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.

Garberi, R., Jabaudon, M., Bayat, S., Gerard, S., Magliocca, A., Pellegrini, M., et al. (2026). Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography. INTENSIVE CARE MEDICINE EXPERIMENTAL, 14(1) [10.1186/s40635-026-00880-x].

Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography

Roberta Garberi;Aurora Magliocca;Alberto Bravin;Emanuele Rezoagli
2026

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.
Articolo in rivista - Review Essay
Acute respiratory distress syndrome (ARDS); Artificial Intelligence (AI); CT-based subphenotyping; Quantitative computed tomography (qCT); Ventilation–perfusion mismatch
English
26-mar-2026
2026
14
1
38
open
Garberi, R., Jabaudon, M., Bayat, S., Gerard, S., Magliocca, A., Pellegrini, M., et al. (2026). Characterizing heterogeneity and subphenotyping acute respiratory distress syndrome with computed tomography. INTENSIVE CARE MEDICINE EXPERIMENTAL, 14(1) [10.1186/s40635-026-00880-x].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/598941
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