Electrical impedance tomography in neonatal respiratory diseases: a clinical review of applications and evidence.
4 affiliations
- 1Department of Pediatrics, Tangdu Hospital, Air Force Medical University, Fourth Military Medical University, Xin-Si Street #569, Xi'an, 710038, China.
- 2The Second Clinical Medical College of Shaanxi University of Chinese Medicine, Xianyang, 712046, China.
- 3Biomedical Engineering, Air Force Medical University, Fourth Military Medical University, Chang-Le Street #169, Xi'an, 710038, China.
- 4Department of Pediatrics, Tangdu Hospital, Air Force Medical University, Fourth Military Medical University, Xin-Si Street #569, Xi'an, 710038, China. [email protected].
Abstract
Neonatal respiratory diseases remain a leading cause of morbidity and mortality in intensive care settings, with management complicated by the limitations of current monitoring tools. Chest radiography provides only static snapshots and cannot capture the dynamic evolution of lung aeration, while lung ultrasound, though portable, remains operator-dependent and incapable of quantifying regional ventilation. Electrical Impedance Tomography (EIT) has emerged as a noninvasive, radiation free imaging modality that addresses these gaps by enabling real time, continuous visualization of regional lung function at the bedside. This review synthesises evidence from studies published between 2011 and 2026, examining how EIT informs the management of neonatal respiratory distress syndrome, acute respiratory distress syndrome, bronchopulmonary dysplasia, pneumothorax, and the transitions inherent to mechanical ventilation. Across these disease contexts, EIT reveals regional ventilation heterogeneity invisible to conventional monitors, provides immediate physiological feedback during therapeutic interventions, and enables early detection of complications before clinical deterioration. We identify key barriers to clinical adoption, including technical limitations, lack of standardised protocols, and the need for outcome driven trials, and propose a research agenda to accelerate translation. By reframing EIT not merely as an imaging tool but as a dynamic decision support system integrated into clinical workflows, we aim to provide clinicians with a framework for leveraging this technology to improve outcomes in the most vulnerable patients.
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BibTeX
@article{wang2026electrical,
title = {{Electrical impedance tomography in neonatal respiratory diseases: a clinical review of applications and evidence.}},
author = {Yifan Wang and Yaping Song and Caiju Xing and Feng Fu and Xun Jiang and Yan Lin},
journal = {Respiratory research},
year = {2026},
month = jul,
doi = {10.1186/s12931-026-03838-5},
url = {https://europepmc.org/article/MED/42897548},
note = {CC BY-NC-ND},
}
RIS
TY - JOUR
TI - Electrical impedance tomography in neonatal respiratory diseases: a clinical review of applications and evidence.
AU - Yifan Wang
AU - Yaping Song
AU - Caiju Xing
AU - Feng Fu
AU - Xun Jiang
AU - Yan Lin
PY - 2026
DA - 2026/07/01
JO - Respiratory research
DO - 10.1186/s12931-026-03838-5
UR - https://europepmc.org/article/MED/42897548
AB - Neonatal respiratory diseases remain a leading cause of morbidity and mortality in intensive care settings, with management complicated by the limitations of current monitoring tools. Chest radiography provides only static snapshots and cannot capture the dynamic evolution of lung aeration, while lung ultrasound, though portable, remains operator-dependent and incapable of quantifying regional ventilation. Electrical Impedance Tomography (EIT) has emerged as a noninvasive, radiation free imaging modality that addresses these gaps by enabling real time, continuous visualization of regional lung function at the bedside. This review synthesises evidence from studies published between 2011 and 2026, examining how EIT informs the management of neonatal respiratory distress syndrome, acute respiratory distress syndrome, bronchopulmonary dysplasia, pneumothorax, and the transitions inherent to mechanical ventilation. Across these disease contexts, EIT reveals regional ventilation heterogeneity invisible to conventional monitors, provides immediate physiological feedback during therapeutic interventions, and enables early detection of complications before clinical deterioration. We identify key barriers to clinical adoption, including technical limitations, lack of standardised protocols, and the need for outcome driven trials, and propose a research agenda to accelerate translation. By reframing EIT not merely as an imaging tool but as a dynamic decision support system integrated into clinical workflows, we aim to provide clinicians with a framework for leveraging this technology to improve outcomes in the most vulnerable patients.
SN - 1465-9921
SN - 1465-993X
ER -