感兴趣区域
背
选择(遗传算法)
电阻抗断层成像
通风(建筑)
生物医学工程
人工智能
计算机科学
生物系统
模式识别(心理学)
电阻抗
物理
解剖
医学
生物
热力学
量子力学
作者
Juliette E. Francovich,Peter Somhorst,Diederik Gommers,Henrik Endeman,Annemijn H. Jonkman
出处
期刊:Physiological Measurement
[IOP Publishing]
日期:2024-09-24
标识
DOI:10.1088/1361-6579/ad7f1f
摘要
Abstract Objective:
Geometrical region of interest (ROI) selection in electrical impedance tomography (EIT) monitoring may lack sensitivity to subtle changes in ventilation distribution. Therefore, we demonstrate a new physiological method for ROI definition. This is relevant when using ROIs to compute subsequent EIT-parameters, such as the ventral-to-dorsal ratio during a positive end-expiratory pressure (PEEP) trial. 

Approach:
Our physiological approach divides an EIT image to ensure exactly 50% tidal impedance variation in the ventral and dorsal region. To demonstrate the effects of our new method, EIT measurements during a decremental PEEP trial in 49 mechanically ventilated ICU-patients were used. We compared the center of ventilation (CoV), a robust parameter for changes in ventro-dorsal ventilation distribution, to our physiological ROI selection method and different commonly used ROI selection methods. Moreover, we determined the impact of different ROI selection methods on the PEEP level corresponding to a ventral-to-dorsal ratio closest to 1.

Main results:
The division line separating the ventral and dorsal ROI was closer to the CoV for our new physiological method for ROI selection compared to geometrical ROI definition. Moreover, the PEEP level corresponding to a ventral-to-dorsal ratio of 1 is strongly influenced by the chosen ROI selection method, which could have a profound clinical impact; the within-subject range of PEEP level was 6.2 cmH2O depending on the chosen ROI selection method.

Significance:
Our novel physiological method for ROI definition is sensitive to subtle ventilation-induced changes in regional impedance (i.e. due to (de)recruitment) during mechanical ventilation, similar to the CoV. 

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