Echocardiographic Longitudinal Strain Analysis in Heart Failure: Real Usefulness for Clinical Management Beyond Diagnostic Value and Prognostic Correlations? A Comprehensive Review

Assessment of new-onset heart failure prediction in a diabetic population using left ventricular global strain: a prospective cohort study based on UK Biobank

Background

Impaired glucose utilization influences myocardial contractile function. However, the prognostic importance of left ventricular global radial strain (LV-GRS), left ventricular global circumferential strain (LV-GCS), and left ventricular global longitudinal strain (LV-GLS) in predicting new-onset heart failure (HF) in a population with diabetes is unclear.

Methods

The study design is prospective cohort from the UK Biobank. Totally 37,899 participants had a complete data of cardiac magnetic resonance (CMR), of which 940 patients with diabetes were included, and all the participants completed follow-up. LV-GRS, LV-GCS, and LV-GLS were measured by completely automated CMR with tissue tagging. Cox proportional hazards regression analysis and C-index was performed to evaluate the association between the strain parameters and the new-onset HF in patients suffering from diabetes.

Results

The average age of the 940 participants was 57.67 ± 6.97 years, with males comprising 66.4% of the overall population. With an average follow-up period of 166.82 ± 15.26 months, 35 (3.72%) patients reached the endpoint (emergence of new-onset HF). Significant associations were found for the three strain parameters and the new-onset HF (LV-GRS-hazard ratio [HR]: 0.946, 95% CI: 0.916-0.976; LV-GCS-HR: 1.162, 95% CI: 1.086-1.244; LV-GCS-HR: 1.181, 95% CI: 1.082-1.289). LV-GRS, LV-GCS, and LV-GLS were closely related to the related indicators to HF, and showed a high relationship to new-onset HF in individuals with diabetes at 5 and 10 years: LV-GRS: 0.75 (95% CI, 0.41-0.94) and 0.76 (95% CI, 0.44-0.98), respectively; LV-GCS: 0.80 (95% CI, 0.50-0.96) and 0.75 (95% CI, 0.41-0.98), respectively; LV-GLS: 0.72 (95% CI, 0.40-0.93) and 0.76 (95% CI, 0.48-0.97), respectively. In addition, age, sex, body mass index (BMI), and presence of hypertension or coronary artery disease (CAD) made no impacts on the association between the global strain parameters and the incidence of HF.

Conclusion

LV-GRS, LV-GCS, and LV-GLS is significantly related to new-onset HF in patients with diabetes at 5 and 10 years.

Cardiac Magnetic Resonance Feature-Tracking Identifies Preclinical Abnormalities in Hypertrophic Cardiomyopathy Sarcomere Gene Mutation Carriers

BACKGROUND

Assessing myocardial strain by cardiac magnetic resonance feature tracking (FT) has been found to be useful in patients with overt hypertrophic cardiomyopathy (HCM). Little is known, however, of its role in sarcomere gene mutation carriers without overt left ventricular hypertrophy (subclinical HCM).

METHODS

Thirty-eight subclinical HCM subjects and 42 healthy volunteers were enrolled in this multicenter case-control study. They underwent a comprehensive cardiac magnetic resonance study. Two-dimensional global radial, circumferential, and longitudinal strain of the left ventricle (LV) were evaluated by FT analysis.

RESULTS

The subclinical HCM sample was 41 (22-51) years old and 32% were men. FT analysis revealed a reduction in global radial strain (29±7.2 versus 47.9±7.4; P<0.0001), global circumferential strain (-17.3±2.6 -versus -20.8±7.4; P<0.0001) and global longitudinal strain (-16.9±2.4 versus -20.5±2.6; P<0.0001) in subclinical HCM compared with control subjects. The significant differences persisted when considering the 23 individuals free of all the structural and functional ECG and cardiac magnetic resonance abnormalities previously described. Receiver operating characteristic curve analyses showed that the differential diagnostic performances of FT in discriminating subclinical HCM from normal subjects were good to excellent (global radial strain with optimal cut-off value of 40.43%: AUC, 0.946 [95% CI, 0.93-1.00]; sensitivity 90.48%, specificity 94.44%; global circumferential strain with cut-off, -18.54%: AUC, 0.849 [95% CI, 0.76-0.94]; sensitivity, 88.10%; specificity, 72.22%; global longitudinal strain with cut-off, -19.06%: AUC, 0.843 [95% CI, 0.76-0.93]; sensitivity, 78.57%; specificity, 78.95%). Similar values were found for discriminating those subclinical HCM subjects without other phenotypic abnormalities from healthy volunteers (global radial strain with optimal cut-off 40.43%: AUC, 0.966 [95% CI, 0.92-1.00]; sensitivity, 90.48%; specificity, 95.45%; global circumferential strain with cut-off, -18.44%: AUC, 0.866 [95% CI, 0.76-0.96]; sensitivity, 92.86%; specificity, 77.27%; global longitudinal strain with cut-off, -17.32%: AUC, 0.838 [95% CI, 0.73-0.94]; sensitivity, 90.48%; specificity, 65.22%).

CONCLUSIONS

Cardiac magnetic resonance FT-derived parameters are consistently lower in subclinical patients with HCM, and they could emerge as a good tool for discovering the disease during a preclinical phase.

Childhood Cancer Survivors Have Impaired Strain-Derived Myocardial Contractile Reserve by Dobutamine Stress Echocardiography

Abnormal left ventricular contractile reserve (LVCR) is associated with adverse cardiac outcomes in different patient cohorts and might be useful in the detection of cardiomyopathy in childhood cancer survivors (CCS) after cardiotoxic treatment. The aim of this study was to evaluate LVCR by dobutamine stress echocardiography (DSE) combined with measures of myocardial strain in CCS previously treated with anthracyclines (AC). Fifty-three CCS (age 25.34 ± 2.44 years, 35 male) and 53 healthy controls (age 24.40 ± 2.40 years, 32 male) were included. Subjects were examined with echocardiography at rest, at low-dose (5 micrograms/kg/min), and at high-dose (40 micrograms/kg/min) dobutamine infusion. Left ventricular ejection fraction (LVEF) and global longitudinal strain (GLS), strain rate (GSR), and early diastolic strain rate (GEDSR) at different DSE phases were used as measures of LVCR. The mean follow-up time among CCS was 15.8 ± 5.8 years. GLS, GSR, and LVEF were lower at rest in CCS compared to controls (p ≤ 0.03). LVEF was within the normal range in CCS. ΔGLS, ΔGSR, and ΔGEDSR but not ΔLVEF were lower in CCS compared to controls after both low- (p ≤ 0.048) and high-dose dobutamine infusion (p ≤ 0.023). We conclude that strain measures during low-dose DSE detect impaired myocardial contractile reserve in young CCS treated with AC at 15-year follow-up. Thus, DSE may help identify asymptomatic CCS at risk for heart failure and allows for tailored follow-up accordingly.

Prognostic value of temporal patterns of global longitudinal strain in patients with chronic heart failure

Background

We investigated whether repeatedly measured global longitudinal strain (GLS) has incremental prognostic value over repeatedly measured left ventricular ejection fraction (LVEF) and N-terminal pro B-type natriuretic peptide (NT-proBNP), and a single "baseline" GLS value, in chronic heart failure (HF) patients.

Methods

In this prospective observational study, echocardiography was performed in 173 clinically stable chronic HF patients every six months during follow up. During a median follow-up of 2.7 years, a median of 3 (25th-75th percentile:2-4) echocardiograms were obtained per patient. The endpoint was a composite of HF hospitalization, left ventricular assist device, heart transplantation, cardiovascular death. We compared hazard ratios (HRs) for the endpoint from Cox models (used to analyze the first available GLS measurements) with HRs from joint models (which links repeated measurements to the time-to-event data).

Results

Mean age was 58 ± 11 years, 76% were men, 81% were in New York Heart Association functional class I/II, and all had LVEF < 50% (mean ± SD: 27 ± 9%). The endpoint was reached by 53 patients. GLS was persistently decreased over time in patients with the endpoint. However, temporal GLS trajectories did not further diverge in patients with versus without the endpoint and remained stable during follow-up. Both single measurements and temporal trajectories of GLS were significantly associated with the endpoint [HR per SD change (95%CI): 2.15(1.34-3.46), 3.54 (2.01-6.20)]. In a multivariable model, repeatedly measured GLS maintained its prognostic value while repeatedly measured LVEF did not [HR per SD change (95%CI): GLS:4.38 (1.49-14.70), LVEF:1.14 (0.41-3.23)]. The association disappeared when correcting for repeatedly measured NT-proBNP.

Conclusion

Temporal evolution of GLS was associated with adverse events, independent of LVEF but not independent of NT-proBNP. Since GLS showed decreased but stable values in patients with adverse prognosis, single measurements of GLS provide sufficient information for determining prognosis in clinical practice compared to repeated measurements, and temporal GLS patterns do not add prognostic information to NT-proBNP.

Subclinical dysfunction of remote myocardium is related to high NT-proBNP and affects global contractility at follow-up, independently of infarct area

Background

In ST-segment elevation myocardial infarction (STEMI), predictors of subclinical dysfunction of remote myocardium are unknown. We prospectively aimed at identifying clinical and biochemical correlates of remote subclinical dysfunction and its impact on left ventricular ejection fraction (LVEF).

Methods

One-hundred thirty-three patients (63.9 ± 12.1 years, 68% male) with first successfully treated (54% anterior, 46% non-anterior, p = 0.19) STEMI underwent echocardiography at 5 ± 2 days after onset and at 8 ± 2-month follow-up, and were compared to 13 age and sex-matched (63.3 ± 11.4) healthy controls. All 16 left ventricular (LV) segments were grouped into ischemic, border, and remote myocardium: mean value of longitudinal strain (LS) within grouped segments were expressed as iLS, bLS, rLS, respectively. LV end-diastolic (EDV), end-systolic (ESV) volumes indexed for body surface area (EDVi, ESVi, respectively), LVEF and global LS (GLS) were determined. Creatinine, glomerular filtration rate, admission level of NT-pro-brain-natriuretic peptide (NT-proBNP) and troponin peaks were considered for the analysis.

Results

At baseline, rLS (15.5 ± 4.4) was better than iLS (12.9 ± 4.8, p < 0.001), but lower than that in controls (19.1 ± 2.7, p < 0.001) and similar to bLS (15 ± 5.4, p = ns), and did not differ between patients with single or multivessel coronary artery disease (CAD). At multivariate regression analysis, only admission NT-proBNP levels but not peak Tn levels independently predicted rLS (β = -0.58, p = 0.001), as well as iLS (β = -0.52, p = 0.001). Both at baseline and at follow-up, rLS correlated to LVEF similarly to iLS and bLS (p < 0.001 for all). Median value of rLS at baseline was 15%: compared to patients with rLS ≥ 15% at baseline, patients with rLS < 15% showed lower LVEF (52.3 ± 9.4 vs. 58.6 ± 7.6, p < 0.001) and GLS (16.3 ± 3.9 vs. 19.9 ± 3.2), and higher EDVi (62.3 ± 19.9 vs. 54 ± 12, p = 0.009) and ESVi (30.6 ± 15.5 vs. 22.3 ± 7.6, p < 0.001) at follow-up.

Conclusion

In optimally treated STEMI, dysfunction of remote myocardium assessed by LS: (1) is predicted by elevated NT-proBNP; (2) could be independent of CAD extent and infarct size; (3) is associated to worse LV morphological and functional indexes at follow-up.

Takotsubo cardiomyopathy Afatinib-related in a non-small cell lung cancer patient: Case report

Endothelial Growth Factor Receptor (EGFR) mutations are frequently found among NSCLC patients. Second-generation Tyrosine Kinase Inhibitor (TKI) Afatinib is frequently used in this population of patients achieving better results than cytotoxic chemotherapy in terms of survival and progression. Afatinib-related cardiotoxicity has been rarely reported. Here we comment on a clinical case of a Takotsubo Cardiomyopathy Afatinib-induced in an NSCLC patient.

Echocardiographic strategy for early detection of cardiotoxicity of doxorubicin: a prospective observational study

Background

Cancer chemotherapy using anthracyclines is associated with cardiotoxicity (CTX), and left ventricular ejection fraction (LVEF) analysis is not sensitive to early cardiotoxic changes. Left ventricular global longitudinal strain (LV GLS) monitoring helps screen subclinical CTX; however, the intervals at which it should be performed remain unclear. We aimed to evaluate the incidence of CTX in women with breast cancer and the associated factors and compare two echocardiographic monitoring strategies using two cutoff points for LV GLS variation.

Methods

Patients with breast cancer prescribed doxorubicin underwent serial LVEF and LV GLS assessments using two-dimensional echocardiography every 3 weeks for 6 months.

Results

We included 43 women; none developed a clinical CTX. Considering a relative reduction of LV GLS > 15%, subclinical CTX was present in 12 (27.9%) and six (14%) patients at 3-week and 3-month intervals, respectively (P = 0.28). Additionally, considering a reduction of > 12%, subclinical CTX was present in 17 (39.5%) and 10 (23.3%) patients (P = 0.16), respectively. There were no significant differences in either reference value at 3-week (P = 0.19) and 3-month intervals (P = 0.41). Age ≥ 60 years (P = 0.018) and hypertension (HTN) (P = 0.022) were associated with subclinical CTX in the univariate analysis.

Conclusions

There was no difference in the incidence of subclinical CTX between the two cutoff points and no benefit in performing echocardiography every 3 weeks compared with quarterly monitoring. Advanced age and HTN were associated with the development of subclinical CTX.

Making Artificial Intelligence Lemonade Out of Data Lemons: Adaptation of a Public Apical Echo Database for Creation of a Subxiphoid Visual Estimation Automatic Ejection Fraction Machine Learning Algorithm

OBJECTIVES

A paucity of point-of-care ultrasound (POCUS) databases limits machine learning (ML). Assess feasibility of training ML algorithms to visually estimate left ventricular ejection fraction (EF) from a subxiphoid (SX) window using only apical 4-chamber (A4C) images.

METHODS

Researchers used a long-short-term-memory algorithm for image analysis. Using the Stanford EchoNet-Dynamic database of 10,036 A4C videos with calculated exact EF, researchers tested 3 ML training permeations. First, training on unaltered Stanford A4C videos, then unaltered and 90° clockwise (CW) rotated videos and finally unaltered, 90° rotated and horizontally flipped videos. As a real-world test, we obtained 615 SX videos from Harbor-UCLA (HUCLA) with EF calculations in 5% ranges. Researchers performed 1000 randomizations of EF point estimation within HUCLA EF ranges to compensate for ML and HUCLA EF mismatch, obtaining a mean value for absolute error (MAE) comparison and performed Bland-Altman analyses.

RESULTS

The ML algorithm EF mean MAE was estimated at 23.0, with a range of 22.8-23.3 using unaltered A4C video, mean MAE was 16.7, with a range of 16.5-16.9 using unaltered and 90° CW rotated video, mean MAE was 16.6, with a range of 16.3-16.8 using unaltered, 90° CW rotated and horizontally flipped video training. Bland-Altman showed weakest agreement at 40-45% EF.

CONCLUSIONS

Researchers successfully adapted unrelated ultrasound window data to train a POCUS ML algorithm with fair MAE using data manipulation to simulate a different ultrasound examination. This may be important for future POCUS algorithm design to help overcome a paucity of POCUS databases.

Left atrial remodeling in heart failure: the role of sphericity index (the SPHERICAT-HF study)

Left atrial sphericity index (LASI) is an echocardiographic index easily obtained; its use in patients with heart failure (HF) has never been investigated so far. This single-centre study aimed to investigate the usefulness of LASI in an unselected cohort of patients hospitalized for acute HF, and its potential correlation with the amino-terminal portion of pro-B-type natriuretic peptide (NT-proBNP) levels and with New York Heart Association (NYHA) functional class. Ninety-four consecutive HF patients underwent a transthoracic echocardiogram with a detailed study of the left atrium (LA) including LASI (calculated from the apical four-chamber view as the ratio between the transverse and longitudinal diameters), and blood tests (including NT-proBNP) on the same day. Median age was 75.5 (interquartile range-IQR 62-82) years and 55% were males, 58.5% had a NYHA class III-IV, and median NT-proBNP was 3284 (IQR 1215-7055) pg/ml. The LA was dilated in 94%, and median biplane LA volume index was 62 ml/m2. Patients with advanced NYHA class showed more advanced LA remodeling. Mean LASI was 0.78 ± 0.09 and did not correlate with NT-proBNP levels (r 0.03; p 0.75) or with patient NYHA class (R2 0.011; p 0.287). None of the echocardiographic indices of LA structural and functional remodeling proved to be independently associated with a high NYHA class on multivariate regression analysis. In conclusion, LA remodeling is almost invariably present in patients with HF. LASI does not correlate with NT-proBNP levels or with NYHA functional class. Further studies are needed to describe the complex patterns of atrial remodeling in HF.

Effects of Hypertrophic and Dilated Cardiac Geometric Remodeling on Ejection Fraction

Background: Both heart failure (HF) with preserved ejection fraction (HFpEF) and heart failure with reduced ejection fraction (HFrEF) can present a wide variety of cardiac morphologies consequent to cardiac remodeling. We sought to study if geometric changes to the heart during such remodeling will adversely affect the ejection fraction (EF) parameter’s ability to serve as an indicator of heart function, and to identify the mechanism for it.

Methods and Results: A numerical model that simulated the conversion of myocardial strain to stroke volume was developed from two porcine animal models of heart failure. Hypertrophic wall thickening was found to elevate EF, while left ventricle (LV) dilation was found to depress EF when myocardial strain was kept constant, causing EF to inaccurately represent the overall strain function. This was caused by EF being calculated using the endocardial boundary rather than the mid-wall layer. Radial displacement of the endocardial boundary resulted in endocardial strain deviating from the overall LV strain, and this deviation varied with LV geometric changes. This suggested that using the epi- or endo-boundaries to calculate functional parameters was not effective, and explained why EF could be adversely affected by geometric changes. Further, when EF was modified by calculating it at the mid-wall layer instead of at the endocardium, this shortcoming was resolved, and the mid-wall EF could differentiate between healthy and HFpEF subjects in our animal models, while the traditional EF could not.

Conclusion: We presented the mechanism to explain why EF can no longer effectively indicate cardiac function during cardiac geometric changes relevant to HF remodeling, losing the ability to distinguish between hypertrophic diseased hearts from healthy hearts. Measuring EF at the mid-wall location rather than endocardium can avoid the shortcoming and better represent the cardiac strain function.

Machine learning algorithm using publicly available echo database for simplified “visual estimation” of left ventricular ejection fraction

BACKGROUND

Left ventricular ejection fraction calculation automation typically requires complex algorithms and is dependent of optimal visualization and tracing of endocardial borders. This significantly limits usability in bedside clinical applications, where ultrasound automation is needed most.

AIM

To create a simple deep learning (DL) regression-type algorithm to visually estimate left ventricular (LV) ejection fraction (EF) from a public database of actual patient echo examinations and compare results to echocardiography laboratory EF calculations.

METHODS

A simple DL architecture previously proven to perform well on ultrasound image analysis, VGG16, was utilized as a base architecture running within a long short term memory algorithm for sequential image (video) analysis. After obtaining permission to use the Stanford EchoNet-Dynamic database, researchers randomly removed approximately 15% of the approximately 10036 echo apical 4-chamber videos for later performance testing. All database echo examinations were read as part of comprehensive echocardiography study performance and were coupled with EF, end systolic and diastolic volumes, key frames and coordinates for LV endocardial tracing in csv file. To better reflect point-of-care ultrasound (POCUS) clinical settings and time pressure, the algorithm was trained on echo video correlated with calculated ejection fraction without incorporating additional volume, measurement and coordinate data. Seventy percent of the original data was used for algorithm training and 15% for validation during training. The previously randomly separated 15% (1263 echo videos) was used for algorithm performance testing after training completion. Given the inherent variability of echo EF measurement and field standards for evaluating algorithm accuracy, mean absolute error (MAE) and root mean square error (RMSE) calculations were made on algorithm EF results compared to Echo Lab calculated EF. Bland-Atlman calculation was also performed. MAE for skilled echocardiographers has been established to range from 4% to 5%.

RESULTS

The DL algorithm visually estimated EF had a MAE of 8.08% (95%CI 7.60 to 8.55) suggesting good performance compared to highly skill humans. The RMSE was 11.98 and correlation of 0.348.

CONCLUSION

This experimental simplified DL algorithm showed promise and proved reasonably accurate at visually estimating LV EF from short real time echo video clips. Less burdensome than complex DL approaches used for EF calculation, such an approach may be more optimal for POCUS settings once improved upon by future research and development.