Assessment Of Aortic Stenosis Severity Research Articles

Aortic Valve Calcification Density Measured by MDCT in the Assessment of Aortic Stenosis Severity.

Aortic valve calcification (AVC) indexation to the aortic annulus (AA) area measured by Doppler echocardiography (AVCdEcho) provides powerful prognostic information in patients with aortic stenosis (AS). However, the indexation by AA measured by multidetector computed tomography (AVCdCT) has never been evaluated. The aim of this study was to compare AVC, AVCdCT, and AVCdEcho with regard to hemodynamic correlations and clinical outcomes in patients with AS. Data from 889 patients, mainly White, with calcific AS who underwent Doppler echocardiography and multidetector computed tomography within the same episode of care were retrospectively analyzed. AA was measured both by Doppler echocardiography and multidetector computed tomography. AVCdCT severity thresholds were established using receiver operating characteristic curve analyses in men and women separately. The primary end point was the occurrence of all-cause mortality. Correlations between gradient/velocity and AVCd were stronger (both P≤0.005) using AVCdCT (r=0.68, P<0.001 and r=0.66, P<0.001) than AVC (r=0.61, P<0.001 and r=0.60, P<0.001) or AVCdEcho (r=0.61, P<0.001 and r=0.59, P<0.001). AVCdCT thresholds for the identification of severe AS were 334 Agatston units (AU)/cm2 for women and 467 AU/cm2 for men. On a median follow-up of 6.62 (6.19-9.69) years, AVCdCT ratio was superior to AVC ratio and AVCdEcho ratio to predict all-cause mortality in multivariate analyses (hazard ratio [HR], 1.59 [95% CI, 1.26-2.00]; P<0.001 versus HR, 1.53 [95% CI, 1.11-1.65]; P=0.003 versus HR, 1.27 [95% CI, 1.11-1.46]; P<0.001; all likelihood test P≤0.004). AVCdCT ratio was superior to AVC ratio and AVCdEcho ratio to predict survival under medical treatment in multivariate analyses (HR, 1.80 [95% CI, 1.27-1.58]; P<0.001 compared with HR, 1.55 [95% CI, 1.13-2.10]; P=0.007; HR, 1.28 [95% CI, 1.03-1.57]; P=0.01; all likelihood test P<0.03). AVCdCT ratio predicts mortality in all subgroups of patients with AS. AVCdCT appears to be equivalent or superior to AVC and AVCdEcho to assess AS severity and predict all-cause mortality. Thus, it should be used to evaluate AS severity in patients with nonconclusive echocardiographic evaluations with or without low-flow status. AVCdCT thresholds of 300 AU/cm2 for women and 500 AU/cm2 for men seem to be appropriate to identify severe AS. Further studies are needed to validate these thresholds, especially in diverse populations.

Transformer-Based Spatio-Temporal Analysis for Classification of Aortic Stenosis Severity From Echocardiography Cine Series.

Aortic stenosis (AS) is characterized by restricted motion and calcification of the aortic valve and is the deadliest valvular cardiac disease. Assessment of AS severity is typically done by expert cardiologists using Doppler measurements of valvular flow from echocardiography. However, this limits the assessment of AS to hospitals staffed with experts to provide comprehensive echocardiography service. As accurate Doppler acquisition requires significant clinical training, in this paper, we present a deep learning framework to determine the feasibility of AS detection and severity classification based only on two-dimensional echocardiographic data. We demonstrate that our proposed spatio-temporal architecture effectively and efficiently combines both anatomical features and motion of the aortic valve for AS severity classification. Our model can process cardiac echo cine series of varying length and can identify, without explicit supervision, the frames that are most informative towards the AS diagnosis. We present an empirical study on how the model learns phases of the heart cycle without any supervision and frame-level annotations. Our architecture outperforms state-of-the-art results on a private and a public dataset, achieving 95.2% and 91.5% in AS detection, and 78.1% and 83.8% in AS severity classification on the private and public datasets, respectively. Notably, due to the lack of a large public video dataset for AS, we made slight adjustments to our architecture for the public dataset. Furthermore, our method addresses common problems in training deep networks with clinical ultrasound data, such as a low signal-to-noise ratio and frequently uninformative frames. Our source code is available at: https://github.com/neda77aa/FTC.git.

Impact of Atrial Fibrillation on the Symptoms and Echocardiographic Evaluation of Patients With Aortic Stenosis

Atrial fibrillation (AF) is common in patients with aortic stenosis (AS) and complicates the assessment of AS severity. The overlapping of symptoms in these 2 conditions may postpone valve replacement. This study aimed to evaluate the effect of AF on the severity assessment of AS and its impact on symptoms and quality of life (QoL). Patients with severe AS were prospectively recruited. Echocardiography, symptom questionnaires, and RAND-36 QoL assessment were performed preoperatively and 3months postoperatively. The aortic valve calcium score (AVC) was measured using computed tomography. Of the 279 patients, 74 (26.5%) had AF. Patients with AF had lower mean gradients and 45.9% had a low-gradient phenotype, with a mean gradient <40mm Hg, compared with 22.4% of those without AF (p <0.001). The AVC measurements revealed severe valve calcification equally in patients with or without AF (85.7% vs 87.7%, p=0.78). Patients with AF were more symptomatic at baseline, with 50.0% versus 27.3% in New York Heart Association class III or higher (p <0.001), and after intervention. Patients with AF had more residual dyspnea (27.3% vs 12.0%, p=0.007) and exercise intolerance (36.4% vs 17.0%, p=0.002). The QoL improved significantly in both groups but was worse at baseline in patients with AF and remained impaired after intervention. In conclusion, low-gradient AS phenotype is overrepresented in patients with AF, but they have equally severe stenosis determined using AVC, despite the lower gradients. Patients with AF have more symptoms and worse QoL, but they improve significantly after intervention. In patients with AF, multimodality imaging is important in the assessment of AS severity.

In-vivo validation of a nomogram with isostiffness-lines for the assessment of aortic stenosis severity

Abstract Background In patients with low-flow, low-gradient aortic stenosis, the aortic valve opening area (AVA) projected at a higher standardized transvalvular flow (Q) is used to assess the severity of aortic stenosis. It assumes a linear relation between Q and AVA. We investigated whether a sigmoid function better captured this relation and whether a nomogram could be constructed. Methods We measured instantaneous AVA and Q in 142 patients with the whole spectrum of AS including very low-flow situation on one ejection cycle. We defined a linear and a sigmoid function containing hyperparameters as well as the relative stiffness. Using a k-fold cross validation algorithm, we first trained the hyperparameters of each function on the subgroup of patients with normal aortic valve. Using the obtained hyperparameters, we then fitted the relative stiffness for each of the patients with AS on the lowest 70%, 50%, 30% and 10% Q of the {Q:AVA} data points of the ejection cycle. We then assessed the accuracy of the two models by computing the mean squared error (MSE) of the predicted AVA vs the measured AVA on the remaining 30%, 50%, 70% and 90% data points and the Akaike Information Criterion (AIC). A receiver operating characteristic (ROC) analysis with computation of its area under the curve (AUC) was performed on the entire range of possible threshold of the relative stiffness to discriminate between severe from non severe aortic stenosis. Results The sigmoid consistently better predicted the remaining 70%, 50%, 30% and 10% AVA than the linear model (MSE: 6.62e-6 vs 14.11e-6, 4.90e-6 vs 12.39e-6, 4.90e-6 vs 14.84e-6, 4.90e-6 vs 22.99e-6; AIC: -7933 vs -7428, -13341 vs -12328, -13341 vs -16990, -13341 vs -21031, respectively). The first figure depicts the assessment of the AVA predicted with the linear (left panel) and sigmoid (right panel) model with Q of the 30% highest Q values with linear regression. The black line on the linear regression graphs represent the identity function (f (x) = x). The closer to this line are the points, the more accurate is the prediction. In the ROC analysis, the calculated AUC was 0.88, performed on all patients with relative stiffness obtained on the first 70% Q of the {Q;AVA} data points. The most discriminative relative stiffness threshold was 1.51 with a corresponding accuracy of 0.85. The second figure depicts a nomogram with mean and confidence interval of iso-stiffness lines for each severity with the following color code: group of normal aortic valve in green, group of mild aortic stenosis in blue, group of moderate aortic stenosis in orange and group of severe aortic stenosis in red. The iso-stiffness line with most discriminant relative stiffness computed on the group of patients with moderate and severe aortic stenosis is depicted in black. Conclusion This study allows to construct a nomogram to compare the stiffness of the aortic valve of any patient at any Q, simplifying the severity grading system of AS.Accuracy of AVA predictionNomogram with iso-stiffness lines

The Mortality Burden of Untreated Aortic Stenosis

BackgroundThe American College of Cardiology/American Heart Association guidelines recommend the assessment and grading of severity of aortic stenosis (AS) as mild, moderate, or severe, per echocardiogram, and recommend aortic valve replacement (AVR) when the AS is severe. ObjectivesThe authors sought to describe mortality rates across the entire spectrum of untreated AS from a contemporary, large, real-world database. MethodsWe analyzed a deidentified real-world data set including 1,669,536 echocardiographic reports (1,085,850 patients) from 24 U.S. hospitals (egnite Database, egnite). Patients >18 years of age were classified by diagnosed AS severity. Untreated mortality and treatment rates were examined with Kaplan-Meier (KM) estimates, with results compared using the log-rank test. Multivariate hazards analysis was performed to assess associations with all-cause mortality. ResultsAmong 595,120 patients with available AS severity assessment, the KM-estimated 4-year unadjusted, untreated, all-cause mortality associated with AS diagnosis of none, mild, mild-to-moderate, moderate, moderate-to-severe, or severe was 13.5% (95% CI: 13.3%-13.7%), 25.0% (95% CI: 23.8%-26.1%), 29.7% (95% CI: 26.8%-32.5%), 33.5% (95% CI: 31.0%-35.8%), 45.7% (95% CI: 37.4%-52.8%), and 44.9% (95% CI: 39.9%-49.6%), respectively. Results were similar when adjusted for informative censoring caused by treatment. KM-estimated 4-year observed treatment rates were 0.2% (95% CI: 0.2%-0.2%), 1.0% (95% CI: 0.7%-1.3%), 4.2% (95% CI: 2.0%-6.3%), 11.4% (95% CI: 9.5%-13.3%), 36.7% (95% CI: 31.8%-41.2%), and 60.7% (95% CI: 58.0%-63.3%), respectively. After adjustment, all degrees of AS severity were associated with increased mortality. ConclusionsPatients with AS have high mortality risk across all levels of untreated AS severity. Aortic valve replacement rates remain low for patients with severe AS, suggesting that more research is needed to understand barriers to diagnosis and appropriate approach and timing for aortic valve replacement.

Physician assessment of aortic stenosis severity, quantitative parameters, and long-term outcomes: Results from the KP-VALVE project

BackgroundContemporary outcomes for aortic stenosis (AS) and the association between physician-assessed AS severity and quantitative parameters is poorly understood. We aimed to evaluate AS natural history, compare outcomes for physicians’ AS assessment vs. quantitative parameters, and identify AS parameters with the most explanatory power. MethodsWe ascertained physician-assessed AS severity, echocardiographic parameters, and clinical data for 546,769 patients from 2008-2018, examined multivariable associations of physician-assessed AS severity and number of quantitative severe AS parameters with death, cardiovascular hospitalization, and aortic valve replacement, and estimated the relative contribution of different quantitative AS parameters on outcomes. ResultsAmong 49,604 AS patients (mean [SD] age 77 [11] years), 17.6% had moderate, 3.6% moderate-severe, and 9.4% severe AS. During median 3.7 [IQR 1.7-6.8] years, physician-assessed AS severity strongly correlated with outcomes, with moderate AS patients tracking closest to mild AS, and moderate-to-severe AS patients more comparable to severe AS. Although the number of quantitative severe AS parameters strongly predicted outcomes (adjusted HR [95% CI] for death 1.40 [1.34-1.46], 1.70 [1.56-1.85], and 1.78 [1.63-1.94] for 1, 2, and 3 parameters, respectively), aortic valve area <1.0 cm2 was the most frequent severe AS parameter, explained the largest relative contribution (67%), and was common in patients classified as moderate (21%) or moderate-severe (56%) AS. ConclusionsPhysician-assessed AS severity predicts outcomes, with cumulative effects for each severe AS parameter. Moderate AS includes a wide spectrum of patients, with discordant AVA <1.0 cm2 being both common and predictive. Better identification of non-classical severe AS phenotypes may improve outcomes.

Impact of Concomitant Mitral Regurgitation on the Hemodynamic Indicators of Aortic Stenosis.

Background In patients with aortic stenosis (AS), the presence of mitral regurgitation (MR) can lead to underestimation of AS severity and worse clinical outcomes. The objective of this study was to characterize the magnitude of the effects of concomitant MR on hemodynamic indicators of AS severity using clinical data and a computational cardiovascular simulation. Methods and Results Echocardiographic data from 1427 patients with severe AS were used to inform a computational cardiovascular system model, and varying degrees of MR and AS were simulated. Hemodynamic data, including left ventricular and aortic pressure waveforms, were generated for all simulations. Simulated reduction in mean transaortic pressure gradient (MPG) associated with MR was then used to calculate the adjusted MPG in the clinical cohort. MR was present in 861 (60%) patients. Compared with patients without MR, patients with MR had a lower aortic-valve area (0.83±0.2 cm2 versus 0.75±0.2; P<0.001) and were more likely to have a low-gradient pattern (MPG <40 mm Hg) (45% versus 54%; P<0.001). Simulations showed that the presence of concomitant mild, moderate, and severe MR with AS was accompanied by a mean reduction in MPG of 10%, 29%, and 40%, respectively. For patients with MR, their calculated adjusted MPG was on average 24% higher than their MPG (52±22 versus 42±16 mm Hg). Of the 467 patients with low-gradient AS and MR, 240 (51%) would reclassify as high gradient based on their adjusted MPG. Conclusions Concomitant MR results in lower MPG and reduced forward flow compared with isolated AS. Careful quantitation of MR should be factored into the assessment of AS severity to mitigate for potential underestimation.

Evidence for a sigmoidal flow-to-valve opening relation in low-flow low-gradient aortic stenosis.

We analyzed the relationship between flow (Q) and aortic valve opening area (AVA) using a sequence of echocardiographic stress tests of increasing strength. Low-dose dobutamine stress echocardiography (DSE) has been used to differentiate pseudo-severe from true severe aortic stenoses. Because the Q-response to DSE is so variable between individuals, AVA has been projected to a standardized flow (AVAproj) using linear interpolation. A linear Q-to-AVA relation implies that AVA shows an unconstrained increase. We applied three stress maneuvers of increasing strength to investigate whether AVA shows signs of saturation. We performed an echocardiographic examination at rest, during the passive leg raise maneuver ("PLR"), maximal dobutamine infusion ("Dmax"), and their combination ("Dmax + PLR") in 45 patients with severe low-flow, low-gradient aortic stenosis. We analyzed the effect of the stress maneuver on Q, AVA, valve compliance (VC), and AVAproj. We also compared the proportion of patients with nonconclusive test (ΔQ < 20%) between stress maneuvers. We computed the Akaike information criterion (AIC) to compare a linear with a saturating function for the Q-AVA relation. Q gradually increased from "PLR" to "Dmax" to "Dmax + PLR" (P < 0.0001), whereas the number of nonconclusive tests concomitantly diminished from n = 35 to n = 3. The stress sequence increased AVA (P < 0.001) but decreased AVAproj (P = 0.006) and VC (P = 0.005). In the pooled Q-AVA data, the AIC value was lower for the saturating (sigmoidal) model compared with the linear model fitting (-1,593 vs. -1,504). "Dmax + PLR" is capable of reducing the number of nonconclusive DSE tests. With increasing stress strength, the Q-AVA relation progressively flattens, indicating saturation.NEW & NOTEWORTHY The relation between transaortic flow (Q) and aortic valve opening area (AVA) shows a saturation when three different stress maneuvers are used to increase Q as much as possible. This has implications for the assessment of aortic stenosis severity.

Current and novel echocardiographic assessment of left ventricular systolic function in aortic stenosis-A comprehensive review.

Aortic stenosis (AS) is a complex and progressive condition that can significantly reduce the quality of life and increase the incidence of premature mortality. Transthoracic echocardiography (TTE) is the gold standard imaging modality for the assessment of AS severity. While left ventricular ejection fraction (LVEF) derived from TTE is a very well-understood parameter, limitations such as high inter and intra-observer variability, insensitivity to sub-clinical dysfunction, and influence of loading conditions make LVEF a complicated and unreliable parameter. Myocardial deformation imaging has been identified as a promising parameter for identifying subclinical left ventricular dysfunction, however, this parameter is still afterload dependent. Myocardial Work is a promising novel assessment technique that accounts for afterload by combining the use of myocardial deformation imaging and non-invasive blood pressure to provide a more comprehensive assessment of mechanics beyond LVEF. This review evaluates the evidence for various echocardiographic assessment parameters used to quantify left ventricular function including myocardial work in patients with AS.

Abstract 10206: Misleading Transvalvular Hemodynamics for Patients With Moderate Aortic Stenosis

Introduction: Aortic stenosis (AS) is a progressive disease that leads to cardiac remodeling. Appropriate management depends on accurate assessment of AS severity. Transvalvular gradients are central to echocardiographic assessment of AS though can be impacted by any conditions that decrease transvalvular flow. Hypothesis: 1) Decline in peak transvalvular gradient over time is associated with more significant cardiac remodeling and 2) Cardiac damage is associated with lower transvalvular flow and masks progression of AS. Methods: Retrospective single center study of patients with moderate AS (defined as peak gradient 25-40mmHg) from 2013-2020 with &gt; 1 transthoracic echocardiogram (TTE). Each TTE was classified into established stages of cardiac damage: no damage (Stage 0), left ventricular damage (Stage 1), left atrial or mitral valve damage (Stage 2), pulmonary vasculature or tricuspid valve damage (Stage 3), or right ventricular damage or subclinical heart failure (Stage 4). Results: Sixty patients with at least 1 follow-up TTE were included. The mean age was 73.5 +/- 11 years with 47% women (28/60) and median time of 381 days (IQR 12.7 months) between echocardiograms. On initial assessment, mean AVA and peak AV gradient were 1.2cm 2 +/- 0.33 and 37mmHg +/- 11.3 respectively. At follow-up, the mean AVA and peak AV gradient were 1.1cm 2 +/- 0.20 and 38mmHg +/- 12.6. Forty-three of 60 patients (72%) had evidence of cardiac damage on initial assessment compared to 55 of 60 patients (92%) on follow-up. Thirty-five (58%) patients displayed a decrease in peak AV gradient over time (average decrease -16% +/- 0.12). Twenty-one of the patients with declining peak gradients (60%) demonstrated progressive cardiac damage compared to 9 of 25 patients (36%) with increasing peak gradients (p= 0.06). Conclusions: Over half of patients with moderate AS demonstrated a decrease in peak AV gradient over time. Reliance on transvalvular gradients as a reflector of AS severity can be misleading as there was a trend toward more significant cardiac damage in this subset of patients. The presence of underlying cardiac damage can obscure traditional echocardiographic assessment and progression of AS and should be incorporated into assessments of disease severity and progression.

Sigmoid isostiffness-lines: An in-vitro model for the assessment of aortic stenosis severity.

IntroductionThe aortic valve opening area (AVA), used to quantify aortic stenosis severity, depends on the transvalvular flow rate (Q). The currently accepted clinical echocardiographic method assumes a linear relation between AVA and Q. We studied whether a sigmoid model better describes this relation and determined “isostiffness-lines” across a wide flow spectrum, thus allowing building a nomogram for the non-invasive estimation of valve stiffness.MethodsBoth AVA and instantaneous Q (Qinst) were measured at 10 different mean cardiac outputs of porcine aortic valves mounted in a pulsatile flow loop. The valves' cusps were chemically stiffened to obtain three stiffness grades and the procedure was repeated for each grade. The relative stiffness was defined as the ratio between LV work at grade with the added stiffness and at native stiffness grade. corresponding to the selected of the highest 3 and 5 cardiac output values was predicted in K-fold cross-validation using sequentially a linear and a sigmoid model. The accuracy of each model was assessed with the Akaike information criterion (AIC).ResultsThe sigmoid model predicted more accurately (AIC for prediction of AVA with of the 3 highest cardiac output values: –1,743 vs. –1,048; 5 highest cardiac output values: –1,471 vs. –878) than the linear model.ConclusionThis study suggests that the relation between AVA and Q can be better described by a sigmoid than a linear model. This construction of “isostiffness-lines” may be a useful method for the assessment of aortic stenosis in clinical echocardiography.

Significance and distribution of aortic valve calcium score before TAVI

Abstract Introduction Aortic valve calcium scoring by multislice computed tomography (MSCT) is an alternative load independent assessment of aortic stenosis severity. Recent studies have further demonstrated that aortic valve calcification load is related to adverse outcomes during and after transcatheter aortic valve implantation (TAVI), however reference values in this population are uncertain. This study aimed to assess aortic valve calcium in P referred for TAVI. Methods Retrospective analysis of consecutive patients (P) submitted to TAVI between 2014 and 2020 in a tertiary care centre. Clinical and echocardiographic characteristics, along with MSCT-derived aortic valve calcium score were collected. Results A total of 467 P were included, 57% female, median age 83 (9) years (minimum 45 and maximum 95 years-old). The prevalence of hypertension, dyslipidemia and diabetes was 83%, 69% and 36%, respectively. Chronic renal failure was present in 51%, atrial fibrillation in 34% and peripheral artery disease in 14%. Considering the 346 P with aortic valve calcification quantified by MSCT, median calcium score was 2161 (1761) AU. Age did not correlate with valvular calcification (r=0.043, p=0.422). Male gender showed significantly higher calcium score (2800 (2093) vs 1850 (1584), p&amp;lt;0.001) (Figs. 1 and 2). 11P had bicuspid aortic valve disease, with this population being younger (75 (16) vs 83 (8) years, p=0.001), nonetheless displaying higher aortic valve calcium load (2800 (2599) vs 2112 (1788), p=0.025). A weak but statistically significant correlation between calcium score and maximum (r=0.366, p&amp;lt;0.001) and mean gradients (r=0.387, p&amp;lt;0.001) and aortic valve area (r=−0.120, p=0.047) was demonstrated. Valvular calcification was not significantly different in P with reduced ejection fraction (&amp;lt;50%) (p=0.388). Conclusion There are significant differences in aortic valve calcium score between men and women referred for TAVI. Higher maximum and mean gradients were associated with increasing valvular calcification. Age and left ventricle ejection fraction were not related. P with bicuspid aortic valve have distinct calcification characteristics. As calcification burden may influence preprocedural planning, this parameter should be incorporated in the general work-up and reference values in this population should be known. Funding Acknowledgement Type of funding sources: None.

Value of Left Ventricular Indexed Ejection Time to Characterize the Severity of Aortic Stenosis.

Aims: The assessment of aortic stenosis (AS) severity is still challenging, especially in abnormal hemodynamic conditions. Left ventricular ejection time (LVET) has been historically related to AS severity, but it also depends on heart rate (HR) and systolic function. Our aim was to verify if correcting LVET (LVET index, LVETI) by its determinants is helpful for the assessment of AS severity, irrespective of hemodynamic conditions. Methods and results: We retrospectively studied 152 patients with AS and 378 patients with heart failure and no-AS. At multivariate analysis, LVET (assessed with pulsed-wave Doppler) showed a strong correlation with stroke volume index (SVI) (Beta 0.354; p < 0.001), HR (−0.385; p < 0.001), AS grade (Beta 0.301; p < 0.001) and, less significantly, ejection fraction (LVEF) (Beta 0.108; p = 0.001). AS grade was confirmed to be a major determinant of LVET, irrespective of forward flow (assessed by SVI and transvalvular flow rate) and LVEF (above and below 50%). A regression equation was derived to index LVET (LVETI) to HR and SVI. By using this formula, LVETI detected severe AS more accurately (AUC 0.812, p < 0.001) than LVET alone (AUC 0.755, p for difference = 0.005). Similar results were observed in patients with abnormal flow status. As an exploratory finding, we observed that the highest tertile of LVETI was associated with a higher rate of aortic valve interventions during follow-up. Conclusions: LVETI correlates with AS severity better than uncorrected LVET, independently from hemodynamic conditions, and may help to discriminate severe AS. This finding needs confirmation in larger prospective multicenter studies.

Multimodality Imaging in Aortic Stenosis.

ABSTRACTAortic stenosis (AS) is the most common cardiac valve lesion in the adult population, with an incidence increasing as the population ages. Accurate assessment of AS severity is necessary for clinical decision-making. Echocardiography is currently the diagnostic method of choice for assessing and managing AS. Transthoracic echocardiography is usually sufficient in most situations. Transesophageal echocardiography and stress echocardiography may also be utilized when there is inadequate image quality and/or discordance in the results and the clinical presentation. There is a role for other imaging modalities such as cardiac computed tomography, magnetic resonance imaging, and catheterization in selected cases. The following describes in some detail the role of these modalities in the diagnosis and assessment of AS.

Artificial intelligence to assist physicians in identifying patients with severe aortic stenosis

Severe aortic stenosis (AS) remains a life-threatening form of valvular heart disease. Missed diagnosis of severe AS can lead to a delay in treatment and poor outcomes, but there are limited tools available to help physicians minimize the risk of missed diagnoses. Here, a Diagnostic Precision Algorithm was developed from a de-identified dataset of 1,147,157 echocardiographic reports from 35 institutions to help physicians identify patients who may have incorrectly not received a severe AS diagnosis and prioritize these findings for secondary clinical review. Inclusion criteria required the presence of three standard Doppler indices (aortic valve area [AVA], jet velocity [JV], and mean pressure gradient [MPG]), with at least one in the severe AS range (per AHA/ACC criteria), and documented assessment of AS severity. Included reports were divided into training/validation (N = 18,040) and test (N = 4,533) datasets. Using a decision tree algorithm, a Severe AS Index that estimates the likelihood that a patient with similar values would have severe AS diagnosed was developed from the training/validation dataset using AVA, JV, and MPG measurements, as well as left ventricular ejection fraction (LVEF) when available. This was compared to the reported interpretation of the echocardiogram, which was extracted using a validated natural language processing algorithm that demonstrated 100% accuracy across a sample of 600 echocardiographic reports. When the prediction of the Severe AS Index and the report interpretation disagreed, the patient was flagged for secondary review. Across the test dataset, the Diagnostic Precision Algorithm successfully predicted the actual severe AS population proportion with an average error of 2.1% points when LVEF was available and 2.2% points when LVEF was not available. The Diagnostic Precision algorithm was highly accurate at identifying the likelihood of severe AS diagnosis and applying this information to prioritize physician follow-up for patients who may have undiagnosed severe disease.

Latest Advances in Multimodality Imaging of Aortic Stenosis.

Aortic stenosis is a common condition associated with major morbidity, mortality, and health-care costs. Nevertheless, we currently lack any effective medical therapies that can treat or prevent disease development or progression. Modern advances in echocardiography and CT have helped improve the assessment of aortic stenosis severity and monitoring of disease progression, whereas cardiac MRI informs on myocardial health and the development of fibrosis. In a series of recent studies, 18F-NaF PET/CT has been shown to assess valvular disease activity and progression, providing mechanistic insights that can inform potential novel therapeutic approaches. This review will examine the latest advances in the imaging of aortic stenosis and bioprosthetic valve degeneration and explore how these techniques can assist patient management and potentially accelerate novel therapeutic developments.

Indirect ultrasound evaluation of left ventricular outflow tract diameter implications for heart failure and aortic stenosis severity assessment.

Whereas dependency of left ventricular outflow tract diameter (LVOTD) from body surface area (BSA) has been established and a BSA-based LVOTD formula has been derived, the relationship between LVOTD and aortic root and LV dimensions has never been explored. This may have implications for evaluation of LV output in heart failure (HF) and aortic stenosis (AS) severity. A cohort of 540 HF patients who underwent transthoracic echocardiography was divided in a derivation and validation subgroup. In the derivation subgroup (N=340), independent determinants of LVOTD were analyzed to derive a regression equation, which was used for predicting LVOTD in the validation subgroup (N=200) and compared with the BSA-derived formula. LVOTD determinants in the derivation subgroup were sinuses of Valsalva diameter (SVD, beta=0.392, P<.001), BSA (beta=0.229, P<.001), LV end-diastolic diameter (LVEDD, beta=0.145, P=.001), and height (beta=0.125, P=.037). The regression equation for predicting LVOTD with the aforementioned variables (LVOTD=6.209+[0.201×SVD]+[1.802×BSA]+[0.03×LVEDD]+[0.025×Height]) did not differ from (P=.937) and was highly correlated with measured LVOTD (R=0.739, P<.001) in the validation group. Repeated analysis with LV end-diastolic volume instead of LVEDD and/or accounting for gender showed similar results, whereas BSA-derived LVOTD values were different from measured LVOTD (P<.001). Aortic root and LV dimensions affect LVOTD independently from anthropometric data and are included in a new comprehensive equation for predicting LVOTD. This should improve evaluation of LV output in HF and severity of AS when direct LVOTD measurement is difficult or impossible.

NON-INVASIVE ASSESSMENT OF CENTRAL AORTIC PRESSURE, AORTIC FLOW AND VASCULAR LOAD IN PATIENTS WITH AORTIC STENOSIS BEFORE AND AFTER TRANSCATHETER AORTIC VALVE REPLACEMENT

Objective: The left ventricle (LV) faces a dual afterload in patients with aortic stenosis (AS), both from the narrowed valve and age-related arterial stiffening. Variability in indices of AS severity assessment suggests an inter-relationship of the valvular pressure gradient on systemic arterial pressure and flow. Our study aims to evaluate the dynamic vascular load (VL) non-invasively in AS patients before and after transcatheter aortic valve replacement (TAVR) using the approach of simultaneous cardiac magnetic resonance (CMR) and radial applanation tonometry (AT). Design and method: Ascending aortic pressure, flow and VL were measured in 3 patients at baseline and post-TAVR using a previously reported simultaneous CMR/AT technique. CMR provided aortic flow, and radial AT waves were converted offline to aortic pressure using SphygmoCor 8.1 (AtCor Medical) and calibrated using brachial cuff values. VL was determined as the relationship of derived aortic pressure to CMR aortic flow velocity, by calculating the average modulus of pressure divided by flow. Following the acquisition of post TAVR data, 300 micrograms of sublingual nitroglycerine (GTN) was introduced to investigate the effect on changing vascular load. Results: At 38 ± 3 days post TAVR, mean aortic pressure (MP) and mean systolic flow (MF) both increased (100 ± 17 pre, 109 ± 12 post, mmHg; 178 ± 44 pre, 230 ± 74 post, ml/s). Following GTN administration, MP (95 ± 3 mmHg) decreased but not MF (228 ± 57 ml/s) – see figure. The steady state systemic vascular resistance (SVR) reduced post TAVR (22501 ± 5929 pre, 20484 ± 6232 post, dynes.s/cm3), but not VL (1082 ± 219 pre, 1111 ± 483 post, dynes.s/cm3). Conversely, GTN administration significantly reduced VL (838 ± 295 dynes.s/cm3) with little effect on SVR (19313 ± 5631 dynes.s/cm3). Conclusions: Our study demonstrates that our novel technique can be reliably replicated in patients to evaluate the changes to aortic pressure, flow and VL before and after TAVR. VL appears to be a dynamic measurement of vascular stiffness independent of AS and may prove to be a useful measure to predict haemodynamic responses and ventriculo-arterial coupling in AS patients post TAVR. Larger longitudinal cohort studies are warranted.

Comprehensive assessment of the aortic valve in critically ill patients for the non-cardiologist. Part I: Aortic stenosis of the native valve.

Aortic stenosis (AS) causes left ventricular outflow obstruction. Severe AS has major haemodynamic implications in critically ill patients, in whom increased cardiac output and oxygen delivery are often required. Transthoracic echocardiography (TTE) plays akey role in the AS severity grading. In this review, we will give an overview of how to use the simplified Bernoulli equation to convert the echo Doppler measured velocities (cm s-1) to AS peak and mean gra-dient (mm Hg) and how to calculate the aortic valve area (AVA), using the continuity equation, based on the principle of preservation of flow. TTE allows quantification of compensatory left ventricular (LV) hypertrophy, assessment of LV systolic function, and determination of LV diastolic function and LV loading. Subsequently, the obtained results from the TTE study need to be integrated to establish the AS severity grading. The pitfalls of echocardiographic AS severity assessment are explained, and how to deal with inconsistency between AVA and mean gradient. The contribution of transoesophageal echocardiography, low-dose dobutamine stress echo (in case of low-flow low-gradient AS), echocardiography strain imaging, cardiac magnetic resonance imaging, cardiac multidetector computed tomography and the relatively new concept of Flow Pressure Gradient Classification to the work-up for aortic stenosis is discussed. Finally, the treatment of AS is overviewed. Elective aortic valve replacement is indicated in patients with severe symptomatic AS. In the ICU, afterload reduction by vasodilator therapy and treatment of pulmonary and venous congestion by diuretics could be considered.

The five-beat averaged method of assessing aortic stenosis in atrial fibrillation significantly underestimates stenosis severity compared to sinus rhythm

Abstract Background Doppler echocardiographic assessment of aortic stenosis (AS) is dependent on trans-valvular flow rate (TVFR) and is most accurately performed in physiologically normal conditions (TVFR &amp;gt;200ml/s). Atrial fibrillation (AF) complicates AS assessment with heart rate variability and reduced averaged indexed stroke volume (SVi) compared to sinus rhythm (SR). We hypothesize that the 5-beat averaging technique in AF leads to underestimation of severity of AS compared to SR, and that diagnostic accuracy may be improved by maximum SVi beat selection. Methods Patients with at least mild AS (mean aortic gradient (MG) &amp;gt;15mmHg) with separate echocardiograms demonstrating SR and AF within a six-month period were identified. Patients with interval cardiac surgery, change in left ventricular ejection fraction (LVEF) of &amp;gt;15%, aortic valve prostheses, infective endocarditis, paced rhythm, severe concomitant valvular dysfunction, LVEF &amp;lt;35%, heart rate &amp;gt;100 beats per minute (bpm) or TVFR &amp;lt;200ml/s on their SR examination were excluded. In AF, individual beat SVi was calculated from individual beat aortic velocity time integral (VTI) and the reported aortic valve area (AVA) via the continuity equation. Results Seventeen patients were identified (mean time between echocardiograms 132 days, mean difference in LVEF 4%, mean difference in heart rate 11bpm). Using the 5-beat averaged model, compared to SR, the presence of AF significantly reduced SVi (−12.68ml/m2, p=0.00007) and TVFR (−69ml/s, p=0.00014). In AF, 9/17 cases demonstrated one or more beats with TVFR &amp;lt;200ml/s, with 6/17 producing a 5-beat averaged TVFR &amp;lt;200ml/s – consistent with a low flow state. Correspondingly, flow derived severity assessment parameters and calculated aortic valve area (AVA) in AF were reduced compared to SR (aortic peak velocity (Vmax) −0.42m/s, p=0.00005, MG −7.01mmHg, p=0.002, AVA −0.11cm2, p=0.025). As a proposed correction in AF, the single beat with the largest SVi was compared with SR. This measure improved concordance with flow conditions and severity assessment in SR (difference SVi −8.77ml/m2, p=0.004, TVFR −46ml/s, p=0.001, Vmax −0.21, p=0.003, MG −3.55mmHg, p=0.02) and equalized calculated AVA (−0.07cm2, p=0.09). Conclusion In individual patients with AS observed in SR and AF within a six-month period, AF was associated with significantly lower SVi and TVFR, with underestimation of AS severity assessment. AS assessment in AF using maximum observed stroke volume beat (as opposed to 5-beat average) improves concordance with SR assessment significantly. Funding Acknowledgement Type of funding source: None