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On fibre dispersion modelling of soft biological tissues: a review.

ABSTRACT: Collagen fibres within fibrous soft biological tissues such as artery walls, cartilage, myocardiums, corneas and heart valves are responsible for their anisotropic mechanical behaviour. It has recently been recognized that the dispersed orientation of these fibres has a significant effect on the mechanical response of the tissues. Modelling of the dispersed structure is important for the prediction of the stress and deformation characteristics in (patho)physiological tissues under various loading conditions. This paper provides a timely and critical review of the continuum modelling of fibre dispersion, specifically, the angular integration and the generalized structure tensor models. The models are used in representative numerical examples to fit sets of experimental data that have been obtained from mechanical tests and fibre structural information from second-harmonic imaging. In particular, patches of healthy and diseased aortic tissues are investigated, and it is shown that the predictions of the models fit very well with the data. It is straightforward to use the models described herein within a finite-element framework, which will enable more realistic (and clinically relevant) boundary-value problems to be solved. This also provides a basis for further developments of material models and points to the need for additional mechanical and microstructural data that can inform further advances in the material modelling.

SUBMITTER: Holzapfel GA

PROVIDER: S-EPMC6501667 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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On fibre dispersion modelling of soft biological tissues: a review.

Holzapfel Gerhard A GA Ogden Ray W RW Sherifova Selda S

Proceedings. Mathematical, physical, and engineering sciences 20190403 2224

Collagen fibres within fibrous soft biological tissues such as artery walls, cartilage, myocardiums, corneas and heart valves are responsible for their anisotropic mechanical behaviour. It has recently been recognized that the dispersed orientation of these fibres has a significant effect on the mechanical response of the tissues. Modelling of the dispersed structure is important for the prediction of the stress and deformation characteristics in (patho)physiological tissues under various loadin ...[more]

PMID: 31105452

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Project description:Radio-frequency (RF) heating of soft biological tissues during electrosurgical procedures is a fast process that involves phase change through evaporation and transport of intra- and extra-cellular water, and where variations in physical properties with temperature and water content play significant role. Accurately predicting and capturing these effects would improve the modeling of temperature change in the tissue allowing the development of improved instrument design and better understanding of tissue damage and necrosis. Previous models based on the Pennes' bioheat model neglect both evaporation and transport or consider evaporation through numerical correlations, however, do not account for changes in physical properties due to mass transport or phase change, nor capture the pressure increase due to evaporation within the tissue. While a porous media approach can capture the effects of evaporation, transport, pressure and changes in physical properties, the model assumes free diffusion of liquid and gas without a careful examination of assumptions on transport parameters in intact tissue resulting in significant under prediction of temperature. These different approaches have therefore been associated with errors in temperature prediction exceeding 20% when compared to experiments due to inaccuracies in capturing the effects of evaporation losses and transport. Here, we present a model of RF heating of hydrated soft tissue based on mixture theory where the multiphase nature of tissue is captured within a continuum thermomechanics framework, simultaneously considering the transport, deformation and phase change losses due to evaporation that occur during electrosurgical heating. The model predictions are validated against data obtained for in vivo ablation of porcine liver tissue at various power settings of the electrosurgical unit. The model is able to match the mean experimental temperature data with sharp gradients in the vicinity of the electrode during rapid low and high power ablation procedures with errors less than 7.9%. Additionally, the model is able to capture fast vaporization losses and the corresponding increase in pressure due to vapor buildup which have a significant effect on temperature prediction beyond 100 °C.

Project description:Multiple sclerosis leads to diffuse damage of the central nervous system, affecting also the normal-appearing white matter. Demyelination and axonal degeneration reduce regional fractional anisotropy in normal-appearing white matter, which can be routinely mapped with diffusion tensor imaging. However, the standard fractional anisotropy metric is also sensitive to physiological variations in orientation dispersion of white matter fibres. This complicates the detection of disease-related damage in large parts of cerebral white matter where microstructure physiologically displays a high degree of fibre dispersion. To resolve this ambiguity, we employed a novel tensor-valued encoding method for diffusion MRI, which yields a microscopic fractional anisotropy metric that is unaffected by regional variations in orientation dispersion. In 26 patients with relapsing-remitting multiple sclerosis, 14 patients with primary-progressive multiple sclerosis and 27 age-matched healthy controls, we compared standard fractional anisotropy mapping with the novel microscopic fractional anisotropy mapping method, focusing on normal-appearing white matter. Mean microscopic fractional anisotropy and standard fractional anisotropy of normal-appearing white matter were significantly reduced in both patient groups relative to healthy controls, but microscopic fractional anisotropy yielded a better reflection of disease-related white-matter alterations. The reduction in mean microscopic fractional anisotropy showed a significant positive linear relationship with physical disability, as reflected by the expanded disability status scale. Mean reduction of microscopic fractional anisotropy in normal-appearing white matter also scaled positively with individual cognitive dysfunction, as measured with the symbol digit modality test. Mean microscopic fractional anisotropy reduction in normal-appearing white matter also showed a positive relationship with total white-matter lesion load as well as lesion load in specific tract systems. None of these relationships between normal-appearing white-matter microstructure and clinical, cognitive or structural measures emerged when using mean fractional anisotropy. Together, the results provide converging evidence that microscopic fractional anisotropy mapping substantially advances the assessment of cerebral white matter in multiple sclerosis by disentangling microstructure damage from variations in physiological fibre orientation dispersion at the stage of data acquisition. Since tensor-valued encoding can be implemented in routine diffusion MRI, microscopic fractional anisotropy mapping bears considerable potential for the future assessment of disease progression in normal-appearing white matter in both relapsing-remitting and progressive forms of multiple sclerosis as well as other white-matter-related brain diseases.

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On fibre dispersion modelling of soft biological tissues: a review.

Publications

On fibre dispersion modelling of soft biological tissues: a review.

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