Quantitative Assessment of Left and Right Atrial Strains Using Cardiovascular Magnetic Resonance Based Tissue Tracking

Qu, Yangyang; Buckert, Dominik; Ma, Genshan; Rasche, Volker

doi:10.3389/fcvm.2021.690240

Cited by 20 publications

(19 citation statements)

References 27 publications

(48 reference statements)

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“…Whereas some studies claim that there is a correlation between the heart rate and aggravation in atrial contraction, some other studies refute this notion (27,46). According to our results, an increase in age was correlated with an increase in the RA contraction function; be that as it may, this association cannot be considered etiologic because what we sought to determine was the source of heterogeneity between studies.…”

Section: Ra Stementioning

confidence: 46%

Normal Ranges of Right Atrial Strain and Strain Rate by Two-Dimensional Speckle-Tracking Echocardiography: A Systematic Review and Meta-Analysis

Hosseinsabet

Mahmoudian

Jalali

et al. 2021

Front. Cardiovasc. Med.

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Background: Normal range values of right atrial (RA) phasic function markers are essential for the identification of normal and abnormal values, comparison with reference values, and the clinical meaning of obtained values. Accordingly, we aimed to define the normal range values of RA phasic function markers obtained by 2D speckle-tracking echocardiography through a meta-analysis and determine the main sources of heterogeneity among reported values.Methods: PUBMED, SCOPUS, and EMBASE databases were searched for the following keywords: “right atrial/right atrium” and “strain/speckle/deformation” and “echocardiography.” Studies were selected that included a human healthy adult group without any cardiovascular diseases or risk factors and that were written in the English language. For the calculation of each marker of RA phasic functions, a random-effect model was used. Meta-regression was employed to define the major sources of variabilities among reported values.Results: Fifteen studies that included 2,469 healthy subjects were selected for analysis. The normal range values for RA strain and strain rate were 42.7% (95% CI, 39.4 to 45.9%) and 2.1 s−1 (95% CI, 2.0 to 2.1 s−1) during the reservoir phase, respectively, 23.6% (95% CI, 20.7 to 26.6%) and −1.9 s−1 (95% CI, −2.2 to −1.7 s−1) during the conduit phase, correspondingly, and 16.1% (95% CI, 13.6 to 18.6%) and −1.8 s−1 (95% CI, −2.0 to −1.5 s−1) during the contraction phase, respectively. The sources of heterogeneity for the normal range of these markers were the number of participants, the type of software, the method of global value calculation, the right ventricular fractional area change, the left ventricular (LV) ejection fraction, the RA volume index, sex, the heart rate, the diastolic blood pressure, the body mass index, and the body surface area.Conclusions: Using 2D speckle-tracking echocardiography, we defined normal values for RA phasic function markers and identified the sources of heterogeneity as demographic, anthropometric, hemodynamic, and echocardiography factors.Systematic Review Registration:https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021236578, identifier: CRD42021236578.

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Section: Ra Stementioning

confidence: 46%

Normal Ranges of Right Atrial Strain and Strain Rate by Two-Dimensional Speckle-Tracking Echocardiography: A Systematic Review and Meta-Analysis

Hosseinsabet

Mahmoudian

Jalali

et al. 2021

Front. Cardiovasc. Med.

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“…Of the clinical covariates, male sex, atrial fibrillation, and a NYHA class of > II were univariable predictors of all-cause mortality ( Table 4 ). Since previous research showed that RA and RV strain values differ between males and females ( 18 ), a sub-analysis was performed to evaluate whether the correlation of RA strain with all-cause mortality differed between the sexes. In female patients ( n = 58), RA reservoir and conduit strain were predictors of all-cause mortality ( n = 9, data not shown).…”

Section: Resultsmentioning

confidence: 99%

The Prognostic Value of Right Atrial and Right Ventricular Functional Parameters in Systemic Sclerosis

Vos

Butcher

Fortuni

et al. 2022

Front. Cardiovasc. Med.

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IntroductionRight ventricular (RV) function is of particular importance in systemic sclerosis (SSc), since common SSc complications, such as interstitial lung disease and pulmonary hypertension may affect RV afterload. Cardiovascular magnetic resonance (CMR) is the gold standard for measuring RV function. CMR-derived RV and right atrial (RA) strain is a promising tool to detect subtle changes in RV function, and might have incremental value, however, prognostic data is lacking. Therefore, the aim of this study was to evaluate the prognostic value of RA and RV strain in SSc.MethodsIn this retrospective study, performed at two Dutch hospitals, consecutive SSc patients who underwent CMR were included. RV longitudinal strain (LS) and RA strain were measured. Unadjusted cox proportional hazard regression analysis and likelihood ratio tests were used to evaluate the association and incremental value of strain parameters with all-cause mortality.ResultsA total of 100 patients (median age 54 [46–64] years, 42% male) were included. Twenty-four patients (24%) died during a follow-up of 3.1 [1.8–5.2] years. RA reservoir [Hazard Ratio (HR) = 0.95, 95% CI 0.91–0.99, p = 0.009] and conduit strain (HR = 0.93, 95% CI 0.88–0.98, p = 0.008) were univariable predictors of all-cause mortality, while RV LS and RA booster strain were not. RA conduit strain proved to be of incremental value to sex, atrial fibrillation, NYHA class, RA maximum volume indexed, and late gadolinium enhancement (p < 0.05 for all).ConclusionRA reservoir and conduit strain are predictors of all-cause mortality in SSc patients, whereas RV LS is not. In addition, RA conduit strain showed incremental prognostic value to all evaluated clinical and imaging parameters. Therefore, RA conduit strain may be a useful prognostic marker in SSc patients.

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“…Further work to evaluate AI metrics in risk stratification is required as has been achieved for RV measurements [ 33 ]. In addition further work will be to clinically evaluate the range of physiological parameters that can be extracted from the AI segmentations, such as RA strain [ 36 , 37 ] and potentially reservoir and conduit function [ 38 , 39 ]. RHC measurements correlated strongly with AI RA measurements, indicating AI metrics may provide physiologically accurate measure of pathophysiological changes in the heart given their high consistency and repeatability.…”

Section: Discussionmentioning

confidence: 99%

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements

Alandejani

Alabed

Garg

et al. 2022

Journal of Cardiovascular Magnetic Resonance

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Background Right atrial (RA) area predicts mortality in patients with pulmonary hypertension, and is recommended by the European Society of Cardiology/European Respiratory Society pulmonary hypertension guidelines. The advent of deep learning may allow more reliable measurement of RA areas to improve clinical assessments. The aim of this study was to automate cardiovascular magnetic resonance (CMR) RA area measurements and evaluate the clinical utility by assessing repeatability, correlation with invasive haemodynamics and prognostic value. Methods A deep learning RA area CMR contouring model was trained in a multicentre cohort of 365 patients with pulmonary hypertension, left ventricular pathology and healthy subjects. Inter-study repeatability (intraclass correlation coefficient (ICC)) and agreement of contours (DICE similarity coefficient (DSC)) were assessed in a prospective cohort (n = 36). Clinical testing and mortality prediction was performed in n = 400 patients that were not used in the training nor prospective cohort, and the correlation of automatic and manual RA measurements with invasive haemodynamics assessed in n = 212/400. Radiologist quality control (QC) was performed in the ASPIRE registry, n = 3795 patients. The primary QC observer evaluated all the segmentations and recorded them as satisfactory, suboptimal or failure. A second QC observer analysed a random subcohort to assess QC agreement (n = 1018). Results All deep learning RA measurements showed higher interstudy repeatability (ICC 0.91 to 0.95) compared to manual RA measurements (1st observer ICC 0.82 to 0.88, 2nd observer ICC 0.88 to 0.91). DSC showed high agreement comparing automatic artificial intelligence and manual CMR readers. Maximal RA area mean and standard deviation (SD) DSC metric for observer 1 vs observer 2, automatic measurements vs observer 1 and automatic measurements vs observer 2 is 92.4 ± 3.5 cm2, 91.2 ± 4.5 cm2 and 93.2 ± 3.2 cm2, respectively. Minimal RA area mean and SD DSC metric for observer 1 vs observer 2, automatic measurements vs observer 1 and automatic measurements vs observer 2 was 89.8 ± 3.9 cm2, 87.0 ± 5.8 cm2 and 91.8 ± 4.8 cm2. Automatic RA area measurements all showed moderate correlation with invasive parameters (r = 0.45 to 0.66), manual (r = 0.36 to 0.57). Maximal RA area could accurately predict elevated mean RA pressure low and high-risk thresholds (area under the receiver operating characteristic curve artificial intelligence = 0.82/0.87 vs manual = 0.78/0.83), and predicted mortality similar to manual measurements, both p < 0.01. In the QC evaluation, artificial intelligence segmentations were suboptimal at 108/3795 and a low failure rate of 16/3795. In a subcohort (n = 1018), agreement by two QC observers was excellent, kappa 0.84. Conclusion Automatic artificial intelligence CMR derived RA size and function are accurate, have excellent repeatability, moderate associations with invasive haemodynamics and predict mortality.

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Quantitative Assessment of Left and Right Atrial Strains Using Cardiovascular Magnetic Resonance Based Tissue Tracking

Cited by 20 publications

References 27 publications

Normal Ranges of Right Atrial Strain and Strain Rate by Two-Dimensional Speckle-Tracking Echocardiography: A Systematic Review and Meta-Analysis

Normal Ranges of Right Atrial Strain and Strain Rate by Two-Dimensional Speckle-Tracking Echocardiography: A Systematic Review and Meta-Analysis

The Prognostic Value of Right Atrial and Right Ventricular Functional Parameters in Systemic Sclerosis

Training and clinical testing of artificial intelligence derived right atrial cardiovascular magnetic resonance measurements

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