Prognostic Value of Preprocedural LV Global Longitudinal Strain for Post-TAVR-Related Morbidity and Mortality: A Meta-Analysis

4-Dimensional Cardiac Modelling of Multi-phase Computed Tomography for Predicting Outcomes Following Transcatheter Aortic Valve Replacement

BACKGROUND

Multi-phase Computed Tomography Angiography (mpCTA) is routinely performed prior to transcatheter aortic valve replacement (TAVR) to determine eligibility and enable pre-procedural planning. Incremental prognostic value may be realized from full-cycle, multi-phase reconstructions to assess the contractile health of cardiac chambers. This study aimed to assess the feasibility of 4D chamber modelling of the left ventricle (LV) to support 3D minimum principal strain (3DminPS) based predictions of clinical outcomes following TAVR.

METHODS

Two hundred and five patients undergoing pre-TAVR mpCTA were studied. UNet-based 3D chamber segmentation was followed by mesh modelling and 3D feature tracking-based deformation to determine global 3DminPS for endocardial, epicardial and transmural layers. Independent associations of 3DminPS with the primary outcome of heart failure hospitalization or death were described.

RESULTS

Of 205 patients, 196 (96%) had analyzable mpCTAs (median age 85 years; 55% male; STS-PROM score 3.10; and echocardiographic LV ejection fraction 60.0%). At a median of 25 months following TAVR, 55 patients (28%) experienced the primary outcome. Following adjustment for baseline variables, patients with an endocardial 3DminPS amplitude worse than -23.7% experienced a 2.7-fold higher risk of the outcome (aHR (95% CI) 2.7 (1.4-5.1), p=0.001), this high-risk cohort experiencing 1-year and 3-year event rates of 32% and 49%, respectively.

CONCLUSION

4D chamber modelling of mpCTA using UNet-based segmentation and standardized mesh deformation is feasible and enables the delivery of 3D deformation markers with strong prognostic value for the prediction of outcomes following TAVR. Prospective validation in a multi-center setting is currently being executed.

Left Ventricular Hypertrophy in Aortic Stenosis: Early Cell and Matrix Regression 2 Months Post-Aortic Valve Replacement

BACKGROUND

In aortic stenosis, the myocardium responds with left ventricular hypertrophy, which is characterized by increased left ventricular mass due to cellular hypertrophy and extracellular matrix expansion. Following aortic valve replacement (AVR), left ventricular hypertrophy regression occurs, but early cellular and extracellular dynamics are unknown.

METHODS

Patients with severe symptomatic aortic stenosis undergoing surgical or transcatheter AVR were prospectively recruited. Pre- and early post-AVR cardiac magnetic resonance imaging assessed left ventricular remodeling, global longitudinal strain, and T1 mapping to determine extracellular volume fraction and volume of cellular and extracellular compartments.

RESULTS

In all, 39 patients (aged 71.4±9.8 years, male 79%, aortic valve peak velocity 4.4±0.5 m/s) underwent cardiac magnetic resonance before and at median 7.7 weeks post-AVR. Left ventricular mass index reduced significantly by 15.4% (P<0.001*), primarily driven by cellular compartment regression (18.7%, P<0.001*), with a smaller reduction in the extracellular compartment (7.2%, P<0.001*). This unbalanced regression led to an apparent increase in extracellular volume fraction (27.4±3.1% to 30.2±2.8%; P<0.001*). Although there was no significant change in global longitudinal strain post-AVR, an increase in extracellular volume fraction was associated with worsening of global longitudinal strain (Pearson r=0.41, P=0.01). Mode of intervention (transcatheter versus surgical) did not influence the above myocardial parameters post-AVR (all P>0.05). The asterisk in P values indicates a statistical significance of <0.05.

CONCLUSIONS

Within 8 weeks of AVR for aortic stenosis, substantial left ventricular hypertrophy regression occurs involving both cellular and extracellular compartments, demonstrating the early myocardial adaptability to afterload relief. Cellular compartment regression is greater than extracellular regression, leading to an apparent increase in extracellular volume fraction. Mode of intervention did not affect degree of reverse remodeling, indicating that both are effective at resulting beneficial changes post-AVR.

REGISTRATION

URL: https://www.isrctn.com; Unique identifier: NCT04627987.

Artificial Intelligence Improves Prediction of Major Adverse Cardiovascular Events in Patients Undergoing Transcatheter Aortic Valve Replacement Planning CT

RATIONALE AND OBJECTIVES

Coronary CT angiography (CCTA) is mandatory before transcatheter aortic valve replacement (TAVR). Our objective was to evaluate the efficacy of artificial intelligence (AI)-powered software in automatically analyzing cardiac parameters from pre-procedural CCTA to predict major adverse cardiovascular events (MACE) in TAVR patients.

MATERIALS AND METHODS

Patients undergoing pre-TAVR CCTA were retrospectively included. AI software automatically extracted 34 morphologic and volumetric cardiac parameters characterizing the ventricles, atria, myocardium, and epicardial adipose tissue. Clinical information and outcomes were recorded from institutional database. Cox regression analysis identified predictors of MACE, including non-fatal myocardial infarction, heart failure hospitalization, unstable angina, and cardiac death. Model performance was evaluated with Harrell's C-index, and nested models were compared using the likelihood ratio test. Manual analysis of 170 patients assessed agreement with automated measurements.

RESULTS

Among the 648 enrolled patients (77 ± 9.3 years, 58.9% men), 116 (17.9%) experienced MACE within a median follow-up of 24 months (interquartile range 10-40). After adjusting for clinical parameters, only left ventricle long axis shortening (LV-LAS) was an independent predictor of MACE (hazard ratio [HR], 1.05 [95% confidence interval, 1.05-1.11]; p = 0.04), with significantly improved C-index (0.620 vs. 0.633; p < 0.001). When adjusted for the Society of Thoracic Surgeons Predicted Risk of Mortality score, LV-LAS was also predictive of MACE (HR, 1.08 [95%CI, 1.03-1.13]; p = 0.002), while improving model performance (C-index: 0.557 vs. 0.598; p < 0.001). All parameters showed good or excellent agreement with manual measurements.

CONCLUSION

Automated AI-based comprehensive cardiac assessment enables pre-TAVR MACE prediction, with LV-LAS outperforming all other parameters.

Evaluating the Clinical Utility of Left Ventricular Strains in Severe AS: A Pilot Study with Feature-Tracking Cardiac Magnetic Resonance

Background: Aortic valve stenosis (AS) is the most common degenerative valvular heart disease, significantly impacting the outcome. Current guidelines recommend valve replacement only for symptomatic patients, but advanced cardiovascular imaging, particularly cardiac magnetic resonance (CMR), may refine these recommendations. Feature-tracking CMR (FT-CMR) effectively assesses left ventricular (LV) strain and shows promise in predicting major adverse cardiovascular events (MACEs), though data on AS are limited. This study explored the role of CMR-derived LV strain in predicting MACEs occurrence in patients with severe AS. Method: We prospectively assessed 84 patients with severe AS and 84 matched controls. Global longitudinal (GLS), circumferential (GCS), and radial strain (GRS) were evaluated using FT-CMR. A composite endpoint-cardiac death, ventricular tachyarrhythmias, and heart failure hospitalization-was analyzed over a median follow-up of 31 months. Results: GLS was considerably reduced in AS patients (-15.8% vs. -19.7%, p < 0.001) and significantly predicted MACEs (HR = 1.24, p = 0.002) after adjusting for LVEF, 6 min walk distance, native T1, and late gadolinium enhancement. This underscores GLS's unique and robust predictive capability for MACEs in severe AS patients. Kaplan-Meier curves and ROC analysis both showed that GLS had the highest predictive performance for MACEs, with an AUC of 0.857. Conclusions: GLS provided independent incremental predictive value for outcome.

Changes and Prognostic Implications of Myocardial Work in Aortic Stenosis Subtypes Undergoing Transcatheter Valve Implantation

Background

Evaluation of left ventricle (LV) systolic function in patients with aortic stenosis (AS) undergoing transcatheter aortic valve implantation (TAVI) is challenging, as LV ejection fraction (LVEF) and global longitudinal strain are afterload dependent. LV global work indices (GWIs) estimate the afterload corrected systolic function.

Objectives

The purpose of this study was to evaluate changes in and prognostic implications of GWIs in subtypes of AS patients before and 1 month after TAVI.

Methods

We included 473 patients undergoing TAVI. GWI was estimated using strain imaging and by adding the aortic valve mean gradient to the systolic blood pressure. The primary endpoint was all-cause mortality, evaluated by Cox proportional hazards and Kaplan-Meier curves.

Results

High gradient, low flow/low gradient, and normal flow/low gradient AS was found in 48%, 27%, and 25%. In patients with LVEF ≥50% delta GWI decreased from preoperative assessment to 1-month follow-up across all subtypes; high gradient (-353 ± 589 mm Hg%, P < 0.01), low flow/low gradient (-151 ± 652 mm Hg%, P = 0.13), and normal flow/low gradient (-348 ± 606 mm Hg%, P < 0.01). For patients with LVEF <50% delta GWI increased; high gradient 127 ± 491 mm Hg%, P = 0.05; low flow/low gradient 106 ± 510 mm Hg%, P = 0.06; normal flow/low gradient 107 ± 550 mm Hg%, P < 0.27. The median follow-up time was 60 months (IQR: 45-69 months). Each step of 100 mm Hg% higher GWI at pre-TAVI assessment was associated with a reduction in all-cause mortality in multivariable analysis (HR: 0.96 [95% CI: 0.92-1.00], P = 0.033).

Conclusions

GWI increases in patients with reduced LVEF after TAVI across AS subtypes whereas GWI decreases in patients with preserved LVEF. Assessment of GWI offers additional prognostic implications beyond LVEF and global longitudinal strain.

Echocardiographic predictors of outcome in severe aortic stenosis patients with preserved or reduced ejection fraction

AIMS

Transcatheter aortic valve implantation (TAVI) has emerged as the treatment of choice for many patients with severe symptomatic aortic stenosis. We sought to identify the echocardiographic predictors of 30-day and 1-year outcomes after TAVI in patients with preserved or reduced left ventricular ejection fraction (LVEF).

METHODS

This single-centre study included 618 aortic stenosis patients (mean age 82 ± 6 years, 47.1% male; 74.8% LVEF > 50%) who underwent balloon-expandable TAVI between July 2009 and October 2018 in our hospital. All patients completed at least 6 months of follow-up by medical history review or telephone interview (median 24, quartiles 12-42 months). The primary endpoint was all-cause death.

RESULTS

All-cause mortality rate was 5.2% (LVEF > 50%: 4.3% vs. LVEF ≤ 50%: 7.7%, p = 0.141) at 30 days and 15.4% (LVEF > 50%: 14.7% vs. LVEF ≤ 50%: 17.3%, p = 0.443) at 12 months post TAVI. Overall all-cause mortality rate was 45.1% (LVEF > 50%: 44.6% vs. LVEF ≤ 50%: 46.8%, p = 0.643). Mean survival time post TAVI was 51 months [95% CI (48; 55)]. In TAVI patients with LVEF > 50%, multivariate Cox regression analysis revealed several independent predictors for increased risk of death after adjusting for echocardiographic and clinical covariates: TAPSE (≤ 17 vs. > 17 mm, HR 1.528, p = 0.016) and sPAP (> 30 vs. ≤ 30 mmHg, HR 1.900, p = 0.002) for overall mortality, E/E' septal for 30-day mortality (> 21 vs. ≤ 21, HR 14.462, p = 0.010) and 12-month mortality (> 21 vs. ≤ 21, HR 1.881, p = 0.026). In TAVI patients with LVEF ≤ 50%, no independent echocardiographic predictors for outcome could be identified.

CONCLUSIONS

LVEF is not a predictor of short- and long-term mortality after TAVI. In patients with preserved LVEF, left ventricular filling pressure (E/E´), systolic pulmonary artery pressure (sPAP), and TAPSE are echocardiographic risk factors for increased mortality post TAVI.

Transcatheter aortic valve replacement outcomes in patients with low-flow very low-gradient aortic stenosis

AIMS

In patients with severe aortic stenosis (AS), low-flow low-gradient (LG) is a known predictor of worse outcomes. However, very LG may represent a distinct population with further cardiac dysfunction. It is unknown whether this population benefits from transcatheter aortic valve replacement (TAVR). We aimed to describe the patient characteristics and clinical outcomes of low-flow very LG severe AS.

METHODS AND RESULTS

This single-centre study included all patients with low-flow severe AS between 2019 and 2021. Patients were divided into groups with very LG [mean pressure gradient (MPG) ≤ 20 mmHg], LG (20 < MPG < 40 mmHg), and high-gradient (HG) (MPG ≥ 40 mmHg). Composite endpoint of all-cause mortality and heart failure rehospitalization was compared. A total of 662 patients [very LG 130 (20%); LG 339 (51%); HG 193 (29%)] were included. Median follow-up was 12 months. Very LG cohort had a higher prevalence of comorbid conditions with lower left ventricular ejection fraction (45% vs. 57% vs. 60%; P < 0.001). There was a graded increase in the risk of composite endpoint in the lower MPG strata (P < 0.001). Among those who underwent TAVR, very LG was an independent predictor of the composite endpoint (adjusted HR 2.42 [1.29-4.55]). While LG and HG cohorts had decreased risk of composite endpoint after TAVR compared with conservative management, very LG was not associated with risk reduction (adjusted HR 0.69 [0.35-1.34]).

CONCLUSION

Low-flow very LG severe AS represents a distinct population with significant comorbidities and worse outcomes. Further studies are needed to evaluate the short- and long-term benefits of TAVR in this population.

Strain Assessment in Aortic Stenosis: Pathophysiology and Clinical Utility

Contemporary echocardiographic criteria for grading aortic stenosis severity have remained relatively unchanged, despite significant advances in noninvasive imaging techniques over the last 2 decades. More recently, attention has shifted to the ventricular response to aortic stenosis and how this might be quantified. Global longitudinal strain, semiautomatically calculated from standard two-dimensional echocardiographic images, has been the focus of extensive research. Global longitudinal strain is a sensitive marker of subtle hypertrophy-related impairment in left ventricular function and has shown promise as a relatively robust prognostic marker, both independently and when added to severity classification systems. Herein we review the pathophysiological basis underpinning the potential utility of global longitudinal strain in the assessment of aortic stenosis, as well as its potential role in quantifying myocardial recovery and prognostic discrimination following aortic valve replacement.

Right vs. left ventricular longitudinal strain for mortality prediction after transcatheter aortic valve implantation

Introduction

This study aims at exploring biventricular remodelling and its implications for outcome in a representative patient cohort with severe aortic stenosis (AS) undergoing transcatheter aortic valve implantation (TAVI).

Methods and results

Pre-interventional echocardiographic examinations of 100 patients with severe AS undergoing TAVI were assessed by speckle tracking echocardiography of both ventricles. Association with mortality was determined for right ventricular global longitudinal strain (RVGLS), RV free wall strain (RVFWS) and left ventricular global longitudinal strain (LVGLS). During a median follow-up of 1,367 [959-2,123] days, 33 patients (33%) died. RVGLS was lower in non-survivors [-13.9% (-16.4 to -12.9)] than survivors [-17.1% (-20.2 to -15.2); P = 0.001]. In contrast, LVGLS as well as the conventional parameters LV ejection fraction (LVEF) and RV fractional area change (RVFAC) did not differ (P = ns). Kaplan-Meier analyses indicated a reduced survival probability when RVGLS was below the -14.6% cutpoint (P < 0.001). Lower RVGLS was associated with higher mortality [HR 1.13 (95% CI 1.04-1.23); P = 0.003] independent of LVGLS, LVEF, RVFAC, and EuroSCORE II. Addition of RVGLS clearly improved the fitness of bivariable and multivariable models including LVGLS, LVEF, RVFAC, and EuroSCORE II with potential incremental value for mortality prediction. In contrast, LVGLS, LVEF, and RVFAC were not associated with mortality.

Discussion

In patients with severe AS undergoing TAVI, RVGLS but not LVGLS was reduced in non-survivors compared to survivors, differentiated non-survivors from survivors, was independently associated with mortality, and exhibited potential incremental value for outcome prediction. RVGLS appears to be more suitable than LVGLS for risk stratification in AS and timely valve replacement.