# Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography

**Authors:** Roberta Garberi, Matthieu Jabaudon, Sam Bayat, Sarah E. Gerard, Aurora Magliocca, Mariangela Pellegrini, Alberto Bravin, Lorraine B. Ware, John J. Marini, Yi Xin, John G. Laffey, Maurizio Cereda, Emanuele Rezoagli

PMC · DOI: 10.1186/s40635-026-00880-x · 2026-03-26

## TL;DR

This paper reviews how computed tomography (CT) can help understand and classify the different types of lung injury in acute respiratory distress syndrome (ARDS), which is a complex and variable condition.

## Contribution

The paper systematically reviews the use of CT imaging to characterize ARDS heterogeneity and its clinical implications, emphasizing novel imaging techniques and computational approaches.

## Key findings

- CT provides detailed regional lung injury information not accessible through standard bedside measurements.
- CT imaging patterns correlate with lung mechanics, gas exchange, and ventilatory response in ARDS patients.
- Quantitative and dual-energy CT methods offer more precise characterization of lung injury heterogeneity.

## Abstract

Acute respiratory distress syndrome (ARDS) is a heterogeneous clinical syndrome rather than a single disease. Patients who meet the same diagnostic criteria may differ in lung morphology, mechanical properties, biological injury, and clinical course. Current classifications rely largely on the severity of hypoxemia and do not capture this variability, limiting prognostic stratification and individualized treatment. This heterogeneity has clinical consequences. Supportive interventions such as positive end-expiratory pressure (PEEP), prone positioning, and recruitment maneuvers are broadly applied, yet their effects vary substantially among patients. Increasing evidence indicates that these differences are partly explained by variation in lung structure, regional aeration, recruitability, and perfusion. Recent international guidelines have identified phenotyping as a priority in ARDS and have highlighted lung morphology as a relevant source of prognostic enrichment and treatment effect heterogeneity. Computed tomography (CT) provides regional, three-dimensional information on lung injury that is not accessible through bedside physiological measurements. It allows evaluation of aeration loss, lung density, lung weight, and perfusion abnormalities. CT has been used to describe key aspects of lung injury in ARDS and to identify imaging patterns associated with lung mechanics, gas exchange, and response to ventilatory settings. Quantitative and dual-energy CT, together with computational methods, allow a more detailed description of these patterns. This review examines the role of CT in characterizing heterogeneity in ARDS, summarizes qualitative, semi-quantitative, and quantitative approaches, and discusses their clinical relevance and limitations, as well as future directions.

## Linked entities

- **Diseases:** acute respiratory distress syndrome (MONDO:0006502), ARDS (MONDO:0006502)

## Full-text entities

- **Diseases:** pancreatitis (MESH:D010195), critically ill (MESH:D016638), lung epithelial injury (MESH:D055370), abnormal lung density (MESH:D008171), bronchiectasis (MESH:D001987), ARDS (MESH:D012128), microvascular obstruction (MESH:D017566), alveolar opacities (MESH:D003318), perfusion abnormalities (MESH:D000014), atelectasis (MESH:D001261), cardiac arrest (MESH:D006323), CT (MESH:C000719218), injury (MESH:D014947), aspiration (MESH:D011015), cysts (MESH:D003560), endothelial injury (MESH:D057772), obesity (MESH:D009765), pneumonia (MESH:D011014), chest compressions (MESH:D013898), pleural effusion (MESH:D010996), ground-glass opacities (MESH:C000721427), CRALE (MESH:D004487), COVID-19 (MESH:D000086382), ARF (MESH:D012131), inflammatory (MESH:D007249), VILI (MESH:D055397), coagulation abnormalities (MESH:D001778), aeration loss (MESH:D016388), sepsis (MESH:D018805), acute lung injury (MESH:D055371), hypoxemia (MESH:D000860), fibrosis (MESH:D005355)
- **Chemicals:** iodine (MESH:D007455), HU (-), oxygen (MESH:D010100), CO2 (MESH:D002245), water (MESH:D014867)
- **Species:** Homo sapiens (human, species) [taxon 9606], Mus musculus (house mouse, species) [taxon 10090], Sus scrofa (pig, species) [taxon 9823]

## Figures

8 figures with captions in the complete paper: https://tomesphere.com/paper/PMC13018537/full.md

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Source: https://tomesphere.com/paper/PMC13018537