Transcatheter aortic valve implantation versus surgical aortic valve replacement in severe aortic stenosis patients at low surgical mortality risk: a cost-effectiveness analysis in Belgium.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) with the SAPIEN 3 device has recently shown significant clinical benefits, compared to surgical aortic valve replacement (SAVR), in patients at low risk for surgical mortality (PARTNER 3 trial, NCT02675114). Currently in Belgium, TAVI use is restricted to high-risk or inoperable patients with severe symptomatic aortic stenosis (sSAS). This cost-utility analysis aimed to assess whether TAVI with SAPIEN 3 could lead to potential cost-savings compared with SAVR, in the low-risk sSAS population in Belgium. METHODS: A previously published, two-stage, Markov-based cost-utility model was used. Clinical outcomes were captured using data from PARTNER 3 and the model was adapted for the Belgian context using cost data from the perspective of the Belgian National Healthcare System, indexed to 2022. A lifetime horizon was chosen. The model outputs included changes in direct healthcare costs, survival and health-related quality of life using TAVI versus SAVR. RESULTS: TAVI with SAPIEN 3 provides meaningful clinical and cost benefits over SAVR, in terms of an increase in quality-adjusted life years (QALYs) of 0.94 and cost-saving of €3 013 per patient. While initial procedure costs were higher for TAVI compared with SAVR, costs related to rehabilitation, disabling stroke, treated atrial fibrillation, and rehospitalization were lower. The cost-effectiveness of TAVI over SAVR remained robust in sensitivity analyses. CONCLUSION: TAVI with SAPIEN 3 may offer a meaningful alternative intervention to SAVR in Belgian low-risk patients with sSAS, showing both clinical benefits and cost savings associated with post-procedure patient management.

Tumour necrosis factor-alpha serum level is an independent predictor of medium-term all-cause mortality after transcatheter aortic valve replacement.

BACKGROUND: Transcatheter aortic valve implantation (TAVI) is a suitable treatment for patients with severe aortic stenosis and severely increased operative risk. There is need for a better preoperative risk assessment for TAVI candidates. AIM: To determine whether Tumour necrosis factor-alfa (TNFα) is an independent predictor of survival 500 days after TAVI. METHODS: Sixty patients undergoing TAVI were enrolled in the study. TNFα was determined. The CT measured low-density muscle fraction (LDM%) of the psoas muscle was determined. Operative risk assessment by Logistic EuroSCORE, EuroSCORE II, and STS score was performed. Frailty scores (FRAIL scale and Barthel index) were determined. RESULTS: Mean age was 81.01 ± 7.54 years. Twenty-six (43.3%) of the patients were males. In the univariable analyses, FRAIL scale and Barthel index were no predictors of survival after TAVI. In the multivariable analysis, including EuroSCORE II, LDM% and TNFα serum concentration, TNFα serum level was an independent predictor of survival 500 days after TAVI (HR: 3.167; 95%: 1.279-7.842; p = 0.013). The multivariable analysis, including TNFα as a categorical variable, showed that compared to patients in the conjugated first and second TNFα serum level tertile, patients in the third tertile had a hazard ratio (HR) of 10.606 (95%CI: 1.203 - 93.467) (p = 0.033). CONCLUSION: TNFα is an incremental independent predictor of long-term survival after TAVI.

Computed tomography measured epicardial adipose tissue and psoas muscle attenuation: new biomarkers to predict major adverse cardiac events and mortality in patients with heart disease and critically ill patients. Part II: Psoas muscle area and density.

Sarcopenia is a syndrome characterised by loss of skeletal muscle mass, loss of muscle quality, and reduced muscle strength, resulting in low performance. Sarcopenia has been associated with increased mortality and complications after medical interventions. In daily clinical practice, sarcopenia is assessed by clinical assessment of muscle strength and performance tests and muscle mass quantification by dual-energy X-ray absorptio-metry (DXA) or bioelectrical impedance analysis (BIA). Assessment of the skeletal muscle quantity and quality obtained by abdominal computed tomography (CT) has gained interest in the medical community, as abdominal CT is performed for various medical reasons, and quantification of the psoas and skeletal muscle can be performed without additional radiation load and dye administration. The definitions of CT-derived skeletal muscle mass quantification are briefly reviewed: psoas muscle area (PMA), skeletal muscle area (SMA), and transverse psoas muscle thickness (TPMT). We explain how CT attenuation coefficient filters are used to determine PMA and SMA, resulting in the psoas muscle index (PMI) and skeletal muscle index (SMI), respectively, after indexation to body habitus. Psoas muscle density (PMD), a biomarker for skeletal muscle quality, can be assessed by measuring the psoas muscle CT attenuation coefficient, expressed in Hounsfield units. The concept of low-density muscle (LDM) is explained. Finally, we review the medical literature on PMI and PMD as predictors of adverse outcomes in patients undergoing trauma or elective major surgery, transplantation, and in patients with cardiovascular and internal disease. PMI and PMD are promising new biomarkers predicting adverse outcomes after medical interventions.

Clinical value of CT-derived simulations of transcatheter-aortic-valve-implantation in challenging anatomies the PRECISE-TAVI trial.

BACKGROUND: Preprocedural computed tomography planning improves procedural safety and efficacy of transcatheter aortic valve implantation (TAVI). However, contemporary imaging modalities do not account for device-host interactions. AIMS: This study evaluates the value of preprocedural computer simulation with FEops HEARTguideTM on overall device success in patients with challenging anatomies undergoing TAVI with a contemporary self-expanding supra-annular transcatheter heart valve. METHODS: This prospective multicenter observational study included patients with a challenging anatomy defined as bicuspid aortic valve, small annulus or severely calcified aortic valve. We compared the heart team's transcatheter heart valve (THV) planning decision based on (1) conventional multislice computed tomography (MSCT) and (2) MSCT imaging with FEops HEARTguideTM simulations. Clinical outcomes and THV performance were followed up to 30 days. RESULTS: A total of 77 patients were included (median age 79.9 years (IQR 74.2-83.8), 42% male). In 35% of the patients, preprocedural planning changed after FEops HEARTguideTM simulations (change in valve size selection [12%] or target implantation height [23%]). A new permanent pacemaker implantation (PPI) was implanted in 13% and >trace paravalvular leakage (PVL) occurred in 28.5%. The contact pressure index (i.e., simulation output indicating the risk of conduction abnormalities) was significantly higher in patients with a new PPI, compared to those without (16.0% [25th-75th percentile 12.0-21.0] vs. 3.5% [25th-75th percentile 0-11.3], p < 0.01) The predicted PVL was 5.7 mL/s (25th-75th percentile 1.3-11.1) in patients with none-trace PVL, 12.7 (25th-75th percentile 5.5-19.1) in mild PVL and 17.7 (25th-75th percentile 3.6-19.4) in moderate PVL (p = 0.04). CONCLUSION: FEops HEARTguideTM simulations may provide enhanced insights in the risk for PVL or PPI after TAVI with a self-expanding supra-annular THV in complex anatomies.

Computed tomography measured epicardial adipose tissue and psoas muscle attenuation: new biomarkers to predict major adverse cardiac events (MACE) and mortality in patients with heart disease and critically ill patients. Part I: Epicardial adipose tissue.

Over the last two decades, the potential role of epicardial adipocyte tissue (EAT) as a marker for major adverse cardiovascular events has been extensively studied. Unlike other visceral adipocyte tissues (VAT), EAT is not separated from the adjacent myocardium by a fascial layer and shares the same microcirculation with the myocardium. Adipocytokines, secreted by EAT, interact directly with the myocardium through paracrine and vasocrine pathways. The role of the Randle cycle, linking VAT accumulation to insulin resistance, and the relevance of blood flow and mitochondrial function of VAT, are briefly discussed. The three available imaging modalities for the assessment of EAT are discussed. The advantages of echocardiography, cardiac CT, and cardiac magnetic resonance (CMR) are compared. The last section summarises the current stage of knowledge on EAT as a clinical marker for major adverse cardiovascular events (MACE). The association between EAT volume and coronary artery disease (CAD) has robustly been validated. There is growing evidence that EAT volume is associated with computed tomography coronary angiography (CTCA) assessed high-risk plaque features. The EAT CT attenuation coefficient predicts coronary events. Many studies have established EAT volume as a predictor of atrial fibrillation after cardiac surgery. Moreover, EAT thickness has been independently associated with severe aortic stenosis and mitral annular calcification. Studies have demonstrated that EAT volume is associated with heart failure. Finally, we discuss the potential role of EAT in critically ill patients admitted to the intensive care unit. In conclusion, EAT seems to be a promising new biomarker to predict MACE.

Atorvastatin downregulates plasma procarboxypeptidase U concentrations and improves fibrinolytic potential dose-dependently in hyperlipidemic individuals.

BACKGROUND: Statins efficiently lower cholesterol and also exert pleiotropic effects that extend beyond lipid lowering. In a recent pilot study, valuable information on the carboxypeptidase U (CPU) system in hyperlipidemia and the effect of statin therapy was collected. It was shown that proCPU levels are increased in hyperlipidemic patients. Statins significantly decreased proCPU levels and improved plasma fibrinolysis. Furthermore, it was suggested that patients with high baseline proCPU levels are most likely to benefit from statin therapy. OBJECTIVES: We aimed to further substantiate the effect of hyperlipidemia and statin therapy on CPU-related parameters in a larger cohort of hyperlipidemic and statin-treated individuals. METHODS: Blood was collected from 141 individuals treated with different dosages of atorvastatin (10-80 mg), 38 normolipidemic, and 37 hyperlipidemic controls. Lipid parameters and markers of fibrinolysis (proCPU and clot lysis time) were determined and compared between the groups. RESULTS: Pilot study results of high proCPU concentrations in hyperlipidemic patients and the proCPU-reducing effect of atorvastatin were confirmed. Accordingly, an improvement in plasma fibrinolytic potential was seen under the influence of atorvastatin. High interindividual variation in proCPU concentrations was observed in the hyperlipidemic cohort, with up to 80% higher proCPU levels compared with normolipidemic controls. Furthermore, proCPU concentration and the dosage of atorvastatin were inversely correlated. CONCLUSIONS: This study clearly shows that plasma proCPU concentrations and its expected effect on the fibrinolytic rate (as measured by clot lysis time) are increased in hyperlipidemic patients and that these effects can be normalized (and even further reduced compared with normolipidemic patients) by atorvastatin treatment.

Automated mitral valve assessment for transcatheter mitral valve replacement planning.

Transcatheter mitral valve replacement (TMVR) has emerged as a minimally invasive alternative for treating patients suffering from mitral valve disease. The number of TMVR procedures is expected to rise as devices currently in clinical trials obtain approval for commercialization. Automating the planning of such interventions becomes, therefore, more relevant in an attempt to decrease inter-subject discrepancies and time spent in patient assessment. This study evaluates the performance of an automated method for detection of anatomical landmarks and generation of relevant measurements for device selection and positioning. Cardiac CT scans of 70 patients were collected retrospectively. Fifty scans were used to generate a statistical shape model (SSM) of the left heart chambers at ten different timepoints, whereas the remaining 20 scans were used for validation of the automated method. The clinical measurements resulting from the anatomical landmarks generated automatically were compared against the measurements obtained through the manual indication of the corresponding landmarks by three observers, during systole and diastole. The automatically generated measurements were in close agreement with the user-driven analysis, with intraclass correlation coefficients (ICC) consistently lower for the saddle-shaped (ICCArea = 0.90, ICCPerimeter 2D = 0.95, ICCPerimeter 3D = 0.93, ICCAP-Diameter = 0.71, ICCML-Diameter = 0.90) compared to the D-shaped annulus (ICCArea = 0.94, ICCPerimeter 2D = 0.96, ICCPerimeter 3D = 0.96, ICCAP-Diameter = 0.95, ICCML-Diameter = 0.92). The larger differences observed for the saddle shape suggest that the main discrepancies occur in the aorto-mitral curtain. This is supported by the fact that statistically significant differences are observed between the two annulus configurations for area (p < 0.001), 3D perimeter (p = 0.009) and AP diameter (p < 0.001), whereas errors for 2D perimeter and ML diameter remained almost constant. The mitral valve center deviated in average 2.5 mm from the user-driven position, a value comparable to the inter-observer variability. The present study suggests that accurate mitral valve assessment can be achieved with a fully automated method, what could result in more consistent and shorter pre-interventional planning of TMVR procedures.

Adiponectin serum level is an independent and incremental predictor of all-cause mortality after transcatheter aortic valve replacement.

BACKGROUND: Quantifiable biomarkers may be useful for a better risk and frailty assessment of patients referred for transcatheter aortic valve implantation (TAVI). HYPOTHESIS: To determine if adiponectin serum concentration predicts all-cause mortality in patients undergoing TAVI. METHODS: 77 consecutive patients, undergoing TAVI, were analyzed. The CT axial slices at the level of the fourth lumbar vertebra were used to measure the psoas muscle area, and its low-density muscle fraction (LDM (%)). To assess the operative risk, the STS (Society of Thoracic Surgeons Predicted Risk of Mortality) score, Log. Euroscore, and Euroscore II were determined. A clinical frailty assessment was performed. ELISA kits were used to measure adiponectin serum levels. We searched for a correlation between serum adiponectin concentration and all-cause mortality after TAVI. RESULTS: The mean age was 80.8 ± 7.4 years. All-cause mortality occurred in 22 patients. The mean follow-up was 1779 days (range: 1572-1825 days). Compared with patients with the lowest adiponectin level, patients in the third tertile had a hazards ratio of all-cause mortality after TAVI of 4.155 (95% CI: 1.364-12.655) (p = .004). In the multivariable model, including STS score, vascular access of TAVI procedure, LDM (%), and adiponectin serum concentration, serum adiponectin level, and LDM(%) were independent predictors of all-cause mortality after TAVI (p = .178, .303, .042, and .017, respectively). Adiponectin level was a predictor of all-cause mortality in females and males (p = .012 and 0.024, respectively). CONCLUSION: Adiponectin serum level is an independent and incremental predictor of all-cause mortality in patients undergoing TAVI.

Final 3-year clinical outcomes following transcatheter aortic valve implantation with a supra-annular self-expanding repositionable valve in a real-world setting: Results from the multicenter FORWARD study.

OBJECTIVES: The Evolut R FORWARD study confirmed safety and effectivenesss of the Evolut R THV in routine clinical practice out to 1 year. Herein, we report the final 3-year clinical follow up of the FORWARD study. BACKGROUND: Transcatheter aortic valve replacement (TAVR) is a proven alternative to surgery in elderly patients with symptomatic severe aortic stenosis. Long-term clinical outcome data with the Evolut R platform are scarce. METHODS: FORWARD is a prospective multicenter observational study that evaluated the Evolut R system in routine clinical practice at 53 centres. Eligible patients had symptomatic native aortic valve stenosis or failed surgical aortic bioprosthesis and elevated operative risk per Heart-Team assessment. TAVR was attempted in 1039 patients. RESULTS: Mean age was 81.8 ± 6.2 years, 64.9% were women, STS score was 5.5 ± 4.5% and 34.2% were frail. Rates of all-cause mortality and disabling stroke were 24.8% and 4.8% at 3 years. Early need for a new pacemaker implantation after TAVR (all-cause mortality: with new PPI; 21.0% vs. without; 22.8%, p = 0.55) and the presence of > trace paravalvular regurgitation (all-cause mortality: no or trace; 22.0% vs. ≥ mild; 25.5%, p = 0.29) did not affect survival. Between 1 and 3 years incidence rates of valve related intervention, endocarditis and clinically relevant valve thrombosis were low. CONCLUSIONS: The Evolut R valve maintained a favorable safety profile through 3 years in routine clinical practice. Rates of transcatheter heart valve-related adverse events were low.

Computed tomography measured psoas muscle attenuation predicts mortality after transcatheter aortic valve implantation.

AIMS: The aim of this study was to determine if computed tomography (CT) psoas muscular attenuation measurements may predict all-cause mortality in patients undergoing TAVI. METHODS: Ninety-four consecutive patients undergoing TAVI were analysed. The CT axial slice at the level of the fourth lumbar vertebra was selected. The psoas muscle areas were manually contoured. The circumferential surface area (CSA) of both psoas muscles was determined by selecting the voxels with attenuation values, ranging from 0 to 100 Hounsfield Units (HU). The mean CT attenuation coefficient of the psoas muscle (Psoas mean HU) was measured. The muscle was subdivided into a low-density muscle (LDM) (0-29 HU) and high-density muscle (HDM) (30-100 HU) portion. The HDM/LDM ratio was calculated. We searched for a correlation between HDM/LDM, CSA LDM (%), Psoas mean HU and all-cause mortality. RESULTS: The mean age was 81.2 ±â€Š7.5 years. Thirty patients had adverse outcome (all-cause mortality). Compared with patients with the lowest CSA LDM (%), patients in the third and second tertiles had an increased hazard ratio for mortality (2.871; 95% confidence interval 0.880-9.371 and 5.044; 95% confidence interval 1.641-15.795, respectively) in a multivariable model with EuroSCORE II, Barthel frailty index and CSA LDM (%) (P = 0.231, 0.097 and 0.019, respectively). HDM/LDM and Psoas mean HU (as continuous variable) were also independent predictors of all-cause mortality (P = 0.019, P = 0.013, respectively). CONCLUSION: CSA LDM (%), Psoas mean HU and HDM/LDM are independent and incremental predictors of all-cause mortality in patients undergoing TAVI.

Effect of Statin Therapy on the Carboxypeptidase U (CPU, TAFIa, CPB2) System in Patients With Hyperlipidemia: A Proof-of-concept Observational Study.

PURPOSE: Statins are commonly used in patients with hypercholesterolemia to lower their cholesterol levels and to reduce their cardiovascular risk. There is also considerable evidence that statins possess a range of cholesterol-independent effects, including profibrinolytic properties. This pilot study aimed to explore the influence of statins on procarboxypeptidase U (proCPU) biology and to search for possible effects and associations that can be followed up in a larger study. METHODS: Blood was collected from 16 patients with hyperlipidemia, before and after 3 months of statin therapy (simvastatin 20 mg or atorvastatin 20 mg). Fifteen age-matched normolipemic persons served as control subjects. Lipid parameters and markers of inflammation and fibrinolysis (proCPU levels and clot lysis times) were determined in all samples. FINDINGS: Mean (SD) proCPU levels were significantly higher in patients with hypercholesterolemia compared to control subjects (1186 [189] U/L vs 1061 [60] U/L). Treatment of these patients with a statin led to a significant average decrease of 11.6% in proCPU levels and brought the proCPU concentrations to the same level as in the control subjects. On a functional level, enhancement in plasma fibrinolytic potential was observed in the statin group, with the largest improvement in fibrinolysis seen in patients with the highest baseline proCPU levels and largest proCPU decrease upon statin treatment. IMPLICATIONS: Increased proCPU levels are present in patients with hyperlipidemia. Statin treatment significantly decreased proCPU levels and improved plasma fibrinolysis in these patients. Moreover, our study indicates that patients with high baseline proCPU levels are most likely to benefit from statin therapy. The latter should be examined further in a large cohort.

Towards patient-specific prediction of conduction abnormalities induced by transcatheter aortic valve implantation: a combined mechanistic modelling and machine learning approach.

Aims: Post-procedure conduction abnormalities (CA) remain a common complication of transcatheter aortic valve implantation (TAVI), highlighting the need for personalized prediction models. We used machine learning (ML), integrating statistical and mechanistic modelling to provide a patient-specific estimation of the probability of developing CA after TAVI. Methods and results: The cohort consisted of 151 patients with normal conduction and no pacemaker at baseline who underwent TAVI in nine European centres. Devices included CoreValve, Evolut R, Evolut PRO, and Lotus. Preoperative multi-slice computed tomography was performed. Virtual valve implantation with patient-specific computer modelling and simulation (CM&S) allowed calculation of valve-induced contact pressure on the anatomy. The primary composite outcome was new onset left or right bundle branch block or permanent pacemaker implantation (PPI) before discharge. A supervised ML approach was applied with eight models predicting CA based on anatomical, procedural and mechanistic data. CA occurred in 59% of patients (n = 89), more often after mechanical than first or second generation self-expanding valves (68% vs. 60% vs. 41%). CM&S revealed significantly higher contact pressure and contact pressure index in patients with CA. The best model achieved 83% accuracy (area under the curve 0.84) and sensitivity, specificity, positive predictive value, negative predictive value, and F1-score of 100%, 62%, 76%, 100%, and 82%. Conclusion: ML, integrating statistical and mechanistic modelling, achieved an accurate prediction of CA after TAVI. This study demonstrates the potential of a synergetic approach for personalizing procedure planning, allowing selection of the optimal device and implantation strategy, avoiding new CA and/or PPI.

Patient-Specific Computer Simulation in TAVR With the Self-Expanding Evolut R Valve.

OBJECTIVES: The aim of this study was to assess the added value and predictive power of the TAVIguide (Added Value of Patient-Specific Computer Simulation in Transcatheter Aortic Valve Implantation) software in clinical practice. BACKGROUND: Optimal outcome after transcatheter aortic valve replacement (TAVR) may become more important as TAVR shifts toward low-risk patients. Patient-specific computer simulation is able to provide prediction of outcome after TAVR. Its clinical role and validation of accuracy, however, have not yet been studied prospectively. METHODS: A prospective, observational, multicenter study was conducted among 80 patients with severe aortic stenosis treated with the Evolut R valve. Simulation was performed in 42 patients and no simulation in 38. A comparison between the valve size (decision 1) and target depth of implantation selected by the operator on the basis of multislice computed tomography and the valve size (decision 2) and target depth of implantation selected after simulation were the primary endpoints. Predictive power was examined by comparing the simulated and observed degree of aortic regurgitation. RESULTS: Decision 2 differed from decision 1 in 1 of 42 patients because of predicted paravalvular leakage, and changes in valve type occurred in 2 of 42. In 39 of 42 patients, decisions 1 and 2 were similar. Target depth of implantation differed in 7 of 42 patients after simulation (lower in 4 and higher in 3). In 16 of 42 patients, simulation affected the TAVR procedure; in 9, the operator avoided additional measures to achieve the target depth of implantation, and in 7 patients, additional measures were performed. There was a trend toward a higher degree of predicted than observed aortic regurgitation (17.5 vs. 12 ml/s; p = 0.13). CONCLUSIONS: Patient-specific computer simulation did not affect valve size selection but did affect the selection of the target depth of implantation and the execution of TAVR to achieve the desired target depth of implantation.

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

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

Uncertainties and challenges in surgical and transcatheter tricuspid valve therapy: a state-of-the-art expert review.

Tricuspid regurgitation (TR) is a frequent and complex problem, commonly combined with left-sided heart disease, such as mitral regurgitation. Significant TR is associated with increased mortality if left untreated or recurrent after therapy. Tricuspid regurgitation was historically often disregarded and remained undertreated. Surgery is currently the only Class I Guideline recommended therapy for TR, in the form of annuloplasty, leaflet repair, or valve replacement. As growing experience of transcatheter therapy in structural heart disease, many dedicated transcatheter tricuspid repair or replacement devices, which mimic well-established surgical techniques, are currently under development. Nevertheless, many aspects of TR are little understood, including the disease process, surgical or interventional risk stratification, and predictors of successful therapy. The optimal treatment timing and the choice of proper surgical or interventional technique for significant TR remain to be elucidated. In this context, we aim to highlight the current evidence, underline major controversial issues in this field and present a future roadmap for TR therapy.

Differences in clinical valve size selection and valve size selection for patient-specific computer simulation in transcatheter aortic valve replacement (TAVR): a retrospective multicenter analysis.

Valve size selection for transcatheter aortic valve replacement (TAVR) is currently based on cardiac CT-scan. At variance with patient-specific computer simulation, this does not allow the assessment of the valve-host interaction. We aimed to compare clinical valve size selection and valve size selection by an independent expert for computer simulation. A multicenter retrospective analysis of valve size selection by the physician and the independent expert in 141 patients who underwent TAVR with the self-expanding CoreValve or Evolut R. Baseline CT-scan was used for clinical valve size selection and for patient-specific computer simulation. Simulation results were not available for clinical use. Overall true concordance between clinical and simulated valve size selection was observed in 47 patients (33%), true discordance in 15 (11%) and ambiguity in 79 (56%). In 62 (44%, cohort A) one valve size was simulated whereas two valve sizes were simulated in 79 (56%, cohort B). In cohort A, concordance was 76% and discordance was 24%; a smaller valve size was selected for simulation in 10 patients and a larger in 5. In cohort B, a different valve size was selected for simulation in all patients in addition to the valve size that was used for TAVR. The different valve size concerned a smaller valve in 45 patients (57%) and a larger in 34 (43%). Selection of the valve size differs between the physician and the independent computer simulation expert who used the same source of information. These findings indicate that valve sizing in TAVR is still more intricate than generally assumed.

Enabling Automated Device Size Selection for Transcatheter Aortic Valve Implantation.

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

Aortic root sizing for transcatheter aortic valve implantation using a shape model parameterisation.

During a transcatheter aortic valve implantation, an axisymmetric implant is placed in an irregularly shaped aortic root. Implanting an incorrect size can cause complications such as leakage of blood alongside or through the implant. The aim of this study was to construct a method that determines the optimal size of the implant based on the three-dimensional shape of the aortic root. Based on the pre-interventional computed tomography scan of 89 patients, a statistical shape model of their aortic root was constructed. The weights associated with the principal components and the volume of calcification in the aortic valve were used as parameters in a classification algorithm. The classification algorithm was trained using the patients with no or mild leakage after their intervention. Subsequently, the algorithms were applied to the patients with moderate to severe leakage. Cross validation showed that a random forest classifier assigned the same size in 65 ± 7% of the training cases, while 57 ± 8% of the patients with moderate to severe leakage were assigned a different size. This initial study showed that this semi-automatic method has the potential to correctly assign an implant size. Further research is required to assess whether the different size implants would improve the outcome of those patients.

Transcatheter Aortic Valve Replacement in Oncology Patients With Severe Aortic Stenosis.

OBJECTIVES: The authors sought to collect data on contemporary practice and outcome of transcatheter aortic valve replacement (TAVR) in oncology patients with severe aortic stenosis (AS). BACKGROUND: Oncology patients with severe AS are often denied valve replacement. TAVR may be an emerging treatment option. METHODS: A worldwide registry was designed to collect data on patients who undergo TAVR while having active malignancy. Data from 222 cancer patients from 18 TAVR centers were compared versus 2,522 "no-cancer" patients from 5 participating centers. Propensity-score matching was performed to further adjust for bias. RESULTS: Cancer patients' age was 78.8 ± 7.5 years, STS score 4.9 ± 3.4%, 62% men. Most frequent cancers were gastrointestinal (22%), prostate (16%), breast (15%), hematologic (15%), and lung (11%). At the time of TAVR, 40% had stage 4 cancer. Periprocedural complications were comparable between the groups. Although 30-day mortality was similar, 1-year mortality was higher in cancer patients (15% vs. 9%; p < 0.001); one-half of the deaths were due to neoplasm. Among patients who survived 1 year after the TAVR, one-third were in remission/cured from cancer. Progressive malignancy (stage III to IV) was a strong mortality predictor (hazard ratio: 2.37; 95% confidence interval: 1.74 to 3.23; p < 0.001), whereas stage I to II cancer was not associated with higher mortality compared with no-cancer patients. CONCLUSIONS: TAVR in cancer patients is associated with similar short-term but worse long-term prognosis compared with patients without cancer. Among this cohort, mortality is largely driven by cancer, and progressive malignancy is a strong mortality predictor. Importantly, 85% of the patients were alive at 1 year, one-third were in remission/cured from cancer. (Outcomes of Transcatheter Aortic Valve Implantation in Oncology Patients With Severe Aortic Stenosis [TOP-AS]; NCT03181997).

1-Year Outcomes With the Evolut R Self-Expanding Transcatheter Aortic Valve: From the International FORWARD Study.

OBJECTIVES: This study sought to report the 1-year safety and efficacy outcomes in the FORWARD (CoreValve Evolut R FORWARD) study following transcatheter aortic valve replacement (TAVR) with the next-generation Evolut R device (Medtronic, Minneapolis, Minnesota) in routine clinical practice. BACKGROUND: The FORWARD study reported low incidences of mortality, disabling stroke, and significant paravalvular leak following TAVR in routine clinical practice at 30 days. Longer-term results in large patient populations with the Evolut R self-expanding, repositionable transcatheter heart valve (THV) are lacking. METHODS: This was a prospective, single-arm, multinational, multicenter, observational study investigating efficacy and safety following TAVR with the next-generation self-expanding THV. Between January and December 2016, 1,040 patients underwent attempted implant of the Evolut R self-expanding repositionable valve at 53 sites worldwide. An independent Clinical Events Committee adjudicated safety endpoints based on Valve Academic Research Consortium-2 definitions. An independent echocardiographic core laboratory evaluated all echocardiograms. RESULTS: The mean age was 81.8 ± 6.2 years, 64.8% were women, and patients had a mean Society of Thoracic Surgeons Predicted Risk of Mortality score of 5.5 ± 4.5% and EuroSCORE II of 5.7 ± 5.0%. The 1-year all-cause mortality rate was 8.9%, with a cardiovascular mortality rate of 6.9%. At 1 year, the incidence of disabling stroke was 2.1%, and a pacemaker was implanted in 19.7% of patients. The incidence of more than mild paravalvular leak was 1.2%. CONCLUSIONS: The FORWARD study demonstrated good safety and efficacy profiles for the next-generation Evolut R THV up to 1-year follow-up, with very low mortality and adverse events. (CoreValve Evolut R FORWARD Study [FORWARD]; NCT02592369).