Age-Dependence of Flow Homeostasis in the Left Ventricle

Stasis imaging predicts the risk of cardioembolic events related to acute myocardial infarction: the ISBITAMI study

INTRODUCTION AND OBJECTIVES

In the setting of ST-segment elevation myocardial infarction (STEMI), imaging-based biomarkers could be useful for guiding oral anticoagulation to prevent cardioembolism. Our objective was to test the efficacy of intraventricular blood stasis imaging for predicting a composite primary endpoint of cardioembolic risk during the first 6 months after STEMI.

METHODS

We designed a prospective clinical study, Imaging Silent Brain Infarct in Acute Myocardial Infarction (ISBITAMI), including patients with a first STEMI, an ejection fraction ≤ 45% and without atrial fibrillation to assess the performance of stasis metrics to predict cardioembolism. Patients underwent ultrasound-based stasis imaging at enrollment followed by heart and brain magnetic resonance at 1-week and 6-month visits. From the stasis maps, we calculated the average residence time, RT, of blood inside the left ventricle and assessed its performance to predict the primary endpoint. The longitudinal strain of the 4 apical segments was quantified by speckle tracking.

RESULTS

A total of 66 patients were assigned to the primary endpoint. Of them, 17 patients had 1 or more events: 3 strokes, 5 silent brain infarctions, and 13 mural thromboses. No systemic embolisms were observed. RT (OR, 3.73; 95%CI, 1.75-7.9; P<.001) and apical strain (OR, 1.47; 95%CI, 1.13-1.92; P=.004) showed complementary prognostic value. The bivariate model showed a c-index=0.86 (95%CI, 0.73-0.95), a negative predictive value of 1.00 (95%CI, 0.94-1.00), and positive predictive value of 0.45 (95%CI, 0.37-0.77). The results were confirmed in a multiple imputation sensitivity analysis. Conventional ultrasound-based metrics were of limited predictive value.

CONCLUSIONS

In patients with STEMI and left ventricular systolic dysfunction in sinus rhythm, the risk of cardioembolism may be assessed by echocardiography by combining stasis and strain imaging. Registered at ClinicalTrials.gov (NCT02917213).

Deriving phenotype-representative left ventricular flow patterns by reduced-order modeling and classification

BACKGROUND

Extracting phenotype-representative flow patterns and their associated numerical metrics is a bottleneck in the clinical translation of advanced cardiac flow imaging modalities. We hypothesized that reduced-order models (ROMs) are a suitable strategy for deriving simple and interpretable clinical metrics of intraventricular flow suitable for further assessments. Combined with machine learning (ML) flow-based ROMs could provide new insight to help diagnose and risk-stratify patients.

METHODS

We analyzed 2D color-Doppler echocardiograms of 81 non-ischemic dilated cardiomyopathy (DCM) patients, 51 hypertrophic cardiomyopathy (HCM) patients, and 77 normal volunteers (Control). We applied proper orthogonal decomposition (POD) to build patient-specific and cohort-specific ROMs of LV flow. Each ROM aggregates a low number of components representing a spatially dependent velocity map modulated along the cardiac cycle by a time-dependent coefficient. We tested three classifiers using deliberately simple ML analyses of these ROMs with varying supervision levels. In supervised models, hyperparameter grid search was used to derive the ROMs that maximize classification power. The classifiers were blinded to LV chamber geometry and function. We ran vector flow mapping on the color-Doppler sequences to help visualize flow patterns and interpret the ML results.

RESULTS

POD-based ROMs stably represented each cohort through 10-fold cross-validation. The principal POD mode captured >80 % of the flow kinetic energy (KE) in all cohorts and represented the LV filling/emptying jets. Mode 2 represented the diastolic vortex and its KE contribution ranged from <1 % (HCM) to 13 % (DCM). Semi-unsupervised classification using patient-specific ROMs revealed that the KE ratio of these two principal modes, the vortex-to-jet (V2J) energy ratio, is a simple, interpretable metric that discriminates DCM, HCM, and Control patients. Receiver operating characteristic curves using V2J as classifier had areas under the curve of 0.81, 0.91, and 0.95 for distinguishing HCM vs. Control, DCM vs. Control, and DCM vs. HCM, respectively.

CONCLUSIONS

Modal decomposition of cardiac flow can be used to create ROMs of normal and pathological flow patterns, uncovering simple interpretable flow metrics with power to discriminate disease states, and particularly suitable for further processing using ML.

Cardiac stasis imaging, stroke, and silent brain infarcts in patients with nonischemic dilated cardiomyopathy

Cardioembolic stroke is one of the most devastating complications of nonischemic dilated cardiomyopathy (NIDCM). However, in clinical trials of primary prevention, the benefits of anticoagulation are hampered by the risk of bleeding. Indices of cardiac blood stasis may account for the risk of stroke and be useful to individualize primary prevention treatments. We performed a cross-sectional study in patients with NIDCM and no history of atrial fibrillation (AF) from two sources: 1) a prospective enrollment of unselected patients with left ventricular (LV) ejection fraction <45% and 2) a retrospective identification of patients with a history of previous cardioembolic neurological event. The primary end point integrated a history of ischemic stroke or the presence intraventricular thrombus, or a silent brain infarction (SBI) by imaging. From echocardiography, we calculated blood flow inside the LV, its residence time (TR) maps, and its derived stasis indices. Of the 89 recruited patients, 18 showed a positive end point, 9 had a history of stroke or transient ischemic attack (TIA) and 9 were diagnosed with SBIs in the brain imaging. Averaged TR, [Formula: see text] performed well to identify the primary end point [AUC (95% CI) = 0.75 (0.61-0.89), P = 0.001]. When accounting only for identifying a history of stroke or TIA, AUC for [Formula: see text] was 0.92 (0.85-1.00) with odds ratio = 7.2 (2.3-22.3) per cycle, P < 0.001. These results suggest that in patients with NIDCM in sinus rhythm, stasis imaging derived from echocardiography may account for the burden of stroke.NEW & NOTEWORTHY Patients with nonischemic dilated cardiomyopathy (NIDCM) are at higher risk of stroke than their age-matched population. However, the risk of bleeding neutralizes the benefit of preventive oral anticoagulation. In this work, we show that in patients in sinus rhythm, the burden of stroke is related to intraventricular stasis metrics derived from echocardiography. Therefore, stasis metrics may be useful to personalize primary prevention anticoagulation in these patients.

Deriving Explainable Metrics of Left Ventricular Flow by Reduced-Order Modeling and Classification

Background

Extracting explainable flow metrics is a bottleneck to the clinical translation of advanced cardiac flow imaging modalities. We hypothesized that reduced-order models (ROMs) of intraventricular flow are a suitable strategy for deriving simple and interpretable clinical metrics suitable for further assessments. Combined with machine learning (ML) flow-based ROMs could provide new insight to help diagnose and risk-stratify patients.

Methods

We analyzed 2D color-Doppler echocardiograms of 81 non-ischemic dilated cardiomyopathy (DCM) patients, 51 hypertrophic cardiomyopathy (HCM) patients, and 77 normal volunteers (Control). We applied proper orthogonal decomposition (POD) to build patient-specific and cohort-specific ROMs of LV flow. Each ROM aggregates a low number of components representing a spatially dependent velocity map modulated along the cardiac cycle by a time-dependent coefficient. We tested three classifiers using deliberately simple ML analyses of these ROMs with varying supervision levels. In supervised models, hyperparameter gridsearch was used to derive the ROMs that maximize classification power. The classifiers were blinded to LV chamber geometry and function. We ran vector flow mapping on the color-Doppler sequences to help visualize flow patterns and interpret the ML results.

Results

POD-based ROMs stably represented each cohort through 10-fold cross-validation. The principal POD mode captured >80% of the flow kinetic energy (KE) in all cohorts and represented the LV filling/emptying jets. Mode 2 represented the diastolic vortex and its KE contribution ranged from <1% (HCM) to 13% (DCM). Semi-unsupervised classification using patient-specific ROMs revealed that the KE ratio of these two principal modes, the vortex-to-jet (V2J) energy ratio, is a simple, interpretable metric that discriminates DCM, HCM, and Control patients. Receiver operating characteristic curves using V2J as classifier had areas under the curve of 0.81, 0.91, and 0.95 for distinguishing HCM vs. Control, DCM vs. Control, and DCM vs. HCM, respectively.

Conclusions

Modal decomposition of cardiac flow can be used to create ROMs of normal and pathological flow patterns, uncovering simple interpretable flow metrics with power to discriminate disease states, and particularly suitable for further processing using ML.

Risk Factors for Left Ventricular Thrombus Formation in Patients with Dilated Cardiomyopathy

BACKGROUND

 Left ventricular thrombus (LVT) is a common complication of dilated cardiomyopathy (DCM), causing morbidity and mortality.

METHODS

 This study retrospectively analyzed patients with DCM from January 2002 to August 2020 in Beijing Anzhen Hospital. Clinical characteristics were compared between the LVT group and the age and sex 1:4 matched with the LVT absent group. The receiver operator characteristic (ROC) curve was plotted to evaluate the diagnostic value of D-dimer predicting LVT occurrence in DCM.

RESULTS

 A total of 3,134 patients were screened, and LVT was detected in 72 (2.3%) patients on echocardiography. The patients with LVT had higher D-dimer, fibrinogen, and lower systolic blood pressure than those without LVT. The ejection fraction (EF) was lower and left ventricular end-systolic diameter was larger in the LVT group. Severe mitral regurgitation (MR) was more common in the LVT absent groups. The prevalence of atrial fibrillation was lower in the LVT group. The ROC curve analysis yielded an optimal cut-off value of 444 ng/mL DDU (D-dimer units) for D-dimer to predict the presence of LVT. Multivariable binary logistic regression analysis revealed that EF (OR = 0.90, 95% CI = 0.86-0.95), severe MR (OR = 0.19, 95% CI = 0.08-0.48), and D-dimer level (OR = 15.4, 95% CI = 7.58-31.4) were independently associated with LVT formation.

CONCLUSION

 This study suggested that elevated D-dimer levels (>444 ng/mL DDU) and reduced EF were independently associated with increased risk of LVT formation. Severe MR could decrease the incidence of LVT.

A Case of Left Ventricular Thrombus and Herpetic Esophagitis in an Immunocompetent Patient With COVID-19

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has been associated with thrombosis, both venous and arterial, but the mechanism behind this coagulation is not fully understood. Several cases involving coronavirus disease 2019 (COVID-19)-positive patients with left ventricular thrombus (LVT), particularly in those with low ejection fraction, have been reported. This report describes a case of a 57-year-old male patient who presented to the hospital with altered mental status and a positive SARS-CoV-2 polymerase chain reaction (PCR) test. CT of the chest revealed the presence of an LVT, and transthoracic echocardiography showed a reduced ejection fraction and confirmed the presence of the thrombus. The patient also reported epigastric chest pain and several bloody bowel movements. A colonoscopy revealed internal hemorrhoids. An esophagogastroduodenoscopy revealed the presence of multiple esophageal ulcers, and biopsy results confirmed herpes simplex virus (HSV) infection. The patient had no history of organ or bone marrow transplant, long-term immunosuppressive therapy, or HIV infection. He was eventually discharged on apixaban for his LVT and acyclovir for his HSV esophagitis.

Retrospective Analysis of Left Ventricular Thrombus Among Heart Failure Patients with Reduced Ejection Fraction at a Single Tertiary Care Hospital in Somalia

Introduction

Left ventricular thrombus (LVT) is a common complication in patients with systolic heart failure and can cause thromboembolic consequences including stroke. In order to determine the characteristics of LV thrombus among heart failure patients with reduced ejection fraction (HFrEF), the present study was undertaken.

Methods and Materials

This was retrospective cross-sectional study conducted from referral tertiary hospital in a year period. A total of 810 transthoracic echocardiograms were carried out in our center from January 2021 to December 2021. Forty participants had met the inclusion criteria of the study.

Results

About 75% of the population was male and the mean age at diagnosis was 51 years (SD: 15). Ischemic cardiomyopathy and dilated cardiomyopathy (DCMP) found to be the most underlying cause of LVT represented (57.5% and 42.5% respectively). Hypertension, hypothyroidism, and atrial fibrillation were found to be the commonest associated risk factors of LVT, 45%, 12.5%, and 30% respectively. Simpson's Biplane's approach yielded a mean LVEF of 25.25 ± 6.97. 60% of the patients had a LVEF of ≤25%. The mean LV end-diastolic and end-systolic diameters were 59.2 ± 9.4 mm and 51 ± 8.3mm respectively. Warfarin was administered to 19 (47.5), Rivaroxaban to 8 (20), and Dabigatran to 10 (25). The most prevalent anticoagulant among the individuals in our study was warfarin. A stroke complication was found in 8 patients (20%), two of them were hemorrhagic stroke and they were on dabigatran. A Peripheral Arterial Disease (PAD) affected 6 of the patients (15%). One of those with PAD had also ischemic stroke.

Conclusion

This study determines that Ischemic and Dilated cardiomyopathy were the most common cause of left ventricular thrombosis among HFrEF patients in Somalia.

Assessment of Blood Flow Transport in the Left Ventricle Using Ultrasound. Validation Against 4-D Flow Cardiac Magnetic Resonance

Four-dimensional flow cardiac magnetic resonance (CMR) is the reference technique for analyzing blood transport in the left ventricle (LV), but similar information can be obtained from ultrasound. We aimed to validate ultrasound-derived transport in a head-to-head comparison against 4D flow CMR. In five patients and two healthy volunteers, we obtained 2D + t and 3D + t (4D) flow fields in the LV using transthoracic echocardiography and CMR, respectively. We compartmentalized intraventricular blood flow into four fractions of end-diastolic volume: direct flow (DF), retained inflow (RI), delayed ejection flow (DEF) and residual volume (RV). Using ultrasound we also computed the properties of LV filling waves (percentage of LV penetration and percentage of LV volume carried by E/A waves) to determine their relationships with CMR transport. Agreement between both techniques for quantifying transport fractions was good for DF and RV (Ric [95% confidence interval]: 0.82 [0.33, 0.97] and 0.85 [0.41, 0.97], respectively) and moderate for RI and DEF (Ric= 0.47 [-0.29, 0.88] and 0.55 [-0.20, 0.90], respectively). Agreement between techniques to measure kinetic energy was variable. The amount of blood carried by the E-wave correlated with DF and RV (R = 0.75 and R = 0.63, respectively). Therefore, ultrasound is a suitable method for expanding the analysis of intraventricular flow transport in the clinical setting.

Non-Newtonian blood rheology impacts left atrial stasis in patient-specific simulations

The lack of mechanically effective contraction of the left atrium (LA) during atrial fibrillation (AF) disturbs blood flow, increasing the risk of thrombosis and ischemic stroke. Thrombosis is most likely in the left atrial appendage (LAA), a small narrow sac where blood is prone to stagnate. Slow flow promotes the formation of erythrocyte aggregates in the LAA, also known as rouleaux, causing viscosity gradients that are usually disregarded in patient-specific simulations. To evaluate these non-Newtonian effects, we built atrial models derived from 4D computed tomography scans of patients and carried out computational fluid dynamics simulations using the Carreau-Yasuda constitutive relation. We examined six patients, three of whom had AF and LAA thrombosis or a history of transient ischemic attacks (TIAs). We modeled the effects of hematocrit and rouleaux formation kinetics by varying the parameterization of the Carreau-Yasuda relation and modulating non-Newtonian viscosity changes based on residence time. Comparing non-Newtonian and Newtonian simulations indicates that slow flow in the LAA increases blood viscosity, altering secondary swirling flows and intensifying blood stasis. While some of these effects are subtle when examined using instantaneous metrics like shear rate or kinetic energy, they are manifested in the blood residence time, which accumulates over multiple heartbeats. Our data also reveal that LAA blood stasis worsens when hematocrit increases, offering a potential new mechanism for the clinically reported correlation between hematocrit and stroke incidence. In summary, we submit that hematocrit-dependent non-Newtonian blood rheology should be considered when calculating patient-specific blood stasis indices by computational fluid dynamics.

Optimization of Microbubble Concentration and Acoustic Pressure for Left Ventricular High-Frame-Rate EchoPIV in Patients

High-frame-rate (HFR) echo-particle image velocimetry (echoPIV) is a promising tool for measuring intracardiac blood flow dynamics. In this study, we investigate the optimal ultrasound contrast agent (UCA: SonoVue) infusion rate and acoustic output to use for HFR echoPIV (PRF = 4900 Hz) in the left ventricle (LV) of patients. Three infusion rates (0.3, 0.6, and 1.2 ml/min) and five acoustic output amplitudes (by varying transmit voltage: 5, 10, 15, 20, and 30 V-corresponding to mechanical indices of 0.01, 0.02, 0.03, 0.04, and 0.06 at 60-mm depth) were tested in 20 patients admitted for symptoms of heart failure. We assess the accuracy of HFR echoPIV against pulsed-wave Doppler acquisitions obtained for mitral inflow and aortic outflow. In terms of image quality, the 1.2-ml/min infusion rate provided the highest contrast-to-background ratio (CBR) (3-dB improvement over 0.3 ml/min). The highest acoustic output tested resulted in the lowest CBR. Increased acoustic output also resulted in increased microbubble disruption. For the echoPIV results, the 1.2-ml/min infusion rate provided the best vector quality and accuracy; mid-range acoustic outputs (corresponding to 15-20-V transmit voltages) provided the best agreement with the pulsed-wave Doppler. Overall, the highest infusion rate (1.2 ml/min) and mid-range acoustic output amplitudes provided the best image quality and echoPIV results.

Intraventricular Flow Patterns in Patients Treated with Left Ventricular Assist Devices

The success of left ventricular assist device (LVAD) therapy is hampered by complications such as thrombosis and bleeding. Understanding blood flow interactions between the heart and the LVAD might help optimize treatment and decrease complication rates. We hypothesized that LVADs modify shear stresses and blood transit in the left ventricle (LV) by changing flow patterns and that these changes can be characterized using 2D echo color Doppler velocimetry (echo-CDV). We used echo-CDV and custom postprocessing methods to map blood flow inside the LV in patients with ongoing LVAD support (Heartmate II, N = 7). We compared it to healthy controls (N = 20) and patients with dilated cardiomyopathy (DCM, N = 20). We also analyzed intraventricular flow changes during LVAD ramp tests (baseline ± 400 rpm). LVAD support reversed the increase in blood stasis associated with DCM, but it did not reduce intraventricular shear exposure. Within the narrow range studied, the ventricular flow was mostly insensitive to changes in pump speed. Patients with significant aortic insufficiency showed abnormalities in blood stasis and shear indices. Overall, this study suggests that noninvasive flow imaging could potentially be used in combination with standard clinical methods for adjusting LVAD settings to optimize flow transport and minimize stasis on an individual basis.

The prevalence of left ventricular thrombus among patients with low ejection fraction by trans-thoracic echocardiography

Background and objectives:

Ejection fraction (EF) is a measurement of heart function that reflects the portion of pumped out blood from the filled left ventricle per each heartbeat. The current study aimed to investigate the prevalence of left ventricular thrombus in patients with EF lower than 35% by using Transthoracic Echocardiography (TTE).

Methods:

In this prospective study, 82 cardiac patients underwent TTE procedure in order to assess the presence of left ventricular thrombus (LVT) from January 1^st to December 31st 2017 at the Military Cardiac Centre in Sana’a, Yemen.

Results:

Out of 82 patients enrolled in this study, the mean age was 49.13 ± 14.8 years and 87.8% were male. The mean of EF was 31.16% and LVT was found in 6.1%. The spontaneous contrast was seen in 25.6% of patients indicating strong relationship with low EF (p < 0.001). Among patients with low EF, ischemic heart disease (IHD) was identified in 50%, hypertension in 30.5%, diabetes mellitus (DM) type 2 in 23.2%, and hyperlipidemia 12.2%. Exactly 80% of LVT were detected in IHD patients with dilated cardiomyopathy (DCMP) and 80% of detected LVT were apical in site.

Conclusion:

Cardiac patients with low ejection fraction developed left ventricular thrombosis, and most of the affected patients were ischemic heart disease with dilated cardiomyopathy. Interestingly, spontaneous contrast was found high significantly in these patients, which may reflect the continuous process of thrombus formation.