Ventricular mechanics in diastole: material parameter sensitivity

Stevens, Carey; Remme, Espen W.; LeGrice, Ian J.; Hunter, Peter

doi:10.1016/s0021-9290(02)00452-9

Cited by 120 publications

(83 citation statements)

References 12 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the PASϩACTϩFIB simulation, E cr during ejection was again more physiological, but the large differences in E cr during filling remained. Agreement between the model and experiment might be improved by carefully tuning the contribution of the three effects, using a method similar to that proposed by Stevens et al (36) to investigate the sensitivity of diastolic ventricular mechanics to settings of passive material properties. We considered such an optimization inappropriate, since in doing so we would compensate for other model simplifications, as discussed below.…”

Section: Discussionmentioning

confidence: 99%

Determinants of left ventricular shear strain

Bovendeerd¹,

Kroon²,

Delhaas³

2009

American Journal of Physiology-Heart and Circulatory Physiology

View full text Add to dashboard Cite

matical models of cardiac mechanics can potentially be used to relate abnormal cardiac deformation, as measured noninvasively by ultrasound strain rate imaging or magnetic resonance tagging (MRT), to the underlying pathology. However, with current models, the correct prediction of wall shear strain has proven to be difficult, even for the normal healthy heart. Discrepancies between simulated and measured strains have been attributed to 1) inadequate modeling of passive tissue behavior, 2) neglecting active stress development perpendicular to the myofiber direction, or 3) neglecting crossover of myofibers in between subendocardial and subepicardial layers. In this study, we used a finite-element model of left ventricular (LV) mechanics to investigate the sensitivity of midwall circumferential-radial shear strain (Ecr) to settings of parameters determining passive shear stiffness, cross-fiber active stress development, and transmural crossover of myofibers. Simulated time courses of midwall LV Ecr were compared with time courses obtained in three healthy volunteers using MRT. Ecr as measured in the volunteers during the cardiac cycle was characterized by an amplitude of ϳ0.1. In the simulations, a realistic amplitude of the Ecr signal could be obtained by tuning either of the three model components mentioned above. However, a realistic time course of Ecr, with virtually no change of Ecr during isovolumic contraction and a correct base-to-apex gradient of Ecr during ejection, could only be obtained by including transmural crossover of myofibers. Thus, accounting for this crossover seems to be essential for a realistic model of LV wall mechanics. magnetic resonance tagging; finite-element model; cardiac mechanics; myofiber angle DEFORMATION OF THE CARDIAC WALL can be assessed noninvasively using ultrasound strain rate imaging (11) or magnetic resonance tagging (MRT) (4). The deformation patterns acquired may deviate from normal in the case of cardiac pathology, e.g., aortic stenosis, ischemia, or conduction disorders (39,40,43). The analysis of abnormal deformation patterns toward the underlying pathology is not straightforward: the relation between the change in the deformation pattern and the pathology is complex, and the criteria for normal and abnormal strain patterns have not yet been defined. A mathematical model capable of predicting the forward relation between pathology and deformation could, if used in an inverse analysis, be a useful clinical tool, not only in diagnosis but also in intervention selection and planning, by simulating candidate interventions beforehand.Several models describing the deformation of cardiac walls have been proposed (5,6,14,19,20,28,35,41,42,45), but none of these models have already been used as a diagnostic tool. As a first step toward this application, one would require the models to be able to correctly predict deformation in the wall of the healthy heart. Most models are able to correctly predict circumferential, longitudinal, and radial strain (5,14,28,41,42,45). However, ...

show abstract

Section: Discussionmentioning

confidence: 99%

Determinants of left ventricular shear strain

Bovendeerd¹,

Kroon²,

Delhaas³

2009

American Journal of Physiology-Heart and Circulatory Physiology

View full text Add to dashboard Cite

show abstract

“…The transmural helix angle typically ranges from Ϫ60°at the epicardium to ϩ60°at the endocardium, although a large variation between measurements exists. This myocardial fiber architecture is found to be essentially similar in humans (24) and other mammalian species (25). Mathematical modeling shows that such double-helical arrangement of LV myocardial fibers is efficient for dispersing strain uniformly and conserving energy expenditure (26).…”

mentioning

confidence: 84%

“…3b). Average FA and mean ADC values were then computed in the infarct, adjacent, and remote regions of the 10 slices (approximately slice 19,21,23,25,27,29,31,33,35, and 37 out of total 40 slices) that covered the entire infarct area. To analyze the possible change of LV double-helix structure near the infarcted region, the transmural distributions of helix angles were assessed as follows.…”

Section: Mr Data Analysismentioning

confidence: 99%

MR diffusion tensor imaging study of postinfarct myocardium structural remodeling in a porcine model

Nicholls

et al. 2007

Magnetic Resonance in Med

116

110

View full text Add to dashboard Cite

This study aimed to investigate postinfarct left ventricular (LV) fiber structural alterations by ex vivo diffusion tensor imaging (DTI) in a porcine heart model. In vivo cardiac MR imaging was first performed to measure ventricular function in six adult pigs with septal infarction near apex induced by the LAD ligation 13 weeks earlier. Hearts were then excised from the infarct pigs (n ‫؍‬ 6) and six intact controls (n ‫؍‬ 6) and fixed in formalin. High-resolution DTI was employed to examine changes in fractional anisotropy (FA), apparent diffusion coefficient (ADC), and transmural helix angle distribution in the infarct, adjacent and remote regions as compared to the sham regions in the controls. FA values were found to decrease in the infarct and differ between the adjacent and remote regions. ADC increase in the infarct region was substantial, while changes in the adjacent and remote regions were insignificant. Structurally, the doublehelix myocardial structure shifted toward more left-handed around the infarcted myocardium. Accordingly, the histological analysis revealed clear fiber structural degradation in the adjacent region. These findings confirmed the subtle alterations in the myocardial fiber quality and structure not only in the in- Key words: myocardium infarction; borderzone; diffusion tensor imaging; fiber architecture Both structural and functional assessments are important in our understanding of myocardial contraction and relaxation in normal and pathologic states (1,2). It has been long known that left ventricular (LV) myocardial microstructure or fiber structure plays a critical role in determining mechanical properties, such as ventricular torsion, strain, and stress (3,4). Owing to the recent advances in cardiac MR and ultrasound imaging, there is an increasing interest in investigating LV by directly associating the LV myocardial fiber geometry to the complex spatial-temporal sequence of electrical activation and mechanical contraction/relaxation in beating hearts (1,2,5). LV is known to electrically activate first at the exits of Purkinje system, close to apical endocardium. The electrical activation then propagates from apex to base via depolarization and repolarization in both septum and free wall (1,6). This is accompanied by successive mechanical shortenings and intracavitary blood flow along the parallel apex-to-base direction, although highly transient and localized myocardial deformations exist.In infarcted myocardium, remodeling involves both structural and functional changes. Such changes have been found to occur in both infarcted myocardium and adjacent and remote myocardium (7-11). The effects of myocardial infarction (MI) on LV function have been investigated in numerous studies. In recent years, cardiac MR (CMR) imaging has become the accepted reference standard to assess LV function since CMR methods are both accurate and highly reproducible (12). These CMR techniques can be used to detect, localize, and quantify both MI and LV functions. Patten et al. (13) found that hearts...

show abstract

“…Gjuvsland et al [41] argued that systems with monotone doseresponse relationships tend to produce more additive GP maps than unimodal or other non-monotone relationships. The low amount of interaction effects in figure 4 suggests that findings from earlier separate studies of stiffness [22], geometry [23] and fibre structure [24] will often remain valid under different conditions, including different genetic backgrounds and more complex and realistic genetic parameter variation. The details of the parameter-to-phenotype mapping will depend on the choice of constitutive law, as they use different parametrizations to capture different aspects of material behaviour.…”

Section: Genotype -Phenotype Map Features For Normal Versus Pathologimentioning

confidence: 99%

“…Specifically, we model the passive filling phase (late diastole) of the left ventricle, in which many individual factors have been studied previously [22][23][24][25]. The mechanics in this phase are relatively simple owing to the absence of active contraction, yet the strain and elastic energy stored in diastole gives our conclusions some relevance to the later phases of the heartbeat as well.…”

Section: Introductionmentioning

confidence: 99%

Towards causally cohesive genotype–phenotype modelling for characterization of the soft-tissue mechanics of the heart in normal and pathological geometries

Nordbø

Gjuvsland

Nermoen

et al. 2015

J. R. Soc. Interface.

View full text Add to dashboard Cite

A scientific understanding of individual variation is key to personalized medicine, integrating genotypic and phenotypic information via computational physiology. Genetic effects are often context-dependent, differing between genetic backgrounds or physiological states such as disease. Here, we analyse in silico genotype–phenotype maps (GP map) for a soft-tissue mechanics model of the passive inflation phase of the heartbeat, contrasting the effects of microstructural and other low-level parameters assumed to be genetically influenced, under normal, concentrically hypertrophic and eccentrically hypertrophic geometries. For a large number of parameter scenarios, representing mock genetic variation in low-level parameters, we computed phenotypes describing the deformation of the heart during inflation. The GP map was characterized by variance decompositions for each phenotype with respect to each parameter. As hypothesized, the concentric geometry allowed more low-level parameters to contribute to variation in shape phenotypes. In addition, the relative importance of overall stiffness and fibre stiffness differed between geometries. Otherwise, the GP map was largely similar for the different heart geometries, with little genetic interaction between the parameters included in this study. We argue that personalized medicine can benefit from a combination of causally cohesive genotype–phenotype modelling, and strategic phenotyping that captures effect modifiers not explicitly included in the mechanistic model.

show abstract

Ventricular mechanics in diastole: material parameter sensitivity

Cited by 120 publications

References 12 publications

Determinants of left ventricular shear strain

Determinants of left ventricular shear strain

MR diffusion tensor imaging study of postinfarct myocardium structural remodeling in a porcine model

Towards causally cohesive genotype–phenotype modelling for characterization of the soft-tissue mechanics of the heart in normal and pathological geometries

Contact Info

Product

Resources

About