How to Define End-Diastole and End-Systole?

Echocardiographic Measurements in Normal Chinese Adults (EMINCA) II focusing on left ventricular and left atrial size and function by three-dimensional echocardiography

Current guidelines encourage large studies in a diverse population to establish normal reference ranges for three-dimensional (3D) echocardiography for different ethnic groups. This study was designed to establish the normal values of 3D-left ventricular (LV) and left atrial (LA) volume and function in a nationwide, population-based cohort of healthy Han Chinese adults. A total of 1117 healthy volunteers aged 18-89 years were enrolled from 28 collaborating laboratories in China. Two sets of 3D echocardiographic instruments were used, and full-volume echocardiographic images were recorded and transmitted to a core laboratory for image analysis with a vendor-independent off-line workstation. Finally, 866 volunteers (mean age of 48.4 years, 402 men) were qualified for final analysis. Most parameters exhibited substantial differences between different sex and age groups, even after indexation by body surface area. The normal ranges of 3D-LV and 3D-LA volume and function differed from those recommended by the American Society of Echocardiography and the European Association of Cardiovascular Imaging guidelines, presented by the World Alliance Societies of Echocardiography (WASE) study, and from the 2D values in the EMINCA study. The normal reference values of 3D echocardiography-derived LV and LA volume and function were established for the first time in healthy Han Chinese adults. Normal ranges of 3D-LV and 3D-LA echocardiographic measurements stratified with sex, age, and race should be recommended for clinical applications.

Cardiac Valve Event Timing in Echocardiography Using Deep Learning and Triplane Recordings

Cardiac valve event timing plays a crucial role when conducting clinical measurements using echocardiography. However, established automated approaches are limited by the need of external electrocardiogram sensors, and manual measurements often rely on timing from different cardiac cycles. Recent methods have applied deep learning to cardiac timing, but they have mainly been restricted to only detecting two key time points, namely end-diastole (ED) and end-systole (ES). In this work, we propose a deep learning approach that leverages triplane recordings to enhance detection of valve events in echocardiography. Our method demonstrates improved performance detecting six different events, including valve events conventionally associated with ED and ES. Of all events, we achieve an average absolute frame difference (aFD) of maximum 1.4 frames (29 ms) for start of diastasis, down to 0.6 frames (12 ms) for mitral valve opening when performing a ten-fold cross-validation with test splits on triplane data from 240 patients. On an external independent test consisting of apical long-axis data from 180 other patients, the worst performing event detection had an aFD of 1.8 (30 ms). The proposed approach has the potential to significantly impact clinical practice by enabling more accurate, rapid and comprehensive event detection, leading to improved clinical measurements.

Left bundle branch pacing better preserves ventricular mechanical synchrony than right ventricular pacing: a two-centre study

AIMS

Left bundle branch pacing (LBBP) has been shown to better maintain electrical synchrony compared with right ventricular pacing (RVP), but little is known about its impact on mechanical synchrony. This study investigates whether LBBP better preserves left ventricular (LV) mechanical synchronicity and function compared with RVP.

METHODS AND RESULTS

Sixty patients with pacing indication for bradycardia were included: LBBP (n = 31) and RVP (n = 29). Echocardiography was performed before and shortly after pacemaker implantation and at 1-year follow-up. The lateral wall-septal wall (LW-SW) work difference was used as a measure of mechanical dyssynchrony. Septal flash, apical rocking, and septal strain patterns were also assessed. At baseline, LW-SW work difference was small and similar in two groups. SW was markedly decreased, while LW work remained mostly unchanged in RVP, resulting in a larger LW-SW work difference compared with LBBP (1253 ± 687 mmHg·% vs. 439 ± 408 mmHg·%, P < 0.01) at last follow-up. In addition, RVP more often induced septal flash or apical rocking and resulted in more advanced strain patterns compared with LBBP. At 1 year follow-up, LV ejection fraction (EF) and global longitudinal strain (GLS) were more decreased in RVP compared with LBBP (ΔLVEF: -7.4 ± 7.0% vs. 0.3 ± 4.1%; ΔLVGLS: -4.8 ± 4.0% vs. -1.4 ± 2.5%, both P < 0.01). In addition, ΔLW-SW work difference was independently correlated with LV adverse remodelling (r = 0.42, P < 0.01) and LV dysfunction (ΔLVEF: r = -0.61, P < 0.01 and ΔLVGLS: r = -0.38, P = 0.02).

CONCLUSION

LBBP causes less LV mechanical dyssynchrony than RVP as it preserves a more physiologic electrical conduction. As a consequence, LBBP appears to preserve LV function better than RVP.

Evaluation of the image quality and validity of handheld echocardiography for stroke volume and left ventricular ejection fraction quantification: a method comparison study

Bedside quantification of stroke volume (SV) and left ventricular ejection fraction (LVEF) is valuable in hemodynamically compromised patients. Miniaturized handheld ultrasound (HAND) devices are now available for clinical use. However, the performance level of HAND devices for quantified cardiac assessment is yet unknown. The aim of this study was to compare the validity of HAND measurements with standard echocardiography (SE) and three-dimensional echocardiography (3DE). Thirty-six patients were scanned with HAND, SE and 3DE. LVEF and SV quantification was done with automated software for the HAND, SE and 3DE dataset. The image quality of HAND and SE was evaluated by scoring segmental endocardial border delineation (2 = good, 1 = poor, 0 = invisible). LVEF and SV of HAND was evaluated against SE and 3DE using correlation and Bland-Altman analysis. The correlation, bias, and limits of agreement (LOA) between HAND and SE were 0.68 [0.46:0.83], 1.60% [- 2.18:5.38], and 8.84% [- 9.79:12.99] for LVEF, and 0.91 [0.84:0.96], 1.32 ml [- 0.36:4.01], 15.54 ml [- 18.70:21.35] for SV, respectively. Correlation, bias, and LOA between HAND and 3DE were 0.55 [0.6:0.74], - 0.56% [- 2.27:1.1], and 9.88% [- 13.29:12.17] for LVEF, and 0.79 [0.62:0.89], 6.78 ml [2.34:11.21], 12.14 ml [- 26.32:39.87] for SV, respectively. The image quality scores were 9.42 ± 2.0 for the apical four chamber views of the HAND dataset and 10.49 ± 1.7 for the SE dataset and (P < 0.001). Clinically acceptable accuracy, precision, and image quality was demonstrated for HAND measurements compared to SE. In comparison to 3DE, HAND showed a clinically acceptable accuracy and precision for LVEF quantification.

Application of myocardial work in predicting adverse events among patients with resistant hypertension

BACKGROUND

Hypertension is the most common chronic disease and the leading risk factor for disability and premature deaths worldwide. Approximately 10-20% of all patients with hypertension and 15-18% of the general population who are treated for hypertension have resistant hypertension (RH). Patients with RH have a higher risk of end-organ damage, such as carotid intima-media thickening, retinopathy, left ventricular hypertrophy and heart failure, myocardial infarction, stroke, impaired renal function, and death than those with controlled blood pressure. In the present study, we applied echocardiography to patients with RH to evaluate myocardial work (MW) and determine whether it is predictive for the occurrence of adverse events within 3 years.

METHODS

We included 283 outpatients and inpatients aged ≥ 18 years who met the clinical criteria for RH, without arrhythmia and severe aortic valve stenosis, between July 2018 and June 2019. The patients were followed up for 3 years from starting enrollment, and any adverse event that occurred during the period was used as the observation end point. Each enrolled patient underwent a complete transthoracic echocardiogram examination, blood pressure was measured and recorded, and MW was then analyzed.

RESULTS

Eighty-two (28.98%) patients with RH had adverse events, such as myocardial infarction (n = 29, 35.36%), heart failure (n = 4, 0.05%), renal insufficiency (n = 40, 48.78%), renal failure (n = 2, 0.02%), cerebral infarction (n = 5, 0.06%), and cerebral hemorrhage (n = 2, 0.02%), and no death events occurred. In patients with RH and adverse events, global longitudinal strain (GLS) (- 16% vs. - 18%), the global work index (2079 mmHg% vs. 2327 mmHg%), global constructive work (2321 mmHg% vs. 2610 mmHg%), and global work efficiency (93% vs. 94%) were lower than those in patients without adverse events. However, global wasted work (GWW) was higher in patients with RH and adverse events than in those without adverse events (161 mmHg% vs. 127 mmHg%). GLS and GWW were the most significant in predicting adverse events.

CONCLUSIONS

MW, especially GLS and GWW, is a good method to predict 3-year adverse events in patients with RH.

A method for measuring the angle between left atrial and left ventricular long axes using 3D echocardiography

BACKGROUND

Left ventricle (LV) optimized views are routinely used for left atrial (LA) volume and strain measurements on 2D echocardiography. This might be a source of the error because of the variation of the angle between the left atrial and left ventricle long axes (LA-LV angle), leading to foreshortening of the LA.

METHODS

We investigated two novel parameters: the angle between the left atrial and left ventricle long axes (LA-LV angle) and its deviation from the 4-chamber plane. To accurately measure the angles in 3D space, these measurements were performed using 3D echocardiography. We developed a method for the measurement based on marking anatomic points of reference in the 3D echocardiogram and measuring the angles between these points. We used three types of phantoms made of wood and agar-agar to investigate the repeatability and reproducibility of these measurements and performed measurements on human subjects.

RESULTS

The ultrasound measurements were in excellent agreement with the true angles of the phantoms: LA-LV angle bias was .5 degrees (95% CI -1.8 to +2.7) in the wooden phantoms and 1.2 degrees (-.7 to +3.1) in the agar-agar phantoms, while the angle deviation from the 4-chamber plane was -.9 degrees (-4.3 to +4.1) in the wooden phantoms and .0 degrees (-3.3 to +3.3) in the agar-agar phantoms. The measurements demonstrated good repeatability and reproducibility (Pearson correlation coefficients ranging from .91 to .99). The measurements from human hearts showed good repeatability (Pearson correlation was .81 for repeated LA-LV angle measurements and .97 for repeated measurements of the deviation from the 4-chamber plane).

CONCLUSION

The measurement of the LA-LV angle is a feasible tool to investigate one eventual error of 2D echocardiography.

Cardiac phase detection in echocardiography using convolutional neural networks

Echocardiography is a commonly used and cost-effective test to assess heart conditions. During the test, cardiologists and technicians observe two cardiac phases-end-systolic (ES) and end-diastolic (ED)-which are critical for calculating heart chamber size and ejection fraction. However, non-essential frames called Non-ESED frames may appear between these phases. Currently, technicians or cardiologists manually detect these phases, which is time-consuming and prone to errors. To address this, an automated and efficient technique is needed to accurately detect cardiac phases and minimize diagnostic errors. In this paper, we propose a deep learning model called DeepPhase to assist cardiology personnel. Our convolutional neural network (CNN) learns from echocardiography images to identify the ES, ED, and Non-ESED phases without the need for left ventricle segmentation or electrocardiograms. We evaluate our model on three echocardiography image datasets, including the CAMUS dataset, the EchoNet Dynamic dataset, and a new dataset we collected from a cardiac hospital (CardiacPhase). Our model outperforms existing techniques, achieving 0.96 and 0.82 area under the curve (AUC) on the CAMUS and CardiacPhase datasets, respectively. We also propose a novel cropping technique to enhance the model's performance and ensure its relevance to real-world scenarios for ES, ED, and Non ES-ED classification.

A novel deep learning model for breast lesion classification using ultrasound Images: A multicenter data evaluation

PURPOSE

Breast cancer is one of the major reasons of death due to cancer in women. Early diagnosis is the most critical key for disease screening, control, and reducing mortality. A robust diagnosis relies on the correct classification of breast lesions. While breast biopsy is referred to as the "gold standard" in assessing both the activity and degree of breast cancer, it is an invasive and time-consuming approach.

METHOD

The current study's primary objective was to develop a novel deep-learning architecture based on the InceptionV3 network to classify ultrasound breast lesions. The main promotions of the proposed architecture were converting the InceptionV3 modules to residual inception ones, increasing their number, and altering the hyperparameters. In addition, we used a combination of five datasets (three public datasets and two prepared from different imaging centers) for training and evaluating the model.

RESULTS

The dataset was split into the train (80%) and test (20%) groups. The model achieved 0.83, 0.77, 0.8, 0.81, 0.81, 0.18, and 0.77 for the precision, recall, F1 score, accuracy, AUC, Root Mean Squared Error, and Cronbach's α in the test group, respectively.

CONCLUSIONS

This study illustrates that the improved InceptionV3 can robustly classify breast tumors, potentially reducing the need for biopsy in many cases.

Contribution of Ventricular Motion and Sampling Location to Discrepancies in Two-Dimensional Versus Three-Dimensional Fetal Ventricular Strain Measures

BACKGROUND

Echocardiographic quantification of fetal cardiac strain is important to evaluate function and the need for intervention, with both two-dimensional (2D) and three-dimensional (3D) strain measurements currently feasible. However, discrepancies between 2D and 3D measurements have been reported, the etiologies of which are unclear. This study sought to determine the etiologies of the differences between 2D and 3D strain measurements.

METHODS

A validated cardiac motion-tracking algorithm was used on 3D cine ultrasound images acquired in 26 healthy fetuses. Both 2D and 3D myocardial strain quantifications were performed on each image set for controlled comparisons. Finite element modeling of 2 left ventricle (LV) models with minor geometrical differences were performed with various helix angle configurations for validating image processing results.

RESULTS

Three-dimensional longitudinal strain (LS) was significantly lower than 2D LS for the LV free wall and septum but not for the right ventricular (RV) free wall, while 3D circumferential strain (CS) was significantly higher than 2D CS for the LV, RV, and septum. The LS discrepancy was due to 2D long-axis imaging not capturing the out-of-plane motions associated with LV twist, while the CS discrepancy was due to the systolic motion of the heart toward the apex that caused out-of-plane motions in 2D short-axis imaging. A timing mismatch between the occurrences of peak longitudinal and circumferential dimensions caused a deviation in zero-strain referencing between 2D and 3D strain measurements, contributing to further discrepancies between the 2.

CONCLUSIONS

Mechanisms for discrepancies between 2D and 3D strain measurements in fetal echocardiography were identified, and inaccuracies associated with 2D strains were highlighted. Understanding of this mechanism is useful and important for future standardization of fetal cardiac strain measurements, which we propose to be important in view of large discrepancies in measured values in the literature.

MAEF-Net: Multi-attention efficient feature fusion network for left ventricular segmentation and quantitative analysis in two-dimensional echocardiography

The segmentation of cardiac chambers and the quantification of clinical functional metrics in dynamic echocardiography are the keys to the clinical diagnosis of heart disease. Identifying the end-diastolic frames (EDFs) and end-systolic frames (ESFs) and manually segmenting the left ventricle in the echocardiographic cardiac cycle before obtaining the left ventricular ejection fraction (LVEF) is a time-consuming and tedious task for clinicians. In this work, we proposed a deep learning-based fully automated echocardiographic analysis method. We proposed a multi-attention efficient feature fusion network (MAEF-Net) to automatically segment the left ventricle. Then, EDFs and ESFs in all cardiac cycles were automatically detected to compute LVEF. The MAEF-Net method used a multi-attention mechanism to guide the network to capture heartbeat features effectively, while suppressing noise, and incorporated deep supervision mechanism and spatial pyramid feature fusion to enhance feature extraction capabilities. The proposed method was validated on the public EchoNet-Dynamic dataset (n = 1226). The Dice similarity coefficient (DSC) of the left ventricular segmentation reached (93.10 ± 2.22)%, and the mean absolute error (MAE) of cardiac phase detection was (2.36 ± 2.23) frames. The MAE for predicting LVEF was 6.29 %. The proposed method was also validated on a private clinical dataset (n = 22). The DSC of the left ventricular segmentation reached (92.81 ± 2.85)%, and the MAE of cardiac phase detection was (2.25 ± 2.27) frames. The MAE for predicting LVEF was 5.91 %, and the Pearson correlation coefficient r reached 0.96. The proposed method may be used as a new method for automatic left ventricular segmentation and quantitative analysis in two-dimensional echocardiography. Our code and trained models will be made available publicly at https://github.com/xiaojinmao-code/MAEF-Net.

A cross-species validation of single-beat metrics of cardiac contractility

The assessment of left ventricular (LV) contractility in animal models is useful in various experimental paradigms, yet obtaining such measures is inherently challenging and surgically invasive. In a cross-species study using small and large animals, we comprehensively tested the agreement and validity of multiple single-beat surrogate metrics of LV contractility against the field-standard metrics derived from inferior vena cava occlusion (IVCO). Fifty-six rats, 27 minipigs and 11 conscious dogs underwent LV and arterial catheterization and were assessed for a range of single-beat metrics of LV contractility. All single-beat metrics were tested for the various underlying assumptions required to be considered a valid metric of cardiac contractility, including load-independency, sensitivity to inotropic stimulation, and ability to diagnose contractile dysfunction in cardiac disease. Of all examined single-beat metrics, only LV maximal pressure normalized to end-diastolic volume (EDV), end-systolic pressure normalized to EDV, and the maximal rate of rise of the LV pressure normalized to EDV showed a moderate-to-excellent agreement with their IVCO-derived reference measure and met all the underlying assumptions required to be considered as a valid cardiac contractile metric in both rodents and large-animal models. Our findings demonstrate that single-beat metrics can be used as a valid, reliable method to quantify cardiac contractile function in basic/preclinical experiments utilizing small- and large-animal models KEY POINTS: Validating and comparing indices of cardiac contractility that avoid caval occlusion would offer considerable advantages for the field of cardiovascular physiology. We comprehensively test the underlying assumptions of multiple single-beat indices of cardiac contractility in rodents and translate these findings to pigs and conscious dogs. We show that when performing caval occlusion is unfeasible, single-beat metrics can be utilized to accurately quantify cardiac inotropic function in basic and preclinical research employing various small and large animal species. We report that maximal left-ventricular (LV)-pressure normalized to end-diastolic volume (EDV), LV end-systolic pressure normalized to EDV and the maximal rate of rise of the LV pressure waveform normalized to EDV are the best three single-beat metrics to measure cardiac inotropic function in both small- and large-animal models.

Optimal Echocardiographic Parameters to Improve the Diagnostic Yield of Tc-99m-Bone Avid Tracer Cardiac Scintigraphy for Transthyretin Cardiac Amyloidosis

BACKGROUND

Echocardiographic deformation-based ratios and novel multi-parametric scores have been suggested to discriminate transthyretin cardiac amyloidosis (ATTR-CM) from other causes of increased left ventricular wall thickness among patients referred for ATTR-CM evaluation. Their relative predictive accuracy has not been well studied. We sought to (1) identify echocardiographic parameters predictive of ATTR-CM and (2) compare the diagnostic accuracy of these parameters in patients with suspected ATTR-CM referred for technetium-99m-pyrophosphate scintigraphy.

METHODS

Echocardiograms from 598 patients referred to 3 major amyloidosis centers for technetium-99m-pyrophosphate to detect ATTR-CM were analyzed, including longitudinal strain (LS) analysis. Deformation ratios (septal apex to base ratio, relative apical sparing, ejection fraction to global LS), a multi-center European increased wall thickness score, and Mayo Clinic derived ATTR score (transthyretin cardiac amyloidosis score) were calculated. A logistic regression model was used to identify the parameters that best associated with a diagnosis of ATTR-CM. Comparison of the diagnostic capacity of the parameters was performed by receiver operating characteristic curves and the area under the curve (AUC).

RESULTS

Over half of the subjects (54.2%) were diagnosed with ATTR-CM (78% were men, median age of 76 years). Age, inferolateral wall thickness, and basal LS were the strongest predictors of ATTR-CM, AUC of 0.87 (95% CI: 0.83, 0.90), superior to the increased wall thickness score AUC of 0.78 (95% CI: 0.73, 0.83; P=0.004). An inferolateral wall thickness of ≥14 mm (AUC: 0.73) was as accurate as the published cut-offs for transthyretin cardiac amyloidosis score and septal apex to base (AUC: 0.72 and 0.69, P=0.8 and P=0.1, respectively), and was superior to ejection fraction to global LS and relative apical sparing (AUC: 0.64 and 0.53, P<0.001, respectively). A cut-off of ≥-8% for average basal LS (AUC: 0.76, CI: 0.72-0.79) had a similar area under the curve to transthyretin cardiac amyloidosis score (TCAS) (P=0.2); outperforming the other indices (P<0.01).

CONCLUSION

Inferolateral wall thickness and average basal LS performed as well as or better than more complex echo ratios and multiparametric scores to predict ATTR-CM.

Echocardiography-Based Cardiac Structure Parameters for the Long-term Risk of End-Stage Kidney Disease in Black Individuals: The Atherosclerosis Risk in Communities Study

OBJECTIVE

To assess whether echocardiographic parameters of left ventricular (LV) structure and function relate to the long-term risk of incident end-stage kidney disease (ESKD).

PATIENTS AND METHODS

We conducted a prospective cohort study analyzing 2137 Black participants from the Jackson site of the Atherosclerosis Risk in Communities Study from January 1, 1993, through July 31, 2017. Echocardiographic parameters of LV structure and function were obtained from 1993 to 1995. The primary outcome incident ESKD was identified through the linkage to the United States Renal Data System. Cox proportional hazards models were used to estimate the hazard ratios (HRs) according to each echocardiographic parameter.

RESULTS

There were 117 incident ESKD cases during a median follow-up of 22.2 (interquartile range, 15.0-23.3) years. Multivariable Cox models revealed that a higher LV mass index was significantly associated with the risk of ESKD (HR, 2.38; 95% CI, 1.21 to 4.68 for highest vs lowest quartile, P = 0.012). The HRs were significant and even higher for LV posterior wall thickness, with slightly higher HRs when their measures in end-systole (HR for highest vs lowest quartile, 4.38; 95% CI, 1.94 to 9.92, P < 0.001) vs end-diastole (HR, 3.50; 95% CI, 1.53 to 8.01, P = 0.003) were used. The associations were not significant for LV function parameters.

CONCLUSION

In Black individuals residing in the community, echocardiographic parameters of LV structure, including LV wall thickness, were robustly associated with the risk of subsequently incident ESKD. These results have potential implications for novel prevention and management strategies for persons with abnormal LV structure.

Automatic cardiac evaluations using a deep video object segmentation network

BACKGROUND

Accurate cardiac volume and function assessment have valuable and significant diagnostic implications for patients suffering from ventricular dysfunction and cardiovascular disease. This study has focused on finding a reliable assistant to help physicians have more reliable and accurate cardiac measurements using a deep neural network. EchoRCNN is a semi-automated neural network for echocardiography sequence segmentation using a combination of mask region-based convolutional neural network image segmentation structure with reference-guided mask propagation video object segmentation network.

RESULTS

The proposed method accurately segments the left and right ventricle regions in four-chamber view echocardiography series with a dice similarity coefficient of 94.03% and 94.97%, respectively. Further post-processing procedures on the segmented left and right ventricle regions resulted in a mean absolute error of 3.13% and 2.03% for ejection fraction and fractional area change parameters, respectively.

CONCLUSION

This study has achieved excellent performance on the left and right ventricle segmentation, leading to more accurate estimations of vital cardiac parameters such as ejection fraction and fractional area change parameters in the left and right ventricle functionalities, respectively. The results represent that our method can predict an assured, accurate, and reliable cardiac function diagnosis in clinical screenings.

Vasodilator Strain Stress Echocardiography in Suspected Coronary Microvascular Angina

Background: In patients with Ischemia and non-obstructive coronary artery stenosis (INOCA) wall motion is rarely abnormal during stress echocardiography (SE). Our aim was to determine if patients with INOCA and reduced coronary flow velocity reserve (CVFR) have altered cardiac mechanics using two-dimensional speckle-tracking echocardiography (2DSTE) during SE. Methods: In a prospective, multicenter, international study, we recruited 135 patients with INOCA. Overall, we performed high dose (0.84 mg/kg) dipyridamole SE with combined assessment of CVFR and 2DSTE. The population was divided in patients with normal CVFR (>2, group 1, n = 95) and abnormal CVFR (≤2, group 2, n = 35). Clinical and 2DSTE parameters were compared between groups. Results: Feasibility was high for CFVR (98%) and 2DSTE (97%). A total of 130 patients (mean age 63 ± 12 years, 67 women) had complete flow and strain data. The two groups showed similar 2DSTE values at rest. At peak SE, Group 1 patients showed lower global longitudinal strain (p < 0.007), higher mechanical dispersion (p < 0.0005), lower endocardial (p < 0.001), and epicardial (p < 0.0002) layer specific strain. Conclusions: In patients with INOCA, vasodilator SE with simultaneous assessment of CFVR and strain is highly feasible. Coronary microvascular dysfunction is accompanied by an impairment of global and layer-specific deformation indices during stress.

Multibeat echocardiographic phase detection using deep neural networks

BACKGROUND

Accurate identification of end-diastolic and end-systolic frames in echocardiographic cine loops is important, yet challenging, for human experts. Manual frame selection is subject to uncertainty, affecting crucial clinical measurements, such as myocardial strain. Therefore, the ability to automatically detect frames of interest is highly desirable.

METHODS

We have developed deep neural networks, trained and tested on multi-centre patient data, for the accurate identification of end-diastolic and end-systolic frames in apical four-chamber 2D multibeat cine loop recordings of arbitrary length. Seven experienced cardiologist experts independently labelled the frames of interest, thereby providing infallible annotations, allowing for observer variability measurements.

RESULTS

When compared with the ground-truth, our model shows an average frame difference of -0.09 ± 1.10 and 0.11 ± 1.29 frames for end-diastolic and end-systolic frames, respectively. When applied to patient datasets from a different clinical site, to which the model was blind during its development, average frame differences of -1.34 ± 3.27 and -0.31 ± 3.37 frames were obtained for both frames of interest. All detection errors fall within the range of inter-observer variability: [-0.87, -5.51]±[2.29, 4.26] and [-0.97, -3.46]±[3.67, 4.68] for ED and ES events, respectively.

CONCLUSIONS

The proposed automated model can identify multiple end-systolic and end-diastolic frames in echocardiographic videos of arbitrary length with performance indistinguishable from that of human experts, but with significantly shorter processing time.

Layer-Specific Strain Is Preload Dependent: Comparison between Speckle-Tracking Echocardiography and Cardiac Magnetic Resonance Feature-Tracking

BACKGROUND

Speckle-tracking echocardiographic (STE) imaging and cardiac magnetic resonance feature-tracking (CMR-FT) are novel imaging techniques enabling layer-specific quantification of myocardial deformation. Conventional echocardiographic parameters are load dependent, but few studies have investigated the effects of loading conditions on STE and CMR-FT layer-specific strain and the interchangeability of the two modalities. The aim of this study was to evaluate the effects of acute preload augmentation by saline infusion on STE and CMR-FT longitudinal and circumferential layer-specific strain parameters and their intermodal agreement.

METHODS

A total of 80 subjects, including 41 control subjects (mean age, 40 ± 12 years; 49% men) and 39 patients with cardiac disease (mean age, 47 ± 15 years; 92% men) were examined using STE and CMR-FT layer-specific strain analysis before and after saline infusion (median, 2.0 L) with quantification of transmural global longitudinal strain (GLS), epicardial GLS, endocardial GLS, transmural global circumferential strain (GCS), epicardial GCS, and endocardial GCS in addition to epicardial-endocardial gradients. Bland-Altman plots and Pearson correlation coefficients were used to evaluate agreement between the two modalities across all strain parameters.

RESULTS

Acute saline infusion increased all STE and CMR-FT layer-specific strain parameters in both groups. STE and CMR-FT GLS increased by 1.4 ± 1.5% and 1.5 ± 2.0% (P < .001) in control subjects and by 0.9 ± 1.8% and 0.9 ± 1.9% (P < .001) in patients with cardiac disease. STE and CMR-FT GCS increased by 2.0 ± 2.2% and 1.8 ± 2.3% (P < .001) in control subjects and by 1.8 ± 2.3% and 1.7 ± 3.6% in patients with cardiac disease (P < .001 and P = .03). STE longitudinal strain correlated strongly with corresponding CMR-FT longitudinal strain (GLS, epicardial GLS, and endocardial GLS: r = 0.81, r = 0.82, and r = 0.81, respectively) despite poor intermodal agreement (bias ± limits of agreement, -2.84 ± 4.06%, 0.16 ± 3.68%, and 2.33 ± 3.52%, respectively) whereas GCS, epicardial GCS, and endocardial GCS correlated weakly between the two modalities (r = 0.28, r = 0.19, and r = 0.34, respectively) and displayed poor intermodal agreement (bias ± limits of agreement, -1.33 ± 6.86%, 4.43 ± 6.49%, and -9.92 ± 8.55%, respectively).

CONCLUSIONS

STE and CMR-FT longitudinal and circumferential layer-specific strain parameters are preload dependent in both control subjects and patients with cardiac disease. STE and CMR-FT longitudinal layer-specific strain parameters are strongly correlated, whereas circumferential layer-specific strain parameters are weakly correlated. STE and CMR-FT longitudinal and circumferential strain should not be used interchangeably, because of poor intermodal agreement.

Estimation of End-Diastole in Cardiac Spectral Doppler Using Deep Learning

Electrocardiogram (ECG) is often used together with a spectral Doppler ultrasound to separate heart cycles by determining the end-diastole locations. However, the ECG signal is not always recorded. In such cases, the cardiac cycles can be estimated manually from the ultrasound data retrospectively. We present a deep learning-based method for automatic detection of the end-diastoles in spectral Doppler spectrograms. The method uses a combination of a convolutional neural network (CNN) for extracting features and a recurrent neural network (RNN) for modeling temporal relations. In echocardiography, there are three Doppler spectrogram modalities, continuous wave, pulsed wave, and tissue velocity Doppler. Both the training and test data sets include all three modalities. The model was tested on 643 spectrograms coming from different hospitals than in the training data set. For the purposes described in this work, a valid end-diastole detection is defined as a prediction being closer than 60 ms to the reference value. We will refer to these as true detections. Similarly, a prediction farther away is defined as nonvalid or false detections. The method automatically rejects spectrograms where the detection of an end-diastole has low confidence. When setting the algorithm to reject 1.9%, the method achieved 97.7% true detections with a mean error of 14 ms and had 2.5% false detections on the remaining spectrograms.

A practical guideline for performing a comprehensive transthoracic echocardiogram in adults: the British Society of Echocardiography minimum dataset

Since cardiac ultrasound was introduced into medical practice around the middle twentieth century, transthoracic echocardiography has developed to become a highly sophisticated and widely performed cardiac imaging modality in the diagnosis of heart disease. This evolution from an emerging technique with limited application, into a complex modality capable of detailed cardiac assessment has been driven by technological innovations that have both refined 'standard' 2D and Doppler imaging and led to the development of new diagnostic techniques. Accordingly, the adult transthoracic echocardiogram has evolved to become a comprehensive assessment of complex cardiac anatomy, function and haemodynamics. This guideline protocol from the British Society of Echocardiography aims to outline the minimum dataset required to confirm normal cardiac structure and function when performing a comprehensive standard adult echocardiogram and is structured according to the recommended sequence of acquisition. It is recommended that this structured approach to image acquisition and measurement protocol forms the basis of every standard adult transthoracic echocardiogram. However, when pathology is detected and further analysis becomes necessary, views and measurements in addition to the minimum dataset are required and should be taken with reference to the appropriate British Society of Echocardiography imaging protocol. It is anticipated that the recommendations made within this guideline will help standardise the local, regional and national practice of echocardiography, in addition to minimising the inter and intra-observer variation associated with echocardiographic measurement and interpretation.

Early impairment of myocardial deformation assessed by regional speckle-tracking echocardiography in the indeterminate form of Chagas disease without fibrosis detected by cardiac magnetic resonance

Chagas disease (CD) will account for 200,000 cardiovascular deaths worldwide over the next 5 years. Early detection of chronic Chagas cardiomyopathy (CCC) is a challenge. We aimed to test if speckle-tracking echocardiography (STE) can detect incipient myocardial damage in CD. METHODS: Among 325 individuals with positive serological tests, 25 (age 55±12yrs) were selected to compose the group with indeterminate form of Chagas disease (IFCD), based on stringent criteria of being asymptomatic and with normal EKG/X-ray studies. This group was compared with a group of 20 patients with CCC (55±11yrs) and a group of 20 non-infected matched control (NC) subjects (48±10yrs). CD patients and NC were submitted to STE and CD patients were submitted to cardiac magnetic resonance (CMR) with late gadolinium administration to detect cardiac fibrosis by the late enhancement technique. Global longitudinal strain (GLS), circumferential (GCS) and radial strain (GRS) were defined as the average of segments measured from three apical view (GLS) and short axis views (GRS and GCS). Regional left ventricular (LV) longitudinal strain (Reg LS) was measured from each of the 17 segments. Twist was measured as systolic peak difference between basal and apical rotation and indexed to LV length to express torsion. RESULTS: STE global indices (GLS, GCS, twist and torsion) were reduced in CCC vs NC (GLS: -14±6.3% vs -19.3±1.6%, p = 0.001; GCS: -13.6±5.2% vs -17.3 ±2.8%; p = 0.008; twist: 8±7° vs 14±7°, p = 0.01 and torsion: 0.96±1°/cm vs 1.9±1°/cm, p = 0.005), but showed no differences in IFCD vs NC. RegLS was reduced in IFCD vs NC in four LV segments: basal-inferior (-16.3±3.3% vs -18.6±2.2%, p = 0.013), basal inferoseptal (-13.1±3.4 vs -15.2±2.7, p = 0.019), mid-inferoseptal (-17.7±3.2 vs -19.4±2, p = 0.032) and mid-inferolateral (-15.2±3.5 vs -17.8±2.8, p = 0.014). These abnormalities in RegLS occurred in the absence of myocardial fibrosis detectable with CMR in nearly 92% of subjects with IFCD, while myocardial fibrosis was present in 65% with CCC. CONCLUSION: RegLS detects early regional impairment of myocardial strain that is independent from fibrosis in IFCD subjects.

Regional longitudinal strain is reduced in IFCD before significant fibrosis. As CD progresses to CF, global STE measurements of left ventricle (GLS, GCS, twist and torsion) and GLS of right ventricle are reduced.

Early abnormal strain pattern of CD comprises inferior, septoinferior and inferolateral segments of LV. Recognizing the regional strain pattern of Chagas cardiomyopathy may help identifying the disease even at early stages.

A direct comparison of natural and acoustic-radiation-force-induced cardiac mechanical waves

Natural and active shear wave elastography (SWE) are potential ultrasound-based techniques to non-invasively assess myocardial stiffness, which could improve current diagnosis of heart failure. This study aims to bridge the knowledge gap between both techniques and discuss their respective impacts on cardiac stiffness evaluation. We recorded the mechanical waves occurring after aortic and mitral valve closure (AVC, MVC) and those induced by acoustic radiation force throughout the cardiac cycle in four pigs after sternotomy. Natural SWE showed a higher feasibility than active SWE, which is an advantage for clinical application. Median propagation speeds of 2.5-4.0 m/s and 1.6-4.0 m/s were obtained after AVC and MVC, whereas ARF-based median speeds of 0.9-1.2 m/s and 2.1-3.8 m/s were reported for diastole and systole, respectively. The different wave characteristics in both methods, such as the frequency content, complicate the direct comparison of waves. Nevertheless, a good match was found in propagation speeds between natural and active SWE at the moment of valve closure, and the natural waves showed higher propagation speeds than in diastole. Furthermore, the results demonstrated that the natural waves occur in between diastole and systole identified with active SWE, and thus represent a myocardial stiffness in between relaxation and contraction.

Myocardial strain imaging: review of general principles, validation, and sources of discrepancies

Myocardial tissue tracking imaging techniques have been developed for a more accurate evaluation of myocardial deformation (i.e. strain), with the potential to overcome the limitations of ejection fraction (EF) and to contribute, incremental to EF, to the diagnosis and prognosis in cardiac diseases. While most of the deformation imaging techniques are based on the similar principles of detecting and tracking specific patterns within an image, there are intra- and inter-imaging modality inconsistencies limiting the wide clinical applicability of strain. In this review, we aimed to describe the particularities of the echocardiographic and cardiac magnetic resonance deformation techniques, in order to understand the discrepancies in strain measurement, focusing on the potential sources of variation: related to the software used to analyse the data, to the different physics of image acquisition and the different principles of 2D vs. 3D approaches. As strain measurements are not interchangeable, it is highly desirable to work with validated strain assessment tools, in order to derive information from evidence-based data. There is, however, a lack of solid validation of the current tissue tracking techniques, as only a few of the commercial deformation imaging softwares have been properly investigated. We have, therefore, addressed in this review the neglected issue of suboptimal validation of tissue tracking techniques, in order to advocate for this matter.

Measurement, Analysis and Interpretation of Pressure/Flow Waves in Blood Vessels

The optimal performance of the cardiovascular system, as well as the break-down of this performance with disease, both involve complex biomechanical interactions between the heart, conduit vascular networks and microvascular beds. ‘Wave analysis’ refers to a group of techniques that provide valuable insight into these interactions by scrutinizing the shape of blood pressure and flow/velocity waveforms. The aim of this review paper is to provide a comprehensive introduction to wave analysis, with a focus on key concepts and practical application rather than mathematical derivations. We begin with an overview of invasive and non-invasive measurement techniques that can be used to obtain the signals required for wave analysis. We then review the most widely used wave analysis techniques—pulse wave analysis, wave separation and wave intensity analysis—and associated methods for estimating local wave speed or characteristic impedance that are required for decomposing waveforms into forward and backward wave components. This is followed by a discussion of the biomechanical phenomena that generate waves and the processes that modulate wave amplitude, both of which are critical for interpreting measured wave patterns. Finally, we provide a brief update on several emerging techniques/concepts in the wave analysis field, namely wave potential and the reservoir-excess pressure approach.

Cardiac magnetic resonance longitudinal strain analysis in acute ST-segment elevation myocardial infarction: A comparison with speckle-tracking echocardiography

BACKGROUND

Strain analysis with speckle-tracking echocardiography (STE) is considered superior to ejection fraction for ventricular function assessment in different clinical scenarios. Feature tracking (FT) permits cardiac magnetic resonance (CMR) strain analysis in routinely acquired cine images. This study evaluated the feasibility of CMR-FT and its agreement with STE in patients with acute ST-segment elevation myocardial infarction (STEMI).

METHODS

An echocardiogram and CMR were performed in 128 patients who underwent primary percutaneous revascularisation after a STEMI. Adequate strain analysis was obtained by both techniques in 98 patients and peak systolic longitudinal strain (LS) was assessed with STE and CMR-FT.

RESULTS

Of 1568 myocardial segments, 97.2% were correctly tracked with STE and 97.7% with CMR-FT. For global LS, STE showed a mean of -14.8 ± 3.3% and CMR-FT -13.7 ± 3.0%, with good agreement between modalities [intraclass correlation coefficient (ICC) 0.826; bias -1.09%; limits of agreement (LOA) ± 4.2%]. On the other hand, segmental LS agreement was only moderate, with an ICC of 0.678 (bias -1.14%; LOA ± 11.76%) and the ICC ranged from 0.538 at the basal antero-lateral segment to 0.815 at the apical lateral segment. Finally, both STE and CMR-FT showed excellent intra- and inter-observer reproducibility (ICC > 0.9).

CONCLUSIONS

CMR-FT provides LS with similar feasibility to STE and both techniques showed good agreement for global LS, although agreement at segmental level was only moderate. CMR-FT showed excellent reproducibility, strengthening its robustness and potential for both research and clinical applications.

2- and 3-Dimensional Myocardial Strain in Cardiac Health and Disease

Advances in speckle-tracking echocardiography allowed the rise of deformation imaging as a feasible, robust, and valuable tool for clinical routine. The global or segmental measurement of strain can objectively quantify myocardial deformation and can characterize myocardial function in a novel way. However, the proper interpretation of deformation measurements requires understanding of cardiac mechanics and the influence of loading conditions, ventricular geometry, conduction delays, and myocardial tissue characteristics on the measured values. The purpose of this manuscript is to review the basic concepts of deformation imaging, briefly describe imaging modalities for strain assessment, and discuss in depth the underlying physical and pathophysiological mechanisms which lead to the respective findings in a specific disease.

Software for Post-Processing Analysis of Strain Curves: The D-Station

Fundamento

O emprego de Speckle Tracking para estudo da função cardíaca tem grande aplicabilidade em diversos cenários. A expansão do uso deste método requer ferramentas que permitam a extração de dados relevantes das curvas de deformação cardíaca e que sejam adicionais aos parâmetros habitualmente utilizados.

Objetivos

O presente trabalho visa apresentar e validar um software de uso livre, denominado D-station, para análise das curvas de deformação cardíaca.

Métodos

A partir de arquivos raw data, o D-Station realiza a separação das fases do ciclo cardíaco, exibe simultaneamente curvas de Strain e Strain Rate de diferentes câmaras cardíacas. Para validação do software utilizamos o parâmetro Global Longitudinal Strain (GLS) avaliando-o: 1) Graficamente, a partir da comparação das Medidas emparelhadas de GLS no EchoPAC e D-Station frente à linha de igualdade; 2) pelo Coeficiente de Correlação dessas medidas; 3) pelo Teste de Hipóteses (p > 0,05); e 4) pelo Método Gráfico de Bland-Altman.

Resultados

O Coeficiente rho de Spearman apontou forte correlação entre as medidas, o Teste de Hipóteses retornou um p-value = 0.6798 >> 0,05, que também indicou a equivalência entre elas; o Método gráfico de Bland-Altman mostrou um viés ≤ 1% e dispersão ≤ 2% entre as medidas. Os testes mostraram que para valores de GLS inferiores à 10% há a tendência de aumento das diferenças percentuais, mas seus valores absolutos ainda são baixos.

Conclusão

O D-Station foi validado como uma aplicação suplementar ao EchoPAC que utiliza o raw data das curvas de Strain e Strain Rate obtidos por software proprietário. (Arq Bras Cardiol. 2020; 114(3):496-506)

Acute redistribution of regional left ventricular work by cardiac resynchronization therapy determines long-term remodelling

Aims 

Investigating the acute impact of cardiac resynchronization therapy (CRT) on regional myocardial work distribution in the left ventricle (LV) and to which extent it is related to long-term reverse remodelling.

Methods and results 

One hundred and thirty heart failure patients, referred for CRT implantation, were recruited in our prospective multicentre study. Regional myocardial work was calculated from non-invasive segmental stress–strain loop area before and immediately after CRT. The magnitude of volumetric reverse remodelling was determined from the change in LV end-systolic volume, 11 ± 2 months after implantation. CRT caused acute redistribution of myocardial work across the LV, with an increase in septal work, and decrease in LV lateral wall work (all P &lt; 0.05). Amongst all LV walls, the acute change in work in the septum and lateral wall of the four-chamber view correlated best and significantly with volumetric reverse remodelling (r = 0.62, P &lt; 0.0001), with largest change seen in patients with most volumetric reverse remodelling. In multivariate linear regression analysis, including conventional parameters, such as pre-implant QRS morphology and duration, LV ejection fraction, ischaemic origin of cardiomyopathy, and the redistribution of work across the septal and lateral walls, the latter appeared as the strongest determinant of volumetric reverse remodelling after CRT (model R2 = 0.414, P &lt; 0.0001).

Conclusion 

The acute redistribution of regional myocardial work between the septal and lateral wall of the LV is an important determinant of reverse remodelling after CRT implantation. Our data suggest that the treatment of the loading imbalance should, therefore, be the main aim of CRT.

Regional myocardial strain analysis via 2D speckle tracking echocardiography: validation with sonomicrometry and correlation with regional blood flow in the presence of graded coronary stenoses and dobutamine stress

Background

Quantitative regional strain analysis by speckle tracking echocardiography (STE) may be particularly useful in the assessment of myocardial ischemia and viability, although reliable measurement of regional strain remains challenging, especially in the circumferential and radial directions. We present an acute canine model that integrates a complex sonomicrometer array with microsphere blood flow measurements to evaluate regional myocardial strain and flow in the setting of graded coronary stenoses and dobutamine stress. We apply this unique model to rigorously evaluate a commercial 2D STE software package and explore fundamental regional myocardial flow-function relationships.

Methods

Sonomicrometers (16 crystals) were implanted in epicardial and endocardial pairs across the anterior myocardium of anesthetized open chest dogs (n = 7) to form three adjacent cubes representing the ischemic, border, and remote regions, as defined by their relative locations to a hydraulic occluder on the mid-left anterior descending coronary artery (LAD). Additional cardiac (n = 3) and extra-cardiac (n = 3) reference crystals were placed to define the cardiac axes and aid image registration. 2D short axis echocardiograms, sonometric data, and microsphere blood flow data were acquired at baseline and in the presence of mild and moderate LAD stenoses, both before and during low-dose dobutamine stress (5 μg/kg/min). Regional end-systolic 2D STE radial and circumferential strains were calculated with commercial software (EchoInsight) and compared to those determined by sonomicrometry and to microsphere blood flow measurements. Post-systolic indices (PSIs) were also calculated for radial and circumferential strains.

Results

Low-dose dobutamine augmented both strain and flow in the presence of mild and moderate stenoses. Regional 2D STE strains correlated moderately with strains assessed by sonomicrometry (R_radial = 0.56, p < 0.0001; R_circ = 0.55, p < 0.0001) and with regional flow quantities (R_radial = 0.61, R_circ = 0.63). Overall, correspondence between 2D STE and sonomicrometry was better in the circumferential direction (Bias ± 1.96 SD: − 1.0 ± 8.2% strain, p = 0.06) than the radial direction (5.7 ± 18.3%, p < 0.0001). Mean PSI values were greatest in low flow conditions and normalized with low-dose dobutamine.

Conclusions

2D STE identifies changes in regional end-systolic circumferential and radial strain produced by mild and moderate coronary stenoses and low-dose dobutamine stress. Regional 2D STE end-systolic strain measurements correlate modestly with regional sonomicrometer strain and microsphere flow measurements.

Cardiac Phase Detection in Echocardiograms With Densely Gated Recurrent Neural Networks and Global Extrema Loss

Accurate detection of end-systolic (ES) and end-diastolic (ED) frames in an echocardiographic cine series can be difficult but necessary pre-processing step for the development of automatic systems to measure cardiac parameters. The detection task is challenging due to variations in cardiac anatomy and heart rate often associated with pathological conditions. We formulate this problem as a regression problem and propose several deep learning-based architectures that minimize a novel global extrema structured loss function to localize the ED and ES frames. The proposed architectures integrate convolution neural networks (CNNs)-based image feature extraction model and recurrent neural networks (RNNs) to model temporal dependencies between each frame in a sequence. We explore two CNN architectures: DenseNet and ResNet, and four RNN architectures: long short-term memory, bi-directional LSTM, gated recurrent unit (GRU), and Bi-GRU, and compare the performance of these models. The optimal deep learning model consists of a DenseNet and GRU trained with the proposed loss function. On average, we achieved 0.20 and 1.43 frame mismatch for the ED and ES frames, respectively, which are within reported inter-observer variability for the manual detection of these frames.

Practical tips and tricks in measuring strain, strain rate and twist for the left and right ventricles

Strain imaging provides an accessible, feasible and non-invasive technique to assess cardiac mechanics. Speckle tracking echocardiography (STE) is the primary modality with the utility for detection of subclinical ventricular dysfunction. Investigation and adoption of this technique has increased significantly in both the research and clinical environment. It is therefore important to provide information to guide the sonographer on the production of valid and reproducible data. The focus of this review is to (1) describe cardiac physiology and mechanics relevant to strain imaging, (2) discuss the concepts of strain imaging and STE and (3) provide a practical guide for the investigation and interpretation of cardiac mechanics using STE.

Variability of longitudinal strain measurements: levelling the playing field

Speckle tracking echocardiography offers a unique opportunity to evaluate myocardial function, and global longitudinal strain (GLS) is currently recommended as a measurement of global left ventricular function. To facilitate clinical applicability of the method, collective efforts have been made to standardise strain measurements and to raise awareness of the potential sources of variability. The purpose of this review is to familiarise the reader with the most common sources of variability of longitudinal strain measurements and detail the possible measures to increase the accuracy and reproducibility of strain parameters.

Natural Shear Wave Imaging in the Human Heart: Normal Values, Feasibility, and Reproducibility

Left ventricular myocardial stiffness could offer superior quantification of cardiac systolic and diastolic function when compared to the current diagnostic tools. Shear wave elastography in combination with acoustic radiation force has been widely proposed to noninvasively assess tissue stiffness. Interestingly, shear waves can also result from intrinsic cardiac mechanical events (e.g., closure of valves) without the need for external excitation. However, it remains unknown whether these natural shear waves always occur, how reproducible they can be detected and what the normal range of shear wave propagation speed is. The present study, therefore, aimed at establishing the feasibility of detecting shear waves created after mitral valve closure (MVC) and aortic valve closure (AVC), the variability of the measurements, and at reporting the normal values of propagation velocity. Hereto, a group of 30 healthy volunteers was scanned with high-frame rate imaging (>1000 Hz) using an experimental ultrasound system transmitting a diverging wave sequence. Tissue Doppler velocity and acceleration were used to create septal color M-modes, on which the shear waves were tracked and their velocities measured. Overall, the methodology was capable of detecting the transient vibrations that spread throughout the intraventricular septum in response to the closure of the cardiac valves in 92% of the recordings. Reference velocities of 3.2±0.6 m/s at MVC and 3.5±0.6 m/s at AVC were obtained. Moreover, in order to show the diagnostic potential of this approach, two patients (one with cardiac amyloidosis and one undergoing a dobutamine stress echocardiography) were scanned with the same protocol and showed markedly higher propagation speeds: the former presented velocities of 6.6 and 5.6 m/s; the latter revealed normal propagation velocities at baseline, and largely increased during the dobutamine infusion (>15 m/s). Both cases showed values consistent with the expected changes in stiffness and cardiac loading conditions.

An introduction to left ventricular strain

PURPOSE OF REVIEW

The assessment of left ventricular function by two-dimensional (2D) transthoracic echocardiography (TTE) is conventionally performed by measuring the ejection fraction, which has been shown to have important prognostic implications. However, left ventricular ejection fraction (LVEF) has notable shortcomings, including limited reproducibility, suboptimal inter/intraobserver variability and dependence on load/volume. Furthermore, subclinical left ventricular dysfunction cannot be measured with LVEF. With the advent of left ventricular deformation (strain) analysis, a new and robust means for assessing left ventricular function has emerged.

RECENT FINDINGS

Contemporary research and guidelines have attempted to standardize the definition, acquisition and measurement of left ventricular strain. In addition, multiple studies have sought to establish normal values for left ventricular strain in addition to evaluating the benefits and prognostic value of strain assessment.

SUMMARY

This article reviews the definition of left ventricular strain, outlines the types of strain and reviews how strain is acquired and measured. In addition, the advantages of strain analysis over LVEF as well as the incremental prognostic value of strain are examined. We further review the challenges associated with strain imaging as well as outline the future of strain imaging.

Automatic detection of end-diastolic and end-systolic frames in 2D echocardiography

BACKGROUND

Correctly selecting the end-diastolic and end-systolic frames on a 2D echocardiogram is important and challenging, for both human experts and automated algorithms. Manual selection is time-consuming and subject to uncertainty, and may affect the results obtained, especially for advanced measurements such as myocardial strain.

METHODS AND RESULTS

We developed and evaluated algorithms which can automatically extract global and regional cardiac velocity, and identify end-diastolic and end-systolic frames. We acquired apical four-chamber 2D echocardiographic video recordings, each at least 10 heartbeats long, acquired twice at frame rates of 52 and 79 frames/s from 19 patients, yielding 38 recordings. Five experienced echocardiographers independently marked end-systolic and end-diastolic frames for the first 10 heartbeats of each recording. The automated algorithm also did this. Using the average of time points identified by five human operators as the reference gold standard, the individual operators had a root mean square difference from that gold standard of 46.5 ms. The algorithm had a root mean square difference from the human gold standard of 40.5 ms (P<.0001). Put another way, the algorithm-identified time point was an outlier in 122/564 heartbeats (21.6%), whereas the average human operator was an outlier in 254/564 heartbeats (45%).

CONCLUSION

An automated algorithm can identify the end-systolic and end-diastolic frames with performance indistinguishable from that of human experts. This saves staff time, which could therefore be invested in assessing more beats, and reduces uncertainty about the reliability of the choice of frame.

Echo Parameters for Differential Diagnosis in Cardiac Amyloidosis: A Head-to-Head Comparison of Deformation and Nondeformation Parameters

BACKGROUND

A plethora of echo parameters has been suggested for distinguishing cardiac amyloidosis (CA) from other causes of myocardial thickening with, however, scarce data on their head-to-head comparison. This study aimed at comparing the diagnostic accuracy of various deformation and conventional echo parameters in differentiating CA from other hypertrophic substrates, especially in the gray zone of mild hypertrophy (maximum wall thickness ≤16 mm) or normal ejection fraction (EF).

METHODS AND RESULTS

=0.0002, respectively) independent of the CA type.

CONCLUSIONS

Our study demonstrated that in patients with thickened hearts, EF global longitudinal strain ratio has the best accuracy in detecting CA, even among the most "challenging" patient subgroups as those with mild hypertrophy and normal EF.

Recent advances in echocardiography: strain and strain rate imaging

Deformation imaging by echocardiography is a well-established research tool which has been gaining interest from clinical cardiologists since the introduction of speckle tracking. Post-processing of echo images to analyze deformation has become readily available at the fingertips of the user. New parameters such as global longitudinal strain have been shown to provide added diagnostic value, and ongoing efforts of the imaging societies and industry aimed at harmonizing methods will improve the technique further. This review focuses on recent advances in the field of echocardiographic strain and strain rate imaging, and provides an overview on its current and potential future clinical applications.