Fluid-structure interactions of peripheral arteries using a coupled in silico and in vitro approach.

Vascular compliance is considered both a cause and a consequence of cardiovascular disease and a significant factor in the mid- and long-term patency of vascular grafts. However, the biomechanical effects of localised changes in compliance cannot be satisfactorily studied with the available medical imaging technologies or surgical simulation materials. To address this unmet need, we developed a coupled silico-vitro platform which allows for the validation of numerical fluid-structure interaction results as a numerical model and physical prototype. This numerical one-way and two-way fluid-structure interaction study is based on a three-dimensional computer model of an idealised femoral artery which is validated against patient measurements derived from the literature. The numerical results are then compared with experimental values collected from compliant arterial phantoms via direct pressurisation and ring tensile testing. Phantoms within a compliance range of 1.4-68.0%/100 mmHg were fabricated via additive manufacturing and silicone casting, then mechanically characterised via ring tensile testing and optical analysis under direct pressurisation with moderately statistically significant differences in measured compliance ranging between 10 and 20% for the two methods. One-way fluid-structure interaction coupling underestimated arterial wall compliance by up to 14.7% compared with two-way coupled models. Overall, Solaris™ (Smooth-On) matched the compliance range of the numerical and in vivo patient models most closely out of the tested silicone materials. Our approach is promising for vascular applications where mechanical compliance is especially important, such as the study of diseases which commonly affect arterial wall stiffness, such as atherosclerosis, and the model-based design, surgical training, and optimisation of vascular prostheses.

Combining experimental and computational techniques to understand and improve dry powder inhalers.

INTRODUCTION: Dry Powder Inhalers (DPIs) continue to be developed to deliver an expanding range of drugs to treat an ever-increasing range of medical conditions; with each drug and device combination needing a specifically designed inhaler. Fast regulatory approval is essential to be first to market, ensuring commercial profitability. AREAS COVERED: In vitro deposition, particle image velocimetry, and computational modeling using the physiological geometry and representative anatomy can be combined to give complementary information to determine the suitability of a proposed inhaler design and to optimize its formulation performance. In combination, they allow the entire range of questions to be addressed cost-effectively and rapidly. EXPERT OPINION: Experimental techniques and computational methods are improving rapidly, but each needs a skilled user to maximize results obtained from these techniques. Multidisciplinary teams are therefore key to making optimal use of these methods and such qualified teams can provide enormous benefits to pharmaceutical companies to improve device efficacy and thus time to market. There is already a move to integrate the benefits of Industry 4.0 into inhaler design and usage, a trend that will accelerate.

Focal spinal arachnoiditis increases subarachnoid space pressure: a computational study.

BACKGROUND: Enlarging fluid filled cystic cavitations form within the spinal cord in up to 28% of spinal cord injured patients. These post-traumatic syrinxes can cause neurological deterioration and current treatment results are unsatisfactory. Localized scar tissue (arachnoiditis) within the subarachnoid space at the level of injury has been suggested to be involved in the pathogenesis of syrinx formation. This study tests the hypothesis that pressure pulses in the subarachnoid space are accentuated adjacent to regions of arachnoiditis, which may drive fluid into the spinal cord and contribute to syrinx formation. METHODS: An axisymmetric, cylindrical computational fluid dynamics model was developed to represent the subarachnoid space under normal physiological conditions and in the presence of arachnoiditis. Cerebrospinal fluid flow into the model was estimated from magnetic resonance imaging flow studies. Arachnoiditis was modelled as a porous obstruction in the subarachnoid space. FINDINGS: Peak fluid pressures were higher above the obstruction than in the absence of obstruction. The peak pressures were strongly dependent on the permeability of the obstruction. INTERPRETATION: Elevations in subarachnoid space pressures due to arachnoiditis may facilitate fluid flow into the spinal cord, enhancing syrinx formation. This suggests that it may be worthwhile to investigate strategies that inhibit arachnoiditis or minimize systolic pressure peaks for treating or preventing syringomyelia.

Computer modelling of the cerebrospinal fluid flow dynamics of aqueduct stenosis.

As the craniospinal space is a pressure loaded system it is difficult to conceptualize and understand the flow dynamics through the ventricular system. Aqueduct stenosis compromises flow, increasing the pressure required to move cerebrospinal fluid (CSF) through the ventricles. Under normal circumstances, less than one pascal (1 Pa) of pressure is required to move a physiological flow of CSF through the aqueduct. This is too small to measure using clinical pressure transducers. A computational fluid dynamics (CFD) program, CFX, has been used to model two forms of aqueduct stenosis: simple narrowing and forking of the aqueduct. This study shows that with mild stenoses, the increase in pressure required to drive flow becomes significant (86-125 Pa), which may result in an increased transmantle pressure difference but not necessarily an increased intraventricular pressure. Severe stenoses will result in both. Wall shear stresses increase concomitantly and may contribute to local damage of the aqueduct wall and further gliosis with narrowing.

Computer modelling of CSF flow in the subarachnoid space.

Computer modelling has been undertaken to determine the resistance to flow in the subarachnoid space (SAS) and to investigate its contribution to the total pressure drop. A Computational Fluid Dynamics model has been used to determine the pressure drop as a function of both the flow rate and the permeability of the subarachnoid space. The conclusion is that the SAS contributes about 1-5% of the total CSF flow resistance. However, scarring of the arachnoid fibres could increase the flow resistance considerably.

Fluid dynamics of the cerebral aqueduct.

Despite a multitude of theories describing the mechanics of the intracranial spaces in diseases such as hydrocephalus, little is known about the mechanics of normal CSF flow. A pressure difference is required to drive CSF flow. Knowing that the pressure difference driving fluid through the aqueduct is beyond the resolution of clinically used pressure transducers, a computational fluid dynamics program was used to analyze flow through an aqueduct shape. Flow through this duct was compared with that through a cylinder and through a double hourglass. Both steady and oscillating flows were tested, revealing that only 1.1 Pa of pressure is required to move CSF through the aqueduct. This suggests that normally less than 5% of the total resistance to CSF flow within the CSF pathways occurs in the aqueduct.