An In Silico Model for Predicting the Efficacy of Edge-to-Edge Repair for Mitral Regurgitation.

In recent years, transcatheter edge-to-edge repair (TEER) has been widely adopted as an effective treatment for mitral regurgitation (MR). The aim of this study is to develop a personalized in silico model to predict the effect of edge-to-edge repair in advance to the procedure for each individual patient. For this purpose, we propose a combination of a valve deformation model for computing the mitral valve (MV) orifice area (MVOA) and a lumped parameter model for the hemodynamics, specifically mitral regurgitation volume (RVol). Although we cannot obtain detailed information on the three-dimensional flow field near the mitral valve, we can rapidly simulate the important medical parameters for the clinical decision support. In the present method, we construct the patient-specific pre-operative models by using the parameter optimization and then simulate the postoperative state by applying the additional clipping condition. The computed preclip MVOAs show good agreement with the clinical measurements, and the correlation coefficient takes 0.998. In addition, the MR grade in terms of RVol also has good correlation with the grade by ground truth MVOA. Finally, we try to investigate the applicability for the predicting the postclip state. The simulated valve shapes clearly show the well-known double orifice and the improvement of the MVOA, compared with the preclip state. Similarly, we confirmed the improved reverse flow and MR grade in terms of RVol. A total computational time is approximately 8 h by using general-purpose PC. These results obviously indicate that the present in silico model has good capability for the assessment of edge-to-edge repair.

Can the response to dialysis treatment be predicted by using patient-specific modeling of fluid and solute exchanges? A multicentric evaluation.

BACKGROUND: Parametric multipool kinetic models were used to describe the intradialytic trends of electrolytes, breakdown products, and body fluids volumes during hemodialysis. Therapy customization can be achieved by the identification of parameters, allowing patient-specific modulation of mass and fluid balance across dialyzer, capillary, and cell membranes. This study wants to evaluate the possibility to use this approach to predict the patient's intradialytic response. METHODS: 6 sessions of 68 patients (DialysIS© project) were considered. Data from the first three sessions were used to train the model, identifying the patient-specific parameters, that, together with the treatment settings and the patient's data at the session start, could be used for predicting the patient's specific time course of solutes and fluids along the sessions. Na+ , K+ , Cl- , Ca2+ , HCO3 - , and urea plasmatic concentrations and hematic volume deviations from clinical data were evaluated. RESULTS: nRMSE predictive error is on average equal to 4.76% when describing the training sessions, and only increases by 0.97 percentage points on average in independent sessions of the same patient. CONCLUSIONS: The proposed predictive approach represents a first step in the development of tools to support the clinician in tailoring the patient's prescription.

The Impact of Technological Innovation on Dentistry.

Technology has revolutionized the way dentists are able to treat their patients. These technological advances have paved the way for the creation of virtual patient models utilizing these 3-dimensional intra-oral patient models, cone bean computer tomography (CBCT) radiograph scans, extraoral 3-dimensional scans, and jaw motion tracings to create a patient-specific model. These models are advantageous in planning surgical treatments by providing 3-dimensional views of vital anatomical structures to accurately identify the location, size, and shape of a structure or defect in order to plan accordingly. Virtual augmentation of either hard tissue (bone) and/or soft tissue (i.e., gingiva) can also be accomplished.Technology has allowed the capture of the dynamic motions of the jaw and combined them with the virtual patient to develop permanent restorations in harmony with the patient's orofacial complex. With the introduction of new technology in the realm of digital dentistry, patient care is being brought to a new and higher level. This creates a level of more optimal care that a dentist can deliver to patients.

Patient-specific stomach biomechanics before and after laparoscopic sleeve gastrectomy.

BACKGROUND: Obesity has become a global epidemic. Bariatric surgery is considered the most effective therapeutic weapon in terms of weight loss and improvement of quality of life and comorbidities. Laparoscopic sleeve gastrectomy (LSG) is one of the most performed procedures worldwide, although patients carry a nonnegligible risk of developing post-operative GERD and BE. OBJECTIVES: The aim of this work is the development of computational patient-specific models to analyze the changes induced by bariatric surgery, i.e., the volumetric gastric reduction, the mechanical response of the stomach during an inflation process, and the related elongation strain (ES) distribution at different intragastric pressures. METHODS: Patient-specific pre- and post-surgical models were extracted from Magnetic Resonance Imaging (MRI) scans of patients with morbid obesity submitted to LSG. Twenty-three patients were analyzed, resulting in forty-six 3D-geometries and related computational analyses. RESULTS: A significant difference between the mechanical behavior of pre- and post-surgical stomach subjected to the same internal gastric pressure was observed, that can be correlated to a change in the global stomach stiffness and a minor gastric wall tension, resulting in unusual activations of mechanoreceptors following food intake and satiety variation after LSG. CONCLUSIONS: Computational patient-specific models may contribute to improve the current knowledge about anatomical and physiological changes induced by LSG, aiming at reducing post-operative complications and improving quality of life in the long run.

Using machine learning to identify local cellular properties that support re-entrant activation in patient-specific models of atrial fibrillation.

AIMS: Atrial fibrillation (AF) is sustained by re-entrant activation patterns. Ablation strategies have been proposed that target regions of tissue that may support re-entrant activation patterns. We aimed to characterize the tissue properties associated with regions that tether re-entrant activation patterns in a validated virtual patient cohort. METHODS AND RESULTS: Atrial fibrillation patient-specific models (seven paroxysmal and three persistent) were generated and validated against local activation time (LAT) measurements during an S1-S2 pacing protocol from the coronary sinus and high right atrium, respectively. Atrial models were stimulated with burst pacing from three locations in the proximity of each pulmonary vein to initiate re-entrant activation patterns. Five atria exhibited sustained activation patterns for at least 80 s. Models with short maximum action potential durations (APDs) were associated with sustained activation. Phase singularities were mapped across the atria sustained activation patterns. Regions with a low maximum conduction velocity (CV) were associated with tethering of phase singularities. A support vector machine (SVM) was trained on maximum local conduction velocity and action potential duration to identify regions that tether phase singularities. The SVM identified regions of tissue that could support tethering with 91% accuracy. This accuracy increased to 95% when the SVM was also trained on surface area. CONCLUSION: In a virtual patient cohort, local tissue properties, that can be measured (CV) or estimated (APD; using effective refractory period as a surrogate) clinically, identified regions of tissue that tether phase singularities. Combing CV and APD with atrial surface area further improved the accuracy in identifying regions that tether phase singularities.

Predicting plaque vulnerability change using intravascular ultrasound + optical coherence tomography image-based fluid-structure interaction models and machine learning methods with patient follow-up data: a feasibility study.

BACKGROUND: Coronary plaque vulnerability prediction is difficult because plaque vulnerability is non-trivial to quantify, clinically available medical image modality is not enough to quantify thin cap thickness, prediction methods with high accuracies still need to be developed, and gold-standard data to validate vulnerability prediction are often not available. Patient follow-up intravascular ultrasound (IVUS), optical coherence tomography (OCT) and angiography data were acquired to construct 3D fluid-structure interaction (FSI) coronary models and four machine-learning methods were compared to identify optimal method to predict future plaque vulnerability. METHODS: Baseline and 10-month follow-up in vivo IVUS and OCT coronary plaque data were acquired from two arteries of one patient using IRB approved protocols with informed consent obtained. IVUS and OCT-based FSI models were constructed to obtain plaque wall stress/strain and wall shear stress. Forty-five slices were selected as machine learning sample database for vulnerability prediction study. Thirteen key morphological factors from IVUS and OCT images and biomechanical factors from FSI model were extracted from 45 slices at baseline for analysis. Lipid percentage index (LPI), cap thickness index (CTI) and morphological plaque vulnerability index (MPVI) were quantified to measure plaque vulnerability. Four machine learning methods (least square support vector machine, discriminant analysis, random forest and ensemble learning) were employed to predict the changes of three indices using all combinations of 13 factors. A standard fivefold cross-validation procedure was used to evaluate prediction results. RESULTS: For LPI change prediction using support vector machine, wall thickness was the optimal single-factor predictor with area under curve (AUC) 0.883 and the AUC of optimal combinational-factor predictor achieved 0.963. For CTI change prediction using discriminant analysis, minimum cap thickness was the optimal single-factor predictor with AUC 0.818 while optimal combinational-factor predictor achieved an AUC 0.836. Using random forest for predicting MPVI change, minimum cap thickness was the optimal single-factor predictor with AUC 0.785 and the AUC of optimal combinational-factor predictor achieved 0.847. CONCLUSION: This feasibility study demonstrated that machine learning methods could be used to accurately predict plaque vulnerability change based on morphological and biomechanical factors from multi-modality image-based FSI models. Large-scale studies are needed to verify our findings.

Role of Vessel Microstructure in the Longevity of End-to-Side Grafts.

Compliance mismatch between the graft and the host artery of an end-to-side (ETS) arterial bypass graft anastomosis increases the intramural stress in the ETS graft-artery junction, and thus may compromise its long-term patency. The present study takes into account the effects of collagen fibers to demonstrate how their orientations alter the stresses. The stresses in an ETS bypass graft anastomosis, as a man-made bifurcation, are compared to those of its natural counterpart with different fiber orientations. Both of the ETS bypass graft anastomosis and its natural counterpart have identical geometric and material models and only their collagen fiber orientations are different. The results indicate that the fiber orientation mismatch between the graft and the host artery may increase the stresses at both the heel and toe regions of the ETS anastomosis (the maximum principal stress at the heel and toe regions increased by 72% and 12%, respectively). Our observations, thus, propose that the mismatch between the collagen fiber orientations of the graft and the host artery, independent of the effect of the suture line, may induce aberrant stresses to the anastomosis of the bypass graft.

Patient-Specific 3-Dimensional Model for High-Intensity Focused Ultrasound Treatment Through the Rib Cage: A Preliminary Study.

OBJECTIVES: The purpose of this study was to develop a patient-specific 3-dimensional model for high-intensity focused ultrasound (HIFU) treatment through the rib cage using patient data. METHODS: Experimental testing to derive parameters used in defining the amount of energy and alteration needed in treatment protocols for upper abdominal disorders under the rib cage was performed. Reconstructed rib cage models based on patient data, tissue-mimicking material phantoms, and magnetic resonance imaging-guided HIFU using a multielement phased array transducer were used in the experiments. Changes in the focal temperature, acoustic power, and acoustic pressure distribution were investigated with and without the presence of the rib cage model. An ExAblate system (InSightec Ltd, Tirat Carmel, Israel) was used to sonicate phantoms by varying the target phantom or rib cage model location. RESULTS: The effect of the rib cage on the acoustic pressure distribution and acoustic power was closely related to the anatomic structures of the ribs. Thermometry revealed that heating at the focus could be controlled by changing either the power or duration of HIFU application to improve the focal temperature change. The focal temperature change was found to be related to the distance between the rib cage model and focus and the shadow area on the transducer elements covered by the rib cage model in the beam path. CONCLUSIONS: Experimental results suggest that the rib cage model is a valuable and useful tool that can provide realistic human anatomic structures and properties for evaluating the effects of the rib cage on ultrasound propagation.

The nested block preconditioning technique for the incompressible Navier-Stokes equations with emphasis on hemodynamic simulations.

We develop a novel iterative solution method for the incompressible Navier-Stokes equations with boundary conditions coupled with reduced models. The iterative algorithm is designed based on the variational multiscale formulation and the generalized-α scheme. The spatiotemporal discretization leads to a block structure of the resulting consistent tangent matrix in the Newton-Raphson procedure. As a generalization of the conventional block preconditioners, a three-level nested block preconditioner is introduced to attain a better representation of the Schur complement, which plays a key role in the overall algorithm robustness and efficiency. This approach provides a flexible, algorithmic way to handle the Schur complement for problems involving multiscale and multiphysics coupling. The solution method is implemented and benchmarked against experimental data from the nozzle challenge problem issued by the US Food and Drug Administration. The robustness, efficiency, and parallel scalability of the proposed technique are then examined in several settings, including moderately high Reynolds number flows and physiological flows with strong resistance effect due to coupled downstream vasculature models. Two patient-specific hemodynamic simulations, covering systemic and pulmonary flows, are performed to further corroborate the efficacy of the proposed methodology.

Longitudinal dissociation and transition in thickness of the His-Purkinje system cause various QRS waveforms of surface ECG under His bundle pacing: A simulation study based on clinical observations.

AIMS: His bundle pacing (HBP) is a feasible and reliable alternative to conventional right ventricular pacing (RVP), but associated ECG (electrocardiogram) changes have not been well-studied. This study aimed to determine the mechanisms underlying ECG changes associated with HBP using patient-specific multiscale heart simulations. METHODS: ECGs were recorded in two patients who were treated by HBP under a native rhythm and HBP at high and low voltages. We created patient-specific multiscale simulation heart models of these patients and performed ECG simulation under these conditions. Using these results and detailed information on the electrical field around the pacing lead, we investigated mechanisms underlying the observed ECG changes. RESULTS: Heart simulations successfully reproduced ECGs under a native rhythm for both cases. In case 1, nonselective HBP produced a left bundle branch (LBB) block pattern, which was reproduced as a selective right bundle branch (RBB) pacing. However, in case 2, ECG under nonselective HBP showed an RBB block pattern, which could not be reproduced by the commonly used framework. Findings on the electrical field and anatomy of the His bundle and its branches suggested that longitudinal dissociation of the His bundle and transition of thickness in the stem of the LBB caused a conduction delay in the RBB to produce these ECG changes in this patient. CONCLUSION: Variations in the anatomy of the His bundle and its branches may underlie the diverse ECG responses to HBP. These variations should be taken into account when performing this therapy.

A Multimodality Image-Based Fluid-Structure Interaction Modeling Approach for Prediction of Coronary Plaque Progression Using IVUS and Optical Coherence Tomography Data With Follow-Up.

Medical image resolution has been a serious limitation in plaque progression research. A modeling approach combining intravascular ultrasound (IVUS) and optical coherence tomography (OCT) was introduced and patient follow-up IVUS and OCT data were acquired to construct three-dimensional (3D) coronary models for plaque progression investigations. Baseline and follow-up in vivo IVUS and OCT coronary plaque data were acquired from one patient with 105 matched slices selected for model construction. 3D fluid-structure interaction (FSI) models based on IVUS and OCT data (denoted as IVUS + OCT model) were constructed to obtain stress/strain and wall shear stress (WSS) for plaque progression prediction. IVUS-based IVUS50 and IVUS200 models were constructed for comparison with cap thickness set as 50 and 200 µm, respectively. Lumen area increase (LAI), plaque area increase (PAI), and plaque burden increase (PBI) were chosen to measure plaque progression. The least squares support vector machine (LS-SVM) method was employed for plaque progression prediction using 19 risk factors. For IVUS + OCT model with LAI, PAI, and PBI, the best single predictor was plaque strain, local plaque stress, and minimal cap thickness, with prediction accuracy as 0.766, 0.838, and 0.890, respectively; the prediction accuracy using best combinations of 19 factors was 0.911, 0.881, and 0.905, respectively. Compared to IVUS + OCT model, IVUS50, and IVUS200 models had errors ranging from 1% to 66.5% in quantifying cap thickness, stress, strain and prediction accuracies. WSS showed relatively lower prediction accuracy compared to other predictors in all nine prediction studies.

Computational Modeling of Human Left Ventricle to Assess the Effects of Trabeculae Carneae on the Diastolic and Systolic Functions.

Trabeculae carneae are irregular structures that cover the endocardial surfaces of both ventricles and account for a significant portion of human ventricular mass. The role of trabeculae carneae in diastolic and systolic functions of the left ventricle (LV) is not well understood. Thus, the objective of this study was to investigate the functional role of trabeculae carneae in the LV. Finite element (FE) analyses of ventricular functions were conducted for three different models of human LV derived from high-resolution magnetic resonance imaging (MRI). The first model comprised trabeculae carneae and papillary muscles, while the second model had papillary muscles and partial trabeculae carneae, and the third model had a smooth endocardial surface. We customized these patient-specific models with myofiber architecture generated with a rule-based algorithm, diastolic material parameters of Fung strain energy function derived from biaxial tests and adjusted with the empirical Klotz relationship, and myocardial contractility constants optimized for average normal ejection fraction (EF) of the human LV. Results showed that the partial trabeculae cutting model had enlarged end-diastolic volume (EDV), reduced wall stiffness, and even increased end-systolic function, indicating that the absence of trabeculae carneae increased the compliance of the LV during diastole, while maintaining systolic function.

Pluripotent Cell Models for Gonadal Research.

Sex development is a complex process involving many genes and hormones. Defects in this process lead to Differences of Sex Development (DSD), a group of heterogeneous conditions not as rare as previously thought. Part of the obstacles in proper management of these patients is due to an incomplete understanding of the genetics programs and molecular pathways involved in sex development and DSD. Several challenges delay progress and the lack of a proper model system for the single patient severely hinders advances in understanding these diseases. The revolutionary techniques of cellular reprogramming and guided in vitro differentiation allow us now to exploit the versatility of induced pluripotent stem cells to create alternatives models for DSD, ideally on a patient-specific personalized basis.

Computational analysis of the electromechanical performance of mitral valve cerclage annuloplasty using a patient-specific ventricular model.

We aimed to propose a novel computational approach to predict the electromechanical performance of pre- and post-mitral valve cerclage annuloplasty (MVCA). Furthermore, we tested a virtual estimation method to optimize the left ventricular basement tightening scheme using a pre-MVCA computer model. The present model combines the three-dimensional (3D) electromechanics of the ventricles with the vascular hemodynamics implemented in a lumped parameter model. 3D models of pre- and post-MVCA were reconstructed from the computed tomography (CT) images of two patients and simulated by solving the electromechanical-governing equations with the finite element method. Computed results indicate that reduction of the dilated heart chambers volume (reverse remodeling) appears to be dependent on ventricular stress distribution. Reduced ventricular stresses in the basement after MVCA treatment were observed in the patients who showed reverse remodeling of heart during follow up over 6 months. In the case who failed to show reverse remodeling after MVCA, more virtual tightening of the ventricular basement diameter than the actual model can induce stress unloading, aiding in heart recovery. The simulation result that virtual tightening of the ventricular basement resulted in a marked increase of myocardial stress unloading provides in silico evidence for a functional impact of MVCA treatment on cardiac mechanics and post-operative heart recovery. This technique contributes to establishing a pre-operative virtual rehearsal procedure before MVCA treatment by using patient-specific cardiac electromechanical modeling of pre-MVCA.

An In Vitro Phantom Study on the Role of the Bird-Beak Configuration in Endograft Infolding in the Aortic Arch.

PURPOSE: To assess endograft infolding for excessive bird-beak configurations in the aortic arch in relation to hemodynamic variables by quantifying device displacement and rotation of oversized stent-grafts deployed in a phantom model. METHODS: A patient-specific, compliant, phantom pulsatile flow model was reconstructed from a patient who presented with collapse of a Gore TAG thoracic endoprosthesis. Device infolding was measured under different flow and pressure conditions for 3 protrusion extensions (13, 19, and 24 mm) of the bird-beak configuration resulting from 2 TAG endografts with oversizing of 11% and 45%, respectively. RESULTS: The bird-beak configuration with the greatest protrusion extension exhibited the maximum TAG device displacement (1.66 mm), while the lowest protrusion extension configuration led to the minimum amount of both displacement and rotation parameters (0.25 mm and 0.6°, respectively). A positive relationship was found between the infolding parameters and the flow circulating in the aorta and left subclavian artery. Similarly, TAG device displacement was positively and significantly (p<0.05) correlated with the pulse pressure for all bird-beak configurations and device sizes. However, no collapse was observed under chronic perfusion testing maintained for 30 days and pulse pressure of 100 mm Hg. CONCLUSION: These findings suggest that endograft infolding depends primarily on the amount of aortic pulsatility and flow rate and that physiological flows do not necessarily engender hemodynamic loads on the proximal bird-beak segment sufficient to cause TAG collapse. Hemodynamic variables may allow for identification of patients at high risk of endograft infolding and help guide preventive intervention to avert its occurrence.

Optimization of catheter ablation of atrial fibrillation: insights gained from clinically-derived computer models.

Atrial fibrillation (AF) is the most common heart rhythm disturbance, and its treatment is an increasing economic burden on the health care system. Despite recent intense clinical, experimental and basic research activity, the treatment of AF with current antiarrhythmic drugs and catheter/surgical therapies remains limited. Radiofrequency catheter ablation (RFCA) is widely used to treat patients with AF. Current clinical ablation strategies are largely based on atrial anatomy and/or substrate detected using different approaches, and they vary from one clinical center to another. The nature of clinical ablation leads to ambiguity regarding the optimal patient personalization of the therapy partly due to the fact that each empirical configuration of ablation lines made in a patient is irreversible during one ablation procedure. To investigate optimized ablation lesion line sets, in silico experimentation is an ideal solution. 3D computer models give us a unique advantage to plan and assess the effectiveness of different ablation strategies before and during RFCA. Reliability of in silico assessment is ensured by inclusion of accurate 3D atrial geometry, realistic fiber orientation, accurate fibrosis distribution and cellular kinetics; however, most of this detailed information in the current computer models is extrapolated from animal models and not from the human heart. The predictive power of computer models will increase as they are validated with human experimental and clinical data. To make the most from a computer model, one needs to develop 3D computer models based on the same functionally and structurally mapped intact human atria with high spatial resolution. The purpose of this review paper is to summarize recent developments in clinically-derived computer models and the clinical insights they provide for catheter ablation.

Specimen-specific finite element representations of implanted hip capsules.

The hip capsule is a ligamentous structure that contributes to hip stability. This article developed specimen-specific finite element models that replicated internal-external (I-E) laxity for ten implanted hip capsules. Capsule properties were calibrated to minimize root mean square error (RMSE) between model and experimental torques. RMSE across specimens was 1.02 ± 0.21 Nm for I-E laxity and 0.78 ± 0.33 Nm and 1.10 ± 0.48 Nm during anterior and posterior dislocation, respectively. RMSE for the same models with average capsule properties was 2.39 ± 0.68 Nm. Specimen-specific models demonstrated the importance of capsule tensioning in hip stability and have relevance for surgical planning and evaluation of implant designs.

Breast simulation pipeline: From medical imaging to patient-specific simulations.

BACKGROUND: Breast-conserving surgery is the most acceptable operation for breast cancer removal from an invasive and psychological point of view. Before the surgical procedure, a preoperative MRI is performed in the prone configuration, while the surgery is achieved in the supine position. This leads to a considerable movement of the breast, including the tumor, between the two poses, complicating the surgeon's task. METHODS: In this work, a simulation pipeline allowing the computation of patient-specific geometry and the prediction of personalized breast material properties was put forward. Through image segmentation, a finite element model including the subject-specific geometry is established. By first computing an undeformed state of the breast, the geometrico-material model is calibrated by surface acquisition in the intra-operative stance. FINDINGS: Using an elastic corotational formulation, the patient-specific mechanical properties of the breast and skin were identified to obtain the best estimates of the supine configuration. The final results are a shape-fitting closest point residual of 4.00 mm for the mechanical parameters Ebreast=0.32 kPa and Eskin=22.72 kPa, congruent with the current state-of-the-art. The Covariance Matrix Adaptation Evolution Strategy optimizer converges on average between 5 to 30 min depending on the initial parameters, reaching a simulation speed of 20 s. To our knowledge, our model offers one of the best compromises between accuracy and speed. INTERPRETATION: Satisfactory results were obtained for the estimation of breast deformation from preoperative to intra-operative configuration. Furthermore, we have demonstrated the clinical feasibility of such applications using a simulation framework that aims at the smallest disturbance of the actual surgical pipeline.

In silico hemodynamical simulations show additional benefits of artery wall softening induced by antihypertensive drugs.

BACKGROUND AND OBJECTIVES: Age-related arterial stiffening increases peripheral resistance and decreases arterial distensibility, thus contributing to hypertension, an important risk factor of atherosclerosis. It causes abnormal blood flow, endothelial dysfunction, higher pulse wave velocity, and consequently elevated pressure wave amplitude. METHODS: This paper presents the influence of these changes via multiscale 3D-0D transient computational fluid dynamics simulations of blood flow in five patient-specific geometries of human carotid bifurcation using archetypal flow waveforms for young and old subjects. RESULTS: The proposed model shows a significant decrease in the time-averaged wall shear stress (TAWSS) for the old archetypal flow waveform. This is in good agreement with clinical data on a straight segment of common carotid arteries available for young and old subjects. Moreover, our study showed that the decrease of area-averaged TAWSS related to the old flow waveform is much more pronounced (2.5 ÷ 4.5 times higher) at risk areas (areas showing TAWSS below its threshold value of 0.48 Pa) than in straight segments commonly considered in clinical studies. CONCLUSIONS: Since arterial stiffness can be lowered through long-term usage of any of the five basic groups of antihypertensives, possible benefits of such medical therapy could be not only lowering blood pressure and peripheral resistance but also in increasing the TAWSS and thus attenuating an important mechanism of the atherosclerotic process.

Determining the changes in morphology and loading status following medial displacement calcaneal osteotomy for flatfoot using patient-specific finite element models.

Medial displacement calcaneal osteotomy (MDCO) is the standard procedure for flatfoot. We investigated the effect of MDCO on the foot using a finite element analysis. Foot models were created from computed tomography data of 8 patients with flat feet. MDCO was performed on each model with bone translation distance of 4, 8, and 12 mm. The morphological changes, plantar pressures, and stress percentage on the talocrural and subtalar joints were evaluated before and after surgery. Morphological evaluation showed improvement in the medial longitudinal arch. The stress percentage of plantar pressure in the medial area decreased, and the stress percentage of plantar pressure in the mid- and lateral forefoot area increased. At the talocrural joint, the medial and middle stress percentage increased, while the lateral and posterior stress percentage decreased. In the subtalar joint, the stress percentage in the middle subtalar joint increased and that in the posterior subtalar joint decreased. Within the posterior subtalar joint, the anterior and medial stress percentage increased, while the posterior and lateral stress percentage decreased. Preoperative simulation using the finite element analysis may be useful in understanding postoperative morphological changes and loading conditions to perform patient-specific surgery.