Patients who receive prosthetic heart valve (PHV) implants require mandatory anticoagulation medication after implantation due to the thrombogenic potential of the valve. Optimization of PHV designs may facilitate reduction of flow-induced thrombogenicity and reduce or eliminate the need for post-implant anticoagulants. We present a methodology entitled Device Thrombogenicty Emulator (DTE) for optimizing the thrombo-resistance performance of PHV by combining numerical and experimental approaches. Two bileaflet mechanical heart valves (MHV) designs -St. Jude Medical (SJM) and ATS were investigated, by studying the effect of distinct flow phases on platelet activation. Transient turbulent and direct numerical simulations (DNS) were conducted, and stress loading histories experienced by the platelets were calculated along flow trajectories. The numerical simulations indicated distinct design dependent differences between the two valves. The stress-loading waveforms extracted from the numerical simulations were programmed into a hemodynamic shearing device (HSD), emulating the flow conditions past the valves in distinct 'hot spot' flow regions that are implicated in MHV thrombogenicity. The resultant platelet activity was measured with a modified prothrombinase assay, and was found to be significantly higher in the SJM valve, mostly during the regurgitation phase. The experimental results were in excellent agreement with the calculated platelet activation potential. This establishes the utility of the DTE methodology for serving as a test bed for evaluating design modifications for achieving better thrombogenic performance for such devices.

Advances in magnetic resonance (MR) imaging techniques enable the accurate measurements of cerebrospinal fluid (CSF) flow in the human brain. In addition, image reconstruction tools facilitate the collection of patient-specific brain geometry data such as the exact dimensions of the ventricular and subarachnoidal spaces (SAS) as well as the computer-aided reconstruction of the CSF-filled spaces. The solution of the conservation of CSF mass and momentum balances over a finite computational mesh obtained from the MR images predict the patients' CSF flow and pressure field. Advanced image reconstruction tools used in conjunction with first principles of fluid mechanics allow an accurate verification of the CSF flow patters for individual patients. This paper presents a detailed analysis of pulsatile CSF flow and pressure dynamics in a normal and hydrocephalic patient. Experimental CSF flow measurements and computational results of flow and pressure fields in the ventricular system, the SAS and brain parenchyma are presented. The pulsating CSF motion is explored in normal and pathological conditions of communicating hydrocephalus. This paper predicts small transmantle pressure differences between lateral ventricles and SASs (approximately 10 Pa). The transmantle pressure between ventricles and SAS remains small even in the hydrocephalic patient (approximately 30 Pa), but the ICP pulsatility increases by a factor of four. The computational fluid dynamics (CFD) results of the predicted CSF flow velocities are in good agreement with Cine MRI measurements. Differences between the predicted and observed CSF flow velocities in the prepontine area point towards complex brain-CSF interactions. The paper presents the complete computational model to predict the pulsatile CSF flow in the cranial cavity.

Mechanical circulatory support (MCS) devices provide both short and long term hemodynamic support for advanced heart failure patients. Unfortunately these devices remain plagued by thromboembolic complications associated with chronic platelet activation – mandating complex, lifelong anticoagulation therapy. To address the unmet need for enhancing the thromboresistance of these devices to extend their long term use, we developed a universal predictive methodology entitled Device Thrombogenicity Emulation (DTE) that facilitates optimizing the thrombogenic performance of any MCS device – ideally to a level that may obviate the need for mandatory anticoagulation.DTE combines in silico numerical simulations with in vitro measurements by correlating device hemodynamics with platelet activity coagulation markers – before and after iterative design modifications aimed at achieving optimized thrombogenic performance. DTE proof-of-concept is demonstrated by comparing two rotary Left Ventricular Assist Devices (LVADs) (DeBakey vs HeartAssist 5, Micromed Houston, TX), the latter a version of the former following optimization of geometrical features implicated in device thrombogenicity. Cumulative stresses that may drive platelets beyond their activation threshold were calculated along multiple flow trajectories and collapsed into probability density functions (PDFs) representing the device ‘thrombogenic footprint’, indicating significantly reduced thrombogenicity for the optimized design. Platelet activity measurements performed in the actual pump prototypes operating under clinical conditions in circulation flow loops – before and after the optimization with the DTE methodology, show an order of magnitude lower platelet activity rate for the optimized device. The robust capability of this predictive technology – demonstrated here for attaining safe and cost-effective pre-clinical MCS thrombo-optimization – indicates its potential for reducing device thrombogenicity to a level that may significantly limit the extent of concomitant antithrombotic pharmacotherapy needed for safe clinical device use.

Using first principles of fluid and solid mechanics a comprehensive model of human intracranial dynamics is proposed. Blood, cerebrospinal fluid (CSF) and brain parenchyma as well as the spinal canal are included. The compartmental model predicts intracranial pressure gradients, blood and CSF flows and displacements in normal and pathological conditions like communicating hydrocephalus. The system of differential equations of first principles conservation balances is discretized and solved numerically. Fluid-solid interactions of the brain parenchyma with cerebral blood and CSF are calculated. The model provides the transitions from normal dynamics to the diseased state during the onset of communicating hydrocephalus. Predicted results were compared with physiological data from Cine phase-contrast magnetic resonance imaging to verify the dynamic model. Bolus injections into the CSF are simulated in the model and found to agree with clinical measurements.

The advent of implantable blood-recirculating devices such as left ventricular assist devices and prosthetic heart valves provides a viable therapy for patients with end-stage heart failure and valvular disease. However, device-generated pathological flow patterns result in thromboembolic complications that require complex and lifelong anticoagulant therapy, which entails hemorrhagic risks and is not appropriate for certain patients. Optimizing the thrombogenic performance of such devices utilizing numerical simulations requires the development of predictive platelet activation models that account for variations in shear-loading rates characterizing blood flow through such devices. Platelets were exposed in vitro to both dynamic and constant shear stress conditions emulating those found in blood-recirculating devices in order to determine their shear-induced activation and sensitization response. Both these behaviors were found to be dependent on the shear loading rates, in addition to shear stress magnitude and exposure time. We then critically examined several current models and evaluated their predictive capabilities using these results. Shear loading rate terms were then included to account for dynamic aspects that are either ignored or partially considered by these models, and model parameters were optimized. Independent optimization for each of the two types of shear stress exposure conditions tested resulted in different sets of best-fit constants, indicating that universal optimization may not be possible. Inherent limitations of the current models require a paradigm shift from these integral-based discretized power law models to better address the dynamic conditions encountered in blood-recirculating devices.

Disturbances of the cerebrospinal fluid (CSF) flow in the brain can lead to hydrocephalus, a condition affecting thousands of people annually in the US. Considerable controversy exists about fluid and pressure dynamics, and about how the brain responds to changes in flow patterns and compression in hydrocephalus. This paper presents a new model based on the first principles of fluid mechanics. This model of fluid-structure interactions predicts flows and pressures throughout the brain's ventricular pathways consistent with both animal intracranial pressure (ICP) measurements and human CINE phase-contrast magnetic resonance imaging data. The computations provide approximations of the tissue deformations of the brain parenchyma. The model also quantifies the pulsatile CSF motion including flow reversal in the aqueduct as well as the changes in ICPs due to brain tissue compression. It does not require the existence of large transmural pressure differences as the force for ventricular expansion. Finally, the new model gives an explanation of communicating hydrocephalus and the phenomenon of asymmetric hydrocephalus.

A three-dimensional model of the human cerebrospinal fluid (CSF) spaces is presented. Patient-specific brain geometries were reconstructed from magnetic resonance images. The model was validated by comparing the predicted flow rates with Cine phase-contrast MRI measurements. The model predicts the complex CSF flow patterns and pressures in the ventricular system and subarachnoid space of a normal subject. The predicted maximum rostral to caudal CSF flow in the pontine cistern precedes the maximum rostral to caudal flow in the ventricles by about 10% of the cardiac cycle. This prediction is in excellent agreement with the subject-specific flow data. The computational results quantify normal intracranial dynamics and provide a basis for analyzing diseased intracranial dynamics.

Approximately 7.5 × 106 patients in the US currently suffer from end-stage heart failure. The FDA has recently approved the designations of the Thoratec HeartMate II ventricular assist device (VAD) for both bridge-to-transplant and destination therapy (DT) due to its mechanical durability and improved hemodynamics. However, incidence of pump thrombosis and thromboembolic events remains high, and the life-long complex pharmacological regimens are mandatory in its VAD recipients. We have previously successfully applied our device thrombogenicity emulation (DTE) methodology for optimizing device thromboresistance to the Micromed Debakey VAD, and demonstrated that optimizing device features implicated in exposing blood to elevated shear stresses and exposure times significantly reduces shear-induced platelet activation and significantly improves the device thromboresistance. In the present study, we compared the thrombogenicity of the FDA-approved HeartMate II VAD with the DTE-optimized Debakey VAD (now labeled HeartAssist 5). With quantitative probability density functions of the stress accumulation along large number of platelet trajectories within each device which were extracted from numerical flow simulations in each device, and through measurements of platelet activation rates in recirculation flow loops, we specifically show that: (a) Platelets flowing through the HeartAssist 5 are exposed to significantly lower stress accumulation that lead to platelet activation than the HeartMate II, especially at the impeller-shroud gap regions (b) Thrombus formation patterns observed in the HeartMate II are absent in the HeartAssist 5 (c) Platelet activation rates (PAR) measured in vitro with the VADs mounted in recirculation flow-loops show a 2.5-fold significantly higher PAR value for the HeartMate II. This head to head thrombogenic performance comparative study of the two VADs, one optimized with the DTE methodology and one FDA-approved, demonstrates the efficacy of the DTE methodology for drastically reducing the device thrombogenic potential, validating the need for a robust in silico/in vitro optimization methodology for improving cardiovascular devices thromboresistance.