Obrist, D. | bioRxiv Science

bioRxiv2023

Multiscale Multimodal Characterization and Simulation of Structural Alterations in Failed Bioprosthetic Heart Valves

Calcific degeneration is the most frequent type of heart valve failure, with rising incidence due to the ageing population. The gold standard treatment to date is valve replacement. Unfortunately, calcification oftentimes re-occurs in bioprosthetic substitutes, with the governing processes remaining poorly understood. Here, we present a multiscale, multimodal analysis of disturbances and extensive mineralisation of the collagen network in failed bioprosthetic bovine pericardium valve explants with full histoanatomical context. In addition to highly abundant mineralized collagen fibres and fibrils, calcified micron-sized particles previously discovered in native valves were also prevalent on the aortic as well as the ventricular surface of bioprosthetic valves. The two mineral types (fibers and particles) were detectable even in early-stage mineralisation, prior to any macroscopic calcification. Based on multiscale multimodal characterisation and high-fidelity simulations, we demonstrate that mineral occurrence coincides with regions exposed to high haemodynamic and biomechanical indicators. These insights obtained by multiscale analysis of failed bioprosthetic valves may serve as groundwork for the evidence-based development of more durable alternatives. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=176 SRC="FIGDIR/small/529530v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@c7e0b5org.highwire.dtl.DTLVardef@71bdbdorg.highwire.dtl.DTLVardef@15fdc23org.highwire.dtl.DTLVardef@6dbd1c_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2018

A multi-scale sub-voxel perfusion model to estimate diffusive capillary wall conductivity in multiple sclerosis lesions from perfusion MRI data

We propose a new mathematical model to infer capillary leakage coefficients from dynamic susceptibility contrast MRI data. To this end, we derive an embedded mixed-dimension flow and transport model for brain tissue perfusion on a sub-voxel scale. This model is used to obtain the contrast agent concentration distribution in a single MRI voxel during a perfusion MRI sequence. We further present a magnetic resonance signal model for the considered sequence including a model for local susceptibility effects. This allows modeling MR signal-time curves that can be compared to clinical MRI data. The proposed model can be used as a forward model in the inverse modeling problem of inferring model parameters such as the diffusive capillary wall conductivity. Acute multiple sclerosis lesions are associated with a breach in the integrity of the blood brain barrier. Applying the model to perfusion MR data of a patient with acute multiple sclerosis lesions, we conclude that diffusive capillary wall conductivity is a good indicator for characterizing activity of lesions, even if other patient-specific model parameters are not well-known.\n\nAuthor summaryThe use of advanced brain imaging techniques has supported in-vivo research targeted to the integrity of the blood-brain barrier. We propose a new type of post-processing for raw image data using contrast agent perfusion simulations on the data-poor capillary scale. Combining modern simulation techniques with the clinical image data allows us to determine patient-specific and pathologically relevant parameters such as the capillary wall conductivity. The presented simulation model is a step towards the quantification of contrast agent leakage in the brain, which is typical for acute multiple sclerosis lesions, but also occurs with other diseases affecting the blood-brain-barrier, such as cerebral gliomas.

bioengineering↗