Stochastic Finite Element Analysis of Biological Systems: Comparison of a Simple Intervertebral Disc Model with Experimental Results

Espino, Daniel M.; Meakin, Judith R.; Hukins, D. W. L.; Reid, Janet Elizabeth

doi:10.1080/10255840310001606071

Cited by 17 publications

(8 citation statements)

References 12 publications

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“…Sensitivity studies are commonplace in the computational biomechanics literature (e.g. [28,32,34,36,38,47,48,[50][51][52][53][54][55][56][57]. Such analyses have been particularly useful for determining how alterations in material coefficients affect model predictions.…”

Section: Sensitivity Studies In Computational Biomechanicsmentioning

confidence: 99%

Verification, validation and sensitivity studies in computational biomechanics

Anderson

Ellis

Weiss

2007

Computer Methods in Biomechanics and Biomedical Engineering

205

149

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Computational techniques and software for the analysis of problems in mechanics have naturally moved from their origins in the traditional engineering disciplines to the study of cell, tissue and organ biomechanics. Increasingly complex models have been developed to describe and predict the mechanical behavior of such biological systems. While the availability of advanced computational tools has led to exciting research advances in the field, the utility of these models is often the subject of criticism due to inadequate model verification and validation (V&V). The objective of this review is to present the concepts of verification, validation and sensitivity studies with regard to the construction, analysis and interpretation of models in computational biomechanics. Specific examples from the field are discussed. It is hoped that this review will serve as a guide to the use of V&V principles in the field of computational biomechanics, thereby improving the peer acceptance of studies that use computational modeling techniques.

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Section: Sensitivity Studies In Computational Biomechanicsmentioning

confidence: 99%

Verification, validation and sensitivity studies in computational biomechanics

Anderson

Ellis

Weiss

2007

Computer Methods in Biomechanics and Biomedical Engineering

205

149

View full text Add to dashboard Cite

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“…The statistical nature of the shape model should also facilitate the development of biomechanical models that aim to incorporate the effects of natural subject variability into their analyses (20)(21). This is important since the results of such models can be more sensitive to differences in geometry than other factors (22).…”

mentioning

confidence: 99%

Characterizing the Shape of the Lumbar Spine Using an Active Shape Model

Meakin¹,

Gregory²,

Smith³

et al. 2008

Spine

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Acknowledgements:We thank Dr Y Hirasawa (MD) and Mrs B MacLennan (research radiographer) for acquiring the MR images.Modelling the lumbar spine shape 2 Structured Abstract Study DesignAnalysis of positional magnetic resonance images of normal volunteers. ObjectivesTo compare the reliability and precision of an active shape model to that of conventional lordosis measurements/ Summary of Background DataCharacterisation of lumbar lordosis commonly relies on measurement of angles; these have been found to have errors of around 10 o . MethodsT2 weighted sagittal images of the lumbar spines of 24 male volunteers in the standing posture were acquired using a positional MR scanner. An active shape model of the vertebral bodies from S1 to L1 was created. Lumbar lordosis was also determined by measuring the angles of the superior end-plates. All measurements were performed twice by one observer and once by a second observer. ResultsThe shape model identified two modes of variation to describe the shape of the lumbar spine (mode 1 described curvature and mode 2 described evenness of curvature). Significant correlations were found between mode 1 and total lordosis (R = 0.97, P < 0.001) and between mode 2 and mean absolute deviation of segmental lordosis (R = 0.80, P < 0.001). Intra-and inter-observer reliability was higher for the shape model (ICCs 0.98 -1.00) than for the Modelling the lumbar spine shape 3 lordosis angle measurements (ICCs 0.68 -0.99). The relative error of the shape model (mode 1 = 4 %; mode 2 = 9 %) was lower than the conventional measurements (total lordosis = 10 %). ConclusionsThe shape of the lumbar spine in the sagittal plane can be comprehensively characterised using a shape model. The results are more reliable and precise than measurements of lordosis calculated from end-plate angles. Key wordsLumbar spine; lordosis; positional MRI; Active Shape Model Mini AbstractAn active shape model was used to characterize the shape of the lumbar spine from positional MRI images of 24 male volunteers in the standing posture. The results of the model were more reliable and precise than the conventional method that uses end-plate angle measurements to characterize the lumbar lordosis.Modelling the lumbar spine shape 4

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“…One of the issues, though, with any patient-specific fluid-structure interaction model is the lack of patient-specific data on material properties of the tissue [20]. Therefore, stochastic methods might be necessary for tissue modelling [54] but this introduces variability into predictions. In terms of rheological comparisons for an individual, a model which focuses only on the use of CFD is not expected to alter the qualitative conclusions obtained.…”

Section: Discussionmentioning

confidence: 99%

Computational analysis to predict the effect of pre-bifurcation stenosis on the hemodynamics of the internal and external carotid arteries

Bouteloup¹,

Marinho²,

Chatpun³

et al. 2020

JMES

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This study assessed the hemodynamics of a patient-specific multiple stenosed common carotid artery including its bifurcation into internal and external carotid arteries; ICA and ECA, respectively. A three-dimensional computational model of the common carotid artery was reconstructed using a process of segmentation. Computational fluid dynamics was applied with the assumption that blood is Newtonian and incompressible under pulsatile conditions through the stenotic artery and subsequent bifurcation. Blood was modelled as ‘normal’ and ‘hyperglycaemic’. A region of large recirculation was found to form at bifurcation. The asymmetric velocity flow profile through the ICA was evident through the cardiac cycle with higher velocity at the inner walls of ICA. Hyperglycaemia was found to increase wall shear stresses on the carotid artery and reduce the blood velocity by as much as 4 times in ECA. In conclusion, hemodynamics in ICA and ECA are not equally affected by stenosis, with hyperglycaemic blood potentially providing additional complications to the clinical case.

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Stochastic Finite Element Analysis of Biological Systems: Comparison of a Simple Intervertebral Disc Model with Experimental Results

Cited by 17 publications

References 12 publications

Verification, validation and sensitivity studies in computational biomechanics

Verification, validation and sensitivity studies in computational biomechanics

Characterizing the Shape of the Lumbar Spine Using an Active Shape Model

Computational analysis to predict the effect of pre-bifurcation stenosis on the hemodynamics of the internal and external carotid arteries

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