Regional assessment of aortic valve calcification using topographic maps in contrast-enhanced CT: in-vivo sex and severity-based differences in calcific presentation.

Background: Procedural planning for transcatheter aortic valve replacement (TAVR) is routinely performed using contrast computed tomography (CT) in patients with severe aortic stenosis (AS). Despite its potential, little investigation has been done into the possibility of aortic valve calcification (AVC) scoring in contrast-enhanced CT. Contrast CT has superior spatial and contrast resolution compared to the non-contrast Agatston score protocol, which would allow for development of better pattern and distribution descriptors of calcific lesions in the aortic valve (AV). Methods: We developed a new false positive rate (FPR) based method that can quantify leaflet calcification based on shape overlap metrics. We also introduce a novel regional scheme for quantifying the shape and structure of calcification using topographic maps. The study was designed to: (I) determine the feasibility of using a novel method based on FPR to detect AVC using contrast-enhanced CT images by assessing the volume scores measured using FPR versus non-contrast methods and alternative contrast methods for volume scoring based on fixed or dynamic HU thresholds. (II) Develop a new scheme for assessing calcific geometry and structure and evaluate patterns of calcification in the varied presentation of AS. Results: Our results show a very strong correlation with non-contrast volume (r=0.919, P<0.001; n=178) and Agatston scores (r=0.913, P<0.001; n=178) that were evaluated using a standard calcium scoring technique. Finally, we analyzed the differences and similarities in the patterns of calcific deposition with respect to sex and degree of severity. Conclusions: The FPR method demonstrates the best overall agreement with non-contrast scores across both low and high ends of calcific density compared to luminal attenuation methods. In addition, we showed that leaflet calcific deposition follows distinctive patterns across the belly of the leaflet, with the rate of calcific progression peaking at the non-coronary cusp (NCC) leaflet and lowest for the right-coronary cusp. Females experience significantly lower calcific deposition compared to males despite showing similar patterns and symptoms. Our findings suggest that precise regional assessment of calcific progression could be an important tool for monitoring AS development as well as predicting peri-procedural complications in TAVR.

Early Detection of Risk of Neo-Sinus Blood Stasis Post-Transcatheter Aortic Valve Replacement Using Personalized Hemodynamic Analysis.

Background: Despite the demonstrated benefits of transcatheter aortic valve replacement (TAVR), subclinical leaflet thrombosis and hypoattenuated leaflet thickening are commonly seen as initial indications of decreased valve durability and augmented risk of transient ischemic attack. Methods: We developed a multiscale patient-specific computational framework to quantify metrics of global circulatory function, metrics of global cardiac function, and local cardiac fluid dynamics of the aortic root and coronary arteries. Results: Based on our findings, TAVR might be associated with a high risk of blood stagnation in the neo-sinus region due to the lack of sufficient blood flow washout during the diastole phase (e.g., maximum blood stasis volume increased by 13, 8, and 2.7 fold in the left coronary cusp, right coronary cusp, and noncoronary cusp, respectively [N = 26]). Moreover, in some patients, TAVR might not be associated with left ventricle load relief (e.g., left ventricle load reduced only by 1.2 % [N = 26]) and diastolic coronary flow improvement (e.g., maximum coronary flow reduced by 4.94%, 15.05%, and 23.59% in the left anterior descending, left circumflex coronary artery, and right coronary artery, respectively, [N = 26]). Conclusions: The transvalvular pressure gradient amelioration after TAVR might not translate into adequate sinus blood washout, optimal coronary flow, and reduced cardiac stress. Noninvasive personalized computational modeling can facilitate the determination of the most effective revascularization strategy pre-TAVR and monitor leaflet thrombosis and coronary plaque progression post-TAVR.

Impact of TAVR on coronary artery hemodynamics using clinical measurements and image-based patient-specific in silico modeling.

In recent years, transcatheter aortic valve replacement (TAVR) has become the leading method for treating aortic stenosis. While the procedure has improved dramatically in the past decade, there are still uncertainties about the impact of TAVR on coronary blood flow. Recent research has indicated that negative coronary events after TAVR may be partially driven by impaired coronary blood flow dynamics. Furthermore, the current technologies to rapidly obtain non-invasive coronary blood flow data are relatively limited. Herein, we present a lumped parameter computational model to simulate coronary blood flow in the main arteries as well as a series of cardiovascular hemodynamic metrics. The model was designed to only use a few inputs parameters from echocardiography, computed tomography and a sphygmomanometer. The novel computational model was then validated and applied to 19 patients undergoing TAVR to examine the impact of the procedure on coronary blood flow in the left anterior descending (LAD) artery, left circumflex (LCX) artery and right coronary artery (RCA) and various global hemodynamics metrics. Based on our findings, the changes in coronary blood flow after TAVR varied and were subject specific (37% had increased flow in all three coronary arteries, 32% had decreased flow in all coronary arteries, and 31% had both increased and decreased flow in different coronary arteries). Additionally, valvular pressure gradient, left ventricle (LV) workload and maximum LV pressure decreased by 61.5%, 4.5% and 13.0% respectively, while mean arterial pressure and cardiac output increased by 6.9% and 9.9% after TAVR. By applying this proof-of-concept computational model, a series of hemodynamic metrics were generated non-invasively which can help to better understand the individual relationships between TAVR and mean and peak coronary flow rates. In the future, tools such as these may play a vital role by providing clinicians with rapid insight into various cardiac and coronary metrics, rendering the planning for TAVR and other cardiovascular procedures more personalized.

A Doppler-exclusive non-invasive computational diagnostic framework for personalized transcatheter aortic valve replacement.

Given the associated risks with transcatheter aortic valve replacement (TAVR), it is crucial to determine how the implant will affect the valve dynamics and cardiac function, and if TAVR will improve or worsen the outcome of the patient. Effective treatment strategies, indeed, rely heavily on the complete understanding of the valve dynamics. We developed an innovative Doppler-exclusive non-invasive computational framework that can function as a diagnostic tool to assess valve dynamics in patients with aortic stenosis in both pre- and post-TAVR status. Clinical Doppler pressure was reduced by TAVR (52.2 ± 20.4 vs. 17.3 ± 13.8 [mmHg], p < 0.001), but it was not always accompanied by improvements in valve dynamics and left ventricle (LV) hemodynamics metrics. TAVR had no effect on LV workload in 4 patients, and LV workload post-TAVR significantly rose in 4 other patients. Despite the group level improvements in maximum LV pressure (166.4 ± 32.2 vs 131.4 ± 16.9 [mmHg], p < 0.05), only 5 of the 12 patients (41%) had a decrease in LV pressure. Moreover, TAVR did not always improve valve dynamics. TAVR did not necessarily result in a decrease (in 9 out of 12 patients investigated in this study) in major principal stress on the aortic valve leaflets which is one of the main contributors in valve degeneration and, consequently, failure of heart valves. Diastolic stresses increased significantly post-TAVR (34%, 109% and 81%, p < 0.001) for each left, right and non-coronary leaflets respectively. Moreover, we quantified the stiffness and material properties of aortic valve leaflets which correspond with the reduced calcified region average stiffness among leaflets (66%, 74% and 62%; p < 0.001; N = 12). Valve dynamics post-intervention should be quantified and monitored to ensure the improvement of patient conditions and prevent any further complications. Improper evaluation of biomechanical valve features pre-intervention as well as post-intervention may result in harmful effects post-TAVR in patients including paravalvular leaks, valve degeneration, failure of TAVR and heart failure.

Reducing Long-Term Mortality Post Transcatheter Aortic Valve Replacement Requires Systemic Differentiation of Patient-Specific Coronary Hemodynamics.

Background Despite the proven benefits of transcatheter aortic valve replacement (TAVR) and its recent expansion toward the whole risk spectrum, coronary artery disease is present in more than half of the candidates for TAVR. Many previous studies do not focus on the longer-term impact of TAVR on coronary arteries, and hemodynamic changes to the circulatory system in response to the anatomical changes caused by TAVR are not fully understood. Methods and Results We developed a multiscale patient-specific computational framework to examine the effect of TAVR on coronary and cardiac hemodynamics noninvasively. Based on our findings, TAVR might have an adverse impact on coronary hemodynamics due to the lack of sufficient coronary blood flow during diastole phase (eg, maximum coronary flow rate reduced by 8.98%, 16.83%, and 22.73% in the left anterior descending, left circumflex coronary artery, and right coronary artery, respectively [N=31]). Moreover, TAVR may increase the left ventricle workload (eg, left ventricle workload increased by 2.52% [N=31]) and decrease the coronary wall shear stress (eg, maximum time averaged wall shear stress reduced by 9.47%, 7.75%, 6.94%, 8.07%, and 6.28% for bifurcation, left main coronary artery, left anterior descending, left circumflex coronary artery, and right coronary artery branches, respectively). Conclusions The transvalvular pressure gradient relief after TAVR might not result in coronary flow improvement and reduced cardiac load. Optimal revascularization strategy pre-TAVR and progression of coronary artery disease after TAVR could be determined by noninvasive personalized computational modeling.

An ultrasound-exclusive non-invasive computational diagnostic framework for personalized cardiology of aortic valve stenosis.

Aortic stenosis (AS) is an acute and chronic cardiovascular disease and If left untreated, 50% of these patients will die within two years of developing symptoms. AS is characterized as the stiffening of the aortic valve leaflets which restricts their motion and prevents the proper opening under transvalvular pressure. Assessments of the valve dynamics, if available, would provide valuable information about the patient's state of cardiac deterioration as well as heart recovery and can have incredible impacts on patient care, planning interventions and making critical clinical decisions with life-threatening risks. Despite remarkable advancements in medical imaging, there are no clinical tools available to quantify valve dynamics invasively or noninvasively. In this study, we developed a highly innovative ultrasound-based non-invasive computational framework that can function as a diagnostic tool to assess valve dynamics (e.g. transient 3-D distribution of stress and displacement, 3-D deformed shape of leaflets, geometric orifice area and angular positions of leaflets) for patients with AS at no risk to the patients. Such a diagnostic tool considers the local valve dynamics and the global circulatory system to provide a platform for testing the intervention scenarios and evaluating their effects. We used clinical data of 12 patients with AS not only to validate the proposed framework but also to demonstrate its diagnostic abilities by providing novel analyses and interpretations of clinical data in both pre and post intervention states. We used transthoracic echocardiogram (TTE) data for the developments and transesophageal echocardiography (TEE) data for validation.

Recent advancements of nanomodified electrodes - Towards point-of-care detection of cardiac biomarkers.

The increasing number of deaths from cardiovascular diseases has become a substantial concern in both developed and underdeveloped countries. Rapid and on-site monitoring of this disease is urgently important to control, prevent and make awareness of public health. Recently, a lot of focus has been placed on nanomaterials and modify these nanomaterials have been explored to detect cardiac biomarkers. By implementing biosensors that are modified with novel recognition elements and more stable nanomaterials, the use of electrochemistry for point-of-care devices is more realistic every day. This review focuses on the current state of nanomaterials conjugated biorecognition elements (enzyme integrated with nanomaterials, antibody conjugated nanomaterials and aptamer conjugated nanomaterials) for electrochemical cardiovascular disease detection. Specifically, a lot of attention has been given to the trends toward more stable biosensors that have increased the potential to be used as point-of-care devices for the detection of cardiac biomarkers due to their high stability and specificity. Moreover, the recent progress on biomolecule-free electrochemical nanosensors for cardiovascular disease detection has been considered. At last, the possibility and drawbacks of some of these techniques for point-of-care cardiac device development in the future have been discussed.

Hemodynamic Modeling, Medical Imaging, and Machine Learning and Their Applications to Cardiovascular Interventions.

Cardiovascular disease is a deadly global health crisis that carries a substantial financial burden. Innovative treatment and management of cardiovascular disease straddles medicine, personalized hemodynamic modeling, machine learning, and modern imaging to help improve patient outcomes and reduce the economic impact. Hemodynamic modeling offers a non-invasive method to provide clinicians with new pre- and post- procedural metrics and aid in the selection of treatment options. Medical imaging is an integral part in clinical workflows for understanding and managing cardiac disease and interventions. Coupling machine learning with modeling, and cardiovascular imaging, provides faster modeling, improved data fidelity, and an enhanced understanding and earlier detection of cardiovascular anomalies, leading to the development of patient-specific diagnostic and predictive tools for characterizing and assessing cardiovascular outcomes. Herein, we provide a scoping review of translational hemodynamic modeling, medical imaging, and machine learning and their applications to cardiovascular interventions. We particularly focus on providing an intuitive understanding of each of these approaches and their ability to support decision making during important clinical milestones.

Long-term prognostic impact of paravalvular leakage on coronary artery disease requires patient-specific quantification of hemodynamics.

Transcatheter aortic valve replacement (TAVR) is a frequently used minimally invasive intervention for patient with aortic stenosis across a broad risk spectrum. While coronary artery disease (CAD) is present in approximately half of TAVR candidates, correlation of post-TAVR complications such as paravalvular leakage (PVL) or misalignment with CAD are not fully understood. For this purpose, we developed a multiscale computational framework based on a patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-structure interaction model to quantify metrics of global circulatory function, metrics of global cardiac function and local cardiac fluid dynamics in 6 patients. Based on our findings, PVL limits the benefits of TAVR and restricts coronary perfusion due to the lack of sufficient coronary blood flow during diastole phase (e.g., maximum coronary flow rate reduced by 21.73%, 21.43% and 21.43% in the left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) respectively (N = 6)). Moreover, PVL may increase the LV load (e.g., LV load increased by 17.57% (N = 6)) and decrease the coronary wall shear stress (e.g., maximum wall shear stress reduced by 20.62%, 21.92%, 22.28% and 25.66% in the left main coronary artery (LMCA), left anterior descending (LAD), left circumflex (LCX) and right coronary artery (RCA) respectively (N = 6)), which could promote atherosclerosis development through loss of the physiological flow-oriented alignment of endothelial cells. This study demonstrated that a rigorously developed personalized image-based computational framework can provide vital insights into underlying mechanics of TAVR and CAD interactions and assist in treatment planning and patient risk stratification in patients.

Impact of extra-anatomical bypass on coarctation fluid dynamics using patient-specific lumped parameter and Lattice Boltzmann modeling.

Accurate hemodynamic analysis is not only crucial for successful diagnosis of coarctation of the aorta (COA), but intervention decisions also rely on the hemodynamics assessment in both pre and post intervention states to minimize patient risks. Despite ongoing advances in surgical techniques for COA treatments, the impacts of extra-anatomic bypass grafting, a surgical technique to treat COA, on the aorta are not always benign. Our objective was to investigate the impact of bypass grafting on aortic hemodynamics. We investigated the impact of bypass grafting on aortic hemodynamics using a patient-specific computational-mechanics framework in three patients with COA who underwent bypass grafting. Our results describe that bypass grafting improved some hemodynamic metrics while worsened the others: (1) Doppler pressure gradient improved (decreased) in all patients; (2) Bypass graft did not reduce the flow rate substantially through the COA; (3) Systemic arterial compliance increased in patients #1 and 3 and didn't change (improve) in patient 3; (4) Hypertension got worse in all patients; (5) The flow velocity magnitude improved (reduced) in patient 2 and 3 but did not improve significantly in patient 1; (6) There were elevated velocity magnitude, persistence of vortical flow structure, elevated turbulence characteristics, and elevated wall shear stress at the bypass graft junctions in all patients. We concluded that bypass graft may lead to pseudoaneurysm formation and potential aortic rupture as well as intimal hyperplasia due to the persistent abnormal and irregular aortic hemodynamics in some patients. Moreover, post-intervention, exposures of endothelial cells to high shear stress may lead to arterial remodeling, aneurysm, and rupture.

Reducing Morbidity and Mortality in Patients With Coarctation Requires Systematic Differentiation of Impacts of Mixed Valvular Disease on Coarctation Hemodynamics.

Background Despite ongoing advances in surgical techniques for coarctation of the aorta (COA) repair, the long-term results are not always benign. Associated mixed valvular diseases (various combinations of aortic and mitral valvular pathologies) are responsible for considerable postoperative morbidity and mortality. We investigated the impact of COA and mixed valvular diseases on hemodynamics. Methods and Results We developed a patient-specific computational framework. Our results demonstrate that mixed valvular diseases interact with COA fluid dynamics and contribute to speed up the progression of the disease by amplifying the irregular flow patterns downstream of COA (local) and exacerbating the left ventricular function (global) (N=26). Velocity downstream of COA with aortic regurgitation alone was increased, and the situation got worse when COA and aortic regurgitation coexisted with mitral regurgitation (COA with normal valves: 5.27 m/s, COA with only aortic regurgitation: 8.8 m/s, COA with aortic and mitral regurgitation: 9.36 m/s; patient 2). Workload in these patients was increased because of the presence of aortic stenosis alone, aortic regurgitation alone, mitral regurgitation alone, and when they coexisted (COA with normal valves: 1.0617 J; COA with only aortic stenosis: 1.225 J; COA with only aortic regurgitation: 1.6512 J; COA with only mitral regurgitation: 1.3599 J; patient 1). Conclusions Not only the severity of COA, but also the presence and the severity of mixed valvular disease should be considered in the evaluation of risks in patients. The results suggest that more aggressive surgical approaches may be required, because regularly chosen current surgical techniques may not be optimal for such patients.

Effects of Choice of Medical Imaging Modalities on a Non-invasive Diagnostic and Monitoring Computational Framework for Patients With Complex Valvular, Vascular, and Ventricular Diseases Who Undergo Transcatheter Aortic Valve Replacement.

Due to the high individual differences in the anatomy and pathophysiology of patients, planning individualized treatment requires patient-specific diagnosis. Indeed, hemodynamic quantification can be immensely valuable for accurate diagnosis, however, we still lack precise diagnostic methods for numerous cardiovascular diseases including complex (and mixed) valvular, vascular, and ventricular interactions (C3VI) which is a complicated situation made even more challenging in the face of other cardiovascular pathologies. Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. In a recent paper, we developed a non-invasive and Doppler-based diagnostic and monitoring computational mechanics framework for C3VI, called C3VI-DE that uses input parameters measured reliably using Doppler echocardiography. In the present work, we have developed another computational-mechanics framework for C3VI (called C3VI-CT). C3VI-CT uses the same lumped-parameter model core as C3VI-DE but its input parameters are measured using computed tomography and a sphygmomanometer. Both frameworks can quantify: (1) global hemodynamics (metrics of cardiac function); (2) local hemodynamics (metrics of circulatory function). We compared accuracy of the results obtained using C3VI-DE and C3VI-CT against catheterization data (gold standard) using a C3VI dataset (N = 49) for patients with C3VI who undergo TAVR in both pre and post-TAVR with a high variability. Because of the dataset variability and the broad range of diseases that it covers, it enables determining which framework can yield the most accurate results. In contrast with C3VI-CT, C3VI-DE tracks both the cardiac and vascular status and is in great agreement with cardiac catheter data.

Personalized intervention cardiology with transcatheter aortic valve replacement made possible with a non-invasive monitoring and diagnostic framework.

One of the most common acute and chronic cardiovascular disease conditions is aortic stenosis, a disease in which the aortic valve is damaged and can no longer function properly. Moreover, aortic stenosis commonly exists in combination with other conditions causing so many patients suffer from the most general and fundamentally challenging condition: complex valvular, ventricular and vascular disease (C3VD). Transcatheter aortic valve replacement (TAVR) is a new less invasive intervention and is a growing alternative for patients with aortic stenosis. Although blood flow quantification is critical for accurate and early diagnosis of C3VD in both pre and post-TAVR, proper diagnostic methods are still lacking because the fluid-dynamics methods that can be used as engines of new diagnostic tools are not well developed yet. Despite remarkable advances in medical imaging, imaging on its own is not enough to quantify the blood flow effectively. Moreover, understanding of C3VD in both pre and post-TAVR and its progression has been hindered by the absence of a proper non-invasive tool for the assessment of the cardiovascular function. To enable the development of new non-invasive diagnostic methods, we developed an innovative image-based patient-specific computational fluid dynamics framework for patients with C3VD who undergo TAVR to quantify metrics of: (1) global circulatory function; (2) global cardiac function as well as (3) local cardiac fluid dynamics. This framework is based on an innovative non-invasive Doppler-based patient-specific lumped-parameter algorithm and a 3-D strongly-coupled fluid-solid interaction. We validated the framework against clinical cardiac catheterization and Doppler echocardiographic measurements and demonstrated its diagnostic utility by providing novel analyses and interpretations of clinical data in eleven C3VD patients in pre and post-TAVR status. Our findings position this framework as a promising new non-invasive diagnostic tool that can provide blood flow metrics while posing no risk to the patient. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.

Towards non-invasive computational-mechanics and imaging-based diagnostic framework for personalized cardiology for coarctation.

Coarctation of the aorta (COA) is a congenital narrowing of the proximal descending aorta. Although accurate and early diagnosis of COA hinges on blood flow quantification, proper diagnostic methods for COA are still lacking because fluid-dynamics methods that can be used for accurate flow quantification are not well developed yet. Most importantly, COA and the heart interact with each other and because the heart resides in a complex vascular network that imposes boundary conditions on its function, accurate diagnosis relies on quantifications of the global hemodynamics (heart-function metrics) as well as the local hemodynamics (detailed information of the blood flow dynamics in COA). In this study, to enable the development of new non-invasive methods that can quantify local and global hemodynamics for COA diagnosis, we developed an innovative fast computational-mechanics and imaging-based framework that uses Lattice Boltzmann method and lumped-parameter modeling that only need routine non-invasive clinical patient data. We used clinical data of patients with COA to validate the proposed framework and to demonstrate its abilities to provide new diagnostic analyses not possible with conventional diagnostic methods. We validated this framework against clinical cardiac catheterization data, calculations using the conventional finite-volume method and clinical Doppler echocardiographic measurements. The diagnostic information, that the framework can provide, is vitally needed to improve clinical outcomes, to assess patient risk and to plan treatment.

A diagnostic, monitoring, and predictive tool for patients with complex valvular, vascular and ventricular diseases.

Hemodynamics quantification is critically useful for accurate and early diagnosis, but we still lack proper diagnosticmethods for many cardiovascular diseases. Furthermore, as most interventions intend to recover the healthy condition, the ability to monitor and predict hemodynamics following interventions can have significant impacts on saving lives. Predictive methods are rare, enabling prediction of effects of interventions, allowing timely and personalized interventions and helping critical clinical decision making about life-threatening risks based on quantitative data. In this study, an innovative non-invasive imaged-based patient-specific diagnostic, monitoring and predictive tool (called C3VI-CMF) was developed, enabling quantifying (1) details of physiological flow and pressures through the heart and circulatory system; (2) heart function metrics. C3VI-CMF also predicts the breakdown of the effects of each disease constituents on the heart function. Presently, neither of these can be obtained noninvasively in patients and when invasive procedures are undertaken, the collected metrics cannot be by any means as complete as the ones C3VI-CMF provides. C3VI-CMF purposefully uses a limited number of noninvasive input parameters all of which can be measured using Doppler echocardiography and sphygmomanometer. Validation of C3VI-CMF, against cardiac catheterization in forty-nine patients with complex cardiovascular diseases, showed very good agreement with the measurements.

Mixed Valvular Disease Following Transcatheter Aortic Valve Replacement: Quantification and Systematic Differentiation Using Clinical Measurements and Image-Based Patient-Specific In Silico Modeling.

Background Mixed valvular disease (MVD), mitral regurgitation (MR) from pre-existing disease in conjunction with paravalvular leak (PVL) following transcatheter aortic valve replacement (TAVR), is one of the most important stimuli for left ventricle (LV) dysfunction, associated with cardiac mortality. Despite the prevalence of MVD, the quantitative understanding of the interplay between pre-existing MVD, PVL, LV, and post-TAVR recovery is meager. Methods and Results We quantified the effects of MVD on valvular-ventricular hemodynamics using an image-based patient-specific computational framework in 72 MVD patients. Doppler pressure was reduced by TAVR (mean, 77%; N=72; P<0.05), but it was not always accompanied by improvements in LV workload. TAVR had no effect on LV workload in 22 patients, and LV workload post-TAVR significantly rose in 32 other patients. TAVR reduced LV workload in only 18 patients (25%). PVL significantly alters LV flow and increases shear stress on transcatheter aortic valve leaflets. It interacts with mitral inflow and elevates shear stresses on mitral valve and is one of the main contributors in worsening of MR post-TAVR. MR worsened in 32 patients post-TAVR and did not improve in 18 other patients. Conclusions PVL limits the benefit of TAVR by increasing LV load and worsening of MR and heart failure. Post-TAVR, most MVD patients (75% of N=72; P<0.05) showed no improvements or even worsening of LV workload, whereas the majority of patients with PVL, but without that pre-existing MR condition (60% of N=48; P<0.05), showed improvements in LV workload. MR and its exacerbation by PVL may hinder the success of TAVR.

Ventricular stroke work and vascular impedance refine the characterization of patients with aortic stenosis.

Aortic stenosis (AS) management is classically guided by symptoms and valvular metrics. However, the natural history of AS is dictated by coupling of the left ventricle, aortic valve, and vascular system. We investigated whether metrics of ventricular and vascular state add to the appreciation of AS state above valve gradient alone. Seventy patients with severe symptomatic AS were prospectively followed from baseline to 30 days after transcatheter aortic valve replacement (TAVR). Quality of life (QOL) was assessed using the Kansas City Cardiomyopathy Questionnaire. Left ventricular stroke work (SWLV) and vascular impedance spectrums were calculated noninvasively using in-house models based on central blood pressure waveforms, along with hemodynamic parameters from echocardiograms. Patients with higher preprocedural SWLV and lower vascular impedance were more likely to experience improved QOL after TAVR. Patients fell into two categories: those who did and those who did not exhibit increase in blood pressure after TAVR. In patients who developed hypertension (19%), vascular impedance increased and SWLV remained unchanged (impedance at zeroth harmonic: Z 0, from 3964.4 to 4851.8 dyne·s/cm3, P = 0.039; characteristic impedance: Z c, from 376.2 to 603.2 dyne·s/cm3, P = 0.033). SWLV dropped only in patients who did not develop new hypertension after TAVR (from 1.58 to 1.26 J; P < 0.001). Reduction in valvular pressure gradient after TAVR did not predict change in SWLV (r = 0.213; P = 0.129). Reduction of SWLV after TAVR may be an important metric in management of AS, rather than relying solely on the elimination of transvalvular pressure gradients.