Relationship between lung ultrasound and electrical impedance tomography as regional assessment tools during PEEP titration in acute respiratory distress syndrome caused by multi-lobar pneumonia: a pilot study.
Pongdhep TheerawitPirun PukapongYuda SutherasanPublished in: Journal of clinical monitoring and computing (2023)
Acute respiratory distress syndrome (ARDS) caused by multilobar pneumonia (MLP) is markedly different from typical ARDS in pathology, imaging characteristics, and lung mechanics. Regional lung assessment is required. We aimed to analyze the relationship between two regional assessment tools, lung ultrasound (LUS) and electrical impedance tomography (EIT) during positive end-expiratory pressure (PEEP) titration, and determine an appropriate PEEP level. We conducted a prospective study of patients with ARDS caused by MLP with PaO 2 /FiO 2 < 150 mmHg. All subjects were equipped with two EIT belts connected with a single EIT machine to measure upper and lower hemithorax impedance change alternatingly at each PEEP level. LUS score was simultaneously determined in chest wall regions corresponding to the EIT regions during PEEP titration. We acquired EIT and LUS data in eight regions of interest at seven PEEP levels in 12 subjects. Therefore, 672 pairs of data were obtained for analysis. There were significant relationships between LUS score and tidal impedance variation and pixel compliance (C pix ). The Spearman's rho between LUS score vs. tidal impedance variation and LUS score vs. the C pix were - 0.142, P < 0.001, and - 0.195, P < 0.001, respectively. The relationship between the LUS score and C pix remained the same at every PEEP level but did not reach statistical significance. The individual's mean expected PEEP by LUS was similar to the EIT [10.33(± 1.67) vs. 10.33(± 1.44) cm H 2 O, P = 0.15]. Regarding the MLP, the LUS scores were associated with EIT parameters, and LUS scores might proof helpful for finding individual PEEP settings in MLP.
Keyphrases
- acute respiratory distress syndrome
- mechanical ventilation
- extracorporeal membrane oxygenation
- magnetic resonance imaging
- respiratory failure
- electronic health record
- dual energy
- computed tomography
- intensive care unit
- big data
- machine learning
- carbon dioxide
- fluorescence imaging
- community acquired pneumonia
- contrast enhanced