Predicting global and regional respiratory response in ARDS patients through individualized physics-based computational lung models: a prospective clinical pilot study.
5 affiliations
- 1Department of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany. [email protected].
- 2Institute for Computational Mechanics, Technical University of Munich, Garching b. München, Germany.
- 3Department of Anesthesiology and Intensive Care Medicine, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany.
- 4Department of Radiology and Neuroradiology, University Medical Center Schleswig-Holstein, Campus Kiel, Kiel, Germany.
- 5Ebenbuild GmbH, Munich, Germany.
Abstract
Background
Lung-protective ventilation is essential in the management of acute respiratory distress syndrome (ARDS), but current approaches are limited by the heterogeneity of lung pathology and a lack of individualized strategies. Patient-specific computational models may overcome these limitations by providing predictive and physiologically interpretable insights into global and regional lung behavior.Methods
Ten mechanically ventilated patients with ARDS were evaluated in a monocentric prospective pilot study. A predefined study protocol included ventilatory maneuvers with systematic changes in ventilator mode, tidal volume, positive end-expiratory pressure (PEEP), and driving pressure. For each patient, a personalized, regionally resolved physics-based computational lung model was generated and calibrated to reproduce the individual respiratory system mechanics. Model predictions of tidal volume, airway and transpulmonary pressures, end-expiratory lung volume (EELV), and electrical impedance tomography (EIT)-derived regional ventilation distribution were simulated for different PEEP levels and evaluated against clinically assessed reference values. Model predictions were compared to clinical data using Pearson correlation coefficients (r), root mean square error (RMSE), and Bland-Altman analyses.Results
A strong agreement was observed between simulated and clinical data for tidal volumes (r = 0.925, p < 0.001, RMSE = 0.053 l) and driving pressures (r = 0.940, p < 0.001, RMSE = 1.328 mbar) across all PEEP levels. At initial PEEP level, a high image correlation (r > 0.8) was found between measured and simulated regional ventilation in five of seven patients where EIT data were available.Conclusions
This pilot study demonstrates the capability of the individualized, regionally resolved physics-based computational lung model to reproduce patient-specific respiratory mechanics and key features of regional ventilation patterns in ARDS. The strong agreement between simulated and measured data supports the potential of this approach to estimate the physiological response to ventilator adjustments and lays the groundwork for future studies integrating computational modeling into clinical decision-making.Trial registration
Registered at the German Clinical Trials Register (DRKS00017151, https://drks.de/search/en/trial/DRKS00017151 ) at 12th April 2019.
Related
- Changes in parent-rated attention-deficit/hyperactivity disorder symptom scores and sleep parameters during individualized multidisciplinary clinical management in children with comorbid obstructive sleep apnea: a prospective cohort study in Vietnam
- Global Protective Ventilator Settings Are Not Regional Protection: A Compartment-Resolved Framework for Personalizing Mechanical Ventilation in Acute Respiratory Distress Syndrome
- Machine learning model for predicting regional lymph node metastasis in acral melanoma
- Prospective Evaluation of Individualized Nutrition Support on the Incidence of High-Output Ileostomy
- Quality-of-Life and Weight Loss Outcomes Following an Individualized Nutrition and Physical Activity Counseling Program in Breast Cancer Survivors: A Prospective Single-Arm Pilot Study
BibTeX
@article{sablewski2026predicting,
title = {{Predicting global and regional respiratory response in ARDS patients through individualized physics-based computational lung models: a prospective clinical pilot study.}},
author = {Armin Sablewski and Maximilian Ludwig and Carolin Eichinger and Matthias Lindner and Inéz Frerichs and Patrick Langguth and Dirk Schädler and Wolfgang A Wall and Tobias Becher},
journal = {Respiratory research},
year = {2026},
month = oct,
doi = {10.1186/s12931-026-03949-z},
url = {https://europepmc.org/article/MED/42902351},
note = {CC BY},
}
RIS
TY - JOUR
TI - Predicting global and regional respiratory response in ARDS patients through individualized physics-based computational lung models: a prospective clinical pilot study.
AU - Armin Sablewski
AU - Maximilian Ludwig
AU - Carolin Eichinger
AU - Matthias Lindner
AU - Inéz Frerichs
AU - Patrick Langguth
AU - Dirk Schädler
AU - Wolfgang A Wall
AU - Tobias Becher
PY - 2026
DA - 2026/10/17
JO - Respiratory research
DO - 10.1186/s12931-026-03949-z
UR - https://europepmc.org/article/MED/42902351
AB - Background Lung-protective ventilation is essential in the management of acute respiratory distress syndrome (ARDS), but current approaches are limited by the heterogeneity of lung pathology and a lack of individualized strategies. Patient-specific computational models may overcome these limitations by providing predictive and physiologically interpretable insights into global and regional lung behavior.Methods Ten mechanically ventilated patients with ARDS were evaluated in a monocentric prospective pilot study. A predefined study protocol included ventilatory maneuvers with systematic changes in ventilator mode, tidal volume, positive end-expiratory pressure (PEEP), and driving pressure. For each patient, a personalized, regionally resolved physics-based computational lung model was generated and calibrated to reproduce the individual respiratory system mechanics. Model predictions of tidal volume, airway and transpulmonary pressures, end-expiratory lung volume (EELV), and electrical impedance tomography (EIT)-derived regional ventilation distribution were simulated for different PEEP levels and evaluated against clinically assessed reference values. Model predictions were compared to clinical data using Pearson correlation coefficients (r), root mean square error (RMSE), and Bland-Altman analyses.Results A strong agreement was observed between simulated and clinical data for tidal volumes (r = 0.925, p < 0.001, RMSE = 0.053 l) and driving pressures (r = 0.940, p < 0.001, RMSE = 1.328 mbar) across all PEEP levels. At initial PEEP level, a high image correlation (r > 0.8) was found between measured and simulated regional ventilation in five of seven patients where EIT data were available.Conclusions This pilot study demonstrates the capability of the individualized, regionally resolved physics-based computational lung model to reproduce patient-specific respiratory mechanics and key features of regional ventilation patterns in ARDS. The strong agreement between simulated and measured data supports the potential of this approach to estimate the physiological response to ventilator adjustments and lays the groundwork for future studies integrating computational modeling into clinical decision-making.Trial registration Registered at the German Clinical Trials Register (DRKS00017151, https://drks.de/search/en/trial/DRKS00017151 ) at 12th April 2019.
SN - 1465-9921
SN - 1465-993X
ER -