Fully Automated Artificial Intelligence Assessment of Aortic Stenosis by Echocardiography.

BACKGROUND: Aortic stenosis (AS) is a common form of valvular heart disease, present in over 12% of the population age 75 years and above. Transthoracic echocardiography (TTE) is the first line of imaging in the adjudication of AS severity but is time-consuming and requires expert sonographic and interpretation capabilities to yield accurate results. Artificial intelligence (AI) technology has emerged as a useful tool to address these limitations but has not yet been applied in a fully hands-off manner to evaluate AS. Here, we correlate artificial neural network measurements of key hemodynamic AS parameters to experienced human reader assessment. METHODS: Two-dimensional and Doppler echocardiographic images from patients with normal aortic valves and all degrees of AS were analyzed by an artificial neural network (Us2.ai) with no human input to measure key variables in AS assessment. Trained echocardiographers blinded to AI data performed manual measurements of these variables, and correlation analyses were performed. RESULTS: Our cohort included 256 patients with an average age of 67.6 ± 9.5 years. Across all AS severities, AI closely matched human measurement of aortic valve peak velocity (r = 0.97, P < .001), mean pressure gradient (r = 0.94, P < .001), aortic valve area by continuity equation (r = 0.88, P < .001), stroke volume index (r = 0.79, P < .001), left ventricular outflow tract velocity-time integral (r = 0.89, P < .001), aortic valve velocity-time integral (r = 0.96, P < .001), and left ventricular outflow tract diameter (r = 0.76, P < .001). CONCLUSIONS: Artificial neural networks have the capacity to closely mimic human measurement of all relevant parameters in the adjudication of AS severity. Application of this AI technology may minimize interscan variability, improve interpretation and diagnosis of AS, and allow for precise and reproducible identification and management of patients with AS.

Application of a Novel Two-Dimensional Echocardiographic Calcium Quantification Method to Assess All Severities of Aortic Stenosis.

BACKGROUND: Aortic valve (AV) calcification (AVC) is a strong predictor of aortic stenosis (AS) severity. The two-dimensional AVC (2D-AVC) ratio, a gain-independent ratio composed of the average pixel density of the AV and the aortic annulus, has previously shown strong correlations with two-dimensional (2D) echocardiographic hemodynamic parameters for severe AS and AVC by cardiac computed tomography. We hypothesize that the 2D-AVC ratio correlates with hemodynamic parameters in all severities of AS. METHODS: A total of 285 patients with a normal AV (n = 49), aortic sclerosis (n = 75), or mild (n = 38), moderate (n = 72), or severe (n = 51) AS undergoing 2D echocardiography were retrospectively evaluated, and the 2D-AVC ratios were correlated to mean AV gradient, peak AV velocity, AV area, and dimensionless index. The 2D-AVC ratios of various AS severities were compared against each other via area under the curve (AUC) analysis. RESULTS: The 2D-AVC ratio is strongly correlated with mean AV gradient (r = 0.79, P < .0001) and peak AV velocity (r = 0.78, P < .0001). There was moderate correlation with the AV area (r = -0.58, P < .0001) and dimensionless index (r = -0.67, P < .0001) across all AS severities. The 2D-AVC ratio also distinguished nonmoderate AS (mild AS + normal AV) from moderate or greater (moderate + severe) AS (AUC = 0.93) and moderate versus severe AS (AUC = 0.88). CONCLUSION: The 2D-AVC ratio exhibits moderate to strong correlation with 2D echocardiographic hemodynamic parameters across all severities of AS.

Impact of Transcatheter Aortic Valve Implantation Among Patients With Co-existing Mild to Moderate Mitral Regurgitation.

A subset of patients with severe aortic stenosis (AS) who are who underwent transcatheter aortic valve implantation (TAVI) also has mitral regurgitation (MR). Clinical outcomes in these patients with combined MR and AS have varied. The purpose of this study was to assess clinical outcomes and echocardiographic outcomes after TAVI in patients with preprocedural MR. A retrospective chart review from March 2018 to June 2020 identified all TAVI patients. Patients were assigned an MR class of mild, moderate, or severe based upon pre-TAVI transthoracic echocardiogram (TTE). Patients were excluded if they were discharged from the hospital and did not have a 6-month follow-up after TAVI. Clinical outcomes at 6 months included all-cause mortality, major adverse cardiovascular events, clinically significant bleeding, changes in ejection fraction (EF) category, and changes in MR severity. Of 118 included patients (age 76 ± 10 years, 79% male, 46% White), 33% had MR, with 26% being mild and 7% moderate MR. Before TAVI, AS + MR patients were more likely to have a reduced EF (<50%) by category compared with those with AS only (33.3% vs 8.8%, p = 0.01) but were more likely to show an increase in EF by category after TAVI (19.4% vs 5.5%, p = 0.039). No significant differences were observed between the 2 groups in terms of all-cause mortality (12.8 vs 5.1%, p = 0.14), major adverse cardiovascular events (17.9 vs 8.9%, p = 0.15), or clinically significant bleeding (10.3 vs 6.3%, p = 0.45). Patients with AS and co-existing MR experienced similar clinical outcomes at 6 months to those with AS only after TAVI. They were more likely to show increases in EF category 6 months after valve implantation. Our results support the conclusion that in addition to treating the aortic valve, TAVI also potentially benefits left ventricular function in the setting of mild or moderate MR.

A Novel Two-Dimensional Echocardiography Method to Objectively Quantify Aortic Valve Calcium and Predict Aortic Stenosis Severity.

Aortic valve calcium (AVC) is a strong predictor of aortic stenosis (AS) severity and is typically calculated by multidetector computed tomography (MDCT). We propose a novel method using pixel density quantification software to objectively quantify AVC by two-dimensional (2D) transthoracic echocardiography (TTE) and distinguish severe from non-severe AS. A total of 90 patients (mean age 76 ± 10 years, 75% male, mean AV gradient 32 ± 11 mmHg, peak AV velocity 3.6 ± 0.6 m/s, AV area (AVA) 1.0 ± 0.3 cm2, dimensionless index (DI) 0.27 ± 0.08) with suspected severe aortic stenosis undergoing 2D echocardiography were retrospectively evaluated. Parasternal short axis aortic valve views were used to calculate a gain-independent ratio between the average pixel density of the entire aortic valve in short axis at end diastole and the average pixel density of the aortic annulus in short axis (2D-AVC ratio). The 2D-AVC ratio was compared to echocardiographic hemodynamic parameters associated with AS, MDCT AVC quantification, and expert reader interpretation of AS severity based on echocardiographic AVC interpretation. The 2D-AVC ratio exhibited strong correlations with mean AV gradient (r = 0.72, p < 0.001), peak AV velocity (r = 0.74, p < 0.001), AVC quantified by MDCT (r = 0.71, p <0.001) and excellent accuracy in distinguishing severe from non-severe AS (area under the curve = 0.93). Conversely, expert reader interpretation of AS severity based on echocardiographic AVC was not significantly related to AV mean gradient (t = 0.23, p = 0.64), AVA (t = 2.94, p = 0.11), peak velocity (t = 0.59, p = 0.46), or DI (t = 0.02, p = 0.89). In conclusion, these data suggest that the 2D-AVC ratio may be a complementary method for AS severity adjudication that is readily quantifiable at time of TTE.

Improvements in global longitudinal strain after transcatheter aortic valve replacement according to race.

OBJECTIVE: In the United States, racial minorities are underrepresented among patients receiving transcatheter aortic valve replacement (TAVR) and data regarding their outcomes is limited. Global longitudinal strain (GLS) is a measure left ventricular function and has independently predicted outcomes after TAVR. The aim of this study is to assess changes in GLS after TAVR according to race and factors predicting these changes. METHODS: Electronic medical records of patients undergoing TAVR at the University of Illinois, Chicago and Jesse Brown Veteran's Administration Medical Center (Chicago, Illinois) from January 2017-February 2020 were reviewed retrospectively. The most recent transthoracic echocardiogram (TTE) prior to TAVR and the TTE 1-month post-procedure were used to determine GLS. Patients were included if both a pre- and post-procedure study were present and TTE images were of sufficient quality to process strain imaging. RESULTS: A total of 103 patients (average age 76 ± 12 years, 80% male, 42% white) were included. At 1-month post-TAVR, GLS improved for all races: white (-2.7 ± 3.5%, P<0.001), African-American (-2.8 ± 3.3%, P<0.001), and Hispanic (-2.0 ± 2.1%, P<0.001). There were no differences in the degree of improvement among races (P=0.62). Baseline GLS was negatively correlated with changes in GLS overall (r=-0.44, P<0.001). Baseline aortic valve area (cm2) was positively correlated with changes in GLS (r=0.2, P=0.036). CONCLUSIONS: This study demonstrated that GLS improved after TAVR independent of race with similar degrees of change across races. Baseline GLS and aortic valve area predicted strain improvement after TAVR, which suggests that those with more impaired LV function may benefit most from the procedure.

Same-Day Discharge After Outpatient PCI in a VA Hospital: Shared Decision Making and the VA MISSION Act.

INTRODUCTION: The VA Mission Act of 2018 sought to increase access to local care facilities for Veterans meeting certain eligibility criteria including a drive time of >60 min from a VA facility. As part of an ongoing review of our VA program's same day discharge (SDD) program following elective percutaneous coronary intervention (PCI), we investigated whether the distance criteria of the VA Mission Act had any impact on overall safety outcomes. METHODS: We performed a single center, retrospective study in patients who underwent outpatient PCI between 2013 and 2019. We stratified patients into an overnight observation (ON) and SDD group. We used Google Maps in order to calculate patient home distance to the Jesse Brown Veterans Affairs Hospital (JBVA). Primary endpoints included all-cause death andmajor adverse cardiac events (MACE; cardiovascular death, myocardial infarction, stroke, and/or target vessel revascularization). Secondary outcomes included total unplanned interactions with the healthcare system. Outcomes were analyzed at 30 days after PCI. RESULTS: There were 76 patients in the SDD group. The SDD group had a median drive time of 80 min from the JBVA. Regarding primary outcomes, there were no cases of MACE in either group and there was no statistically significant difference in terms of all-cause mortality (ON: 1.3%, SDD: 0%, p = .5) 30 days following PCI. All secondary outcomes at 30 days did not demonstrate a statistically significant difference between either group. CONCLUSION: Same day discharge following successful PCI procedures appears safe. In response to the VA Mission Act, drive time and distance travelled did not appear to impact outcomes. SUMMARY: Same day discharge in select patients at our VA hospital was both safe and feasible. Neither drive time nor distance travelled affected overall outcomes in response to the 2018 VA MISSION Act. As such, shared decision making between patients and physicians remains essential to ensure Veterans continue to receive high quality care that is in their best medical interest.