Modeling Mechanical Ventilation In Silico—Potential and Pitfalls

Hannon, D. M.; Mistry, Sonal; Das, Anup; Saffaran, Sina; Laffey, John G.; Brook, Bindi S.; Hardman, Jonathan G.; Bates, Declan G.

doi:10.1055/s-0042-1744446

Cited by 5 publications

(1 citation statement)

References 112 publications

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“…The proposed design was simulated on the MATLAB platform. Hannon et al, [10] presented a review on the advancement in the modelling of human anatomy, physiology and pathophysiology via mathematical modelling and computer simulation. Clinical applications in various disease states were emphasized.…”

Section: Related Workmentioning

confidence: 99%

A Novel Mixed Finite/Infinite Dimensional Port-Hamiltonian Model of a Mechanical Ventilator

Madahana,

Ekoru,

Nyandoro

2024

Preprint

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Mechanical ventilation is a life-saving treatment for critically ill patients who are struggling to breathe independently due to injury or disease. Globally, large numbers of Individuals have always required mechanical ventilation per year. The Covid-19 pandemic elevated the significance of the mechanical ventilation which have played a significant role in sustaining Covid 19 infected critically ill patients who could not breathe on their own. The pandemic drew the attention of the world to the shortage of ventilators globally.This research work presents the formulation of a detailed Port Hamiltonian model of a mechanical ventilator integrated to the human respiratory system. The interconnection and coupling conditions for the various subsystem within the mechanical ventilator and the coupling between the mechanical ventilator and the human respiratory system is also presented.A structure preservation discretization is provided along side numerical simulations and results. The obtained results are found to be comparable to results presented in literature.The future work will include the design of suitable controllers for system.

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Section: Related Workmentioning

confidence: 99%

A Novel Mixed Finite/Infinite Dimensional Port-Hamiltonian Model of a Mechanical Ventilator

Madahana,

Ekoru,

Nyandoro

2024

Preprint

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Mathematical modeling of lung mechanics and pressure‐controlled ventilation design for barotrauma minimization: A numerical simulation study

D'Orsi,

Borri,

De Gaetano

2024

Intl J Robust & Nonlinear

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SummaryMechanical ventilation represents a fundamental mode of therapy for severely ill patients who cannot breathe autonomously. At the same time, it has the potential of determining Ventilator‐Induced Lung Injury (VILI) and further damaging the patient's respiratory system. In this work we present a model‐based approach for pressure delivery optimization in the context of pressure‐control mechanical ventilation, with the aim of maintaining oxygenation while minimizing barotrauma. A simple compartmental model of respiration describes both mechanical ventilation, alveolar oxygen exchange and blood oxygen transport. Model Predictive Control is used to optimize delivered air pressure at the mouth at each inspiration, optimizing a trade‐off between oxygenation and barotrauma. Numerical simulations with different values of the trade‐off parameter and in two emblematic pulmonary disease scenarios (ARDS and COPD) show the effectiveness of the proposed approach.

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Digital Twins of Acute Hypoxemic Respiratory Failure Patients Suggest a Mechanistic Basis for Success and Failure of Noninvasive Ventilation

Weaver,

Shamohammadi,

Saffaran

et al. 2024

Critical Care Medicine

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Objectives: To clarify the mechanistic basis for the success or failure of noninvasive ventilation (NIV) in acute hypoxemic respiratory failure (AHRF). Design: We created digital twins based on mechanistic computational models of individual patients with AHRF. Setting: Interdisciplinary Collaboration in Systems Medicine Research Network. Subjects: We used individual patient data from 30 moderate-to-severe AHRF patients who had failed high-flow nasal cannula (HFNC) therapy and subsequently underwent a trial of NIV. Interventions: Using the digital twins, we evaluated lung mechanics, quantified the separate contributions of external support and patient respiratory effort to lung injury indices, and investigated their relative impact on NIV success or failure. Measurements and Main Results: In digital twins of patients who successfully completed/failed NIV, after 2 hours of the trial the mean (sd) of the change in total lung stress was –10.9 (6.2)/–0.35 (3.38) cm H2O, mechanical power –13.4 (12.2)/–1.0 (5.4) J/min, and total lung strain 0.02 (0.24)/0.16 (0.30). In the digital twins, positive end-expiratory pressure (PEEP) produced by HFNC was similar to that set during NIV. In digital twins of patients who failed NIV vs. those who succeeded, intrinsic PEEP was 3.5 (0.6) vs. 2.3 (0.8) cm H2O, inspiratory pressure support was 8.3 (5.9) vs. 22.3 (7.2) cm H2O, and tidal volume was 10.9 (1.2) vs. 9.4 (1.8) mL/kg. In digital twins, successful NIV increased respiratory system compliance +25.0 (16.4) mL/cm H2O, lowered inspiratory muscle pressure –9.7 (9.6) cm H2O, and reduced the contribution of patient spontaneous breathing to total driving pressure by 57.0%. Conclusions: In digital twins of AHRF patients, successful NIV improved lung mechanics, lowering respiratory effort and indices associated with lung injury. NIV failed in patients for whom only low levels of positive inspiratory pressure support could be applied without risking patient self-inflicted lung injury due to excessive tidal volumes.

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Modeling Mechanical Ventilation In Silico—Potential and Pitfalls

Cited by 5 publications

References 112 publications

A Novel Mixed Finite/Infinite Dimensional Port-Hamiltonian Model of a Mechanical Ventilator

A Novel Mixed Finite/Infinite Dimensional Port-Hamiltonian Model of a Mechanical Ventilator

Mathematical modeling of lung mechanics and pressure‐controlled ventilation design for barotrauma minimization: A numerical simulation study

Digital Twins of Acute Hypoxemic Respiratory Failure Patients Suggest a Mechanistic Basis for Success and Failure of Noninvasive Ventilation

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