刺激来获得。然后，使用半自动技术估计的指数开发二叉树模型（BTM）来估计 3 个或 5 个 RAP 类别（BTM3 和 BTM5）。然后，将这些 BTM 与两种标准估计（SE）超声心动图方法进行比较，分别表示为 A 和 B，区分 3 个和 5 个 RAP 类别。使用右心导管检查（RHC）期间获得的直接 RAP 测量值作为参考。纳入了 62 例连续的“所有患者”，因技术原因排除了 13 例。因此，本研究纳入了 49 例患者（平均年龄 62.2±15.2 岁，75.5%肺动脉高压，34.7%严重左心室功能障碍和 51%右心室功能障碍）。SE 方法对 RAP 估计的准确性较差（方法 A：错误分类错误，ME=51%，R=0.22；方法 B：ME=69%，R=0.26）。相反，新的半自动方法 BTM3 和 BTM5 具有更高的准确性（ME=14%，R=0.47 和 ME=22%，R=0.61）。总之，使用半自动方法提取 IVC 指数的多参数方法是更准确估计 RAP 的有前途的工具。
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