Image-Based Mechanical Analysis of Stent Deformation: Concept and Exemplary Implementation for Aortic Valve Stents

Gessat, Michael; Hopf, Raoul; Pollok, Thomas; Russ, Christoph; Frauenfelder, Thomas; Sündermann, Simon H.; Hirsch, Sven; Mazza, Edoardo; Székely, Gábor; Falk, Volkmar

doi:10.1109/tbme.2013.2273496

Cited by 27 publications

(11 citation statements)

References 19 publications

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“…Including fluid flow would allow us to predict shear stresses on the myocardial wall, and more importantly, on the four heart valves, throughout the entire cardiac cycle [21]. This presents tremendous opportunities to better understand the mechanisms of valvular disease and optimize their treatment in the form of valve repair or replacement, either through open heart surgery or minimally invasive intervention [14]. …”

Section: Discussionmentioning

confidence: 99%

The Living Heart Project: A robust and integrative simulator for human heart function

Baillargeon

Rebelo

Fox

et al. 2014

European Journal of Mechanics - A/Solids

287

266

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The heart is not only our most vital, but also our most complex organ: Precisely controlled by the interplay of electrical and mechanical fields, it consists of four chambers and four valves, which act in concert to regulate its filling, ejection, and overall pump function. While numerous computational models exist to study either the electrical or the mechanical response of its individual chambers, the integrative electro-mechanical response of the whole heart remains poorly understood. Here we present a proof-of-concept simulator for a four-chamber human heart model created from computer topography and magnetic resonance images. We illustrate the governing equations of excitation-contraction coupling and discretize them using a single, unified finite element environment. To illustrate the basic features of our model, we visualize the electrical potential and the mechanical deformation across the human heart throughout its cardiac cycle. To compare our simulation against common metrics of cardiac function, we extract the pressure-volume relationship and show that it agrees well with clinical observations. Our prototype model allows us to explore and understand the key features, physics, and technologies to create an integrative, predictive model of the living human heart. Ultimately, our simulator will open opportunities to probe landscapes of clinical parameters, and guide device design and treatment planning in cardiac diseases such as stenosis, regurgitation, or prolapse of the aortic, pulmonary, tricuspid, or mitral valve.

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Section: Discussionmentioning

confidence: 99%

The Living Heart Project: A robust and integrative simulator for human heart function

Baillargeon

Rebelo

Fox

et al. 2014

European Journal of Mechanics - A/Solids

287

266

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“…The process of postoperative CT image acquisition, the method for extracting information about the postoperative stent shape from these images and how that information is used in a mechanical analysis to create an estimate of the radial forces between the stent and the surrounding tissues and calcifications is presented in [9] and [10]. Here, we confine ourselves to a brief overview over these techniques, and refer the reader to the cited papers for further detail.…”

Section: Data Preprocessing and Mechanical Analysismentioning

confidence: 99%

“…A mechanical model of the stent in its original (undeformed) shape was created from microCT scans of the device and a method for using the grid points extracted from the patient images as soft kinematic constraints was developed [14]. In [10] we describe, how this method is used to simultaneously reduce point localization errors that occur during the localization of the grid points and to extract estimates for the radial force between the stent and its surroundings. The basic idea here is to derive the radial forces from the deformation of the implanted stent when compared to the relaxed stent shape.…”

Section: Data Preprocessing and Mechanical Analysismentioning

confidence: 99%

“…For the presented approach, two additional manual processing steps were added to the pipeline as described in [10]: (1) With an expert clinician, six anatomical landmarks at the aortic annulus (the three commissures and the three sinuses) as well as the approximate position of the left and right coronary arteries were marked manually in the CT images (see Fig. 2a).…”

Section: Data Preprocessing and Mechanical Analysismentioning

confidence: 99%

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Stent Maps — Comparative Visualization for the Prediction of Adverse Events of Transcatheter Aortic Valve Implantations

Born

Sündermann

Russ

et al. 2014

IEEE Trans. Visual. Comput. Graphics

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Transcatheter aortic valve implantation (TAVI) is a minimally-invasive method for the treatment of aortic valve stenosis in patients with high surgical risk. Despite the success of TAVI, side effects such as paravalvular leakages can occur postoperatively. The goal of this project is to quantitatively analyze the co-occurrence of this complication and several potential risk factors such as stent shape after implantation, implantation height, amount and distribution of calcifications, and contact forces between stent and surrounding structure. In this paper, we present a two-dimensional visualization (stent maps), which allows (1) to comprehensively display all these aspects from CT data and mechanical simulation results and (2) to compare different datasets to identify patterns that are typical for adverse effects. The area of a stent map represents the surface area of the implanted stent - virtually straightened and uncoiled. Several properties of interest, like radial forces or stent compression, are displayed in this stent map in a heatmap-like fashion. Important anatomical landmarks and calcifications are plotted to show their spatial relation to the stent and possible correlations with the color-coded parameters. To provide comparability, the maps of different patient datasets are spatially adjusted according to a corresponding anatomical landmark. Also, stent maps summarizing the characteristics of different populations (e.g. with or without side effects) can be generated. Up to this point several interesting patterns have been observed with our technique, which remained hidden when examining the raw CT data or 3D visualizations of the same data. One example are obvious radial force maxima between the right and non-coronary valve leaflet occurring mainly in cases without leakages. These observations confirm the usefulness of our approach and give starting points for new hypotheses and further analyses. Because of its reduced dimensionality, the stent map data is an appropriate input for statistical group evaluation and machine learning methods.

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“…The boundaries of the flow in the arteries are not rigid, and cannot be predicted using rigid wall, or predefined-boundarymotion calculations [2]. The methodology developed is to improve a commercially available computational fluid dynamics (CFD) method [3] to assess hemodynamic in ISO's 5840 [4]. The stress analysis by combining corresponding functions and the restenosis problem were studied by cardiovascular simulations as research concept shown in Fig.…”

Section: Introductionmentioning

confidence: 99%

Computational Material Analysis of Structural and Hemodynamic Model of Coronary Stent by CFD/FEA in Computer Aided Mechanical Engineering Approach

Karaçal

2016

Acta Phys. Pol. A

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With the development of new technologies, it is very popular to use a coronary stent that is a small mesh tubeshaped medical device deployed to treat narrow or weak arteries as part of a procedure called percutaneous coronary intervention. Several aspects, such as stent design, stent wire type, mechanical and material characteristics of stent have different influences on stent intervention. It has not been reported about what impacts on stent struts by the hemodynamic behavior on stent material and very few numerical studies have considered both the mechanical and hemodynamic impact of stent implementation. Computational simulation method for realization of realistic structural and hemodynamic micro environment model in this research provided valuable results of long-term functional knowledge of stent material behavior that are time consuming and expensive to determine otherwise. Computational fluid dynamics and finite element analysis simulation models were investigated and developed to evaluate engineering properties that affect stent functional attributes. These characteristics are dependences of material properties on blood flow conditions such as structural load, shear-strain rate, radial strength, and wall shear stresses, which need to be scientifically explored. To understand the material (Fe-18Cr-14Ni-2.5Mo as stainless steel 316LVM) mechanical performance of the stent, a finite element analysis simulation model was established when exposed to pulsatile blood pressure. In this study, computational fluid dynamics model was generated to calculate the wall shear stresses and strain distribution in stented vessel carrying blood to heart. The analytical analysis of mechanical and hemodynamic conduct of a stent in this investigation may help for better designs of stent, and provide deeper comprehension to support clinical cardiovascular surgeons and guide potential therapeutic strategies.

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Image-Based Mechanical Analysis of Stent Deformation: Concept and Exemplary Implementation for Aortic Valve Stents

Cited by 27 publications

References 19 publications

The Living Heart Project: A robust and integrative simulator for human heart function

The Living Heart Project: A robust and integrative simulator for human heart function

Stent Maps — Comparative Visualization for the Prediction of Adverse Events of Transcatheter Aortic Valve Implantations

Computational Material Analysis of Structural and Hemodynamic Model of Coronary Stent by CFD/FEA in Computer Aided Mechanical Engineering Approach

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