In a groundbreaking study published in the Journal of Perinatology in early 2026, researchers have unveiled pioneering insights into the pulmonary function abnormalities faced by preterm infants suffering from bronchopulmonary dysplasia (BPD). The study employs electrical impedance tomography (EIT), an innovative, non-invasive imaging technology, to reveal detailed patterns of ventilation and perfusion heterogeneity in the lungs of these vulnerable infants. This novel approach addresses a critical gap in neonatal respiratory care and could revolutionize how clinicians approach diagnosis and management of BPD.
Bronchopulmonary dysplasia is a complex chronic lung disease that predominantly affects premature infants who have required mechanical ventilation or oxygen therapy due to underdeveloped lungs. Despite advancements in neonatal medicine, BPD remains a leading cause of respiratory morbidity in this population, complicating their clinical course and long-term prognosis. A major challenge in managing BPD has been the lack of reliable, bedside imaging tools that can effectively characterize the delicate interplay between pulmonary ventilation and perfusion—two fundamental physiological processes essential for optimal gas exchange.
Electrical impedance tomography emerges as a promising candidate to fill this unmet clinical need. Unlike traditional imaging modalities such as X-rays or CT scans, which provide static structural images, EIT offers dynamic, real-time visualization of lung function by measuring the distribution of electrical impedance within the thorax. Because air and blood differ in their electrical properties, EIT can simultaneously capture spatial and temporal changes in ventilation (air movement) and perfusion (blood flow), granting clinicians unprecedented insights into V/Q matching or mismatching in the neonatal lung.
In this study, Enzer and colleagues meticulously applied EIT to a cohort of infants diagnosed with BPD, investigating how ventilation and perfusion heterogeneity manifests in early life stages. Their findings revealed marked disparities in both parameters, with notable regional mismatches that likely contribute to impaired oxygenation and ventilation inefficiencies. Such nuanced information has previously been difficult to obtain without invasive procedures or ionizing radiation, underscoring the clinical significance of EIT as a bedside tool that aligns with the strict safety standards required in neonatology.
The technology behind EIT capitalizes on the principle that different tissues conduct electricity differently. For infants with fragile pulmonary systems, this means EIT can rapidly detect changes in impedance that correspond to variations in lung inflation and blood volume distribution as the cardiovascular and respiratory systems interact. The study demonstrated that these impedance changes map distinct areas of the lung that are either well-ventilated but poorly perfused or vice versa, elucidating complex patterns unique to BPD that might inform more tailored respiratory therapies.
The implications of these findings are profound. Current clinical strategies often rely on generalized respiratory support settings without adequate real-time feedback on whether blood flow and air flow to various lung regions are balanced. This lack of precision can inadvertently exacerbate lung injury or fail to optimize oxygen delivery. By integrating EIT into routine monitoring, clinicians could potentially adjust ventilation patterns, oxygen concentrations, or pharmacologic interventions on the fly, minimizing damage and improving outcomes in infants with compromised lung function.
Moreover, the non-invasiveness of EIT makes it an exceptionally valuable asset over repeated imaging methods, which expose infants to cumulative radiation risk. This aligns well with the ethos of neonatal care, which prioritizes the minimal disturbance of these already critically ill patients. EIT’s real-time data acquisition also facilitates longitudinal monitoring, enabling the tracking of disease progression or resolution and the assessment of therapeutic efficacy with unparalleled precision.
Beyond its clinical applications, this pioneering research opens the door to a deeper understanding of the pathophysiological mechanisms underpinning BPD. By visualizing ventilation-perfusion mismatches, researchers can begin to map how various factors—such as inflammation, fibrosis, or vascular remodeling—impact pulmonary function during crucial periods of lung development. This knowledge may ultimately accelerate the discovery of innovative interventions that target specific lung compartments or functional impairments.
The work by Enzer et al. also serves as a catalyst for expanding the role of EIT into other neonatal and pediatric lung conditions characterized by V/Q abnormalities. Diseases such as congenital diaphragmatic hernia, persistent pulmonary hypertension of the newborn, and acute respiratory distress syndrome may all benefit from more precise functional imaging to optimize treatment modalities. As EIT technology continues to evolve, it is expected to be integrated with machine learning algorithms and multimodal monitoring systems, further enhancing its resolution, specificity, and clinical impact.
To realize the full potential of EIT in neonatal care, however, several challenges must be addressed. These include standardizing image acquisition protocols, refining interpretive algorithms for heterogenous pediatric lungs, and training clinicians in the use and integration of EIT data into decision-making processes. The current study lays robust groundwork by elucidating the patterns of ventilation and perfusion heterogeneity, but ongoing multicenter trials and larger sample sizes will be essential to validate findings and establish clinical guidelines.
The introduction of electrical impedance tomography as a method to visualize the intricate ventilation and perfusion landscape in fragile preterm lungs represents a paradigm shift in neonatal respiratory medicine. With further development and adoption, this technology holds the promise of dramatically improving diagnostic precision, therapeutic tailoring, and ultimately, the quality of life for infants afflicted with bronchopulmonary dysplasia and beyond. The intersection of cutting-edge bioengineering and neonatology embodied in this research exemplifies the future of personalized, real-time clinical imaging.
As the research community digests these compelling findings, the hope is that EIT will rapidly transition from experimental use to a routine clinical tool in neonatal intensive care units worldwide. This vision is buoyed by its capacity to improve patient safety through non-invasive means, provide continuous functional lung assessments, and deliver actionable insights that can adapt to the fluctuating clinical status of preterm infants. The study’s timely contribution thus not only illuminates the lung’s delicate physiology but also stokes a wider movement towards more sophisticated, technology-driven neonatal care.
Ultimately, the integration of electrical impedance tomography into the clinical armamentarium for bronchopulmonary dysplasia represents more than incremental technological progress—it is a leap toward more humane, data-informed medicine for the smallest and most vulnerable patients. Unlocking the complex dynamics of ventilation and perfusion in real time offers a tangible pathway to alleviating the burden of chronic lung disease in premature infants and potentially transforming their long-term respiratory health trajectories.
Subject of Research: Pulmonary ventilation and perfusion heterogeneity in preterm infants with bronchopulmonary dysplasia (BPD) using electrical impedance tomography (EIT).
Article Title: Electrical impedance tomography reveals ventilation and perfusion heterogeneity in infants with bronchopulmonary dysplasia.
Article References:
Enzer, K.G., Barbosa Da Rosa, N., Keck, A. et al. Electrical impedance tomography reveals ventilation and perfusion heterogeneity in infants with bronchopulmonary dysplasia. J Perinatol (2026). https://doi.org/10.1038/s41372-026-02590-4
Image Credits: AI Generated
DOI: 24 February 2026
