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<p>Venovenous extracorporeal membrane oxygenation (VV-ECMO) is a form of mechanical respiratory support therapy for patients with acute lung injury or end-stage lung disease. Clinical demand for VV-ECMO has increased substantially, yet consensus on optimal patient management strategies remains limited. ECMO physiology is complex and difficult to predict, given the three-way interactions between the patient, the mechanical ventilator, and the extracorporeal circuit. A physiological simulation platform would be valuable for applications like clinical decision support, but current models have limited capability to simulate high-resolution transient responses. To fill this gap, we present a patient-specific, computational model of VV-ECMO based on the Pulse Physiology Engine. The model was first validated using a dataset of ten patients from a prior clinical VV-ECMO study. Simulations showed oxygenation response that depended on blood flow and <InlineEquation ID="IEq1"><EquationSource Format="TEX">\(FdO_2\)</EquationSource></InlineEquation>, and <InlineEquation ID="IEq2"><EquationSource Format="TEX">\(\hbox {CO}_2\)</EquationSource></InlineEquation> response dependent on sweep, both agreeing with the original publication. We also demonstrate the model’s capability to simulate transient oxygen response that agreed with data from N=1 porcine VV-ECMO study. Finally, we show an example on the use of Pulse to optimize lung-protective ventilator settings during VV-ECMO. This model provides a foundation for future research and development of digital twins, clinical decision support, and automation of ECMO.</p>

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Patient-specific, computational model of venovenous extracorporeal membrane oxygenation based on pulse physiology engine

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年7月29日

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  • Rei Ukita,
  • Jeffrey B. Webb,
  • Sriya Bapatla,
  • Yerin Woo,
  • Andrew Kumpfbeck,
  • Aaron Bray,
  • Matthew Bacchetta,
  • Rachel B. Clipp,
  • Steven P. Keller

摘要

Venovenous extracorporeal membrane oxygenation (VV-ECMO) is a form of mechanical respiratory support therapy for patients with acute lung injury or end-stage lung disease. Clinical demand for VV-ECMO has increased substantially, yet consensus on optimal patient management strategies remains limited. ECMO physiology is complex and difficult to predict, given the three-way interactions between the patient, the mechanical ventilator, and the extracorporeal circuit. A physiological simulation platform would be valuable for applications like clinical decision support, but current models have limited capability to simulate high-resolution transient responses. To fill this gap, we present a patient-specific, computational model of VV-ECMO based on the Pulse Physiology Engine. The model was first validated using a dataset of ten patients from a prior clinical VV-ECMO study. Simulations showed oxygenation response that depended on blood flow and \(FdO_2\), and \(\hbox {CO}_2\) response dependent on sweep, both agreeing with the original publication. We also demonstrate the model’s capability to simulate transient oxygen response that agreed with data from N=1 porcine VV-ECMO study. Finally, we show an example on the use of Pulse to optimize lung-protective ventilator settings during VV-ECMO. This model provides a foundation for future research and development of digital twins, clinical decision support, and automation of ECMO.