MR Image-Based Geometric and Hemodynamic Investigation of the Right Coronary Artery with Dynamic Vessel Motion

Torii, Ryo; Keegan, Jennifer; Wood, Nigel B.; Dowsey, Andrew W.; Hughes, Alun D.; Yang, Guang; Firmin, David N.; Thom, Simon; Xu, Xiao Yun

doi:10.1007/s10439-010-0008-4

Cited by 50 publications

(45 citation statements)

References 56 publications

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“…We will denote this approach 4D Image Based (4DIB). A similar technique has been proposed in [71,76] where the authors apply this image-based motion approach to intra-cranial aneurysms and coronary arteries respectively, even if implementing different strategies for some steps of the procedure.…”

Section: Image Assimilation In a Moving Domain Simulationmentioning

confidence: 99%

Applications of variational data assimilation in computational hemodynamics

D’Elia

Mirabella

Passerini

et al. 2012

MS&A

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The development of new technologies for acquiring measures and images in order to investigate cardiovascular diseases raises new challenges in scientific computing. These data can be in fact merged with the numerical simulations for improving the accuracy and reliability of the computational tools. Assimilation of measured data and numerical models is well established in meteorology, whilst it is relatively new in computational hemodynamics. Different approaches are possible for the mathematical setting of this problem. Among them, we follow here a variational formulation, based on the minimization of the mismatch between data and numerical results by acting on a suitable set of control variables. Several modeling and methodological problems related to this strategy are open, such as the analysis of the impact of the noise affecting the data, and the design of effective numerical solvers. In this chapter we present three examples where a mathematically sound (variational) assimilation of data can significantly improve the reliability of the numerical models. Accuracy and reliability of computational models are increasingly important features in view of the progressive adoption of numerical tools in the design of new therapies and, more in general, in the decision making process of medical doctors.

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Section: Image Assimilation In a Moving Domain Simulationmentioning

confidence: 99%

Applications of variational data assimilation in computational hemodynamics

D’Elia

Mirabella

Passerini

et al. 2012

MS&A

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“…Their conclusion was that the computed flow field only agreed with the measured flow field when the full wall motion (displacement due to pressure changes and translation due to the beating heart) was included, suggesting that the flow field is not only dependent on the geometry but also on the motion of the aorta. In a study by Torii et al [17], the motion of the right coronary artery over 14 time points in the cardiac cycle was measured and implemented in a numerical solver. The MRI data acquisition in their study required seven separate scanning sessions, each lasting 75-90 minutes, over a period of a month.…”

Section: Introductionmentioning

confidence: 99%

Improving Blood Flow Simulations by Incorporating Measured Subject-Specific Wall Motion

Lantz

Dyverfeldt

Ebbers

2014

Cardiovasc Eng Tech

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Phone: +4613282335, email: Jonas.Lantz@liu.se, fax: +4613281101 2 Abstract Purpose: Physiologically relevant simulations of blood flow require models that allow for wall deformation.Normally a fluid-structure interaction (FSI) approach is used; however, this method relies on several assumptions and patient-specific material parameters that are difficult or impossible to measure in vivo. Method:In order to circumvent the assumptions inherent in FSI models, aortic wall motion was measured with MRI and prescribed directly in a numerical solver. In this way is not only the displacement of the vessel accounted for, but also the interaction with the beating heart and surrounding organs. In order to highlight the effect of wall motion, comparisons with standard rigid wall models was performed in a healthy human aorta. Results:The additional computational cost associated with prescribing the wall motion was low (17%). Standard hemodynamic parameters such as time-averaged wall shear stress and oscillatory shear index seemed largely unaffected by the wall motion, as a consequence of the smoothing effect inherent in time-averaging. Conversely, instantaneous wall shear stress was greatly affected by the wall motion; the wall dynamics seemed to produce a lower wall shear stress magnitude compared to a rigid wall model. In addition, it was found that if wall motion was taken into account the computed flow field agreed better with in vivo measurements. Conclusion:This article show that it is feasible to include measured subject-specific wall motion into numerical simulations, and that the wall motion greatly affects the flow field. This approach to incorporate measured motion should be considered in future studies of arterial blood flow simulations.

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“…The medical-image-based time-dependent anatomical model comes from [43]. The MRI-based method used in extracting that model can be found in [43].…”

Section: Mri-based Time-dependent Anatomical Modelmentioning

confidence: 99%

“…In this paper, we focus on coronary arterial dynamics analysis, with the medical-image-based time-dependent anatomical model coming from [43]. The long-term objective is to have a better understanding of the interaction between the blood flow and arterial dynamics, which is difficult to observe experimentally.…”

Section: Introductionmentioning

confidence: 99%

“…One reason for that is the difficulty in acquiring the wall thickness and the motion of a coronary artery, which is substantial in the RCA. Approaches used for acquiring such time-dependent anatomical data [39,[41][42][43] include the time-dependent anatomical-model extraction method introduced in [43], which is based fully on magnetic resonance imaging (MRI). This MRI-based method was used in [43] for blood flow analysis with cardiac-induced arterial motion.…”

Section: Introductionmentioning

confidence: 99%

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Coronary arterial dynamics computation with medical-image-based time-dependent anatomical models and element-based zero-stress state estimates

et al. 2014

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We propose a method for coronary arterial dynamics computation with medical-image-based time-dependent anatomical models. The objective is to improve the computational analysis of coronary arteries for better understanding of the links between the atherosclerosis development and mechanical stimuli such as endothelial wall shear stress and structural stress in the arterial wall. The method has two components. The first one is element-based zero-stress (ZS) state estimation, which is an alternative to prestress calculation. The second one is a "mixed ZS state" approach, where the ZS states for different elements in the structural mechanics mesh are estimated with reference configurations based on medical images coming from different instants within the cardiac cycle. We demonstrate the robustness of the method in a patient-specific coronary arterial dynamics computation where the motion of a thin strip along the arterial surface and two cut surfaces at the arterial ends is specified to match the motion extracted from the medical images.

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MR Image-Based Geometric and Hemodynamic Investigation of the Right Coronary Artery with Dynamic Vessel Motion

Cited by 50 publications

References 56 publications

Applications of variational data assimilation in computational hemodynamics

Applications of variational data assimilation in computational hemodynamics

Improving Blood Flow Simulations by Incorporating Measured Subject-Specific Wall Motion

Coronary arterial dynamics computation with medical-image-based time-dependent anatomical models and element-based zero-stress state estimates

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