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Credibility Evidence for Computational Patient Models Used in the Development of Physiological Closed-Loop Controlled Devices for Critical Care Medicine.

ABSTRACT: Physiological closed-loop controlled medical devices automatically adjust therapy delivered to a patient to adjust a measured physiological variable. In critical care scenarios, these types of devices could automate, for example, fluid resuscitation, drug delivery, mechanical ventilation, and/or anesthesia and sedation. Evidence from simulations using computational models of physiological systems can play a crucial role in the development of physiological closed-loop controlled devices; but the utility of this evidence will depend on the credibility of the computational model used. Computational models of physiological systems can be complex with numerous non-linearities, time-varying properties, and unknown parameters, which leads to challenges in model assessment. Given the wide range of potential uses of computational patient models in the design and evaluation of physiological closed-loop controlled systems, and the varying risks associated with the diverse uses, the specific model as well as the necessary evidence to make a model credible for a use case may vary. In this review, we examine the various uses of computational patient models in the design and evaluation of critical care physiological closed-loop controlled systems (e.g., hemodynamic stability, mechanical ventilation, anesthetic delivery) as well as the types of evidence (e.g., verification, validation, and uncertainty quantification activities) presented to support the model for that use. We then examine and discuss how a credibility assessment framework (American Society of Mechanical Engineers Verification and Validation Subcommittee, V&V 40 Verification and Validation in Computational Modeling of Medical Devices) for medical devices can be applied to computational patient models used to test physiological closed-loop controlled systems.

SUBMITTER: Parvinian B

PROVIDER: S-EPMC6445134 | biostudies-other | 2019

REPOSITORIES: biostudies-other

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Credibility Evidence for Computational Patient Models Used in the Development of Physiological Closed-Loop Controlled Devices for Critical Care Medicine.

Parvinian Bahram B Pathmanathan Pras P Daluwatte Chathuri C Yaghouby Farid F Gray Richard A RA Weininger Sandy S Morrison Tina M TM Scully Christopher G CG

Frontiers in physiology 20190326

Physiological closed-loop controlled medical devices automatically adjust therapy delivered to a patient to adjust a measured physiological variable. In critical care scenarios, these types of devices could automate, for example, fluid resuscitation, drug delivery, mechanical ventilation, and/or anesthesia and sedation. Evidence from simulations using computational models of physiological systems can play a crucial role in the development of physiological closed-loop controlled devices; but the ...[more]

PMID: 30971934

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Project description:Physiological closed-loop controlled (PCLC) medical devices are complex systems integrating one or more medical devices with a patient's physiology through closed-loop control algorithms; introducing many failure modes and parameters that impact performance. These control algorithms should be tested through safety and efficacy trials to compare their performance to the standard of care and determine whether there is sufficient evidence of safety for their use in real care setting. With this aim, credible mathematical models have been constructed and used throughout the development and evaluation phases of a PCLC medical device to support the engineering design and improve safety aspects. Uncertainties about the fidelity of these models and ambiguities about the choice of measures for modeling performance need to be addressed before a reliable PCLC evaluation can be achieved. This research develops tools for evaluating the accuracy of physiological models and establishes fundamental measures for predictive capability assessment across different physiological models. As a case study, we built a refined physiological model of blood volume (BV) response by expanding an original model we developed in our prior work. Using experimental data collected from 16 sheep undergoing hemorrhage and fluid resuscitation, first, we compared the calibration performance of the two candidate physiological models, i.e., original and refined, using root-mean-squared error (RMSE), Akiake information criterion (AIC), and a new multi-dimensional approach utilizing normalized features extracted from the fitting error. Compared to the original model, the refined model demonstrated a significant improvement in calibration performance in terms of RMSE (9%, P = 0.03) and multi-dimensional measure (48%, P = 0.02), while a comparable AIC between the two models verified that the enhanced calibration performance in the refined model is not due to data over-fitting. Second, we compared the physiological predictive capability of the two models under three different scenarios: prediction of subject-specific steady-state BV response, subject-specific transient BV response to hemorrhage perturbation, and leave-one-out inter-subject BV response. Results indicated enhanced accuracy and predictive capability for the refined physiological model with significantly larger proportion of measurements that were within the prediction envelope in the transient and leave-one-out prediction scenarios (P < 0.02). All together, this study helps to identify and merge new methods for credibility assessment and physiological model selection, leading to a more efficient process for PCLC medical device evaluation.

Project description:Cardiac mechanical activity leads to periodic changes in the distribution of blood throughout the body, which causes micro-oscillations of the body's center of mass and can be measured by ballistocardiography (BCG). However, many of the BCG findings are based on parameters whose origins are poorly understood. Here, we generate simulated multidimensional BCG signals based on a more exhaustive and accurate computational model of blood circulation than previous attempts. This model consists in a closed loop 0D-1D multiscale representation of the human blood circulation. The 0D elements include the cardiac chambers, cardiac valves, arterioles, capillaries, venules, and veins, while the 1D elements include 55 systemic and 57 pulmonary arteries. The simulated multidimensional BCG signal is computed based on the distribution of blood in the different compartments and their anatomical position given by whole-body magnetic resonance angiography on a healthy young subject. We use this model to analyze the elements affecting the BCG signal on its different axes, allowing a better interpretation of clinical records. We also evaluate the impact of filtering and healthy aging on the BCG signal. The results offer a better view of the physiological meaning of BCG, as compared to previous models considering mainly the contribution of the aorta and focusing on longitudinal acceleration BCG. The shape of experimental BCG signals can be reproduced, and their amplitudes are in the range of experimental records. The contributions of the cardiac chambers and the pulmonary circulation are non-negligible, especially on the lateral and transversal components of the velocity BCG signal. The shapes and amplitudes of the BCG waveforms are changing with age, and we propose a scaling law to estimate the pulse wave velocity based on the time intervals between the peaks of the acceleration BCG signal. We also suggest new formulas to estimate the stroke volume and its changes based on the BCG signal expressed in terms of acceleration and kinetic energy.

Project description:ObjectivesThe United States National Institute for Occupational Safety and Health (NIOSH) is developing a protocol to assess the containment performance of closed system transfer devices (CSTDs) when used for drug preparation (task 1) and administration (task 2) and published a draft protocol in September 2016. Nine possible surrogates were proposed by NIOSH for use in the testing. The objectives of this study were to: (A) select the most appropriate surrogate; (B) validate the NIOSH protocol using this surrogate; and (C) determine the containment performance of four commercial CSTDs as compared with an open system of needle and syringe using the validated NIOSH protocol.Methods2-Phenoxyethanol (2-POE) was selected as a surrogate based on its water solubility, Henry's volatility constant, detectability by mass spectrometry, and non-toxicity. Standard analytical validation methods including system suitability, limit of detection (LOD), and limit of quantitation (LOQ) as well as system cleaning validation were performed. The amount of 2-POE released when the CSTDs were manipulated according to two tasks defined by NIOSH was determined using mass spectrometry coupled to thermal desorption and gas chromatography. This approach allows sensitivity of detection below 1 part per billion (ppb). Equashield, Tevadaptor (OnGuard), PhaSeal, and ChemoClave were assessed according to manufacturers' instructions for use.Results2-POE was tested and validated for suitability of use within the NIOSH protocol. A simple and efficient cleaning protocol achieved consistently low background values, with an average value, based on 85 measurements, of 0.12 ppb with a 95% confidence interval (CI) of ±0.16 ppb. This gives an LOD for the tests of 0.35 ppb and an LOQ of 0.88 ppb. The Equashield, Tevadaptor (OnGuard), and PhaSeal devices all showed average releases, based on 10 measurements from five tests, that were less than the LOQ (i.e. < 0.88 ppb), while the ChemoClave Vial Shield with Spinning Spiros showed average releases of 2.9±2.3 ppb and 7.5±17.9 ppb for NIOSH tasks 1 and 2 respectively at the 95% confidence level. The open system of needle and syringe showed releases, based on two measurements from a single test, of 4.2±2.2 ppb and 5.1±1.7 ppb for NIOSH tasks 1 and 2 respectively at the 95% confidence level.Conclusions2-POE proved to be an ideal surrogate for testing of CSTDs using the NIOSH protocol. We propose that a CSTD can be qualified using the NIOSH testing approach if the experimental LOQ is less than 1 ppb and the release values are below the LOQ. Equashield, Tevadaptor (OnGuard), and PhaSeal meet these acceptance criteria and can therefore all be qualified as CSTDs, but the ChemoClave system does not and so would not qualify as a CSTD.

Dataset Information

Credibility Evidence for Computational Patient Models Used in the Development of Physiological Closed-Loop Controlled Devices for Critical Care Medicine.

Publications

Credibility Evidence for Computational Patient Models Used in the Development of Physiological Closed-Loop Controlled Devices for Critical Care Medicine.

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