Pislaru, Sorin V.

Introduction: A significant portion of patients with aortic stenosis (AS) have low-gradient AS (LGAS) defined as aortic valve area ≤ 1.0 cm 2 and a trans-aortic mean systolic gradient and peak velocity < 40 mmHg and < 4 m/s, respectively. LGAS has been shown previously to have worse mortality compared to high-gradient AS (HGAS). Etiologies for LGAS include diastolic dysfunction, heart failure, other significant valvular disease, and atrial fibrillation (AF). AF is associated with worse outcomes compared to sinus rhythm (SR) in HGAS. AF is common in LGAS, but whether AF is associated with worse outcomes versus SR in LGAS has not been elucidated. Hypothesis: We hypothesize that AF is associated with higher mortality compared to SR in patients with LGAS. Methods: We retrospectively identified and reviewed charts of patients who were diagnosed with LGAS on transthoracic echocardiogram (TTE) from 2010-2020 at Mayo Clinic. Patient were classified according to rhythm at the time of TTE and history of AF was ascertained among those in SR. Patents were divided into 3 groups; SR without history of AF (group 1), SR with history of AF (group 2), and AF during TTE (group 3). Primary endpoints of overall mortality and cardiac mortality were ascertained. Results: A total of 3400 patients were included: n=2036 in group 1, n=519 in group 2, and n=845 in group 3. After adjusting for age, sex, and the Charlson index, group 2 and group 3 patient had significantly higher overall mortality (HR 1.22 and HR 1.52, respectively, p<0.0001 for both) and cardiac mortality (HR 1.37 and HR 2.05, respectively, p<0.0001 for both), Figure . Conclusions: In LGAS, AF is a significant prognostic indicator of overall mortality and cardiac mortality. LAGS associated with AF may need different management strategies given the higher mortality associated with the presence of AF.

Introduction: The predictive value of left atrial (LA) volume and reservoir function (ResF) post-atrial fibrillation (AF) ablation has been scarcely studied. Hypothesis: Abnormal LA volume and ResF post-ablation are associated with adverse cardiovascular events. Methods: We analyzed LA maximum (LAVImax) and minimum (LAVImin) volume index, and 2 measures of ResF, emptying fraction (LAEF) and expansion index (LAEI), prospectively measured at 3-month post-procedure in patients in sinus rhythm who underwent AF ablation between 2007-2016. Composite endpoint (CE) at follow up was all-cause mortality, cardiac hospitalization (heart failure or acute ischemic event) and stroke. Results: 792 patients were studied ( age 60±10 years, 25% women ; Table 1) . Over 7.5 years [IQR 3.0-9.7], 96 (12%) patients experienced CE, which was more prevalent in patients with enlarged LA and reduced ResF. Impaired LA volumes and ResF were each independently associated with CE ( Fig.1 ), even after adjustment for clinical, demographic and echo characteristics (Model A, Fig.2 ) (LAVImax ≥35 ml/m 2 : HR 2.15 [95% CI, 1.35-3.43], p=0.001; LAVImin≥20.5 ml/m 2 : HR 2.88 [1.77-4.69], p<0.0001; LAEF<39%: HR 2.00 [1.31-3.05], p=0.001; LAEI<65%: HR 1.95 [1.27-3.01], p=0.003). ResF measures (LAEF and LAEI) were incremental to LAVImax (all p<0.05), but not LAVImin (all p>0.05; Fig.2 ). In patients with normal LA (LAVImax <35 ml/m 2 ; n=408), increased LAVImin (≥20.5 ml/m 2 ) remained associated with CE (HR 3.11 [1.45-6.67], p=0.004) and cardiac hospitalization (HR 5.81 [1.87-18.01], p=0.002). These findings were independent of AF recurrence. Conclusions: In these patients, enlarged LA and impaired ResF at 3-month post-ablation were strongly associated with adverse cardiovascular outcomes, regardless of AF recurrence. Measures of LA ResF were incremental to LAVImax. Notably, LAVImin showed the strongest associations and even identified a high-risk subgroup among patients with non-dilated LA.

Introduction: Acceleration time (AT) and Doppler Velocity Index (DVI) are critical parameters in assessment of bioprosthetic aortic valve dysfunction (BAVD). AT>100ms and DVI < 0.25 are highly suggestive of prosthetic obstruction and are incorporated in all triage algorithms. Little is known about their relationship with flow. Hypothesis: AT and DVI may be affected by transprosthetic flow in patients with significant bioprosthetic aortic valve dysfunction (BAVD). Methods: Single center, retrospective analysis of patients with severe BAVD (confirmed at surgical re-replacement, transcatheter valve-in-valve implantation, or successfully treated bioprosthetic valve thrombosis). Standard prosthetic parameters (AT, DVI, effective orifice area (EOA), mean gradient, presence and degree of regurgitation), flow (stroke volume index, Svi; transprosthetic flow rate, FR) were measured on the transthoracic echocardiogram at the time of diagnosis with severe BAVD. Results: A total of 266 patients with severe BAVD underwent treatment between 2008-2020. BAVD mechanism was obstruction (N=192, 72%), regurgitation (n=48, 18%) mixed stenosis and regurgitation (n=15, 6%) and patient-prosthetic mismatch (n=12, 5%). DVI was moderately correlated with FR (r=0.50, p<0.001); AT had a weak but significant inverse correlation with FR (r=0.24, p<0.001). SVi had a weaker influence on DVI (r=0.35, p<0.001) and no correlation with AT. Conclusions: AT and DVI are influenced by transprosthetic flow rate. This flow-dependency should be considered when assessing the mechanism of BAVD.

Introduction: Hypertrophic cardiomyopathy (HCM) is associated with excessive left ventricular (LV) hypertrophy (LVH), myocyte disarray and expansion of interstitial collagen. These factors alter mechanical properties of the myocardial tissue. Intrinsic velocity propagation (iVP) of myocardial stretch is a new validated measure of myocardial elasticity. Hypothesis: iVP in left ventricular (LV) myocardium of patients with HCM will be increased compared to normal subjects. Methods: We studied prospectively 100 subjects: 42 with HCM (age 57 ± 14 years; 79% with asymmetric septal LVH) and 58 normal controls without cardiovascular disease (age 48 ± 13 years). Patients had comprehensive transthoracic echocardiography and cardiac magnetic resonance imaging (MRI; n=29). iVP was measured throughout the LV myocardium during late diastole using ultra-high frame rate tissue Doppler imaging (350-460 fps) (6 LV walls, 3 standard apical views). Chamber stiffness (CS) was evaluated from end-diastolic pressure-volume relationship (EDPVR) estimated noninvasively by the single-beat method (EDP=αV β ). End-diastolic pressure (EDP) was estimated from E/e’. Results: LV ejection fraction was normal in both groups (HCM: 68 ± 7%; Controls: 65 ± 5%). Myocardial stiffness by iVP was markedly higher in HCM vs. controls (Fig.A, left panel). This was confirmed by EDPVRs, which were steeper and shifted leftward (Fig. B, left). The slope (β, load-independent) of EDPVR and CS (dP/dV) were higher and LV capacitance (V 30 , estimated volume at 30 mmHg EDP) was lower in HCM (Fig. B, right) and correlated significantly, though weakly, with iVP (β: r = 0.41; CS dP/dV: r = 0.48; EDP: r = 0.61; p<0.002 for all). Patients with apical variant had lower levels of global iVP compared to patients with predominant septal LVH and diffuse concentric LVH (Fig. A, right). Conclusions: Myocardial stiffness measured noninvasively by the intrinsic wave method is highly abnormal in HCM. This novel approach allows mapping of myocardial elasticity of the entire left ventricle and shows promise to become a clinical tool for evaluation of patients with diastolic tissue abnormalities.

Introduction: Bioprosthetic valve thrombosis (BPVT) is a well-recognized cause of prosthetic dysfunction. Anticoagulation restores prosthetic valve gradients, but long term outcomes and complications from therapy are unknown. Objectives: To define the complications and long-term outcomes of anticoagulant therapy for BPVT. Methods: Retrospective matched cohort study of patients treated with warfarin for presumed BPVT at a single center from 1999 to 2016. Controls with normal bioprostheses by echocardiography were matched 2:1 for age at implantation, gender, prosthetic valve position, and type of prosthesis (porcine / pericardial). Results: A total of 83 presumed BPVT patients (40 aortic, 21 mitral, 18 tricuspid, and 4 pulmonary) and 166 controls were included. Age at BPVT diagnosis was 60±19 yrs (41±41 months post implantation); 45 (54%) were male. Transvalvular gradients returned to baseline in 63 (76%) of the patients, after 5±4 months of warfarin; 60 (72%) patients were maintained on warfarin indefinitely. Recurrent BPVT was seen in 13 (16%) patients, 33±31 months after initial therapy. When compared to controls, warfarin-treated BPVT patients had similar incidence of stroke [4(5%) vs 5 (3%), p=0.49], peripheral embolic events [4(5%) vs 10 (6%), p=0.78)], and death [12 (14%) vs 28 (17%), p= 0.72] (Figure, left panel), but more bleeding requiring transfusion [18 (22%) vs 3 (2%), p<0.0001]. Presumed BPVT patients more often required surgical or percutaneous valve re-replacement (Figure, center panel); this difference persisted even when comparing only patients with confirmed BPVT (those who responded to anticoagulant therapy) vs. their matched controls (Figure, right panel). Conclusion: Warfarin anticoagulation for presumed BPVT is successful in the majority of patients, without increase in stroke, peripheral embolism or death, but at the cost of excess bleeding. Recurrent BPVT occured in 16% of patients. Importantly, patients with BPVT required more often valve re-replacement. This finding suggests that anticoagulant therapy does not fully restore prosthetic valve durability, and that BPVT patients should be closely monitored.

Background: Non-cardiac surgery (NCS) in patients with severe aortic stenosis has traditionally been associated with high perioperative mortality. Aortic valve replacement is recommended prior to elective NCS, but the impact of this strategy has not been systematically assessed. Methods: A retrospective review was performed of all patients with severe aortic stenosis undergoing major NCS at Mayo Clinic between 2000 and 2013. Patients undergoing aortic valve intervention (AVI) prior to NCS were compared to those undergoing surgery without prior AVI (control). Patients undergoing emergency surgery were excluded. Primary endpoint was occurrence of major adverse cardiac events (MACE; combination of death, stroke, myocardial infarction, new/worsening heart failure, ventricular arrhythmia) within 30 days of NCS; secondary endpoints were mortality at 30 days and 1 year after NCS. Results: 180 patients (age 74.5 ± 10.5 years, 64% male) who underwent NCS within 12 months after AVI, were compared to 232 patients (age 76.6 ± 10.7 years, 56% male) in the control group. Patients undergoing AVI were more often symptomatic than controls (41% vs 26%, p = 0.002). MACE was significantly higher in the control group (21.6% vs 5.6%, p < 0.001), mainly due to the increased risk of heart failure in the postoperative period in this group (18.5% vs 2.2%, p < 0.001). There was no significant difference in the rate of myocardial infarction (1.7% vs 0.6%, p = 0.39), ventricular arrhythmia (0.9 % vs 0 %, p = 0.51) or stroke (0.9 % vs 0 %, p = 0.51). Kaplan-Meier assessment demonstrated no significant difference at 30 days but a reduction in 1 year mortality in the AVI group compared to the control group (Figure). Conclusions: Pre-operative AVI for severe aortic stenosis results in reduced heart failure and improved 1 year survival. However, other MACE and 30 day mortality appears unchanged. Pre-operative AVI should be considered in symptomatic patients, where the benefit of AVI is demonstrated to be greatest.

Abstract Aims Augmenting echocardiography with artificial intelligence would allow for automated assessment of routine parameters and identification of disease patterns not easily recognized otherwise. View classification is an essential first step before deep learning can be applied to the echocardiogram. Methods and results We trained two- and three-dimensional convolutional neural networks (CNNs) using transthoracic echocardiographic (TTE) studies obtained from 909 patients to classify nine view categories (10 269 videos). Transthoracic echocardiographic studies from 229 patients were used in internal validation (2582 videos). Convolutional neural networks were tested on 100 patients with comprehensive TTE studies (where the two examples chosen by CNNs as most likely to represent a view were evaluated) and 408 patients with five view categories obtained via point-of-care ultrasound (POCUS). The overall accuracy of the two-dimensional CNN was 96.8%, and the averaged area under the curve (AUC) was 0.997 on the comprehensive TTE testing set; these numbers were 98.4% and 0.998, respectively, on the POCUS set. For the three-dimensional CNN, the accuracy and AUC were 96.3% and 0.998 for full TTE studies and 95.0% and 0.996 on POCUS videos, respectively. The positive predictive value, which defined correctly identified predicted views, was higher with two-dimensional rather than three-dimensional networks, exceeding 93% in apical, short-axis aortic valve, and parasternal long-axis left ventricle views. Conclusion An automated view classifier utilizing CNNs was able to classify cardiac views obtained using TTE and POCUS with high accuracy. The view classifier will facilitate the application of deep learning to echocardiography.

Background Aortic valve calcium score is associated with hemodynamic severity of aortic stenosis. Whether this association is present in calcific mitral stenosis remains unknown. Methods and Results This study was a retrospective analysis of consecutive patients with mitral stenosis secondary to mitral annular calcification (MAC) undergoing transseptal catheterization. All patients underwent invasive mitral valve assessment via direct left atrial and left ventricular pressure measurement. Computed tomography within 1 year of cardiac catheterization and with adequate visualization of the mitral annulus was included. MAC calcium score quantification by Agatston method was obtained offline using dedicated software (Aquarius, TeraRecon, V.4). Median patient age was 66.9±11.2 years, 47% of patients were women, 50% had coronary artery disease, 40% had atrial fibrillation, 47% had prior cardiac surgery, and 33% had prior chest radiation. Median diastolic mitral valve gradient was 9.4±3.4 mm Hg on echocardiography and 8.5±4 mm Hg invasively. Invasive median mitral valve area using the Gorlin formula was 1.87±0.9 cm 2 . Median MAC calcium score for the cohort was 7280±7937 Hounsfield units. MAC calcium score correlated with the presence of atrial fibrillation ( P =0.02) but was not associated with other comorbidities. There was no correlation between MAC calcium score and mitral valve area ( r =0.07; P =0.6) or mitral valve gradient ( r =−0.03; P =0.8). Conclusions MAC calcium score did not correlate with invasively measured mitral valve gradient and mitral valve area in patients with MAC‐related mitral stenosis, suggesting that calcium score should not be used as a surrogate for invasive hemodynamic parameters.

Background: Enlargement or dilation of the left ventricle (LV) is associated with increased cardiovascular morbidity and mortality, and is an established precursor of ventricular dysfunction and heart failure in almost all major cardiovascular conditions. Although there are existing artificial intelligence frameworks that make use of deep learning to detect LV enlargement, many entail LV segmentation, which can be error-prone especially for point-of-care ultrasound (POCUS) images. Goal: To develop a fully end-to-end deep learning framework that takes as input either transthoracic echocardiographic (TTE) or POCUS 2D image clips, and classifies directly (i.e., without first segmenting the LV) whether a patient has an enlarged LV. Methods: Using a sample of retrospective TTE data enriched for LV enlargement (out of 13,868 patients total, 3,351 had an enlarged LV defined using sex-specific guideline-directed criteria), we trained a classifier that takes as input apical 2-chamber and parasternal long axis videos, and provides as output a binary label denoting whether a patient has an enlarged LV. Then, we evaluated the trained model using a holdout testing dataset of retrospective TTE data (2,087 patients) as well as data from a prospective cohort of 428 patients from whom TTE and POCUS were collected simultaneously. Results: For the retrospective TTE testing dataset, the AUC was 0.851 (95% confidence interval (CI) of 0.830-871). For the prospective cohort, the model performed comparably for both TTE and POCUS video clips (TTE: AUC of 0.865, 95% CI of 0.823-0.906; POCUS: AUC of 0.840, 95% CI of 0.797-0.883). Conclusions: The current deep learning model performed comparably well for both TTE and POCUS echocardiograms. We regard these results as a proof-of-concept of the potential utility of this model in helping point-of-care clinicians make decisions regarding whether patients should receive further evaluation for LV enlargement and associated conditions.

Introduction: Multiple Valvular Heart Disease (VHD), defined as at least moderate stenotic or regurgitant lesions in ≥2 valves, mixed VHD as combination of lesions in the same valve and mitral annular calcification (MAC) are common conditions. Association between multiple-mixed VHD (MMVHD), MAC and MACE in patients exposed to Radiation Therapy (RT) and/or chemotherapy (CT) who underwent Transcatheter Aortic Valve Replacement (TAVR) has not been studied. Aim: Assess the presence of MMVHD and MAC in cancer patients with prior RT and/or CT and their correlation with MACE (cardiovascular death, myocardial infarction, revascularization, stroke and hospitalization for heart failure) after TAVR. Methods: 544 patients were included and divided into 3 groups: 187 with prior chest RT and CT (RT/CT), 155 CT only, and 202 without CT/RT as controls (Table 1). Data was obtained from the pre-procedure echocardiogram and quantified in a 1-6 scale (none, mild, mild/moderate, moderate, moderate/severe and severe). Fisher’s exact test or chi-square were used to compare categorical. Multiple VHD-MACE correlation was evaluated through multivariable Cox analysis using a proportional hazards model. Results: The prevalence of Multiple VHD was 37.4% in RT/CT, 23.2% in CT, and 13.9% in controls p<0.001(Figure 1). The RT/CT group had a significantly higher prevalence of severe MAC. Multiple VHD predicted MACE at 18 months after TAVR in RT/CT (HR 3.42, CI 1.93-6.08, p<0.001) and in CT (HR 2.55, CI 1.39-4.66, p=0.002) (Table 2). In RT/CT, severe MAC also predicted MACE (HR 3.68, CI 2.13-6.37, p<0.001), while it was not a predictor in the other groups. Stenotic or regurgitant VHD was more prevalent in the RT/CT group (Figure 2). Conclusions: Multiple VHD was found higher in RT/CT and predicted MACE at 18 months post-TAVR, including CT only patients. Severe MAC was also a strong predictor of the outcome in RT/CT patients. Pre-TAVR evaluation of MMVHD lesions is crucial for optimal patient management.