Endocardial Border Research Articles

Forthcoming Issues

Fetuses with an estimated fetal weight below the 10th centile have an increased risk of adverse perinatal and long-term outcomes as well as increased rates of cardiac dysfunction, which often alters cardiac size and shape of the 4-chamber view and the individual ventricles. As a result, a simple method has emerged to screen for potential cardiac dysfunction in fetuses with estimated fetal weights <10th centile by measuring the size and shape of the 4-chamber view and the size of the ventricles.To determine the number of fetuses with an abnormal size and shape of the 4-chamber view and size of the ventricles in fetuses with an estimated fetal weight <10th centile.This was a retrospective study of 50 fetuses between 25 and 37 weeks of gestation with an estimated fetal weight <10th centile. Data from their last examination were analyzed. From an end-diastolic image of the 4-chamber view, the largest basal–apical length and transverse width were measured from their corresponding epicardial borders. This allowed the 4-chamber view area and global sphericity index (4-chamber view length/4-chamber view width) to be computed. In addition, tracing along the endocardial borders with speckle tracking software enabled measurements of the right and left ventricular chamber areas and the right ventricle/left ventricle area ratios to be computed. Doppler waveform pulsatility indices from the umbilical (umbilical artery pulsatility index) and middle cerebral arteries (middle cerebral artery pulsatility index) were analyzed, and the cerebroplacental ratio (middle cerebral artery pulsatility index/umbilical artery pulsatility index) computed. Umbilical artery pulsatility indices >90th and cerebroplacental ratios <10th centile were considered abnormal. Using data from the control fetuses, the centile for each of the cardiac measurements was categorized by whether it was <10th or >90th centile, depending upon the measurement.Of the 50 fetuses with estimated fetal weight <10th centile, 50% (n = 25) had a normal umbilical artery pulsatility index and cerebroplacental ratio. These fetuses had significantly more (P < 0.02 to <0.0001) abnormalities of the size and shape of the 4-chamber view than controls. In all, 44% had a 4-chamber view area >90th centile, 32% had a 4-chamber view global sphericity index <10th centile, 56% had a 4-chamber view width >90th centile, and 80% had 1 or more abnormalities of size and/or shape. The remaining 50% of fetuses (n = 25) had abnormalities of 1 or both for the umbilical artery pulsatility index and/or cerebroplacental ratio. These fetuses had significantly higher rates of abnormalities (P <0.05 to <0.0001) than controls for the following 4-chamber view measurements: 36% had a 4-chamber view area >90th centile; 28% had a 4-chamber view global sphericity index <10th centile; and 68% had a 4-chamber view width >90th centile. Only those fetuses with an abnormal umbilical artery pulsatility index had significant changes in ventricular size; 56% had a left ventricular area <10th centile; 28% had a right ventricular area <10th centile; 36% had right ventricular/left ventricular area ratio >90th centile. One or more of the above abnormal measurements were present in 92% of the fetuses.Higher rates of abnormalities of cardiac size and shape of the 4-chamber view were found in fetuses with an estimated fetal weight <10th centile, regardless of their umbilical artery pulsatility index and cerebroplacental ratio measurements. Those with a normal umbilical artery pulsatility index and an abnormal cerebroplacental ratio had larger and wider measurements of the 4-chamber view. In addition, the shape of the 4-chamber view was more globular or round than in controls. These fetuses may have an increased risk of perinatal complications and childhood and/or adult cardiovascular disease. Screening tools derived from the 4-chamber view, acting as surrogates for ventricular dysfunction, may identify fetuses who could benefit from further comprehensive testing and future preventive interventions.

Assessment of mitral valve function in children and young adults with hypertrophic cardiomyopathy using three-dimensional echocardiography

ObjectiveThe objective of this study was to assess papillary muscle (PM) and mitral valve (MV) structure and function in children and young adults with mild and moderate hypertrophic cardiomyopathy (HCM) using real-time three-dimensional echocardiography (3DE) and to correlate them with HCM related adverse outcomes. MethodsTransthoracic research 3DE was performed in HCM patients and controls matched for age and gender. Anterolateral and posteromedial PM mass, apical displacement of anterolateral PM, and left ventricular (LV) mass were measured and indexed to body surface area. The MV annulus and leaflet structure and function were analyzed. Individual PMs were manually planimetered by tracing the endocardial borders on each mid systole frame, taking care to distinguish PMs as distinct from the LV wall. Apical PM displacement was expressed as ratio of the distance between the apex and the base of the anterolateral PM to the entire length of the LV lateral wall (APL index). All 3DE measurements were correlated to adverse outcomes. ResultsForty subjects were studied, including 20 HCM patients (age 18.1 ± 9.6 years, 16 male and 4 female), and 20 controls (18.2 ± 9.6 years, 16 male and 4 female). The indexed LV mass in HCM was 74.8 ± 25.8 g/m2 compared to 50.8 ± 12.4 g/m2 in controls (p = 0.001). The anterolateral, posteromedial and combined PM mass were 3.1 ± 2.2 g/m2, 1.7 ± 1.2 g/m2 and 4.9 ± 2.7 g/m2 in HCM, in contrast to respective measurements of 1.1 ± 0.6 g/m2, 1.2 ± 0.6 g/m2 and 2.3 ± 0.8 g/m2 in controls (p < 0.001, p = 0.062, and p < 0.001, respectively). The mitral valve annular parameters (annulus circumference, height and area) in HCM were not significantly different from controls. The APL index in HCM was less than in controls (0.44 ± 0.07 vs. 0.55 ± 0.04, p < 0.001). The LV lateral wall length and LV mass correlated with adverse HCM outcomes, while the APL index and PM total mass were not associated with adverse events. ConclusionIt is feasible to evaluate PM muscles and MV annulus geometry in children and young adults with HCM using 3DE. The morphologic and functional changes of anterolateral PM may occur in the absence of MV annulus changes. Prospective validation will be required to determine if LV lateral wall length and LV mass may be used as predictors of adverse events.

Systolic longitudinal global and segmental myocardial mechanics in symptomatic isolated left ventricular non-compaction cardiomyopathy.

Left ventricular (LV) non-compaction cardiomyopathy (LV-NC) is rare, and data of segmental myocardial mechanics are largely lacking. We investigated myocardial longitudinal mechanics in adults with symptomatic LV-NC (n=30) versus individuals with healthy hearts (n=150). The contribution of compacted and non-compacted myocardial layer to systolic LV function has to be determined. Seven parameters derived from speckle tracking echocardiography were evaluated and documented utilizing polar-diagrams to obtain overviews of myocardial mechanics of the entire LV. According to embryonal myocardial development, non-compacted myocardium was mostly located in mid-ventricular and apical segments of the free LV wall. LV ejection fraction was reduced in LV-NC (34±15%, healthy 63±5%, P<.0001). The compact wall layer in LV-NC demonstrated increasing systolic radial thickness (diastolic 5.6±1.4, systolic 6.5±1.4mm, P=.016), whereas the non-compacted layer remained unchanged or tended to decrease in thickness (diastolic 17.6±5.3, systolic 16.0±4.6mm, P=.22). Compared with heart-healthy individuals in LV-NC peak systolic longitudinal strain (healthy -21.1% vs. LV-NC -8.8, P<.0001), peak systolic longitudinal strain-rate (-1.23%/s vs. -0.64, P<.0001), and peak longitudinal displacement (12.1 vs. 5.6mm, P<.0001) were reduced, while pre-systolic stretch index (1.31% vs. 3.2%, P<.0001) and post-systolic index (2.5% vs. 15.9%, P<.0001) increased. Time-to-peak longitudinal strain (371 vs. 389ms, P=.065) and time-to-peak longitudinal strain rate (181 vs. 200ms, P=.0677) did not differ significantly. In LV-NC, there were no significant differences between analyses using an interpolated endocardial border along the edges of the recesses and the endocardial edge of the compact wall layer. Hence, LV function appeared to depend only on the thin compact wall layer. In LV-NC, myocardial efficiency is severely diminished compared with healthy controls and LV function seemed to depend mainly on the compact myocardial wall layer.

Fully-automated global and segmental strain analysis of DENSE cardiovascular magnetic resonance using deep learning for segmentation and phase unwrapping

BackgroundCardiovascular magnetic resonance (CMR) cine displacement encoding with stimulated echoes (DENSE) measures heart motion by encoding myocardial displacement into the signal phase, facilitating high accuracy and reproducibility of global and segmental myocardial strain and providing benefits in clinical performance. While conventional methods for strain analysis of DENSE images are faster than those for myocardial tagging, they still require manual user assistance. The present study developed and evaluated deep learning methods for fully-automatic DENSE strain analysis.MethodsConvolutional neural networks (CNNs) were developed and trained to (a) identify the left-ventricular (LV) epicardial and endocardial borders, (b) identify the anterior right-ventricular (RV)-LV insertion point, and (c) perform phase unwrapping. Subsequent conventional automatic steps were employed to compute strain. The networks were trained using 12,415 short-axis DENSE images from 45 healthy subjects and 19 heart disease patients and were tested using 10,510 images from 25 healthy subjects and 19 patients. Each individual CNN was evaluated, and the end-to-end fully-automatic deep learning pipeline was compared to conventional user-assisted DENSE analysis using linear correlation and Bland Altman analysis of circumferential strain.ResultsLV myocardial segmentation U-Nets achieved a DICE similarity coefficient of 0.87 ± 0.04, a Hausdorff distance of 2.7 ± 1.0 pixels, and a mean surface distance of 0.41 ± 0.29 pixels in comparison with manual LV myocardial segmentation by an expert. The anterior RV-LV insertion point was detected within 1.38 ± 0.9 pixels compared to manually annotated data. The phase-unwrapping U-Net had similar or lower mean squared error vs. ground-truth data compared to the conventional path-following method for images with typical signal-to-noise ratio (SNR) or low SNR (p < 0.05), respectively. Bland–Altman analyses showed biases of 0.00 ± 0.03 and limits of agreement of − 0.04 to 0.05 or better for deep learning-based fully-automatic global and segmental end-systolic circumferential strain vs. conventional user-assisted methods.ConclusionsDeep learning enables fully-automatic global and segmental circumferential strain analysis of DENSE CMR providing excellent agreement with conventional user-assisted methods. Deep learning-based automatic strain analysis may facilitate greater clinical use of DENSE for the quantification of global and segmental strain in patients with cardiac disease.

Atri-U: assisted image analysis in routine cardiovascular magnetic resonance volumetry of the left atrium

BackgroundArtificial intelligence can assist in cardiac image interpretation. Here, we achieved a substantial reduction in time required to read a cardiovascular magnetic resonance (CMR) study to estimate left atrial volume without compromising accuracy or reliability. Rather than deploying a fully automatic black-box, we propose to incorporate the automated LA volumetry into a human-centric interactive image-analysis process.Methods and resultsAtri-U, an automated data analysis pipeline for long-axis cardiac cine images, computes the atrial volume by: (i) detecting the end-systolic frame, (ii) outlining the endocardial borders of the LA, (iii) localizing the mitral annular hinge points and constructing the longitudinal atrial diameters, equivalent to the usual workup done by clinicians. In every step human interaction is possible, such that the results provided by the algorithm can be accepted, corrected, or re-done from scratch. Atri-U was trained and evaluated retrospectively on a sample of 300 patients and then applied to a consecutive clinical sample of 150 patients with various heart conditions. The agreement of the indexed LA volume between Atri-U and two experts was similar to the inter-rater agreement between clinicians (average overestimation of 0.8 mL/m2 with upper and lower limits of agreement of − 7.5 and 5.8 mL/m2, respectively). An expert cardiologist blinded to the origin of the annotations rated the outputs produced by Atri-U as acceptable in 97% of cases for step (i), 94% for step (ii) and 95% for step (iii), which was slightly lower than the acceptance rate of the outputs produced by a human expert radiologist in the same cases (92%, 100% and 100%, respectively). The assistance of Atri-U lead to an expected reduction in reading time of 66%—from 105 to 34 s, in our in-house clinical setting.ConclusionsOur proposal enables automated calculation of the maximum LA volume approaching human accuracy and precision. The optional user interaction is possible at each processing step. As such, the assisted process sped up the routine CMR workflow by providing accurate, precise, and validated measurement results.

Texture Analysis of Native T1 Images as a Novel Method for Noninvasive Assessment of Uremic Cardiomyopathy

Noncontrast cardiac T1 times are increased in dialysis patients which might indicate fibrotic alterations in uremic cardiomyopathy. To explore the application of the texture analysis (TA) of T1 images in the assessment of myocardial alterations in dialysis patients. Case-control study. A total of 117 subjects, including 22 on hemodialysis, 44 on peritoneal dialysis, and 51 healthy controls. A 3 T, steady-state free precession (SSFP) sequence, modified Look-Locker imaging (MOLLI). Two independent, blinded researchers manually delineated endocardial and epicardial borders of the left ventricle (LV) on midventricular T1 maps for TA. Texture feature selection was performed, incorporating reproducibility verification, machine learning, and collinearity analysis. Multivariate linear regressions were performed to examine the independent associations between the selected texture features and left ventricular function in dialysis patients. Texture features' performance in discrimination was evaluated by sensitivity and specificity. Reproducibility was estimated by the intraclass correlation coefficient (ICC). Dialysis patients had greater T1 values than normal (P< 0.05). Five texture features were filtered out through feature selection, and four showed a statistically significant difference between dialysis patients and healthy controls. Among the four features, vertical run-length nonuniformity (VRLN) had the most remarkable difference among the control and dialysis groups (144 ± 40 vs. 257 ± 74, P< 0.05), which overlap was much smaller than Global T1 times (1268 ± 38 vs. 1308 ± 46 msec, P< 0.05). The VRLN values were notably elevated (cutoff=170) in dialysis patients, with a specificity of 97% and a sensitivity of 88%, compared with T1 times (specificity=76%, sensitivity=60%). In dialysis patients, VRLN was significantly and independently associated with left ventricular ejection fraction (P< 0.05), global longitudinal strain (P< 0.05), radial strain (P< 0.05), and circumferential strain (P< 0.05); however, T1 was not. The texture features obtained by TA of T1 images and VRLN may be a better parameter for assessing myocardial alterations than T1 times. 4 TECHNICAL EFFICACY: Stage 3.

Myocardial Strain Measured by Epicardial Transducers—Comparison Between Velocity Estimators

This study describes results from an experimental ultrasound system with miniature transducers sutured directly onto the epicardial surface and used to measure heart contractions continuously. This system was used to find velocity distributions through the myocardium. The resulting velocities were used to track the motion of four layers at different depths through the myocardium and to find the regional strain in each of the four layers. Velocities inside the myocardium vary from the epicardial to the endocardial borders. Conventional velocity estimators based on Doppler and on time delay estimation were modified to better handle these variations. Results from four different velocity estimators were tested against a simulation model for ultrasound echoes from moving tissue and on ultrasound recordings from five animals. We observed that the tested velocity estimators were able to reproduce the myocardial velocity distributions, track the myocardial layer motion and estimate strain at different positions inside the myocardium for both simulated and real ultrasound recordings. The most accurate results were obtained when the digitized ultrasound scanlines were upsampled by a factor of 10 before applying cross-correlation to estimate time delays. A modified Doppler algorithm allowing the velocity to vary linearly with time throughout the duration of the pulse packet (constant acceleration Doppler) was found to be better at capturing rapidly changing velocities compared with conventional Doppler processing. The best results were obtained using upsamling and time delay estimation, but the long computation time required by this method may make it best suited in a laboratory setting. In a real-time system, the computationally quicker constant acceleration Doppler may be preferred.

T1 mapping-derived signature of myocardial involvement in idiopathic inflammatory myopathy compared to acute viral myocarditis: a texture-based analysis

Abstract Funding Acknowledgements Type of funding sources: None. Background. Recent studies revealed the ability of MRI T1 mapping to characterize myocardial involvement in both idiopathic inflammatory myopathy (IIM) and acute viral myocarditis (AVM), as compared to healthy controls. However, neither myocardial T1 nor T2 maps were able to discriminate between IIM and AVM patients, when considering conventional myocardial mean values and derived indices such as lambda and extracellular volume. Purpose. To investigate the ability of T1 mapping-derived texture analysis to differentiate IIM from AVM. Methods. Forty patients, 20 with IIM (51 ± 17 years, 9 men) and 20 with AVM (34 ± 13 years, 16 men) underwent 1.5T MRI T1 mapping using a modified Look-Locker inversion-recovery sequence before and 15 minutes after injection of a gadolinium contrast agent. After manual delineation of endocardial and epicardial borders and co-registration of all inversion time images, native and post-contrast T1 maps were estimated. Myocardial texture analysis was performed on native T1 maps. Textural features such as: autocorrelation, contrast, dissimilarity, energy and sum entropy were used to build a least squares-based linear regression model. Finally, receiver operating characteristic (ROC) analysis was used to investigate the ability of such texture features score to classify IIM vs. AVM patients, compared to the performance of mean myocardial T1. A Wilcoxon rank-sum test was also used to test difference significance between groups. Results. Both native and post-contrast mean myocardial T1 values were comparable between IIM (native: 1022 ± 43 ms; post-contrast: 319 ± 44 ms) and AVM (1056 ± 59 ms, p = 0.07; 318 ± 35 ms, p = 0.90, respectively) groups. Results of ROC analyses are provided in the Table, indicating that a better discrimination between IIM and AVM patients was obtained when using texture features, with higher AUC and accuracy than mean T1 values (Figure). Conclusion. Texture analysis derived from MRI T1 maps without contrast agent injection was able to discriminate between IIM and AVM with higher accuracy, sensitivity and specificity than conventional T1 indices. Such analysis could provide a useful myocardial signature to help diagnose and manage cardiac alterations associated with IIM in patients presenting with myocarditis and primarily suspected of AVM. Table Area under curve (AUC) Accuracy Sensitivity Specificity Native T1 0.67 0.70 0.65 0.75 Post-contrast T1 0.49 0.60 0.25 0.95 Texture features score 0.85 0.82 0.90 0.75 ROC analyses for classification between IIM and AVM patients Abstract Figure

Hemodynamic forces and myocardial deformation using cine MRI in Marfan syndrome

Abstract Funding Acknowledgements Type of funding sources: None. Introduction. Cardiovascular assessment of Marfan syndrome (MS) patients has normally focused on the aortic root and vascular manifestations due to the high risk of aortic dissection. Although primary myocardial impairment has long been suspected, the evidence has been controversial. Advanced in CMR may support the early detection of cardiac dysfunction. Beyond left ventricle ejection fraction (EF) and myocardial strain (S), a new parameter is emerging, the hemodynamic forces (HF) exchanged between the blood flowing in the heart and the myocardium. The application of these techniques to MS could be useful in demonstrating the presence of primary myocardial impairment. Aim. The aim of this study is to explore myocardial function in MS through the evaluation in cine CMR of EF, S and cardiac HF exchanged between the blood and the myocardium and compare these data with those of a control group (C). Methods. We retrospectively analysed CMR cine images of MS (diagnosed according revised Ghent criteria) without valvular disease or previous cardio surgery, and C, in standard long-axis projections, to define endocardial borders for subsequent quantification of left ventricular volumes, EF, longitudinal, circumferential and radial S, apex-to-base and lateral-to-septum HF (expressed in mN and as a percentage of gravity acceleration). The analysis were performed on Medical Imaging Systems (QStrain version 1.3.0.79; MEDIS) (Figure 1). Results. 108 MS and 44 C had a good quality study, suitable for MEDIS analysis. The mean age was 33 ± 13 ys in MS, 35 ± 12 ys in C; 39% were male in MS, 50% in C. The results of left ventricular function were: EF 63 ± 7% in MS vs 66 ± 5% in C group, p .008, global longitudinal S -24.5 ± 4.1% in MS vs -26.2 ± 4.1 in C, p .014; global circumferential S -30.6 ± 6.3% in MS vs -33.8 ± 4.4 in C, p .002; radial S 64.5 ± 16.2% in MS vs 72.7 ± 15.9 in C, p .005; apex-to-base HF 13.2 ± 4.7% in MS vs 17.8 ± 7.6% in C, p .000; lateral-to-septum 2.6 ± 1.3% in MS vs 3.1 ± 1.4% in C, p .048. Moreover, 4.6% MS patients had mid reduced EF (40-50%); 9.2% had global longitudinal S reduction (cut off -19.3%); 7.4% had global circumferential S reduction (cut-off -21.7%). Conclusion. These data provide support for the existence of a cardiomyopathy in MS. In our opinion, the term "primary cardiomyopathy" is not appropriate to describe this condition: patients with MS have changes in aortic stiffness and probably in cardiac afterload. The HF data are the most interesting of this study, both in the validation of this new parameter and in early detection a cardiomyopathy in MS Moreover, the reduction of global circumferential S, as wall as global longitudinal S, in MS patients may help provide new elements to characterize the MS cardiomyopathy: sure enough, in literature, circumferential strain abnormalities are related to afterload increase. HF analysis is really a new challenge of cardiac imaging, as sensitive markers of subtle systolic dysfunction. Abstract Figure. Figue 1. Analisis exemple.

Large Biventricular Thrombosis in Acute Myocardial Infarction Assessed at CT Scan

Background: Ventricular thrombosis represents a not uncommon complication of Acute Myocardial Infarction (AMI) and Left Ventricular (LV) thrombosis may complicate large anterior ST-elevation myocardial infarction with anteroapical aneurysm. Right ventricular thrombosis is a more rare complication of inferior infarction. Transthoracic echocardiogram is routinely performed in patients with AMI to assess left ventricular function and the occurrence of thrombotic complications. However, other imaging techniques are occasionally required to more clearly evaluate thrombus extent and endocardial border line. Methods: We report a case of biventricular thrombosis firstly found at echocardiograph examination; the exact extension of biventricular thrombosis, however, was more clearly defined at CT scan. Results: In case of large ventricular thrombosis, CT scan may be useful in the exact definition of thrombus extension when cardiac magnetic resonance is not feasible. Conclusion: When transthoracic ultrasonography does not allow adequate characterization of the thrombus and cardiac magnetic resonance is not feasible, CT scan can provide additional definition of cardiac walls and the extent of the thrombus.

Trabecular complexity as an early marker of cardiac involvement in Fabry disease.

Fabry cardiomyopathy is characterized by glycosphingolipid storage and increased myocardial trabeculation has also been demonstrated. This study aimed to explore by cardiac magnetic resonance whether myocardial trabecular complexity, quantified by endocardial border fractal analysis, tracks phenotype evolution in Fabry cardiomyopathy. Study population included 20 healthy controls (12 males, age 32±9) and 45 Fabry patients divided into three groups: 15 left ventricular hypertrophy (LVH)-negative patients with normal T1 (5 males, age 28±13; Group 1); 15 LVH-negative patients with low T1 (9 males, age 33±9.6; Group 2); 15 LVH-positive patients (11 males, age 53.5±9.6; Group 3). Trabecular fractal dimensions (Dfs) (total, basal, mid-ventricular, and apical) were evaluated on cine images. Total Df was higher in all Fabry groups compared to controls, gradually increasing from controls to Group 3 (1.27±0.02 controls vs. 1.29±0.02 Group 1 vs. 1.30±0.02 Group 2 vs. 1.34±0.02 Group 3; P<0.001). Group 3 showed significantly higher values of all Dfs compared to the other Groups. Both basal and total Dfs were significantly higher in Group 1 compared with controls (basal: 1.30±0.03 vs. 1.26±0.04, P=0.010; total: 1.29±0.02 vs. 1.27±0.02, P=0.044). Total Df showed significant correlations with: (i) T1 value (r=-0.569; P<0.001); (ii) LV mass (r=0.664, P<0.001); (iii) trabecular mass (r=0.676; P<0.001); (iv) Mainz Severity Score Index (r=0.638; P<0.001). Fabry cardiomyopathy is characterized by a progressive increase in Df of endocardial trabeculae together with shortening of T1 values. Myocardial trabeculation is increased before the presence of detectable sphingolipid storage, thus representing an early sign of cardiac involvement.

Automated Segmental Analysis of Fully Quantitative Myocardial Blood Flow Maps by First-Pass Perfusion Cardiovascular Magnetic Resonance.

First pass gadolinium-enhanced cardiovascular magnetic resonance (CMR) perfusion imaging allows fully quantitative pixel-wise myocardial blood flow (MBF) assessment, with proven diagnostic value for coronary artery disease. Segmental analysis requires manual segmentation of the myocardium. This work presents a fully automatic method of segmenting the left ventricular myocardium from MBF pixel maps, validated on a retrospective dataset of 247 clinical CMR perfusion studies, each including rest and stress images of three slice locations, performed on a 1.5T scanner. Pixel-wise MBF maps were segmented using an automated pipeline including region growing, edge detection, principal component analysis, and active contours to segment the myocardium, detect key landmarks, and divide the myocardium into sectors appropriate for analysis. Automated segmentation results were compared against a manually defined reference standard using three quantitative metrics: Dice coefficient, Cohen Kappa and myocardial border distance. Sector-wise average MBF and myocardial perfusion reserve (MPR) were compared using Pearson’s correlation coefficient and Bland-Altman Plots. The proposed method segmented stress and rest MBF maps of 243 studies automatically. Automated and manual myocardial segmentation had an average (± standard deviation) Dice coefficient of 0.86 ± 0.06, Cohen Kappa of 0.86 ± 0.06, and Euclidian distances of 1.47 ± 0.73 mm and 1.02 ± 0.51 mm for the epicardial and endocardial border, respectively. Automated and manual sector-wise MBF and MPR values correlated with Pearson’s coefficient of 0.97 and 0.92, respectively, while Bland-Altman analysis showed bias of 0.01 and 0.07 ml/g/min. The validated method has been integrated with our fully automated MBF pixel mapping pipeline to aid quantitative assessment of myocardial perfusion CMR.

Comparison of Four Different Techniques for Estimation of Left Ventricular Volumes Using Intraoperative Real Time Three Dimensional Transesophageal Echocardiography--A Prospective Observational Study

The primary objective of the present study was to compare cardiac output derived with four methods of QLab (Philips, Amsterdam, Netherlands) software using real-time three-dimensional (3D) transesophageal echocardiography, with cardiac output obtained with the 3D left ventricular outflow tract (LVOT) cardiac output method. The secondary objective was to assess left ventricular (LV) volumes, LV ejection fraction, and cardiac output derived with four different methods of real time 3D transesophageal echocardiography processed in QLab software and to determine whether these parameters differed among these four methods. A prospective observational study. A tertiary referral center and a university level teaching hospital. The study comprised 50 patients scheduled for elective coronary artery bypass surgery without any concomitant valvular lesions. Three-dimensional full-volume datasets were obtained in optimum conditions. The 3D datasets were analyzed using four different methods in QLab, version 9. In method A, LV volumes were derived without endocardial border adjustment. In method B, LV volumes were obtained after endocardial border adjustment in the long-axis view alone. In method C, the iSlice tool (Philips) was used to adjust the endocardial borders in 16 short-axis slices. In method D, endocardial borders were adjusted after dataset processing to obtain LV volumes. The cardiac output derived with the 3D echocardiography LVOT method was 3.93 ± 1.44 L/min, with method A was 3.26 ± 1.42 L/min, with method B was 3.51 ± 1.2 L/min, with method C was 4.01 ± 1.40 L/min, and with method D was 4.18 ± 1.58 L/min. There was a significant positive correlation between the cardiac output derived using the 3D LVOT method and method C (r = 0.71). Readjusting the endocardial border contours resulted in higher LV volumes than the volumes estimated using semiautomated border algorithms. The iSlice method produced the highest and the most accurate LV volumes, although it required the longest time to analyze and derive results. The ejection fraction obtained with all four methods of QLab demonstrated no statistical differences and had a strong correlation with the two-dimensional echocardiography-derived left ventricular ejection fraction.

A New Strategy for Left Ventricular Assist Device Outflow Graft Interrogation Using Ultrasound Contrast

Interrogation of the outflow graft (OTG)-ascending aorta anastomosis is an integral part of the transthoracic echocardiographic (TTE) evaluation of left ventricular assist devices (LVADs) as it is important to confirm patency of this communication. However, it can be challenging to image the OTG anastomosis on TTE. Ultrasound enhancing agents (UEAs) have been used successfully to enhance visualization of endocardial borders and intracardiac masses.1-3 We hypothesized that UEAs would improve OTG detection, optimize the alignment of Doppler velocity signals with graft flow, and enable more meaningful peak velocity measurements across the anastomosis of the OTG to the ascending aorta.

LU-Net: A Multistage Attention Network to Improve the Robustness of Segmentation of Left Ventricular Structures in 2-D Echocardiography.

Segmentation of cardiac structures is one of the fundamental steps to estimate volumetric indices of the heart. This step is still performed semiautomatically in clinical routine and is, thus, prone to interobserver and intraobserver variabilities. Recent studies have shown that deep learning has the potential to perform fully automatic segmentation. However, the current best solutions still suffer from a lack of robustness in terms of accuracy and number of outliers. The goal of this work is to introduce a novel network designed to improve the overall segmentation accuracy of left ventricular structures (endocardial and epicardial borders) while enhancing the estimation of the corresponding clinical indices and reducing the number of outliers. This network is based on a multistage framework where both the localization and segmentation steps are optimized jointly through an end-to-end scheme. Results obtained on a large open access data set show that our method outperforms the current best-performing deep learning solution with a lighter architecture and achieved an overall segmentation accuracy lower than the intraobserver variability for the epicardial border (i.e., on average a mean absolute error of 1.5 mm and a Hausdorff distance of 5.1mm) with 11% of outliers. Moreover, we demonstrate that our method can closely reproduce the expert analysis for the end-diastolic and end-systolic left ventricular volumes, with a mean correlation of 0.96 and a mean absolute error of 7.6 ml. Concerning the ejection fraction of the left ventricle, results are more contrasted with a mean correlation coefficient of 0.83 and an absolute mean error of 5.0%, producing scores that are slightly below the intraobserver margin. Based on this observation, areas for improvement are suggested.

Artificial Intelligence Aids Cardiac Image Quality Assessment for Improving Precision in Strain Measurements

ObjectivesThe aim of this study was to develop an artificial intelligence tool to assess echocardiographic image quality objectively. BackgroundLeft ventricular global longitudinal strain (LVGLS) has recently been used to monitor cancer therapeutics−related cardiac dysfunction (CTRCD) but image quality limits its reliability. MethodsA DenseNet-121 convolutional neural network was developed for view identification from an athlete’s echocardiographic dataset. To prove the concept that classification confidence (CC) can serve as a quality marker, values of longitudinal strain derived from feature tracking of cardiac magnetic resonance (CMR) imaging and strain analysis of echocardiography were compared. The CC was then applied to patients with breast cancer free from CTRCD to investigate the effects of image quality on the reliability of strain analysis. ResultsCC of the apical 4-chamber view (A4C) was significantly correlated with the endocardial border delineation index. CC of A4C >900 significantly predicted a <15% relative difference in longitudinal strain between CMR feature tracking and automated echocardiographic analysis. Echocardiographic studies (n =752) of 102 patients with breast cancer without CTRCD were investigated. The strain analysis showed higher parallel forms, inter-rater, and test-retest reliabilities in patients with CC of A4C >900. During sequential comparisons of automated LVGLS in individual patients, those with CC of A4C >900 had a lower false positive detection rate of CTRCD. ConclusionsCC of A4C was associated with the reliability of automated LVGLS and could also potentially be used as a filter to select comparable images from sequential echocardiographic studies in individual patients and reduce the false positive detection rate of CTRCD.

Abstract 14082: The Effect of Diagnostic Ultrasound Mediated High Mechanical Impulses on Cardiac Output During an Ultrasound Enhancing Agent Infusion

Introduction: Diagnostic ultrasound high mechanical index (MI) impulses are used during an ultrasound enhancing agent (UEA) infusion to improve endocardial border resolution and study myocardial perfusion. They have also been shown to cause endothelial shear, resulting in prolonged increases in ATP release and augment microvascular flow. The potential for these high MI impulses to alter cardiac output (CO) are unknown. Hypothesis: To study the impact of high MI impulses on CO Methods: Fifty one patients (mean age 63±15 years; 41% female) referred for contrast echocardiography underwent very low MI imaging with intermittent high MI impulses (1.6-1.7 Megahertz) in three different apical windows during either a Definity (Lantheus Medical) or Lumason (Bracco Diagnostics) infusion or bolus. CO was determined from Doppler measurements of left ventricular outflow tract stroke volume and heart rate. Mean contrast enhanced biplane left ventricular ejection fraction (LVEF) was 53±15%; (range 10-75%). CO from baseline without contrast (COwoC) and baseline after contrast (COwC) before high MI impulses were compared to CO after contrast and after high MI impulses (COaHMI). All CO measurements were made by an independent reviewer blinded to time of measurement (before or after high MI impulses). Results: Although heart rate did not change before and after intermittent high MI impulse administration, COaHMI increased significantly when compared to COwoC and COwC (p&lt; 0.001 for both comparisons; Figure). In nine patients (18%), CO increased by more than 20%. In patients with LVEF &lt; 40% COwC was 2.4±0.8 liters per minute (LPM) and COaHMI increased to 2.7± 0.8 LPM (p=0001). In patients with LVEF≥40%, COwC was 3.4±1.06 LPM while COaHMI increased to 3.8± 1.2 LPM (p=0.00001). Conclusions: Application of diagnostic guided high MI impulses during a commercially available microbubble infusion significantly increases CO irrespective of underlying left ventricular systolic function.

Comparing the Non-Quiver and Quiver Techniques for Identification of the Endocardial Borders Used for Speckle-Tracking Analysis of the Ventricles of the Fetal Heart.

This study compared the non-quiver with the quiver technique for identifying the end-systolic and end-diastolic endocardium of the fetal right ventricle (RV) and left ventricle (LV) used for speckle-tracking analysis. Bland-Altman and t test analyses showed no significant differences in measurements between the techniques for the RV and LV. The difference in the time required to perform the non-quiver analysis was significantly longer (P < .001) for the RV and LV than the quiver technique. The quiver technique allows the examiner to efficiently identify the endocardial borders of the fetal heart compared with the non-quiver method.

The effect of pulmonary arterial hypertension specific treatment on the left ventricle in patients with pulmonary arterial hypertension

Abstract Background Pulmonary arterial hypertension (PAH) is characterized by right ventricular (RV) pressure overload, leading to RV dilation, failure and death. In the course of the disease, the left ventricle (LV) is often impaired, due to interventricular interaction. Although the impact of PAH treatment on the RV has been well described, less is known on the LV. Purpose To examine effects of advanced PAH treatments on the volumes, function and strain of the left atrium and ventricle. Methods This is a retrospective study. All patients underwent CMR and right heart catheterization, both at diagnosis and at 12-months follow up. Ventricular volumes and LV filling rate were calculated from the stack of short axis cine images using Simpsons method while left atrial (LA) volumes from the 4-chamber cine images using the area-length method. Tissue tracking was used for the evaluation of myocardial deformation. The LV endocardial and epicardial borders were manually delineated in all analysed sections with the initial contour set at end-diastole. All analyses were performed offline using dedicated software. Results In total, 66 patients (mean age 56.3±17.9 years, 67%women, 77%idiopathic and heritable PAH, 23% connective tissue disease associated PAH) and 29 normal controls were included. The improvement in metrics of right and left heart size and function after the initiation of advanced PAH treatment, are presented in panel A. Of note, LV stroke volume was markedly increased (54.6±19.6ml at baseline vs 70.8±21.7ml at follow up, p&amp;lt;0.0001) to reach controls. LV filling was markedly increased in latter two-thirds of the diastolic phase (panel B), especially at atrial kick point (arrow). Change in LA max volume was associated with changes in diastolic filling (r=0.354, p=0.004), LV end-diastolic and end-systolic volumes and stroke volume. These correlations were more robust in patients that increased LV filling compared to those that failed to increase LV filling (panels C-E). No association between changes in LV circumferential strain and LV volume load was observed. A weak correlation of change of LV peak longitudinal strain with stroke volume (r=−0.345, p=0.006), LV end diastolic volume (r=−0.284, p=0.027), LV ejection fraction (r=−0.337, p=0.008) and LA maximum area (r=−0.447, p&amp;lt;0.0001) was observed. The changes of LV strain showed no correlation with the changes in patients' haemodynamics. Conclusion Improvement in stroke volume after the initiation of advanced PAH treatment is associated with an increase in LA size, LV end diastolic volume and normalisation of strain. This reflects the improved filling state of the left ventricle and the potential of the left atrium to monitor treatment effects. Changes after PAH treatment Funding Acknowledgement Type of funding source: None

Left ventricular septal convexity in differentiating hypertrophic cardiomyopathy from hypertensive heart disease – cardiac MRI study

Abstract Background Subjects with hypertrophic cardiomyopathy (HCM) and hypertensive heart disease (HHD) have left ventricular hypertrophy (LVH). It is a common clinical problem to distinguish HCM from HHD. Septal convexity (SC) into the left ventricle is increased in subjects with hypertrophic cardiomyopathy (HCM)-causing mutations with and without LVH. Purpose Our objective was to study if SC by cardiac magnetic resonance (CMR) differentiates between HCM and HHD. Methods We measured SC in 29 subjects with hypertension and LVH (left ventricular maximal wall thickness (LVMWT) ≥13 mm), in 49 subjects with HCM (LVMWT ≥13 mm) caused by the D175N mutation in the alpha-tropomyosin (TPM1) or the Q1061X mutation in the myosin binding protein C (MYBPC3) genes, and in 20 healthy controls with no LVH. SC into the LV was measured in end-diastolic 4-chamber images as the maximal distance between LV septal endocardial border and a line connecting septal mid-wall points at the level of tricuspid valve insertion and at the level of apical right ventricular insertion on the LV. Results Subjects with HCM had significantly increased septal convexity compared to subjects with HHD both in non-indexed and in BSA-indexed measurements (10.7±4.0 mm vs 4.9±2.7 mm, P&amp;lt;0.001 and 5.5±2.1 mm/m2 vs 2.4±1.3 mm/m2, P&amp;lt;0.001). To differentiate between HCM and HHD, septal convexity cutoff value of 7.85 mm performed best with sensitivity of 77% and specificity of 90%. BSA-indexed SC cutoff value of 3.68 mm differentiated between HCM and HHD with sensitivity of 81% and specificity of 86%. Conclusions CMR derived septal convexity is easily measured and is useful in discriminating between HCM caused by sarcomere mutations versus HHD. Measurement of septal convexity Funding Acknowledgement Type of funding source: Private grant(s) and/or Sponsorship. Main funding source(s): Finnish Foundation of Cardiovascular Research, the special governmental subsidy for health sciences research of the University Hospital of Kuopio