bluuebunny/crossref_metadata_2025_split huggingface dataset:
Natural shear wave imaging outperforms conventional echocardiographic parameters in detecting elevated left ventricular filling pressures
Authors: Youssef A , Desmet W , Castaldi G , Frederiks P , Dhooge J , Voigt J U 
Published: January 2025

Abstract

Background
Current conventional echocardiographic assessment of diastolic function relies on predicting left ventricular (LV) filling pressure as a surrogate of diastolic function. However, the current guidelines algorithm for estimation of LV filling pressures is complex. High frame rate (HFR) Shear wave (SW) imaging is emerging as a novel parameter for assessing myocardial stiffness, a key determinant of diastolic function. Natural SW can be induced, e.g., by mitral valve closure (MVC) and their propagation speed is directly related to myocardial stiffness. Little is known, however, to what extent SW after MVC can reflect diastolic LV filling pressures.

Purpose
We aimed at investigating the relationship between natural SW and LV diastolic filling pressures in comparison to conventional echocardiographic parameters.

Methods
Thirty patients (mean age 68.4±9.9 years) scheduled for clinically indicated left heart catheterization were prospectively recruited irrespective of diastolic function status. Conventional as well as HFR echocardiography (ca. 1200 frames/second) was performed immediately after the catheterization. We tracked SW occurring after MVC along the ventricular septum in the parasternal long axis view using an anatomical M-mode from base to apex colour coded for tissue acceleration. SW appeared immediately after as tilted green bands and their propagation velocity was measured semi-automatically (Figure 1).

Results
In our cohort, the LV mid-diastolic pressure (LVMDP) ranged from 5 to 19 mmHg, while the LV end-diastolic pressure (LVEDP) ranged from 7.5 to 29.5 mmHg. LV filling pressures were considered elevated if exceed 15 mmHg for LVMDP and 16 mmHg for LVEDP. Out of the conventional echocardiographic parameters, only mitral inflow to mitral relaxation velocity ratio (E/e’) correlated moderately with LV filling pressures (r=0.47, p=0.009 for LVMDP; and r=0.49, p=0.006 for LVEDP) (Figure 2 A,B). The accuracy of the conventional E/e’ cut-off value of 14 to predict elevated LV filling pressure is 76% for LVMDP and 70% for LVEDP (Figure 2C). SW velocities after MVC correlated strongly with diastolic LV pressures (r=0.65, p&lt;0.001 for LVMDP; r=0.78, p&lt;0.001 for LVEDP) (Figure 2 D,E). Interestingly, a cut-off value for SW velocity of 5.8 m/s showed an excellent ability to discriminate raised LVMDP (AUC: 0.93; sensitivity: 80%, specificity: 80%, accuracy: 80%) and elevated LVEDP (AUC: 0.96 ; Sensitivity: 89%, specificity: 95%, accuracy: 93%) (Figure 2F).

Conclusions
Our preliminary data showed that SW velocities at end-diastole are strongly related to LV filling pressures and can predict elevated LV filling pressures more accurately than conventional echocardiographic parameters. This ongoing study shows the potential of natural shear wave imaging as a promising innovative tool for assessment of diastolic function.
Figure 1
Figure 2
External validation of automated deep-learning based echocardiogram analysis
Authors: Merin R , Gvili-Perelman M , Tzuberi M , Merin H , Topilsky Y , Flint N 
Published: January 2025

Abstract

Background
The use of artificial intelligence (AI) in echocardiography is constantly expanding. Several AI algorithms now enable fully automated measurement of echocardiographic parameters, which can potentially reduce measurement variability and increase efficiency. These AI algorithms have demonstrated accuracy comparable to conventional human-based measurements. However, to adopt automated AI echocardiography analysis for routine use, we need a deeper understanding of its performance compared with that of human expert readers.

Purpose
This study aims to perform a real-world external validation of a commercial, fully automated AI algorithm by comparing its performance standard to echocardiographic measurements done by human experts.

Methods
We retrospectively analyzed 889 consecutive hospitalized patients who underwent a clinically indicated transthoracic echocardiographic study. Each study was performed by experienced cardiac sonographers and reviewed by expert echo cardiologists. All studies were also analyzed by a commercial, fully automated AI software (Us2.AI). We analyzed the correlation between standard echocardiographic parameters measured by human experts to those measured by the AI algorithm.

Results
Of the 889 patients, 731 (82%) had sufficient echocardiographic data to be included in the analysis (mean age 68±16, 46% Female). As shown in Table 1, the measures with the strongest correlation were E wave velocity (r=0.96, P&lt;0.001), E/e' ratio (r=0.86, P&lt;0.001), and systolic pulmonary artery pressure (r=0.88, P&lt;0.001) whereas posterior wall thickness and left ventricular ejection fraction (LVEF) had lower correlation coefficients (r=0.52 and r=0.61, respectively, both P&lt;0.001). On Bland-Altman plot (Figure 1), mean AI-obtained LVEF values were significantly higher compared to human-estimated LVEF values with a mean difference of 5.8. This discrepancy was specifically evident in cases where the human-based LVEF was 45% or higher.

Conclusion
In this external validation study, AI-based echocardiographic measurements showed a strong correlation with human-based measurements. LVEF values obtained by AI tended to be higher than human LVEF estimation.
Correlation of echocardiographic measure
Bland Altman for LV EF
How can we more efficiently train new users of echocardiography?
Authors: Stowell C , Lane B , Francis D , Shun-Shin M 
Published: January 2025

Abstract

Background/Introduction
Improving uptake and accessibility of echocardiography necessitates more efficient training. Current training programmes are focused around expert mentorship, clinical practicals, and lectures. All of these are resource-intensive, and difficult to scale.
Research into the way humans learn has consistently found that techniques such as spaced testing and interleaving of subjects, deliver superior retention - even of complex topics. These can be most easily and cost-effectively delivered online.

Purpose
To test how quickly students learn using an online platform, utilising contemporary teaching methods, made freely available to individuals within the NHS.

Methods
We designed our platform to facilitate interactive questioning of medical images, and performing interpretive and measurement tasks within echocardiography (Picture 1).
We piloted it in two phases. In phase one, to establish the acquisition of knowledge and skills without our platform, we recruited non-cardiology trainee doctors with daily access to a handheld cardiac ultrasound device, but without formal teaching. They received 5 consecutive 21-question quizzes, delivered by email and text at weekly intervals. Each quiz was balanced to include knowledge questions, such as anatomy identification; and interpretive questions, including grading ventricular function, chamber size, and valve disease severity. No feedback was provided. To provide a benchmark, 3 experts undertook the same quizzes.
In phase two, we opened up to anyone interested in learning echocardiography. In addition to the optimised quizzes, these participants received daily 21-question training modules.

Results
7 participants enrolled in phase one. They showed no improvement in test performance across the 5 weeks (+2% per week, 95% CI -2% to 6%, p=0.33). Questions which proved to be properly constructed (scores of 100% for experts) yet "too easy" (scores of 90% or higher for learners) were eliminated, and not used for the testing phase.
12 participants enrolled in phase two. All worked through the modules at their own pace (of those who did all 19 quizzes, time taken ranged from 6.6 to 15.6 weeks; median 14.3 weeks). Participants showed significant improvement over time (+11% per week, 95% CI, p&lt;0.001). Those who took the quizzes later into any training programmes they were undertaking in parallel did not outperform those who took them earlier (p=0.89).
For LV function, participants showed little improvement over time (+9% per week, 95% CI -13% to +51%, p=0.23); but after undertaking a 5-quiz module on LV function, test scores increased 36% (95% CI 0% to 74%, p=0.05) from the previous week.

Conclusions
Our findings suggest that key skills in echocardiography can be efficiently learnt outside of the lecture theatre or clinical environment. Furthermore, precious time spent in the echo lab or on clinical placement might be more efficiently utilised by completing our online modules ahead of time.
Clinical validation of a novel fully automated measurement method for echocardiographic mechanical dispersion using deep learning
Authors: Melichova D , Nyberg J , Nguyen T M , Salte I M , Brunvand H , Haugaa K H , Edvardsen T , Dalen H , Lovstakken L , Ostvik A , Grenne B 
Published: January 2025

Abstract

Background
Evaluation of left ventricular (LV) function by strain echocardiography and mechanical dispersion (MD) has demonstrated improved prediction of ventricular arrhythmia in patients with heart failure (HF) and reduced ejection fraction. However, analyzing MD is both time consuming and operator dependent, thus its clinical use remains limited. Fully automated measurements of MD using a novel deep learning (DL) method may be a solution to facilitate clinical implementation.

Purpose
We aimed to validate a novel DL based method for fully automated measurements of MD, by evaluating its correlation and agreement with manual reference measurements in a large cohort of patients with heart failure and left ventricular ejection fraction (LVEF) &lt;40%.

Methods
In this prospective multicenter follow-up study, we consecutively included patients with recently diagnosed heart failure of all causes with LVEF ≤ 40%. All patients were treated according to contemporary guidelines with optimal medical therapy and revascularization if necessary. Two experienced cardiologists recorded all echocardiograms using Vivid E9 or E95 scanners (GE HealthCare, Horten, Norway). Measurements of MD were performed both by an experienced cardiologist using a commercial semi-automatic method, and an in-house developed fully automated deep learning-based method.

Results
MD was measured in 200 patients (73 ± 14 years old, 33% females). Mean LVEF was 32% ± 6. Mean MD by reference measurements was 61 ± 17ms and by the deep learning method 63 ± 19 ms . Deep learning-based measurements of MD had excellent agreement with reference, with bias of 2ms and Limits of Agreement only 28ms (Figure 1). The correlation between methods was good, with R2 46%, p&lt;0.001. Calculation time for automated measurements of MD per patient was only 6.4 ± 2.5 seconds per echocardiogram.

Conclusion
The novel fully automated deep learning-based method provides rapid measurements of MD and excellent agreement with manual reference measurements, and may thus facilitate clinical implementation of MD for improved risk stratification in patients with HF.
Agreement between automated echocardiography and expert cardiologist for aortic valve hemodynamic parameters in severe aortic stenosis patients
Authors: Abramikas Z , Kazukauskiene I , Sablauskas K , Cesnaite G , Vrublevska G , Pugaciauskaite K , Balciunaite G , Glaveckaite S 
Published: January 2025

Abstract

Background
Aortic stenosis is one of the leading valve diseases. Transthoracic echocardiography (TTE) is the primary imaging technique for diagnosing aortic stenosis, providing comprehensive evaluations of valve hemodynamics and cardiac remodeling. However, it is time-consuming and requires significant expertise. While automated echocardiographic tools hold promise in potentially streamlining diagnostic processes and reducing measurement variability, their accuracy and reliability relative to expert cardiologist measurements require validation.

Purpose
To assess the agreement of aortic valve (AV) hemodynamic parameters derived from automated echocardiography analysis software compared to measurements performed by experienced cardiologists.

Methods
Fifty-eight patients with severe symptomatic aortic stenosis underwent comprehensive TTE evaluation. Each patient underwent a comprehensive TTE evaluation, where several key parameters were measured. For AV assessment, maximum velocity (Vmax), maximum gradient (Gmax), mean gradient (Gmean). TTE measurements were performed using standard protocols and guidelines. AV measurements were obtained from multiple acoustic windows, ensuring optimal visualization and alignment for accurate velocity and gradient assessments. Automated analysis algorithms were applied to the same echocardiographic studies to perform analogous measurements of AV parameters.

Results
The analysis demonstrated a high yield of 94.83% for aortic valve (AV) parameters. Pearson correlation analysis revealed strong agreement between human and AI measurements for AV Vmax, AV Gmax, and AV Gmean, with correlation coefficients of 0.78, 0.80, and 0.77, respectively. There was minimal bias for AV Vmax (0.1, ± 0.81 limits of agreement) and AV Gmax (bias of 3.34, ±30.02 limits of agreement). However, AV Gmean exhibited a bias of -3.63 (±22.14 limits of agreement).

Conclusion
The study shows strong agreement between automated and human measurements for aortic valve parameters.
Right ventricular dysfunction in ischemic vs nonischemic dilated cardiomyopathy
Authors: Saraiya S , Agrawal A , C R 
Published: January 2025

Abstract

Background
Non-ischemic cardiomyopathy (NICM) and ischemic cardiomyopathy (ICM) can both lead to right ventricular (RV) dysfunction. Data on direct head to head comparisons of the two entities regarding RV size and function using state-of-the-art imaging techniques is sparse. Such a comparison may help to better understand the underlying pathophysiology of RV dysfunction in both NICM and ICM. Also, differentiation between the two etiologies for cardiomyopathy has important therapeutic implications because ICM may benefit from coronary revascularization.

Purpose
The aim of this study was to investigate RV function using conventional transthoracic and tissue Doppler echocardiography in patients with dilated cardiomyopathy (ICM and NICM groups) and compare the various parameters of the RV assessment in both the groups and correlate with etiology of cardiomyopathy.

Methods
35 patients with NICM and 35 patients with ICM, both groups with LVEF&lt;35% evaluated at our center were included in the study. Transthoracic echocardiography was done for all of them for assessment of Right ventricular volumes and function using conventional and Tissue Doppler parameters.

Results
Baseline LVEF was similar in the two groups with mean LVEF of 28% in ICM group and 27% in NICM group [p=0.71]. RV dysfunction was seen in 22 (62.9%) patients in ICM group as compared to 25 (71.4%) patients in NICM group [p=0.445]. PAH was present in 31(44.3%) patients, with presence of PAH more common in NICM group (n=18, 51.4%) as compared to ICM group (n=13, 37.1%) [p=0.009]. There was a significant positive correlation between LVEF & RV Basal S’ velocity (R2 0.33, p=0.02) and LVEF & TAPSE (R2 0.309, p=0.03) in the ICM group. Presence of more than mild MR (p=0.047), TAPSE &lt; 1.5 cm (p&lt;0.001) and RV Basal S’ velocity &lt; 8.6 cm/s (p=0.02) were significant predictors of RV dysfunction in these patients.

Conclusion
RV dysfunction is common in both NICM and ICM patients. However, there is no significant association of underlying cause of LV dysfunction with presence of RV dysfunction in these patients. Pulmonary artery hypertension was more common in patients in NICM group.
Echocardiographic nomograms of heart chambers and great arteries in peruvian children living at high altitude according to sex
Authors: Mekonnen D , Ren C , Pilgrim T , Spitzer E 
Published: January 2025

Abstract

Background
Reference values in pediatric echocardiography are crucial for clinical decision making. The availability of nomograms may support interpretation of the echocardiographic findings and clinical diagnosis. Cardiac chamber dimensions vary according to body size, age, sex, and to some extent, geographic background in children.

Purpose
The aim of this study was to establish two-dimensional and M-mode echocardiographic reference values for cardiac chambers, outflow tracts and great vessels for school children living at high altitude, differentiated between male and female.

Methods
This is a post-hoc analysis from a cluster randomized cross-sectional survey of rheumatic heart disease in school children in Arequipa, Peru. Children with normal echocardiographic screening were included for this sub-study. The echocardiograms were acquired with a portable machine and the images were analyzed centrally with a standardized methodology. Body surface area (BSA) was used as an independent variable to predict the mean values of echocardiographic measurements for both male and female groups. Reference values are presented with z-scores and nomograms based on the sex.

Results
A total of 985 students from ages 5-16 years were included. The Haycock formula provided the best fit and was used when presenting data as predicted values for a given BSA. The z-score and nomograms for all essential dimensional measures of cardiac chambers and great vessel, as well as functional surrogates are presented based on sex. Left ventricular chamber and mass are presented in Figure 1 and right ventricular dimensions are presented in Figure 2.

Conclusions
Normal reference values and nomograms of cardiac chamber, outflow tracts and great arteries in healthy school children living at high altitude based on sex were reported. These data partly cover a gap in existing pediatric echocardiographic nomograms.
Left ventricular chamber and mass
Right ventricular dimensions
Hypercontractile phenotype of the left ventricle in patients with heart failure with preserved ejection fraction: too strong to be normal?
Authors: Wang Y , Zhang Q , Wang S , Xu Y , Yin L 
Published: January 2025

Abstract

Background
Hypercontractile phenotype (HP) of the left ventricle (LV) is an actionable therapeutic target in patients with chronic coronary syndromes (CCS), but its prevalence and meaning in patients with heart failure and preserved ejection fraction (HFpEF) remains unclear.

Purpose
To assess the myocardial work correlates of the HP in patients with HFpEF.

Methods
In a prospective, observational, single-center, cross-sectional study, we recruited 62 healthy controls (55 ± 7 yrs, 36 males, 58.1%) and 129 patients (58 ± 8 yrs, 70 males, 54.3%) with HFpEF referred for resting transthoracic echocardiography with volumetric echocardiography and assessment of global work efficiency (GWE). We measured systolic blood pressure (SBP) with a cuff sphygmomanometer. We assessed quantitatively LV end-diastolic volume (EDV), end-systolic volume (ESV), ejection fraction (EF), force (SBP/ESV), stroke volume (SV), arterial elastance (SBP/SV), ventricular-arterial coupling (VAC, as SV/ESV), and cardiac output (CO= SV*heart rate).HP was identified a priori as value &gt;7.87 mmHg/ml, corresponding to a value exceeding &gt; 2SD (95% of values) of the distribution in normals. GWE was assessed with a single vendor together with global longitudinal strain (GLS), global work index (GWI), global constructive work (GCW), global wasted work (GWW), and GWE.

Results
LVEF and GLS values were similar in normal and HFpEF (EF: 63.3±4.7% vs 67.2±6.3%, p &gt; 0.05; GLS: 21.4±1.4% vs 19.1±2.7%, p &gt; 0.05). However, at individual patient analysis, 42 patients of the HFpEF group showed HP (32.6%). Compared to controls and patients with HFpEF without HP, HP patients showed higher values of heart rate and EF but lower values of SV, LVESV, LVEDV, similar values of GLS, and markedly higher values of GWI, GCW, and GWW with lower GWE. Multivariable linear regression analysis showed that force was independently associated with GWE (β=-0.356, P=0.002) and LVEF (β=0.219, P&lt;0.0001), NTproBNP was independently associated with GWW (β=0.589, P=0.020) and GWE (β=-31.120, P&lt;0.0001).

Conclusion
A HP of the LV with high force is frequent in HFpEF and is associated with a small heart, reduced SV, and lower mechanical efficiency with higher global work but a disproportionate increase in wasted work. Work analysis is more effective than GLS in identifying HFpEF with HP.
Comparison of algorithms of left ventricular diastole function assessment in hypertensive individuals with preserved ejection fraction
Authors: Zhemanyuk S , Syvolap V 
Published: January 2025

Abstract

The aim of the study was to compare two echo-algorithms of the assessment of the left ventricular diastole function (2016 the American Society of Echocardiography/the European Association of Cardiovascular Imaging and the 2024 British Society of Echocardiography guidelines) in routine clinical practice.

Methods
We retrospectively enrolled 142 adult hypertensive patients with cardiovascular disease of different aetiologies who underwent transthoracic echocardiography examination (2D imaging, Doppler) for routine clinical indications. It was measured echocardiography parameters for diastolic function evaluation as transmitral Doppler E wave, mitral annular Tissue Doppler Imaging e`septal and e` lateral, average E/e`, left atrium volume index, the velocity of tricuspid regurgitation.

Results
Overall, a total of 90 subjects were finally included (mean age 61.8 years (95% CI 59.1 to 64.5), 44.4% women) who had preserved left ventricular (LV) ejection fraction (≥50%). By applying the 2024 recommendations, 11% of individuals fulfilled the criteria for impaired diastolic function with elevated filling pressure, 83 % of subjects were diagnosed with normal diastolic function, and only 4.4% had impaired diastolic function with normal filling pressures. Meanwhile, according to the 2016 recommendations, 12 % were diagnosed with diastolic dysfunction, 54% had a normal diastolic function and 34%subjects had indeterminate diastolic function, and required additional examination.

Conclusions
This study demonstrates that a low number of individuals with impaired diastolic function with normal filling pressures was classified based on British recommendation 2024, however, a high number of patients with indeterminate diastolic function was diagnosed through guideline 2016. The new echocardiographic approach for estimating the left ventricular diastole function presented in 2024 could have higher clinical utility, especially in resource-limited settings for routine examination of hypertensive patients.