Development of the PhysioVessel: a customizable platform for simulating physiological fluid resuscitation

Abstract

Uncontrolled hemorrhage is a leading cause of death in trauma situations. Developing solutions to automate hemorrhagic shock resuscitation may improve the outcomes for trauma patients. However, testing and development of automated solutions to address critical care interventions, oftentimes require extensive large animal studies for even initial troubleshooting. The use of accurate laboratory or in-silico models may provide a way to reduce the need for large animal datasets. Here, a tabletop model, for use in the development of fluid resuscitation with physiologically relevant pressure-volume responsiveness for high throughput testing, is presented. The design approach shown can be applied to any pressure-volume dataset through a process of curve-fitting, 3D modeling, and fabrication of a fluid reservoir shaped to the precise curve fit. Two case studies are presented here based on different resuscitation fluids: whole blood and crystalloid resuscitation. Both scenarios were derived from data acquired during porcine hemorrhage studies, used a pressure-volume curve to design and fabricate a 3D model, and evaluated to show that the test platform mimics the physiological data. The vessels produced based on data collected from pigs infused with whole blood and crystalloid were able to reproduce normalized pressure-volume curves within one standard deviation of the porcine data with mean residual differences of 0.018 and 0.016, respectively. This design process is useful for developing closed-loop algorithms for resuscitation and can simplify initial testing of technologies for this life-saving medical intervention.

Evaluation of a Proportional–Integral–Derivative Controller for Hemorrhage Resuscitation Using a Hardware-in-Loop Test Platform

“…Hemorrhage data was compiled from a previous swine study [ 16 ] and analyzed using MATLAB (MathWorks, Natick, MA, USA) to assess the relationship between bolus infusion volume of whole blood (WB) and mean arterial pressure (MAP). Animal subjects underwent a controlled hemorrhage of 24 mL/kg followed by a spleen injury prior to the bolus infusion.…”

“…The loop included two PhysioVessels that acted as the venous capacitance for the system: one for mimicking whole blood (PV WB ) and the second for mimicking crystalloid (PV Crys ). We have previously shown that these PhysioVessels were constructed based on pressure–volume relationship functions derived from experimental swine hemorrhagic shock resuscitation data, such that the geometry of the PhysioVessel causes hydrostatic pressure to mimic volume responsiveness during fluid resuscitation with different fluids [ 16 ]. This empiric approach was meant to circumvent the need for a complex physiological model but it has its limitations due to the data it is based on, meaning its use is limited to healthy swine subjects with their volume status in the range between profound shock (loss of over 35% of estimated blood volume) and damage-control resuscitation goals, with the resuscitation performed using either whole blood or crystalloids.…”

“…Scenario 2 began the same as the first scenario, except crystalloid was used for the infusion fluid type. This changed the volume responsiveness but, due to the design of PV Crys accounting for fluid compartmentalization in the hydrostatic column, re-bleeds at high pressure were not physiologically relevant for crystalloid when using HATRC [ 16 ]. As a result, the second part of the scenario mimicking tourniquet slippage was not evaluated for crystalloid infusion.…”

“…Towards this, we have developed a hardware-in-loop automated testbed for resuscitation controllers (HATRC) [ 15 ] that allows for setting a range of hemorrhage situations in a physical test platform. HATRC’s volume responsiveness is set by a custom-designed hydrostatic reservoir, termed the PhysioVessel [ 16 ], and hemorrhage rate, coagulation profile and initial blood pressure can all be tailored to special scenarios, allowing individual controller evaluation in a range of circumstances and patient variabilities.…”

Closed-Loop Controlled Fluid Administration Systems: A Comprehensive Scoping Review

“…An example for such a testing platform is reported by Bighamian et al [ 18 ]. This method allows for high-throughput tests of the controller at minimal cost and time, using only a computer on existing datasets but cannot test the hardware components; Hardware-in-loop (HIL) testing —A testing method that incorporates hardware components in a physical, manufactured system that simulates a variety of patient scenarios, while measuring the closed-loop controlled system’s performance [ 19 ]. These systems can sometimes be merged with an in silico simulation platform [ 20 ]; In vivo studies (animals) —Testing the entire system’s performance in a real, whole-body physiological system, with subject variability, allows for the additional validation for the system’s performance and enabling measurements of the additional relevant data, such as biochemical markers.…”