Normothermic Ex Situ Heart Perfusion in Working Mode: Assessment of Cardiac Function and Metabolism
January 12th, 2019
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Normothermic ex situ heart perfusion (ESHP), preserves the heart in a beating, semi-physiologic state. When performed in a working mode, ESHP provides the opportunity to perform sophisticated assessments of donor heart function and organ viability. Here, we describe our method for myocardial performance evaluation during ESHP.
Overview
Normothermic ex situ heart perfusion (ESHP) maintains the heart in a semi-physiologic state, allowing for detailed assessments of donor heart function. This method enables the evaluation of donor hearts beyond indirect metabolic assessments, providing insights into their viability for transplantation.
Key Study Components
Area of Science
- Cardiovascular physiology
- Transplantation science
- Organ preservation techniques
Background
- ESHP allows for the functional evaluation of donor hearts.
- It addresses key questions regarding heart preservation and suitability for transplantation.
- Technical expertise is required for the safe connection of the heart to the perfusion device.
- Visual demonstrations are essential for learning the technical aspects of the procedure.
Purpose of Study
- To evaluate donor heart function during ESHP.
- To assess the viability of donor hearts for transplantation.
- To improve techniques for preserving and evaluating donor hearts.
Methods Used
- Median sternotomy performed on anesthetized pigs.
- Use of Metzenbaum scissors to open the pericardium.
- Assessment of heart response to noxious stimuli.
- Connection of the heart to an ex situ perfusion device.
Main Results
- Functional evaluations can be performed repeatedly over time.
- The method allows for direct assessment of heart function.
- Technical challenges can be mitigated through visual instruction.
- Improved understanding of donor heart viability for transplantation.
Conclusions
- ESHP provides a reliable method for evaluating donor hearts.
- The technique enhances the potential for successful heart transplantation.
- Future studies may expand on the implications of this method for dysfunctional donor hearts.
Frequently Asked Questions
What is normothermic ex situ heart perfusion?
It is a technique that preserves the heart in a beating, semi-physiologic state for evaluation.
Why is visual demonstration important in this method?
Visual aids help overcome the technical challenges of connecting the heart safely.
How does ESHP improve donor heart evaluation?
It allows for direct functional assessments rather than relying solely on metabolic indicators.
What are the main advantages of using ESHP?
It enables repeated assessments of heart function and provides insights into organ viability.
What challenges do beginners face with this technique?
Beginners may struggle with the technical aspects of heart retrieval and connection.
What is the significance of assessing heart response to stimuli?
It helps confirm the viability and functionality of the donor heart before transplantation.
Executive Industry Relevance
Normothermic ex situ heart perfusion in working mode enables functional and metabolic evaluation of donor hearts under physiologic conditions, addressing limitations of cold storage preservation. This approach supports mechanistic de-risking in cardiac transplantation by providing quantitative, real-time assessments of cardiac performance, thereby improving predictive confidence in graft suitability. The method enhances translational continuity from preclinical models to clinical application, particularly for extended-criteria and donation after circulatory death hearts.
Strategic Applications in Biopharma R&D
Early Discovery & Target Validation
- Scientific Value: Enables interrogation of therapeutic hypotheses by assessing cardiac function under controlled hemodynamic loads.
- Operational Value: Supports pathway clarification through real-time monitoring of electrophysiological and contractile parameters.
- Predictive Value: Facilitates biological de-risking by allowing repeated functional assessments over time to evaluate stability and recovery.
Screening & Assay Development
- Scientific Value: Prepares validated biological systems for downstream workflows by maintaining heart viability in a near-physiologic state.
- Operational Value: Ensures assay standardization and reproducibility through automated control of aortic and left atrial pressures via software feedback loops.
- Scalability: Enables platform reuse across different animal models and heart sizes due to adaptable perfusion protocols.
Translational & Preclinical Research
- Scientific Value: Supports disease-relevant system evaluation by allowing assessment of metabolic state through perfusate lactate and oxygen consumption measurements.
- Operational Value: Provides continuity from discovery through preclinical validation by enabling echocardiographic and pressure-volume loop analysis during perfusion.
- Risk Mitigation: Informs risk-adjusted advancement decisions by identifying dysfunctional grafts prior to transplantation.
Pipeline & Workflow Integration
The method integrates into the discovery continuum from early target validation through preclinical evaluation, supporting go/no-go decisions based on functional and metabolic outputs.
- Discovery Biology: Supports hypothesis testing by enabling load-dependent and load-independent functional assessments, such as preload recruitable stroke work analysis.
- Screening: Enhances assay readiness through real-time, automated regulation of perfusion parameters, reducing need for manual intervention.
- Analytics: Delivers quantitative readouts including stroke work, pressure-volume relationships, and metabolic markers that allow comparative condition evaluation.
- Translational Research: Connects to preclinical continuity by permitting longitudinal assessment of heart function and metabolism, aligning with biomarker development efforts.
- Enterprise Reuse: Functions as a reusable capability for evaluating donor heart suitability across multiple experimental models and preservation strategies.
Operational & Enterprise Impact
- Scientific Value: Increases predictive confidence by enabling direct functional evaluation beyond indirect metabolic assessments.
- Operational Value: Improves standardization and reproducibility via software-controlled perfusion dynamics and automated data collection.
- Strategic Value: Supports better go/no-go decisions by providing longitudinal functional data that reduce late-stage biological risk in transplantation pipelines.
- Portfolio Impact: Enables risk-adjusted prioritization of grafts through objective functional and metabolic thresholds, such as preload recruitable stroke work correlation coefficients >0.95.
Implementation Considerations
- Requires expertise in cardiovascular surgery and perfusion technology for safe heart retrieval, cannulation, and device connection.
- Dependent on instrumentation capable of real-time pressure and flow regulation, including programmable pumps and integrated software feedback loops.
- Necessitates cross-team standardization in perfusate preparation, data acquisition protocols, and functional analysis methods.
- Involves adaptation considerations when applying the protocol across varying heart sizes and species, necessitating recalibration of flow and pressure parameters.
- Limited by the need for sterile, isotonic perfusate components and anticoagulated blood to prevent thrombosis and maintain coronary flow during prolonged perfusion.
Biopharma FAQs
Why does preload recruitable stroke work analysis matter for target validation?
Preload recruitable stroke work analysis provides a load-independent index of cardiac contractility, enabling mechanistic de-risking by distinguishing intrinsic myocardial function from loading conditions. This quantitative output supports target validation by offering a reproducible, software-derived metric that correlates with ventricular performance under standardized conditions. A correlation coefficient >0.95 ensures data reliability, reinforcing predictive confidence in functional assessments.
How does independent variable isolation fit the discovery pipeline?
Isolating independent variables such as left atrial pressure allows researchers to assess the direct effects of interventions on cardiac function without confounding hemodynamic influences. This control is critical in early discovery for pathway clarification and target validation, where distinguishing specific molecular effects from systemic variability is essential. The software-driven feedback loop in working mode ESHP automates this isolation, enhancing reproducibility across experimental groups.
What quantitative dependent variable measurements enable mechanistic de-risking?
Dependent variables including left ventricle stroke work, aortic flow, and perfusate lactate concentration provide quantifiable readouts of cardiac performance and metabolic state during perfusion. These measurements enable mechanistic de-risking by revealing functional recovery, ischemic burden, and mitochondrial efficiency over time. Serial sampling and real-time monitoring allow longitudinal tracking, supporting go/no-go decisions based on objective thresholds.
Why do replication requirements matter for cross-functional collaboration?
Replication requirements ensure that functional and metabolic assessments are consistent across operators, laboratories, and preclinical models, which is essential for cross-functional collaboration in drug discovery and translational research. Standardized protocols, such as fixed perfusion durations and pressure targets, reduce variability and enhance data comparability between teams. This consistency strengthens confidence in shared datasets used for target selection and lead optimization.
What statistical analysis capabilities are required before implementation?
Implementation requires statistical capabilities to perform linear regression on pressure-volume loop data to derive preload recruitable stroke work and assess goodness of fit via correlation coefficient. The software automates this analysis, but users must verify that the correlation coefficient exceeds 0.95 to accept the result as valid. This threshold ensures sufficient data quality for reliable functional evaluation, supporting downstream decision-making in preclinical pipelines.
