Evidence map›Paper›PMID 31345220›Full record

ArticleBiomedical engineering online2019

Integrated EIT system for functional lung ventilation imaging.

Geuk Young Jang, Ghazal Ayoub, Young Eun Kim, Tong In Oh, Chi Ryang Chung, Gee Young Suh, Eung Je Woo

Open access · goldAbstract read
In one paragraph

Article in Biomedical engineering online, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.

0numbers the graph read from it
0cells of the map it votes in
11citing papers in PubMed
1.9field-weighted citation impact, top 13% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

11 citing papers in PubMed, 31 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 3 institutions in 1 country.

Geuk Young JangDepartment of Biomedical Engineering, Graduate School, Kyung Hee University, Yongin, South Korea.
Ghazal AyoubDepartment of Biomedical Engineering, Graduate School, Kyung Hee University, Yongin, South Korea.
Young Eun KimDepartment of Biomedical Engineering, College of Medicine, Kyung Hee University, Seoul, South Korea.
Tong In OhDepartment of Biomedical Engineering, College of Medicine, Kyung Hee University, Seoul, South Korea. tioh@khu.ac.kr.ORCID http://orcid.org/0000-0003-3820-0107
Chi Ryang ChungDepartment of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Gee Young SuhDepartment of Critical Care Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, South Korea.
Eung Je WooDepartment of Biomedical Engineering, College of Medicine, Kyung Hee University, Seoul, South Korea.
Kyung Hee University · KRSamsung Medical Center · KRKyung Hee Cyber University · KR

Funding

Ministry of Health and Welfare HI14C0743National Research Foundation of Korea NRF-2017R1A2B2002169
6 · The paper itself

Abstract

backgroundElectrical impedance tomography (EIT) has been used for functional lung imaging of regional air distributions during mechanical ventilation in intensive care units (ICU). From numerous clinical and animal studies focusing on specific lung functions, a consensus about how to use the EIT technique has been formed lately. We present an integrated EIT system implementing the functions proposed in the consensus. The integrated EIT system could improve the usefulness when monitoring of mechanical ventilation for lung protection so that it could facilitate the clinical acceptance of this new technique.

methodsUsing a custom-designed 16-channel EIT system with 50 frames/s temporal resolution, the integrated EIT system software was developed to implement five functional images and six EIT measures that can be observed in real-time screen view and analysis screen view mode, respectively. We evaluated the performance of the integrated EIT system with ten mechanically ventilated porcine subjects in normal and disease models.

resultsQuantitative and simultaneous imaging of tidal volume (TV), end-expiratory lung volume change ([Formula: see text]EELV), compliance, ventilation delay, and overdistension/collapse images were performed. Clinically useful parameters were successfully extracted including anterior/posterior ventilation ratio (A/P ratio), center of ventilation ([Formula: see text], [Formula: see text]), global inhomogeneity (GI), coefficient of variation (CV), ventilation delay and percentile of overdistension/collapse. The integrated EIT system was demonstrated to suggest an optimal positive end-expiratory pressure (PEEP) for lung protective ventilation in normal and in the disease model of an acute injury. Optimal PEEP for normal and disease model was 2.3 and [Formula: see text], respectively.

conclusionsThe proposed integrated approach for functional lung ventilation imaging could facilitate clinical acceptance of the bedside EIT imaging method in ICU. Future clinical studies of applying the proposed methods to human subjects are needed to show the clinical significance of the method for lung protective mechanical ventilation and mechanical ventilator weaning in ICU.

Indexed as

Pulmonary VentilationAnimalsElectric ImpedanceLungSoftwareSwineTidal VolumeTomographyElectrical impedance tomographyFunctional lung ventilation imagingIntegrated approachMechanical ventilationReal-time bedside imaging

Identifiers

PMID31345220
PMCPMC6659234
OpenAlexW2963437804

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.