Force distribution within the frame of self-expanding transcatheter aortic valve: Insights from in-vivo finite element analysis.

We sought to assess the amount and distribution of force on the valve frame after transcatheter aortic valve replacement (TAVR) via patient-specific computer simulation. Patients successfully treated with the self-expanding Venus A-Valve and multislice computed tomography (MSCT) pre- and post-TAVR were retrospectively included. Patient-specific finite element models of the aortic root and prosthesis were constructed. The force (in Newton) on the valve frame was derived at every 3 mm from the inflow and at every 22.5° on each level. Twenty patients of whom 10 had bicuspid aortic valve (BAV) were analyzed. The total force on the frame was 74.9 N in median (interquartile range 24.0). The maximal force was observed at level 5 that corresponds with the nadir of the bioprosthetic leaflets and was 9.9 (7.1) N in all patients, 10.3 (6.6) N in BAV and 9.7 (9.2) N for patients with tricuspid aortic valve (TAV). The level of maximal force located higher from the native annulus in BAV and TAV patients (8.8 [4.8] vs. 1.8 [7.4] mm). The area of the valve frame at the level of maximal force decreased from 437.4 (239.7) mm2 at the annulus to 377.6 (114.3) mm2 in BAV, but increased from 397.5 (114.3) mm2 at the annulus to 406.7 (108.9) mm2 in TAV. The maximum force on the bioprosthetic valve frame is located at the plane of the nadir of the bioprosthetic leaflets. It remains to be elucidated whether this may be associated with bioprosthetic frame and leaflet integrity and/or function.

A study on the efficacy of AFO stiffness prescriptions.

PURPOSE: Ankle foot orthosis (AFO) stiffness is a key characteristic that determines how much support or restraint an AFO can provide. Thus, the goal of the current study is twofold: (1) to quantify AFO prescriptions for a group of patients; (2) to evaluate what impact these AFO have on the push-off phase. METHOD: Six patients were included in the study. Three patients were prescribed an AFO for ankle support and three patients were prescribed an AFO for ankle and knee support. Two types of AFO - a traditional polypropylene AFO (AFOPP) and a novel carbon-selective laser sintered polyamide AFO (AFOPA), were produced for each patient. AFO ankle stiffness was measured in a dedicated test rig. Gait analysis was performed under shod and orthotic conditions. RESULTS: Patient mass normalized AFOPP stiffness for ankle support ranged from 0.042 to 0.069 N·m·deg-1·kg-1, while for ankle and knee support it ranged from 0.081 to 0.127 N·m·deg-1·kg-1. On the group level, the ankle range of motion and mean ankle velocity in the push-off phase significantly decreased in both orthotic conditions, while peak ankle push-off power decreased non-significantly. Accordingly, on the group level, no significant improvements in walking speed were observed. However, after patient differentiation into good and bad responders it was found that in good responders peak ankle push-off power tended to be preserved and walking speed tended to increase. CONCLUSIONS: Quantification of AFO stiffness may help to understand why certain orthotic interventions are successful (unsuccessful) and ultimately lead to better AFO prescriptions. Implications for rehabilitation AFO ankle stiffness is key characteristic that determines how much support or restraint an AFO can provide. In a typical clinical setting, AFO ankle stiffness is not quantified. AFO has to meet individual patient's biomechanical needs. More objective AFO prescription and more controlled AFO production methods are needed to increase AFO success rate.

Mechanical and morphometric study of mitral valve chordae tendineae and related papillary muscle.

The mitral valve (MV) apparatus is a complex mechanical structure including annulus, valve leaflets, papillary muscles (PMs) and connected chordae tendineae. Chordae anchor to the papillary muscles to help the valve open and close properly during one cardiac cycle. It is of paramount importance to understand the functional, mechanical, and microstructural properties of mitral valve chordae and connecting PMs. In particular, little is known about the biomechanical properties of the anterior and posterior papillary muscle and corresponding chords. In this work, we performed uniaxial and biaxial tensile tests on the anterolateral (APM) and posteromedial papillary muscle (PPM), and their respective corresponding chordae tendineae, chordaeAPM and chordaePPM, in porcine hearts. Histology was carried out to link the microstructure and macro-mechanical behavior of the chordae and PMs. Our results demonstrate that chordaePPM are less in number, but significantly longer and stiffer than chordaeAPM. These different biomechanical properties may be partially explained by the higher collagen core ratio and larger collagen fibril density of chordaePPM. No significant mechanical or microstructural differences were observed along the circumferential and longitudinal directions of APM and PPM samples. Data measured on chordae and PMs were further fitted with the Ogden and reduced Holzapfel - Ogden strain energy functions, respectively. This study presents the first comparative anatomical, mechanical, and structural dataset of porcine mitral valve chordae and related PMs. Results indicate that a PM based classification of chordae will need to be considered in the analysis of the MV function or planning a surgical treatment, which will also help developing more precise computational models of MV.

Automatic Detection of the Aortic Annular Plane and Coronary Ostia from Multidetector Computed Tomography.

Anatomic landmark detection is crucial during preoperative planning of transcatheter aortic valve implantation (TAVI) to select the proper device size and assess the risk of complications. The detection is currently a time-consuming manual process influenced by the image quality and subject to operator variability. In this work, we propose a novel automatic method to detect the relevant aortic landmarks from MDCT images using deep learning techniques. We trained three convolutional neural networks (CNNs) with 344 multidetector computed tomography (MDCT) acquisitions to detect five anatomical landmarks relevant for TAVI planning: the three basal attachment points of the aortic valve leaflets and the left and right coronary ostia. The detection strategy used these three CNN models to analyse a single MDCT image and yield three segmentation volumes as output. These segmentation volumes were averaged into one final segmentation volume, and the final predicted landmarks were obtained during a postprocessing step. Finally, we constructed the aortic annular plane, defined by the three predicted hinge points, and measured the distances from this plane to the predicted coronary ostia (i.e., coronary height). The methodology was validated on 100 patients. The automatic landmark detection was able to detect all the landmarks and showed high accuracy as the median distance between the ground truth and predictions is lower than the interobserver variations (1.5 mm [1.1-2.1], 2.0 mm [1.3-2.8] with a paired difference -0.5 ± 1.3 mm and p value <0.001). Furthermore, a high correlation is observed between predicted and manually measured coronary heights (for both R 2 = 0.8). The image analysis time per patient was below one second. The proposed method is accurate, fast, and reproducible. Embedding this tool based on deep learning in the preoperative planning routine may have an impact in the TAVI environments by reducing the time and cost and improving accuracy.

Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation.

The number of transcatheter aortic valve implantation (TAVI) procedures is expected to increase significantly in the coming years. Improving efficiency will become essential for experienced operators performing large TAVI volumes, while new operators will require training and may benefit from accurate support. In this work, we present a fast deep learning method that can predict aortic annulus perimeter and area automatically from aortic annular plane images. We propose a method combining two deep convolutional neural networks followed by a postprocessing step. The models were trained with 355 patients using modern deep learning techniques, and the method was evaluated on another 118 patients. The method was validated against an interoperator variability study of the same 118 patients. The differences between the manually obtained aortic annulus measurements and the automatic predictions were similar to the differences between two independent observers (paired diff. of 3.3 ± 16.8 mm2 vs. 1.3 ± 21.1 mm2 for the area and a paired diff. of 0.6 ± 1.7 mm vs. 0.2 ± 2.5 mm for the perimeter). The area and perimeter were used to retrieve the suggested prosthesis sizes for the Edwards Sapien 3 and the Medtronic Evolut device retrospectively. The automatically obtained device size selections accorded well with the device sizes selected by operator 1. The total analysis time from aortic annular plane to prosthesis size was below one second. This study showed that automated TAVI device size selection using the proposed method is fast, accurate, and reproducible. Comparison with the interobserver variability has shown the reliability of the strategy, and embedding this tool based on deep learning in the preoperative planning routine has the potential to increase the efficiency while ensuring accuracy.

The Impact of Size and Position of a Mechanical Expandable Transcatheter Aortic Valve: Novel Insights Through Computational Modelling and Simulation.

Transcatheter aortic valve implantation has become an established procedure to treat severe aortic stenosis. Correct device sizing/positioning is crucial for optimal outcome. Lotus valve sizing is based upon multiple aortic root dimensions. Hence, it often occurs that two valve sizes can be selected. In this study, patient-specific computer simulation is adopted to evaluate the influence of Lotus size/position on paravalvular aortic regurgitation (AR) and conduction abnormalities, in patients with equivocal aortic root dimensions. First, simulation was performed in 62 patients to validate the model in terms of predicted AR and conduction abnormalities using postoperative echocardiographic, angiographic and ECG-based data. Then, two Lotus sizes were simulated at two positions in patients with equivocal aortic root dimensions. Large valve size and deep position were associated with higher contact pressure, while only large size, not position, significantly reduced the predicted AR. Despite general trends, simulations revealed that optimal device size/position is patient-specific.

Optimization of a Transcatheter Heart Valve Frame Using Patient-Specific Computer Simulation.

PURPOSE: This study proposes a new framework to optimize the design of a transcatheter aortic valve through patient-specific finite element and fluid dynamics simulation. METHODS: Two geometrical parameters of the frame, the diameter at ventricular inflow and the height of the first row of cells, were examined using the central composite design. The effect of those parameters on postoperative complications was investigated by response surface methodology, and a Nonlinear Programming by Quadratic Lagrangian algorithm was used in the optimization. Optimal and initial devices were then compared in 12 patients. The comparison was made in terms of device performance [i.e., reduced contact pressure on the atrioventricular conduction system and paravalvular aortic regurgitation (AR)]. RESULTS: Results suggest that large diameters and high cells favor higher anchoring of the device within the aortic root reducing the contact pressure and favor a better apposition of the device to the aortic root preventing AR. Compared to the initial device, the optimal device resulted in almost threefold lower predicted contact pressure and limited AR in all patients. CONCLUSIONS: In conclusion, patient-specific modelling and simulation could help to evaluate device performance prior to the actual first-in-human clinical study and, combined with device optimization, could help to develop better devices in a shorter period.

A validated computational framework to evaluate the stiffness of 3D printed ankle foot orthoses.

The purpose of this study was to create and validate a standardized framework for the evaluation of the ankle stiffness of two designs of 3D printed ankle foot orthoses (AFOs). The creation of four finite element (FE) models allowed patient-specific quantification of the stiffness and stress distribution over their specific range of motion during the second rocker of the gait. Validation was performed by comparing the model outputs with the results obtained from a dedicated experimental setup, which showed an overall good agreement with a maximum relative error of 10.38% in plantarflexion and 10.66% in dorsiflexion. The combination of advanced computer modelling algorithms and 3D printing techniques clearly shows potential to further improve the manufacturing process of AFOs.

Computational and experimental evaluation of the mechanical properties of ankle foot orthoses: A literature review.

BACKGROUND: Ankle foot orthoses are external medical devices applied around the ankle joint area to provide stability to patients with neurological, muscular, and/or anatomical disabilities, with the aim of restoring a more natural gait pattern. STUDY DESIGN: This is a literature review. OBJECTIVES: To provide a description of the experimental and computational methods present in the current literature for evaluating the mechanical properties of the ankle foot orthoses. METHODS: Different electronic databases were used for searching English-language articles realized from 1990 onward in order to select the newest and most relevant information available. RESULTS: A total of 46 articles were selected, which describe the different experimental and computational approaches used by research groups worldwide. CONCLUSION: This review provides information regarding processes adopted for the evaluation of mechanical properties of ankle foot orthoses, in order to both improve their design and gain a deeper understanding of their clinical use. The consensus drawn is that the best approach would be represented by a combination of advanced computational models and experimental techniques, capable of being used to optimally mimic real-life conditions. CLINICAL RELEVANCE: In literature, several methods are described for the mechanical evaluation of ankle foot orthoses (AFOs); therefore, the goal of this review is to guide the reader to use the best approach in the quantification of the mechanical properties of the AFOs and to help gaining insight in the prescription process.

Kinematic boundary conditions substantially impact in silico ventricular function.

Computational cardiac mechanical models, individualized to the patient, have the potential to elucidate the fundamentals of cardiac (patho-)physiology, enable non-invasive quantification of clinically significant metrics (eg, stiffness, active contraction, work), and anticipate the potential efficacy of therapeutic cardiovascular intervention. In a clinical setting, however, the available imaging resolution is often limited, which limits cardiac models to focus on the ventricles, without including the atria, valves, and proximal arteries and veins. In such models, the absence of surrounding structures needs to be accounted for by imposing realistic kinematic boundary conditions, which, for prognostic purposes, are preferably generic and thus non-image derived. Unfortunately, the literature on cardiac models shows no consistent approach to kinematically constrain the myocardium. The impact of different approaches (eg, fully constrained base, constrained epi-ring) on the predictive capacity of cardiac mechanical models has not been thoroughly studied. For that reason, this study first gives an overview of current approaches to kinematically constrain (bi) ventricular models. Next, we developed a patient-specific in silico biventricular model that compares well with literature and in vivo recorded strains. Alternative constraints were introduced to assess the influence of commonly used mechanical boundary conditions on both the predicted global functional behavior of the in-silico heart (cavity volumes, stroke volume, ejection fraction) and local strain distributions. Meaningful differences in global functioning were found between different kinematic anchoring strategies, which brought forward the importance of selecting appropriate boundary conditions for biventricular models that, in the near future, may inform clinical intervention. However, whilst statistically significant differences were also found in local strain distributions, these differences were minor and mostly confined to the region close to the applied boundary conditions.

A modular inverse elastostatics approach to resolve the pressure-induced stress state for in vivo imaging based cardiovascular modeling.

Patient-specific biomechanical modeling of the cardiovascular system is complicated by the presence of a physiological pressure load given that the imaged tissue is in a pre-stressed and -strained state. Neglect of this prestressed state into solid tissue mechanics models leads to erroneous metrics (e.g. wall deformation, peak stress, wall shear stress) which in their turn are used for device design choices, risk assessment (e.g. procedure, rupture) and surgery planning. It is thus of utmost importance to incorporate this deformed and loaded tissue state into the computational models, which implies solving an inverse problem (calculating an undeformed geometry given the load and the deformed geometry). Methodologies to solve this inverse problem can be categorized into iterative and direct methodologies, both having their inherent advantages and disadvantages. Direct methodologies are typically based on the inverse elastostatics (IE) approach and offer a computationally efficient single shot methodology to compute the in vivo stress state. However, cumbersome and problem-specific derivations of the formulations and non-trivial access to the finite element analysis (FEA) code, especially for commercial products, refrain a broad implementation of these methodologies. For that reason, we developed a novel, modular IE approach and implemented this methodology in a commercial FEA solver with minor user subroutine interventions. The accuracy of this methodology was demonstrated in an arterial tube and porcine biventricular myocardium model. The computational power and efficiency of the methodology was shown by computing the in vivo stress and strain state, and the corresponding unloaded geometry, for two models containing multiple interacting incompressible, anisotropic (fiber-embedded) and hyperelastic material behaviors: a patient-specific abdominal aortic aneurysm and a full 4-chamber heart model.

Evaluation of a modified Cheatham-Platinum stent for the treatment of aortic coarctation by finite element modelling.

OBJECTIVES: Stent implantation for the treatment of aortic coarctation has become a standard approach for the management of older children and adults. Criteria for optimal stent design and construction remain undefined. This study used computational modelling to compare the performance of two generations of the Cheatham-Platinum stent (NuMED, Hopkinton, NY, USA) deployed in aortic coarctation using finite element analysis. DESIGN: Three-dimensional models of both stents, reverse engineered from microCT scans, were implanted in the aortic model of one representative patient. They were virtually expanded in the vessel with a 16 mm balloon and a pressure of 2 atm. RESULTS: The conventional stent foreshortened to 96.5% of its initial length, whereas the new stent to 99.2% of its initial length. Diameters in 15 slices across the conventional stent were 11.6-15 mm (median 14.2 mm) and slightly higher across the new stent: 10.7-15.3 mm (median 14.5 mm) (p= 0.021). Apposition to the vessel wall was similar: conventional stent 31.1% and new stent 28.6% of total stent area. CONCLUSIONS: The new design Cheatham-Platinum stent showed similar deployment results compared to the conventional design. The new stent design showed slightly higher expansion, using the same delivery balloon. Patient-specific computational models can be used for virtual implantation of new aortic stents and promise to inform subsequent in vivo trials.

From 4D Medical Images (CT, MRI, and Ultrasound) to 4D Structured Mesh Models of the Left Ventricular Endocardium for Patient-Specific Simulations.

With cardiovascular disease (CVD) remaining the primary cause of death worldwide, early detection of CVDs becomes essential. The intracardiac flow is an important component of ventricular function, motion kinetics, wash-out of ventricular chambers, and ventricular energetics. Coupling between Computational Fluid Dynamics (CFD) simulations and medical images can play a fundamental role in terms of patient-specific diagnostic tools. From a technical perspective, CFD simulations with moving boundaries could easily lead to negative volumes errors and the sudden failure of the simulation. The generation of high-quality 4D meshes (3D in space + time) with 1-to-1 vertex becomes essential to perform a CFD simulation with moving boundaries. In this context, we developed a semiautomatic morphing tool able to create 4D high-quality structured meshes starting from a segmented 4D dataset. To prove the versatility and efficiency, the method was tested on three different 4D datasets (Ultrasound, MRI, and CT) by evaluating the quality and accuracy of the resulting 4D meshes. Furthermore, an estimation of some physiological quantities is accomplished for the 4D CT reconstruction. Future research will aim at extending the region of interest, further automation of the meshing algorithm, and generating structured hexahedral mesh models both for the blood and myocardial volume.

Patient-Specific Computer Simulation to Elucidate the Role of Contact Pressure in the Development of New Conduction Abnormalities After Catheter-Based Implantation of a Self-Expanding Aortic Valve.

BACKGROUND: The extent to which pressure generated by the valve on the aortic root plays a role in the genesis of conduction abnormalities after transcatheter aortic valve replacement (TAVR) is unknown. This study elucidates the role of contact pressure and contact pressure area in the development of conduction abnormalities after TAVR using patient-specific computer simulations. METHODS AND RESULTS: Finite-element computer simulations were performed to simulate TAVR of 112 patients who had undergone TAVR with the self-expanding CoreValve/Evolut R valve. On the basis of preoperative multi-slice computed tomography, a patient-specific region of the aortic root containing the atrioventricular conduction system was determined by identifying the membranous septum. Contact pressure and contact pressure index (percentage of area subjected to pressure) were quantified and compared in patients with and without new conduction abnormalities. Sixty-two patients (55%) developed a new left bundle branch block or a high-degree atrioventricular block after TAVR. Maximum contact pressure and contact pressure index (median [interquartile range]) were significantly higher in patients with compared with those without new conduction abnormalities (0.51 MPa [0.43-0.70 MPa] and 33% [22%-44%], respectively, versus 0.29 MPa [0.06-0.50 MPa] and 12% [1%-28%]). By multivariable regression analysis, only maximum contact pressure (odds ratio, 1.35; confidence interval, 1.1-1.7; P=0.01) and contact pressure index (odds ratio, 1.52; confidence interval, 1.1-2.1; P=0.01) were identified as independent predictors for conduction abnormalities, but not implantation depth. CONCLUSIONS: Patient-specific computer simulations revealed that maximum contact pressure and contact pressure index are both associated with new conduction abnormalities after CoreValve/Evolut R implantation and can predict which patient will have conduction abnormalities.

An in silico biomechanical analysis of the stent-esophagus interaction.

Despite all technological innovations in esophageal stent design over the past 20 years, the association between the stent design's mechanical behavior and its effect on the clinical outcome has not yet been thoroughly explored. A parametric numerical model of a commercially available esophageal bioresorbable polymeric braided wire stent is set up, accounting for stent design aspects such as braiding angle, strut material, wire thickness, degradation and friction between the wires comprising a predictive tool on the device's mechanical behavior. Combining this tool with complex multilayered numerical models of the pathological in vivo stressed, actively contracting and buckling esophagus could provide clinicians and engineers with a patient-specific window into the mechanical aspects of stent-based esophageal intervention. This study integrates device and soft tissue mechanics in one computational framework to potentially aid in the understanding of the occurrence of specific symptoms and complications after stent placement.

Erratum to: An in silico biomechanical analysis of the stent-esophagus interaction.

In the original publication of the article, Tables 2 and 3 were published with error. The correct tables are provided below (Tables 2, 3). The original version of the article has also been corrected.

Procedure to describe clavicular motion.

BACKGROUND: For many years, researchers have attempted to describe shoulder motions by using different mathematical methods. The aim of this study was to describe a procedure to quantify clavicular motion. METHODS: The procedure proposed for the kinematic analysis consists of 4 main processes: 3 transcortical pins in the clavicle, motion capture, obtaining 3-dimensional bone models, and data processing. RESULTS: Clavicular motion by abduction (30° to 150°) and flexion (55° to 165°) were characterized by an increment of retraction of 27° to 33°, elevation of 25° to 28°, and posterior rotation of 14° to 15°, respectively. In circumduction, clavicular movement described an ellipse, which was reflected by retraction and elevation. Kinematic analysis shows that the articular surfaces move by simultaneously rolling and sliding on the convex surface of the sternum for the 3 movements of abduction, flexion, and circumduction. CONCLUSION: The use of 3 body landmarks in the clavicle and the direct measurement of bone allowed description of the osteokinematic and arthrokinematic movement of the clavicle.

Automated femoral landmark extraction for optimal prosthesis placement in total hip arthroplasty.

The automated extraction of anatomical reference landmarks in the femoral volume may improve speed, precision, and accuracy of surgical procedures, such as total hip arthroplasty. These landmarks are often hard to achieve, even via surgical incision. In addition, it provides a presurgical guidance for prosthesis sizing and placement. This study presents an automated workflow for femoral orientation and landmark extraction from a 3D surface mesh. The extraction of parameters such as the femoral neck axis, the femoral middle diaphysis axis, both trochanters and the center of the femoral head will allow the surgeon to establish the correct position of bony cuts to restore leg length and femoral offset. The definition of the medullary canal endosteal wall is used to position the prosthesis' stem. Furthermore, prosthesis alignment and sizing methods were implemented to provide the surgeon with presurgical information about performance of each of the patient-specific femur-implant couplings. The workflow considers different commercially available hip stems and has the potential to help the preoperative planning of a total hip arthroplasty in an accurate, repeatable, and reliable way. The positional and orientation errors are significantly reduced, and therefore, the risk of implant failure and subsequent revision surgery are also reduced.