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

Sanna, Giuseppe D; Canonico, Mario Enrico; Santoro, Ciro; Esposito, Roberta; Masia, Sara; Galderisi, Maurizio; Nihoyannopoulos, Petros

doi:10.1007/s11897-021-00530-1

Cited by 18 publications

(19 citation statements)

References 85 publications

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“…Currently, there is a contradictory observation between the LV global flow function indicated by the LVEF and LV myocardial contractility indicated by the global strains in HFpEF or hypertrophic LV patients. A few studies show that LV strain, especially the global longitudinal strain (GLS) could be a sensitive predictor for HFpEF than LVEF ( Kraigher-Krainer et al, 2014 ; Hasselberg et al, 2015 ; Tadic et al, 2017 ; Potter and Marwick, 2018 ; Sanna et al, 2021 ), even in HFrEF patients ( Mignot et al, 2010 ; Sengeløv et al, 2015 ; Park et al, 2018 ). Meanwhile, Kim et al‘s study suggested that global circumferential strain (GCS) was a better predictor than GLS or global radial strain (GRS) in HFpEF ( Kim et al, 2020 ).…”

Section: Introductionmentioning

confidence: 99%

Effects of Hypertrophic and Dilated Cardiac Geometric Remodeling on Ejection Fraction

et al. 2022

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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.

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Section: Introductionmentioning

confidence: 99%

Effects of Hypertrophic and Dilated Cardiac Geometric Remodeling on Ejection Fraction

et al. 2022

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“…With the use of 2-D M-Mode echocardiography, fractional shortening rate is an easy and reliable measure that represents the contractile function of the left ventricle [ 28 ]. Using 2-D speckle tracking software, the longitudinal strain rate is a useful echocardiographic technique to evaluate left ventricular dysfunction by recording data on systolic and diastolic functioning [ 29 ]. The longitudinal strain has been observed to detect left ventricular dysfunction earlier in cancer patients than changes in LVEF [ 30 ].…”

Section: Reviewmentioning

confidence: 99%

Potential Therapeutic Treatments for Doxorubicin-Induced Cardiomyopathy

Kabir¹,

Lingappa²,

Mayrovitz³

2022

Cureus

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Doxorubicin (DOX) is an anthracycline antibiotic used to treat many cancers, including breast cancer, leukemia, and Hodgkin's lymphoma. Positive aspects of DOX use are limited by the cardiomyopathy that it may cause. For this reason, it is crucial to uncover effective treatments against DOX-induced cardiomyopathy (DIC). Oxidative stress plays a pivotal role in DIC, and this understanding has helped guide potential treatments for DIC. The purpose of this study was to review and describe current and emerging treatments for DIC and their potential cardioprotective effects against DIC. The goals were to: (1) provide a single-source report to aid clinicians in exploring different treatment plans that are personalized for their patients and (2) stimulate researchers to consider evaluating promising and emerging treatment modalities. Evolving understanding of DIC pathophysiology remains fundamental in elucidating the course for future medical therapies. The main conclusion of this study was that the use of existing pharmaceutical agents might represent a possible approach towards mitigating DIC with more extensive clinical data. A limitation of all reviewed studies was that none included an experimental model in which DOX was used to treat animals with preexisting cancer. This limitation fails to identify the impacts that cancer may play in DIC pathophysiology and the potential mitigating effects of DIC treatments. Future research should consider this limitation with appropriately revised protocols.

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“…Magnetic resonance imaging, while providing high accuracy, is logistically difficult to perform in most urgent or emergent situations[ 3 , 4 ]. The resultant effective criterion standard is EF calculation by comprehensive 2-D echocardiography, typically using the modified Simpson’s rule[ 5 ]. However, despite ultrasound’s lower cost and greater accessibility than MRI, and the potential for bedside imaging by an echocardiography tech, results are typically delayed by hours to days after examination performance.…”

Section: Introductionmentioning

confidence: 99%

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

Blaivas¹,

Blaivas²

2022

WJEM

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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.

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

Cited by 18 publications

References 85 publications

Effects of Hypertrophic and Dilated Cardiac Geometric Remodeling on Ejection Fraction

Effects of Hypertrophic and Dilated Cardiac Geometric Remodeling on Ejection Fraction

Potential Therapeutic Treatments for Doxorubicin-Induced Cardiomyopathy

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

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