Height and body surface area versus wall stress for stratification of mid-term outcomes in ascending aortic aneurysm.

Objectives: Current diameter-based guidelines for ascending thoracic aortic aneurysms (aTAA) do not consistently predict risk of dissection/rupture. ATAA wall stresses may enhance risk stratification independent of diameter. The relation of wall stresses and diameter indexed to height and body surface area (BSA) is unknown. Our objective was to compare aTAA wall stresses with indexed diameters in relation to all-cause mortality at 3.75 years follow-up. Methods: Finite element analyses were performed in a veteran population with aortas ≥ 4.0 cm. Three-dimensional geometries were reconstructed from computed tomography with models accounting for pre-stress geometries. A fiber-embedded hyperelastic material model was applied to obtain wall stress distributions under systolic pressure. Peak wall stresses were compared across guideline thresholds for diameter/BSA and diameter/height. Hazard ratios for all-cause mortality and surgical aneurysm repair were estimated using cause-specific Cox proportional hazards models. Results: Of 253 veterans, 54 (21 %) had aneurysm repair at 3.75 years. Indexed diameter alone would have prompted repair at baseline in 17/253 (6.7 %) patients, including only 4/230 (1.7 %) with diameter < 5.5 cm. Peak wall stresses did not significantly differ across guideline thresholds for diameter/BSA (circumferential: p = 0.15; longitudinal: p = 0.18), but did differ for diameter/height (circumferential: p = 0.003; longitudinal: p = 0.048). All-cause mortality was independently associated with peak longitudinal stresses (p = 0.04). Peak longitudinal stresses were best predicted by diameter (c-statistic = 0.66), followed by diameter/height (c-statistic = 0.59), and diameter/BSA (c-statistic = 0.55). Conclusions: Diameter/height improved stratification of peak wall stresses compared to diameter/BSA. Peak longitudinal stresses predicted all-cause mortality independent of age and indexed diameter and may aid risk stratification for aTAA adverse events.

Aortic area/height ratio, peak wall stresses, and outcomes in veterans with tricuspid versus bicuspid aortic valve-associated ascending thoracic aortic aneurysms.

BACKGROUND: In ascending thoracic aortic aneurysm risk stratification, aortic area/height ratio is a reasonable alternative to maximum diameter. Biomechanically, aortic dissection may be initiated by wall stress exceeding wall strength. Our objective was to evaluate the association between aortic area/height and peak aneurysm wall stresses in relation to valve morphology and 3-year all-cause mortality. METHODS: Finite element analysis was performed on 270 ascending thoracic aortic aneurysms (46 associated with bicuspid and 224 with tricuspid aortic valves) in veterans. Three-dimensional aneurysm geometries were reconstructed from computed tomography and models developed accounting for prestress geometries. Fiber-embedded hyperelastic material model was applied to obtain aneurysm wall stresses during systole. Correlations of aortic area/height ratio and peak wall stresses were compared across valve types. Area/height ratio was evaluated across peak wall stress thresholds obtained from proportional hazards models of 3-year all-cause mortality, with aortic repair treated as a competing risk. RESULTS: Aortic area/height 10 cm2/m or greater coincided with 23/34 (68%) 5.0 to 5.4 cm and 20/24 (83%) 5.5 cm or greater aneurysms. Area/height correlated weakly with peak aneurysm stresses: for tricuspid valves, r = 0.22 circumferentially and r = 0.24 longitudinally; and for bicuspid valves, r = 0.42 circumferentially and r = 0.14 longitudinally. Age and peak longitudinal stress, but not area/height, were independent predictors of all-cause mortality (age: hazard ratio, 2.20 per 9-year increase, P = .013; peak longitudinal stress: hazard ratio, 1.78 per 73-kPa increase, P = .035). CONCLUSIONS: Area/height was more predictive of high circumferential stresses in bicuspid than tricuspid valve aneurysms, but similarly less predictive of high longitudinal stresses in both valve types. Peak longitudinal stress, not area/height, independently predicted all-cause mortality. VIDEO ABSTRACT.

Ascending thoracic aortic aneurysm elongation occurs in parallel with dilatation in a nonsurgical population.

OBJECTIVES: Rapid diameter growth is a criterion for ascending thoracic aortic aneurysm repair; however, there are sparse data on aneurysm elongation rate. The purpose of this study was to assess aortic elongation rates in nonsyndromic, nonsurgical aneurysms to understand length dynamics and correlate with aortic diameter over time. METHODS: Patients with <5.5-cm aneurysms and computed tomography angiography imaging at baseline and 3-5 years follow-up underwent patient-specific three-dimensional aneurysm reconstruction using MeVisLab. Aortic length was measured along the vessel centreline between the annulus and aortic arch. Maximum aneurysm diameter was determined from imaging in a plane normal to the vessel centreline. Average rates of aneurysm growth were evaluated using the longest available follow-up. RESULTS: Over the follow-up period, the mean aortic length for 67 identified patients increased from 118.2 (95% confidence interval: 115.4-121.1) mm to 120.2 (117.3-123.0) mm (P = 0.02) and 15 patients (22%) experienced a change in length of ≥5% from baseline. The mean annual growth rate for length [0.38 (95% confidence interval: 0.11-0.65) mm/year] was correlated with annual growth rate for diameter [0.1 (0.03-0.2) mm/year] (rho = 0.30, P = 0.01). Additionally, annual percentage change in length [0.3 (0.1-0.5)%/year] was similar to percentage change in diameter [0.2 (0.007-0.4)%/year, P = 0.95]. CONCLUSIONS: Aortic length increases in parallel with aortic diameter at a similar percentage rate. Further work is needed to identify whether elongation rate is associated with dissection risk. Such studies may provide insight into why patients with aortic diameters smaller than surgical guidelines continue to experience dissection events.

Looking towards the future: patient-specific computational modeling to optimize outcomes for transcatheter mitral valve repair.

Severe mitral valve regurgitation (MR) is a heart valve disease that progresses to end-stage congestive heart failure and death if left untreated. Surgical repair or replacement of the mitral valve (MV) remains the gold standard for treatment of severe MR, with repair techniques aiming to restore the native geometry of the MV. However, patients with extensive co-morbidities may be ineligible for surgical intervention. With the emergence of transcatheter MV repair (TMVR) treatment paradigms for MR will evolve. The longer-term outcomes of TMVR and its effectiveness compared to surgical repair remain unknown given the differing patient eligibility for either treatment at this time. Advances in computational modeling will elucidate answers to these questions, employing techniques such as finite element method and fluid structure interactions. Use of clinical imaging will permit patient-specific MV models to be created with high accuracy and replicate MV pathophysiology. It is anticipated that TMVR technology will gradually expand to treat lower-risk patient groups, thus pre-procedural computational modeling will play a crucial role guiding clinicians towards the optimal intervention. Additionally, concerted efforts to create MV models will establish atlases of pathologies and biomechanics profiles which could delineate which patient populations would best benefit from specific surgical vs. TMVR options. In this review, we describe recent literature on MV computational modeling, its relevance to MV repair techniques, and future directions for translational application of computational modeling for treatment of MR.

Machine learning used for simulation of MitraClip intervention: A proof-of-concept study.

Introduction: Severe mitral regurgitation (MR) is a mitral valve disease that can lead to lifethreatening complications. MitraClip (MC) therapy is a percutaneous solution for patients who cannot tolerate surgical solutions. In MC therapy, a clip is implanted in the heart to reduce MR. To achieve optimal MC therapy, the cardiologist needs to foresee the outcomes of different scenarios for MC implantation, including the location of the MC. Although finite element (FE) modeling can simulate the outcomes of different MC scenarios, it is not suitable for clinical usage because it requires several hours to complete. Methods: In this paper, we used machine learning (ML) to predict the outcomes of MC therapy in less than 1 s. Two ML algorithms were used: XGBoost, which is a decision tree model, and a feed-forward deep learning (DL) model. The MC location, the geometrical attributes of the models and baseline stress and MR were the features of the ML models, and the predictions were performed for MR and maximum von Mises stress in the leaflets. The parameters of the ML models were determined to achieve the minimum errors obtained by applying the ML models on the validation set. Results: The results for the test set (not used during training) showed relative agreement between ML predictions and ground truth FE predictions. The accuracy of the XGBoost models were better than DL models. Mean absolute percentage error (MAPE) for the XGBoost predictions were 0.115 and 0.231, and the MAPE for DL predictions were 0.154 and 0.310, for MR and stress, respectively. Discussion: The ML models reduced the FE runtime from 6 hours (on average) to less than 1 s. The accuracy of ML models can be increased by increasing the dataset size. The results of this study have important implications for improving the outcomes of MC therapy by providing information about the outcomes of MC implantation in real-time.

Computational analysis of ventricular mechanics in hypertrophic cardiomyopathy patients.

Hypertrophic cardiomyopathy (HCM) is a genetic heart disease that is associated with many pathological features, such as a reduction in global longitudinal strain (GLS), myofiber disarray and hypertrophy. The effects of these features on left ventricle (LV) function are, however, not clear in two phenotypes of HCM, namely, obstructive and non-obstructive. To address this issue, we developed patient-specific computational models of the LV using clinical measurements from 2 female HCM patients and a control subject. Left ventricular mechanics was described using an active stress formulation and myofiber disarray was described using a structural tensor in the constitutive models. Unloaded LV configuration for each subject was first determined from their respective end-diastole LV geometries segmented from the cardiac magnetic resonance images, and an empirical single-beat estimation of the end-diastolic pressure volume relationship. The LV was then connected to a closed-loop circulatory model and calibrated using the clinically measured LV pressure and volume waveforms, peak GLS and blood pressure. Without consideration of myofiber disarray, peak myofiber tension was found to be lowest in the obstructive HCM subject (60 kPa), followed by the non-obstructive subject (242 kPa) and the control subject (375 kPa). With increasing myofiber disarray, we found that peak tension has to increase in the HCM models to match the clinical measurements. In the obstructive HCM patient, however, peak tension was still depressed (cf. normal subject) at the largest degree of myofiber disarray found in the clinic. The computational modeling workflow proposed here can be used in future studies with more HCM patient data.

Regional and directional delamination properties of healthy human ascending aorta and sinotubular junction.

PURPOSE: Acute type A aortic dissection (AD) is a catastrophic event associated with high mortality. Biomechanics can provide an understanding of the forces that lead the initial intimal tear to propagate, resulting in aortic dissection. We previously studied the material properties of normal human aortic roots. In this study, our objective was to determine the regional and directional delamination properties of healthy human ascending aorta (AscAo) and sinotubular junction (STJ). RESULTS: From 19 healthy donor hearts, total 107 samples from the AscAo and STJ were collected and tested along the circumferential and longitudinal directions. Specimens were subjected to uniaxial peeling testing with a manually created tear in the medial layer. The lateral AscAo subregion (greater curvature) had significantly lower delamination strength and dissection energy than anterior, medial, and posterior subregions in the longitudinal direction. Regionally, the delamination strength at AscAo was significantly lower than at STJ overall (p = 0.02) and in circumferential direction (p = 0.02) only. Directionally, the delamination strength at AscAo overall and in the anterior AscAo was significant lower in circumferential direction than longitudinal direction. Dissection energy demonstrated similar regional and directional trend as delamination strength. In addition, both dissection energy and delamination strength were correlated positively with thickness and negatively with age in the AscAo. In addition, the dissection energy was negatively related to stiffness at physiologic mean blood pressure. CONCLUSIONS: The greater curvature of the AscAo had the lowest delamination strength and dissection energy suggesting that region was most vulnerable to dissection propagation distally. Increased thickness of AscAo would be protective of dissection propagation while propagation would be more likely with increased AscAo stiffness.

Association of 3-Year All-Cause Mortality and Peak Wall Stresses of Ascending Thoracic Aortic Aneurysms in Veterans.

Risk of aortic dissection in ascending thoracic aortic aneurysms is not sufficiently captured by size-based metrics. From a biomechanical perspective, dissection may be initiated when wall stress exceeds wall strength. Our objective was to assess the association between aneurysm peak wall stresses and 3-year all-cause mortality. Finite element analysis was performed in 273 veterans with chest computed tomography for surveillance of ascending thoracic aortic aneurysms. Three-dimensional geometries were reconstructed and models developed accounting for prestress geometries. A fiber-embedded hyperelastic material model was applied to obtain circumferential and longitudinal wall stresses under systolic pressure. Patients were followed up to 3 years following the scan to assess aneurysm repair and all-cause mortality. Fine-Gray subdistribution hazards were estimated for all-cause mortality based on age, aortic diameter, and peak wall stresses, treating aneurysm repair as a competing risk. When accounting for age, subdistribution hazard of mortality was not significantly increased by peak circumferential stresses (p = 0.30) but was significantly increased by peak longitudinal stresses (p = 0.008). Aortic diameter did not significantly increase subdistribution hazard of mortality in either model (circumferential model: p = 0.38; longitudinal model: p = 0.30). The effect of peak longitudinal stresses on subdistribution hazard of mortality was maximized at a binary threshold of 355kPa, which captured 34 of 212(16%) patients with diameter <5 cm, 11 of 36(31%) at 5.0-5.4 cm, and 11 of 25(44%) at ≥5.5 cm. Aneurysm peak longitudinal stresses stratified by age and diameter were associated with increased hazard of 3-year all-cause mortality in a veteran cohort. Risk prediction may be enhanced by considering peak longitudinal stresses.

Numerical simulation of transcatheter mitral valve replacement: The dynamic implication of LVOT obstruction in the valve-in-ring case.

Transcatheter mitral valve replacement (TMVR) has been used for "off-label" treatment when annuloplasty band ring for mitral repair fails. However, the complex anatomy and function of the mitral valve may lead to fatal complications as a result of the left ventricular outflow tract (LVOT) obstruction in TMVR. We report the structural and hemodynamic response of LVOT obstruction resulting from TMVR with the Edwards SAPIEN 3 Ultra (S3) device. We modified the original Living Heart Human Model (LHHM) to account for a failed mitral valve with an annuloplasty band ring and simulated the cardiac beating condition in the setting of S3 device implantation. Findings demonstrated a high dynamic behavior of the newly formed LVOT (neoLVOT) as confined by the displaced mitral valve and the interventricular septum. During the cardiac beat, the neoLVOT area oscillated from a maximum of 472.1 mm2 at early systole to the minimum of 183 mm2 at end-systole. The profile of both anchoring force and contact pressure revealed that the band ring serves as the anchoring zone while mitral valve is primally displaced by the deployed device. At early systole, computational flow dynamics highlighted hemodynamic disturbances associated with the LVOT obstruction, with a skewed flow towards the septum and a pressured drop of 4.5 mmHg between the left ventricular apex and the neoLVOT region. This study can lead to a more accurate assessment of the risk induced by the LVOT obstruction when stratifying patient anatomic suitability for TMVR.

A Computationally Efficient Approach to Simulate Heart Rate Effects Using a Whole Human Heart Model.

Computational modeling of the whole human heart has become a valuable tool to evaluate medical devices such as leadless pacemakers, annuloplasty rings and left ventricular assist devices, since it is often difficult to replicate the complex dynamic interactions between the device and human heart in bench-top and animal tests. The Dassault Systèmes Living Heart Human Model (LHHM) is a finite-element model of whole-human-heart electromechanics that has input parameters that were previously calibrated to generate physiological responses in a healthy heart beating at 60 beat/min (resting state). This study demonstrates that, by adjusting only six physiologically meaningful parameters, the LHHM can be recalibrated to generate physiological responses in a healthy heart beating at heart rates ranging from 90−160 beat/min. These parameters are as follows: the sinoatrial node firing period decreases from 0.67 s at 90 bpm to 0.38 s at 160 bpm, atrioventricular delay decreases from 0.122 s at 90 bpm to 0.057 s at 160 bpm, preload increases 3-fold from 90 bpm to 160 bpm, body resistance at 160 bpm is 80% of that at 90 bpm, arterial stiffness at 160 bpm is 3.9 times that at 90 bpm, and a parameter relating myofiber twitch force duration and sarcomere length decreases from 238 ms/mm at 90 bpm to 175 ms/mm at 160 bpm. In addition, this study demonstrates the feasibility of using the LHHM to conduct clinical investigations in AV delay optimization and hemodynamic differences between pacing and exercise. AV delays in the ranges of 40 ms to 250 ms were simulated and stroke volume and systolic blood pressure showed clear peaks at 120 ms for 90 bpm. For a heart during exercise, the increase in cardiac output continues to 160 bpm. However, for a heart during pacing, those physiological parameter adjustments are removed that are related to changes in body oxygen requirements (preload, arterial stiffness and body resistance). Consequently, cardiac output increases initially with heart rate; as the heart rate goes up (>100 bpm), the increasing rate of cardiac output slows down and approaches a plateau.

Inversion of Left Atrial Appendage Will Cause Compressive Stresses in the Tissue: Simulation Study of Potential Therapy.

In atrial fibrillation (AF), thromboembolic events can result from the particular conformation of the left atrial appendage (LAA) bearing increased clot formation and accumulation. Current therapies to reduce the risk of adverse events rely on surgical exclusion or percutaneous occlusion, each of which has drawbacks limiting application and efficacy. We sought to quantify the hemodynamic and structural loads of a novel potential procedure to partially invert the "dead" LAA space to eliminate the auricle apex where clots develop. A realistic left atrial geometry was first achieved from the heart anatomy of the Living Heart Human Model (LHHM) and then the left atrial appendage inversion (LAAI) was simulated by finite-element analysis. The LAAI procedure was simulated by pulling the elements at the LAA tip and prescribing a displacement motion along a predefined path. The deformed configuration was then used to develop a computational flow analysis of LAAI. Results demonstrated that the inverted LAA wall undergoes a change in the stress distribution from tensile to compressive in the inverted appendage, and this can lead to resorption of the LAA tissue as per a reduced stress/resorption relationship. Computational flow analyses highlighted a slightly nested low-flow velocity pattern for the inverted LAA with minimal differences from that of a model without inversion of the LAA apex. Our study revealed important insights into the biomechanics of LAAI and demonstrated the inversion of the stress field (from tensile to compressive), which &can ultimately lead the long-term resorption of the LAA.

Left Ventricle Biomechanics of Low-Flow, Low-Gradient Aortic Stenosis: A Patient-Specific Computational Model.

This study aimed to create an imaging-derived patient-specific computational model of low-flow, low-gradient (LFLG) aortic stenosis (AS) to obtain biomechanics data about the left ventricle. LFLG AS is now a commonly recognized sub-type of aortic stenosis. There remains much controversy over its management, and investigation into ventricular biomechanics may elucidate pathophysiology and better identify patients for valve replacement. ECG-gated cardiac computed tomography images from a patient with LFLG AS were obtained to provide patient-specific geometry for the computational model. Surfaces of the left atrium, left ventricle (LV), and outflow track were segmented. A previously validated multi-scale, multi-physics computational human heart model was adapted to the patient-specific geometry, yielding a model consisting of 91,000 solid elements. This model was coupled to a virtual circulatory system and calibrated to clinically measured parameters from echocardiography and cardiac catheterization data. The simulation replicated key physiologic parameters within 10% of their clinically measured values. Global LV systolic myocardial stress was 7.1 ± 1.8 kPa. Mean stress of the basal, middle, and apical segments were 7.7 ± 1.8 kPa, 9.1 ± 3.8 kPa, and 6.4 ± 0.4 kPa, respectively. This is the first patient-specific computational model of LFLG AS based on clinical imaging. Low myocardial stress correlated with low ejection fraction and eccentric LV remodeling. Further studies are needed to understand how alterations in LV biomechanics correlates with clinical outcomes of AS.

Association of diameter and wall stresses of tricuspid aortic valve ascending thoracic aortic aneurysms.

OBJECTIVE: Ascending thoracic aortic aneurysms carry a risk of acute type A dissection. Elective repair guidelines are designed around size thresholds, but the 1-dimensional parameter of maximum diameter cannot predict acute events in small aneurysms. Biomechanically, dissection can occur when wall stress exceeds strength. Patient-specific ascending thoracic aortic aneurysm wall stresses may be a better predictor of dissection. Our aim was to compare wall stresses in tricuspid aortic valve-associated ascending thoracic aortic aneurysms based on diameter. METHODS: Patients with tricuspid aortic valve-associated ascending thoracic aortic aneurysm and diameter 4.0 cm or greater (n = 221) were divided into groups by 0.5-cm diameter increments. Three-dimensional geometries were reconstructed from computed tomography images, and finite element models were developed taking into account prestress geometries. A fiber-embedded hyperelastic material model was applied to obtain longitudinal and circumferential wall stress distributions under systolic pressure. Median stresses with interquartile ranges were determined. The Kruskal-Wallis test was used for comparisons between size groups. RESULTS: Peak longitudinal wall stresses for tricuspid aortic valve-associated ascending thoracic aortic aneurysm were 290 (265-323) kPa for size 4.0 to 4.4 cm versus 330 (296-359) kPa for 4.5 to 4.9 cm versus 339 (320-373) kPa for 5.0 to 5.4 cm versus 318 (293-351) kPa for 5.5 to 5.9 cm versus 373 (363-449) kPa for 6.0 cm or greater (P = 8.7e-8). Peak circumferential wall stresses were 460 (421-543) kPa for size 4.0 to 4.4 cm versus 503 (453-569) kPa for 4.5 to 4.9 cm versus 549 (430-588) kPa for 5.0 to 5.4 cm versus 540 (471-608) kPa for 5.5 to 5.9 cm versus 596 (506-649) kPa for 6.0 cm or greater (P = .0007). CONCLUSIONS: Circumferential and longitudinal wall stresses are higher as diameter increases, but size groups had large overlap of stress ranges. Wall stress thresholds based on aneurysm wall strength may be a better predictor of patient-specific risk of dissection than diameter in small ascending thoracic aortic aneurysms.

Regional wall stress differences on tricuspid aortic valve-associated ascending aortic aneurysms.

OBJECTIVES: Ascending thoracic aortic aneurysms (aTAAs) carry a risk of acute type A dissection. Elective repair guidelines are based on diameter, but complications often occur below diameter threshold. Biomechanically, dissection can occur when wall stress exceeds wall strength. Aneurysm wall stresses may better capture dissection risk. Our aim was to investigate patient-specific aTAA wall stresses associated with a tricuspid aortic valve (TAV) by anatomic region. METHODS: Patients with aneurysm diameter ≥4.0 cm underwent computed tomography angiography. Aneurysm geometries were reconstructed and loaded to systemic pressure while taking prestress into account. Finite element analyses were conducted to obtain wall stress distributions. The 99th percentile longitudinal and circumferential stresses were determined at systole. Wall stresses between regions were compared using one-way analysis of variance with post hoc Tukey HSD for pairwise comparisons. RESULTS: Peak longitudinal wall stresses on aneurysms (n = 204) were 326 [standard deviation (SD): 61.7], 246 (SD: 63.4) and 195 (SD: 38.7) kPa in sinuses of Valsalva, sinotubular junction (STJ) and ascending aorta (AscAo), respectively, with significant differences between AscAo and both sinuses (P < 0.001) and STJ (P < 0.001). Peak circumferential wall stresses were 416 (SD: 85.1), 501 (SD: 119) and 340 (SD: 57.6) kPa for sinuses, STJ and AscAo, respectively, with significant differences between AscAo and both sinuses (P < 0.001) and STJ (P < 0.001). CONCLUSIONS: Circumferential and longitudinal wall stresses were greater in the aortic root than AscAo on aneurysm patients with a TAV. Aneurysm wall stress magnitudes and distribution relative to respective regional wall strength could improve understanding of aortic regions at greater risk of dissection in a particular patient.

Mitral Valve Atlas for Artificial Intelligence Predictions of MitraClip Intervention Outcomes.

Severe mitral regurgitation (MR) is a cardiac disease that can lead to fatal consequences. MitraClip (MC) intervention is a percutaneous procedure whereby the mitral valve (MV) leaflets are connected along the edge using MCs. The outcomes of the MC intervention are not known in advance, i.e., the outcomes are quite variable. Artificial intelligence (AI) can be used to guide the cardiologist in selecting optimal MC scenarios. In this study, we describe an atlas of shapes as well as different scenarios for MC implantation for such an AI analysis. We generated the MV geometrical data from three different sources. First, the patients' 3-dimensional echo images were used. The pixel data from six key points were obtained from three views of the echo images. Using PyGem, an open-source morphing library in Python, these coordinates were used to create the geometry by morphing a template geometry. Second, the dimensions of the MV, from the literature were used to create data. Third, we used machine learning methods, principal component analysis, and generative adversarial networks to generate more shapes. We used the finite element (FE) software ABAQUS to simulate smoothed particle hydrodynamics in different scenarios for MC intervention. The MR and stresses in the leaflets were post-processed. Our physics-based FE models simulated the outcomes of MC intervention for different scenarios. The MR and stresses in the leaflets were computed by the FE models for a single clip at different locations as well as two and three clips. Results from FE simulations showed that the location and number of MCs affect subsequent residual MR, and that leaflet stresses do not follow a simple pattern. Furthermore, FE models need several hours to provide the results, and they are not applicable for clinical usage where the predicted outcomes of MC therapy are needed in real-time. In this study, we generated the required dataset for the AI models which can provide the results in a matter of seconds.

Patient-Specific Analysis of Ascending Thoracic Aortic Aneurysm with the Living Heart Human Model.

In ascending thoracic aortic aneurysms (ATAAs), aneurysm kinematics are driven by ventricular traction occurring every heartbeat, increasing the stress level of dilated aortic wall. Aortic elongation due to heart motion and aortic length are emerging as potential indicators of adverse events in ATAAs; however, simulation of ATAA that takes into account the cardiac mechanics is technically challenging. The objective of this study was to adapt the realistic Living Heart Human Model (LHHM) to the anatomy and physiology of a patient with ATAA to assess the role of cardiac motion on aortic wall stress distribution. Patient-specific segmentation and material parameter estimation were done using preoperative computed tomography angiography (CTA) and ex vivo biaxial testing of the harvested tissue collected during surgery. The lumped-parameter model of systemic circulation implemented in the LHHM was refined using clinical and echocardiographic data. The results showed that the longitudinal stress was highest in the major curvature of the aneurysm, with specific aortic quadrants having stress levels change from tensile to compressive in a transmural direction. This study revealed the key role of heart motion that stretches the aortic root and increases ATAA wall tension. The ATAA LHHM is a realistic cardiovascular platform where patient-specific information can be easily integrated to assess the aneurysm biomechanics and potentially support the clinical management of patients with ATAAs.

Regional biomechanical and failure properties of healthy human ascending aorta and root.

PURPOSE: Aortic dissection (AD) is a life-threatening event that occurs when the intimal entry tear propagates and separates inner from outer layers of the aorta. Diameter, the current criterion for aneurysm repair, is far from ideal and additional evidence to optimize clinical decision would be extremely beneficial. Biomechanical investigation of the regional failure properties of aortic tissue is essential to understand and proactively prevent AD. We previously studied biaxial mechanical properties of healthy human aorta. In this study, we investigated the regional failure properties of healthy human ascending aorta (AscAo) including sinuses of Valsalva (SOV), and sinotubular junction (STJ). RESULTS: A total of 430 intact tissue samples were harvested from 19 healthy donors whose hearts were excluded from heart transplantation. The donors had mean age of 51 ± 11.7 years and nearly equal gender distribution. Samples were excised from aortic regions and subregions at defined locations. Tissue strips were subjected to either biaxial or uniaxial failure testing. Wall thickness varied regionally being thickest at AscAo (2.08 ± 0.66 mm) and thinnest at SOV (1.46 ± 0.31 mm). Biaxial testing demonstrated hyperplastic behavior of aortic tissues. Posterior and lateral STJ subregions were found to be stiffer than anterior and medial subregions in both circumferential and longitudinal directions. Failure stresses were significantly higher in the circumferential than longitudinal directions in each subregion of AscAo, STJ, and SOV. Longitudinal failure stresses were significantly greater in AscAo than those in STJ or SOV. Longitudinal failure stresses in AscAo were much smaller anteriorly than posteriorly, and medially than laterally. CONCLUSIONS: The finding of weakest region at the sinotubular junction along the longitudinal direction corroborates clinical observations of that region being commonly involved as the initial site of intimal tear in aortic dissections. Failure stretch ratios correlated to elastic modulus at each region. Furthermore, strong correlation was seen between STJ failure stresses and elastic modulus at physiological pressure along both circumferential and longitudinal directions. Correlating in-vivo aortic elastic modulus based on in-vivo imaging with experimentally determined elastic modulus at physiological pressure and failure stresses may potentially provide valuable information regarding aortic wall strength. Better understanding of aortic biomechanics in normal physiologic and aneurysmal pathologic states may aid in determining risk factors for predicting dissection in patient-specific fashion.

Computational Modeling Studies of the Roles of Left Ventricular Geometry, Afterload, and Muscle Contractility on Myocardial Strains in Heart Failure with Preserved Ejection Fraction.

Global longitudinal strain and circumferential strain are found to be reduced in HFpEF, which some have interpreted that the global left ventricular (LV) contractility is impaired. This finding is, however, contradicted by a preserved ejection fraction (EF) and confounded by changes in LV geometry and afterload resistance that may also affect the global strains. To reconcile these issues, we used a validated computational framework consisting of a finite element LV model to isolate the effects of HFpEF features in affecting systolic function metrics. Simulations were performed to quantify the effects on myocardial strains due to changes in LV geometry, active tension developed by the tissue, and afterload. We found that only a reduction in myocardial contractility and an increase in afterload can simultaneously reproduce the blood pressures, EF and strains measured in HFpEF patients. This finding suggests that it is likely that the myocardial contractility is reduced in HFpEF patients. Graphical abstract.

Finite-element based optimization of left ventricular passive stiffness in normal volunteers and patients after myocardial infarction: Utility of an inverse deformation gradient calculation of regional diastolic strain.

INTRODUCTION: Left ventricular (LV) diastolic dysfunction (DD) is common after myocardial infarction (MI). Whereas current clinical assessment of DD relies on indirect markers including LV filling, finite element (FE) -based computational modeling directly measures regional diastolic stiffness. We hypothesized that an inverse deformation gradient (DG) method calculation of diastolic strain (IDGDS) allows the FE model-based calculation of regional diastolic stiffness (material parameters; MP) in post-MI patients with DD. METHODS: Cardiac magnetic resonance (CMR) with tags (CSPAMM) and late gadolinium enhancement (LGE) was performed in 10 patients with post-MI DD and 10 healthy volunteers. The 3-dimensional (3D) LV DG from end-diastole (ED) to early diastolic filling (EDF; DGED→EDF) was calculated from CSPAMM. Diastolic strain was calculated from DGEDF→ED by inverting the DGED→EDF. FE models were created with MI and non-MI (remote; RM) regions determined by LGE. Guccione MPs C, and exponential fiber, bf, and transverse, bt , terms were optimized with IDGDS strain. RESULTS: 3D circumferential and longitudinal diastolic strain (Ecc;Ell) calculated using IDGDS in CSPAMM obtained in volunteers and MI patients were [Formula: see text]  = 0.27 ± 0.01, [Formula: see text]  = 0.24 ± 0.03 and [Formula: see text]  = 0.21 ± 0.02, and [Formula: see text]  = 0.15 ± 0.02, respectively. MPs in the volunteer group were CH = 0.013 [0.001, 0.235] kPa, [Formula: see text]  = 20.280 ± 4.994, and [Formula: see text]  = 7.460 ± 2.171 and CRM = 0.0105 [0.010, 0.011] kPa, [Formula: see text]  = 50.786 ± 13.511 (p = 0.0846), and [Formula: see text]  = 17.355 ± 2.743 (p = 0.0208) in the remote myocardium of post-MI patients. CONCLUSION: Diastolic strain, calculated from CSPAMM with IDGDS, enables calculation of FE model-based regional diastolic material parameters. Transverse stiffness of the remote myocardium, , may be a valuable new metric for determination of DD in patients after MI.

Wall stress analyses in patients with ≥5 cm versus <5 cm ascending thoracic aortic aneurysm.

OBJECTIVE: Current guidelines for elective surgery of ascending thoracic aortic aneurysms (aTAAs) use aneurysm size as primary determinant for risk stratification of adverse events. Biomechanically, dissection may occur when wall stress exceeds wall strength. Determining patient-specific aTAA wall stresses by finite element analysis can potentially predict patient-specific risk of dissection. This study compared peak wall stresses in patients with ≥5.0 cm versus <5.0 cm aTAAs to determine correlation between diameter and wall stress. METHODS: Patients with aTAA ≥5.0 cm (n = 47) and <5.0 cm (n = 53) were studied. Patient-specific aneurysm geometries obtained from echocardiogram-gated computed tomography were meshed and prestress geometries determined. Peak wall stresses and stress distributions were determined using LS-DYNA finite element analysis software (LSTC Inc, Livermore, Calif), with user-defined fiber-embedded material models under systolic pressure. RESULTS: Peak circumferential stresses at systolic pressure were 530 ± 83 kPa for aTAA ≥5.0 cm versus 486 ± 87 kPa for aTAA <5.0 cm (P = .07), whereas peak longitudinal stresses were 331 ± 57 kPa versus 310 ± 54 kPa (P = .08), respectively. For aTAA ≥5.0 cm, correlation between peak circumferential stresses and size was 0.41, whereas correlation between peak longitudinal wall stresses and size was 0.33. However, for aTAA <5.0 cm, correlation between peak circumferential stresses and size was 0.23, whereas correlation between peak longitudinal stresses and size was 0.14. CONCLUSIONS: Peak patient-specific aTAA wall stresses overall were larger for ≥5.0 cm than aTAA <5.0 cm. Although some correlation between size and peak wall stresses was found in aTAA ≥5.0 cm, poor correlation existed between size and peak wall stresses in aTAA <5.0 cm. Patient-specific wall stresses are particularly important in determining patient-specific risk of dissection for aTAA <5.0 cm.