Cardiac Wall Motion Abnormalities Research Articles

Abstract 17934: Performance of an Electrocardiographic Deep Learning Model for Detecting Wall Motion Abnormalities: An Analysis of Impact From Cardiovascular Comorbidities and Race in an External Validation Study

Introduction: Cardiac wall motion abnormalities (WMA) are key prognostic indicators for major cardiovascular events and mortality (MACE), yet poorly detected by current ECG screening such as for Q waves. Given that race and gender impact the ECG, it is also unknown if ECG screening for WMA could be applied broadly. We hypothesized that deep learning of the ECG could accurately identify WMA in diverse patients with varying comorbidities at 2 Institutions. Methods: We developed a DL Convolutional Neural Network model on N=35,210 ECG records from Stanford University (iECG, Philips), labeled by natural language processing of echocardiography reports within 60 days ( Panel A ). The tested model was then externally validated on an independent set of N=2338 ECGs from Emory University (Muse, GE). Patients with ventricular pacing were excluded. The patient cohort was segmented by cardiovascular comorbidity (<3, >=3) and white vs. non-white race to compare model performance. Results: The Stanford cohort (62.9±16.9 years, 47% female, 58% white, 6% black, 16% Asian, 23% >=3 comorbidities) differed from the Emory cohort (61.9±16.0 years, 48% female, 48% white, 41% black, 6% Asian, 52% >=3 comorbidities). Nevertheless, the Stanford model detected WMA in the Emory cohort with AUC 0.723. For patients with low and high comorbidity burdens, the AUC was 0.71 and 0.69, respectively. For White and Non-White patients, the AUC was 0.74/0.70 and 0.65/0.66, respectively ( Panel B ). Conclusions: Across racial groups and patients with variable burden of comorbidities, a DL model of electrocardiograms robustly identifies WMAs in an external validation cohort despite differences in the populations. The model’s performance across different comorbidity and racial demographic groups underscores its potential for general clinical application, offering an effective tool for clinical screening and enhanced risk stratification.

Abstract 19210: Interpretation of Deep Learning Model That Identifies Regional Myocardial Dysfunction From the Surface Ecg

Introduction: Cardiac wall motion abnormalities (WMA) are key prognostic indicators for major cardiovascular events and mortality, yet they are poorly detected by current ECG screening tools such as Q waves. Deep learning (DL) models have improved analysis of complex data and novel tools may provide interpretation of these models. Hypothesis: ECG features beyond the Q wave may be identified by analyzing an ECG-trained DL model to improve WMA detection over standard ECG measurements. Methods: We developed a DL neural network using 36,964 unique patients (62.9±16.9 years, 47% female, 58% white) labeled by natural language processing of echocardiography reports within 60 days. To understand how the CNN model identifies WMAs from the ECG input, we implemented Shapley Additive exPlanations (SHAP) and DeepExplainer on R-wave aligned beats over 300ms surrounding the QRS complexes to identify hot-spots across the ECG. We then retrained classifiers on 60mg windows of the ECG to identify which timepoints produced the greatest performance (ablation method). Results: Probing the CNN revealed that ECG regions throughout the QRS and T-waves identified WMA. Analysis output shows that such ECG regions arose throughout the QRS and T-waves, and not just at early regions corresponding to Q waves (Panel A) . An aggregate view of the ECG reports summarizes the most discriminatory ECG regions for all patients (Panel B) . Stepwise analysis of limited windows within aligned ECG beats also confirmed this analysis (Panel C) . We found that the highest performance window was 60-120ms (AUC 0.814), containing most of the QRS, with the lowest performance in the window of 0-60 ms (AUC 0.699) and 0.20-0.80ms (AUC 0.707). Conclusions: The DL model show promise in accurately detecting WMAs and provides key insights into critical ECG regions for WMA detection beyond the Q wave. Further analysis of WMA detection with these expanded regions is needed.

Abstract 17420: Enhanced Identification of Cardiac Wall Motion Abnormalities: An Externally Validated Deep Neural Network Approach Outperforms Expert and Quantitative Analysis of Electrocardiograms

Background: Cardiac wall motion abnormalities (WMA) independently predict mortality and other adverse events beyond ejection fraction. Clinical screening relies on detection of ECG Q waves yet has poor predictive accuracy. Hypothesis: We hypothesized that ECG features beyond the Q wave could be identified by deep learning to improve WMA detection over standard ECG measurements. Methods: We collected ECGs and echocardiogram pairs (Panel A) in 35,210 unique patients who underwent both studies within 60 days at Stanford University. WMAs were determined by natural language processing (NLP) of clinical reports (Panel B). Five second ECG signals were extracted digitally and used to develop and test a DNN. For development, 80% of the pairs were used and 20% (N = 7042) were reserved for internal validation. We then tested the model performance on 2,338 echo/ECG pairs from Emory University. For comparison, qualitative physician statements from the ECG interpretation suggesting myocardial injury, ischemia, or infarct were labeled using NLP, and a logistic regression model was developed to include quantitative Q-wave measurements. Results: In the internal validation cohort (62.9±16.9 years, 47% female, 58% white), DNN of the ECG detected echocardiographic WMA with a c-statistic of 0.781 (CI: 0.764-0.798) which was superior to quantitative ECG Q wave measurement (0.632, CI: 0.605-0.661) or qualitative interpretation (0.595) (Panel C). Performance was not improved by incorporating demographic data. In the external cohort (61.9±16.0 years, 48% female, 48% white), the DNN AUC was 0.723 (CI:0.689-0.758). Conclusion: Deep learning improves detection of cardiac WMAs from the electrocardiogram in an externally validated model compared with standard ECG analysis. Application of this model may provide improved screening for regional myocardial injury. Further work will determine which features beyond the Q wave provide improved performance.

Abstract 18102: Impact of Regional Cardiac Wall Motion Abnormalities on Ejection Fraction and Mortality: Large Data Enabled by Natural Language Processing

Background: Cardiac wall motion abnormalities (WMA) independently predict mortality and other adverse events beyond ejection fraction. The impact on mortality and ejection fraction has not been studied in large cohorts with long term follow up. Aim: We aimed to describe the relationship of specific regional cardiac WMAs with ejection fraction and mortality in a large referral academic center. Methods: We collected echocardiograms, demographics, and follow-up data from 35,210 patients from Stanford University. Specific regional abnormalities were determined by natural language processing (NLP) of clinical reports. WMAs were stratified across 5 anatomic regions and compared. Ejection fraction effect were compared by the Mann-Whitney U test and visualized with violin plots. Mortality between regions was assessed with Cox proportional hazards model and visualized with Kaplan-Meier plot. Results: In the Stanford University cohort, (62.9±16.9 years, 47% female, 58% white), regional WMAs were associated variable reductions in EF with apical, anterior, and septal WMAs resulting in an EF 41.6-42.8 +/- 12.8%, which was greater than lateral (45.4 +/- 10.2%) and inferior/posterior (46.3 +/- 12.1) (p< .01 for all comparisons). Distributions for inferior/posterior and lateral were more left-skewed and apex/septal were more bimodal ( Panel A ). In follow-up, having at least one WMA increased the risk of overall mortality with a hazard ratio of 1.8 (CI: 1.61-2.00) over a > 4 year period ( Panel B ). Conclusion: In a very large population of echocardiograms performed in an academic referral center, wall motion abnormalities in different areas were associated with variable effects on ejection fraction and long-term mortality. Natural language processing enabled analysis of a large database of echocardiogram reports.

Acute right insular ischaemic lesions and poststroke left ventricular dysfunction

IntroductionMyocardial injury related to acute ischaemic stroke is common even without primary cardiac disease. We intended to determine associations between values of left ventricular ejection fraction (LVEF) and ischaemic stroke...

Efficacy and Safety of Angiotensin Receptor Blockers in a Pre-Clinical Model of Arrhythmogenic Cardiomyopathy.

Arrhythmogenic Cardiomyopathy (ACM) is a familial heart disease, characterized by contractile dysfunction, ventricular arrhythmias (VAs), and the risk of sudden cardiac death. Currently, implantable cardioverter defibrillators and antiarrhythmics are the mainstays in ACM therapeutics. Angiotensin receptor blockers (ARBs) have been highlighted in the treatment of heart diseases, including ACM. Yet, recent research has additionally implicated ARBs in the genesis of VAs and myocardial lipolysis via the peroxisome proliferator-activated receptor gamma (PPARγ) pathway. The latter is of particular interest, as fibrofatty infiltration is a pathological hallmark in ACM. Here, we tested two ARBs, Valsartan and Telmisartan, and the PPAR agonist, Rosiglitazone, in an animal model of ACM, homozygous Desmoglein-2 mutant mice (Dsg2mut/mut). Cardiac function, premature ventricular contractions (PVCs), fibrofatty scars, PPARα/γ protein levels, and PPAR-mediated mRNA transcripts were assessed. Of note, not a single mouse treated with Rosiglitazone made it to the study endpoint (i.e., 100% mortality: n = 5/5). Telmisartan-treated Dsg2mut/mut mice displayed the preservation of contractile function (percent ejection fraction [%EF]; 74.8 ± 6.8%EF) compared to Vehicle- (42.5 ± 5.6%EF) and Valsartan-treated (63.1 ± 4.4%EF) mice. However, Telmisartan-treated Dsg2mut/mut mice showed increased cardiac wall motion abnormalities, augmented %PVCs, electrocardiographic repolarization/depolarization abnormalities, larger fibrotic lesions, and increased expression of PPARy-regulated gene transcripts compared to their Dsg2mut/mut counterparts. Alternatively, Valsartan-treated Dsg2mut/mut mice harbored fewer myocardial scars, reduced %PVC, and increased Wnt-mediated transcripts. Considering our findings, caution should be taken by physicians when prescribing medications that may increase PPARy signaling in patients with ACM.

Detection of left ventricular wall motion abnormalities from volume rendering of 4DCT cardiac angiograms using deep learning.

BackgroundThe presence of left ventricular (LV) wall motion abnormalities (WMA) is an independent indicator of adverse cardiovascular events in patients with cardiovascular diseases. We develop and evaluate the ability to detect cardiac wall motion abnormalities (WMA) from dynamic volume renderings (VR) of clinical 4D computed tomography (CT) angiograms using a deep learning (DL) framework.MethodsThree hundred forty-three ECG-gated cardiac 4DCT studies (age: 61 ± 15, 60.1% male) were retrospectively evaluated. Volume-rendering videos of the LV blood pool were generated from 6 different perspectives (i.e., six views corresponding to every 60-degree rotation around the LV long axis); resulting in 2058 unique videos. Ground-truth WMA classification for each video was performed by evaluating the extent of impaired regional shortening visible (measured in the original 4DCT data). DL classification of each video for the presence of WMA was performed by first extracting image features frame-by-frame using a pre-trained Inception network and then evaluating the set of features using a long short-term memory network. Data were split into 60% for 5-fold cross-validation and 40% for testing.ResultsVolume rendering videos represent ~800-fold data compression of the 4DCT volumes. Per-video DL classification performance was high for both cross-validation (accuracy = 93.1%, sensitivity = 90.0% and specificity = 95.1%, κ: 0.86) and testing (90.9, 90.2, and 91.4% respectively, κ: 0.81). Per-study performance was also high (cross-validation: 93.7, 93.5, 93.8%, κ: 0.87; testing: 93.5, 91.9, 94.7%, κ: 0.87). By re-binning per-video results into the 6 regional views of the LV we showed DL was accurate (mean accuracy = 93.1 and 90.9% for cross-validation and testing cohort, respectively) for every region. DL classification strongly agreed (accuracy = 91.0%, κ: 0.81) with expert visual assessment.ConclusionsDynamic volume rendering of the LV blood pool combined with DL classification can accurately detect regional WMA from cardiac CT.

Association of major adverse cardiovascular events in stroke patients with cardiac wall motion abnormalities

Association of major adverse cardiovascular events in stroke patients with cardiac wall motion abnormalities

Association of Major Adverse Cardiovascular Events in Patients With Stroke and Cardiac Wall Motion Abnormalities.

BackgroundThe association of cardiac wall motion abnormalities (CWMAs) in patients with stroke who have major adverse cardiovascular events (MACE) remains unclear. The purpose of this study was to estimate the 50‐month risk of MACE, including stroke recurrence, acute coronary events, and vascular death in patients with stroke who have CWMAs.Methods and ResultsWe performed a retrospective analysis of prospectively collected acute stroke data (acute stroke and transient ischemic attack) over 50 months by electronic medical records. Data included demographic and clinical information, vascular imaging, and echocardiography data including CWMAs and MACE. Of a total of 2653 patients with acute stroke/transient ischemic attack, CWMA was observed in 355 (13.4%). In patients with CWMAs, the embolic stroke of undetermined source (50.7%) was the most frequent index stroke subtype and stroke recurrences (P=0.001). In multivariate Cox regression after adjustment for demographics, traditional risk, and confounding factors, CWMA was independently associated with a higher risk of MACE (adjusted hazard ratio [HR], 1.74; 95% CI, 1.37–2.21 [P=0.001]). Similarly, CWMA independently conferred an increased risk for ischemic stroke recurrence (adjusted HR, 1.50; 95% CI, 1.01–2.17 [P=0.04]), risk of acute coronary events (aHR, 2.50; 95% CI, 1.83–3.40 [P=0.001]) and vascular death (adjusted HR, 1.57; 95% CI, 1.04–2.40 [P=0.03]), in comparison to the patients with stroke without CWMA.ConclusionsIn a multiethnic cohort of ischemic stroke with CWMA, CWMA was associated with 1.7‐fold higher risks of MACE independent of established risk factors. Embolic stroke of undetermined source was the most common stroke association with CWMA. Patients with stroke should be screened for CWMA to identify those at higher risk of MACE.

Parametric Methods for the Regional Assessment of Cardiac Wall Motion Abnormalities: Comparison Study

Left ventricular (LV) dysfunction is mainly assessed by global contractile indices such as ejection fraction and LV Volumes in cardiac MRI. While these indices give information about the presence or not of LV alteration, they are not able to identify the location and the size of such alteration. The aim of this study is to compare the performance of three parametric imaging techniques used in cardiac MRI for the regional quantification of cardiac dysfunction. The proposed approaches were evaluated on 20 patients with myocardial infarction and 20 subjects with normal function. Three parametric images approaches: covariance analysis, parametric images based on Hilbert transform and those based on the monogenic signal were evaluated using cine-MRI frames acquired in three planes of views. The results show that parametric images generated from the monogenic signal were superior in term of sensitivity (89.69%), specificity (86.51%) and accuracy (89.06%) to those based on covariance analysis and Hilbert transform in the detection of contractile dysfunction related to myocardial infarction. Therefore, the parametric image based on the monogenic signal is likely to provide additional regional indices about LV dysfunction and it may be used in clinical practice as a tool for the analysis of the myocardial alterations.

Role of Depression and Anxiety Disorders in Takotsubo Syndrome: The Psychiatric Side of Broken Heart.

Takotsubo syndrome (TTS), also called broken heart syndrome, is an acute and transient cardiac wall motion abnormality of the left ventricle. The patient prototype is a post-menopausal woman with myocardial infarction-like symptoms (angina pectoris, breathlessness, palpitations, etc.) who has experienced sudden emotional or physical stress. Although prognosis is generally considered relatively benign, both complications and recurrence rates are not insignificant. Pathophysiological mechanisms underlying TTS are not entirely understood, but the sympathetic system over-activity has a leading role. Moreover, since emotional stress frequently triggers TTS and since precedent diagnosis of psychiatric disorders sometimes coexists, the psychological response to stress could be another potential therapeutic target. Indeed, this article aims to explore the association between underlying depression and anxiety disorders and TTS, as well as to find ideal therapeutic options useful to treat and prevent TTS. Thus in our review, we considered case reports, case-control studies, and review articles from PubMed. Papers dealing with Takotsubo syndrome and anxiety disorder or depression were selected. We included papers published since 2010 and whose abstract was in English. We concluded that anxiety disorders, but not depression, are associated with a higher occurrence of TTS. There is a link between anxiety, TTS, and inflammation leading to increased sympathetic activity. Nevertheless, patients with pre-admission psychiatric disorders have a higher risk of recurrent TTS. Importantly, the use of selective serotonin reuptake inhibitors (SSRIs) could be a potential therapeutic aid in preventing TTS's recurrence in selected patients.

Review of ultrasound contrast agents in current clinical practice with special focus on DEFINITY® in cardiac imaging.

Echocardiography is the most widely used noninvasive modality to evaluate the structure and function of the cardiac muscle in daily practice. However, up to 15-20% of echocardiograms are considered suboptimal. To enable accurate assessment of cardiac function and wall motion abnormality, the use of ultrasound microbubble contrast has shown substantial benefits in cases of salvaging nondiagnostic studies and enhancing the diagnostic accuracy in daily practice. DEFINITY® is a perflutren based, lipid shelled microbubble contrast agent, which is USFDA approved for left ventricular opacification. The basis of ultrasound microbubbles, its development, and the clinical role of DEFINITY(characteristics, indications and case examples, side effect profile and existing evidence) is the subject of discussion in this review.

Feasibility and Clinical Implications of Remotely Guided Ultrasound Examinations.

BACKGROUND: Remotely guided ultrasound (US) examinations carried out by nonmedical personnel (novices) have been shown to produce clinically useful examinations, at least in small pilot studies. Comparison of the quality of such exams to those carried out by trained medical professionals is lacking in the literature. This study compared the objective quality and clinical utility of cardiac and pulmonary US examinations carried out by novices and trained physicians.METHODS: Cardiac and pulmonary US examinations were carried out by novices under remote guidance by an US expert and independently by US trained physicians. Exams were blindly evaluated by US experts for both a task-based objective score as well as a subjective assessment of clinical utility.RESULTS: Participating in the study were 16 novices and 9 physicians. Novices took longer to complete the US exams (median 641.5 s vs. 256 s). For the objective component, novices scored higher in exams evaluating for pneumothorax (100% vs. 87.5%). For the subjective component, novices more often obtained clinically useful exams in the assessment of cardiac regional wall motion abnormalities (56.3% vs. 11.1%). No other comparisons yielded statistically significant differences between the two groups. Both groups had generally higher scores for pulmonary examinations compared to cardiac. There was variability in the quality of exams carried out by novices depending on their expert guide.CONCLUSION: Remotely guided novices are able to carry out cardiac and pulmonary US examinations with similar, if not better, technical proficiency and clinical utility as US trained physicians, though they take longer to do so.Dufurrena Q, Ullah KI, Taub E, Leszczuk C, Ahmad S. Feasibility and clinical implications of remotely guided ultrasound examinations. Aerosp Med Hum Perform. 2020; 91(7):592-596.

Cardiac wall motion abnormality as a predictor for undetermined stroke with embolic lesion-pattern

ObjectivesSeveral strokes of potential embolism do not clearly meet the definitions of embolic stroke with unknown source, cryptogenic stroke, or cardioembolic (CE) stroke. Considering the high mortality and recurrence of CE strokes, it is very important to detect treatable cardiac sources of embolism. Although regional wall motion abnormality (RWMA) of the left ventricle (LV) seems to be related to CE stroke, association between cerebral embolic risk and RWMA remains unclear. The purpose of this study was to investigate the influence of RWMA on undetermined stroke with embolic lesion-pattern (USELP). Patients and methodsAmong a total of 2327 patients with acute ischemic stroke, we excluded 148 patients without a transthoracic echocardiography (TTE). According to a stepwise approach, we excluded patients without an embolic lesion-pattern. Finally, we divided patients into two groups (USELP, 119, and non-embolic stroke, 1237). We classified patients’ RWMAs into three major arterial territories according to the standard 17-segment model of TTE. ResultsAmong the included 1356 patients, those with USELP had larger internal dimension at diastole and systole in LV, reduced LV ejection fraction, increased E/A ratios, mitral valve disease, and RWMA. After adjusting for multiple variables, binary logistic regression revealed that RWMA was significantly associated with USELP (OR 7.02, 95 % CI: 3.51–14.01, p<0.001). ConclusionThis study provides significant information to support that RWMA can be a predictor for undetermined embolic stroke. In this regard, RWMA were highly correlated with patients whose imaging supported an embolic source compared to those without this radiographic pattern.

Cardiac Hydatid Cyst

A 52-year-old female presented with features suggestive of acute coronary syndrome. A transthoracic echocardiogram done to assess the cardiac function and regional wall motion abnormality revealed a large cardiac cystic lesion instead, in the apical part of the interventricular septum, suggestive of a hydatid cyst. Cystic hydatid disease results from infection with the larval or adult form of the Echinococcus granulosus tapeworm. Cardiac hydatid cyst is a rare condition seen in 0.5%–2% of patients with hydatid disease, and the location of a hydatid cyst in the interventricular septum is exceptional. Cardiac hydatid cysts can rupture and cause cardiac tamponade, fatal arrhythmias, or systemic infection. The atypical location of a large hydatid cyst in the apical interventricular septum encroaching into the right ventricular cavity filling almost half of it, was an interesting finding, found worth reporting. Also, further investigations that unraveled two more hydatid cysts in the liver, made the case more interesting to report.

Embolic Pattern of Stroke Associated with Cardiac Wall Motion Abnormalities; Narrowing the Embolic Stroke of Undetermined Source Category

BackgroundThere is ambiguity regarding the role of left ventricle wall motion abnormalities (LVWMAs) as a potential cardioembolic source in patients, who satisfy embolic stroke of undetermined source (ESUS) criteria. Methods and resultsWe analyzed prospectively collected data in 345 acute stroke patients, 185 (53.6%) stroke with atrial fibrillation (SwAF), and 160 (46.4%) stroke with LVWMA. LVWMA were younger (P = .003), had significantly higher frequency of stroke risk factors and lower ejection fraction (P < .001). No significant difference was found between the stroke pattern in SwAF and LVWMA except focal cortical, cortical-subcortical lesions were more frequent in LVWMA (P = .002). Mean wall motion score index (WMSI) was 1.523 (range 1.05-2.71) without any correlation between the severity of WMSI and multiple strokes (P = .976). In subgroup analyses vertical basal WMSI (P = .030) and vertical mid cavity WMSI (P = .010) was significantly related to branch arterial stroke. LVWMA 94 (65%) patients were on antiplatelet/anticoagulation compared to 47 (52.4%) with atrial fibrillation (AF), with no significant difference in stroke recurrence during 4 years follow-up (P = .15). ConclusionsPatients with LVWMA who satisfy ESUS criteria, have stroke pattern on diffusion-weighted magnetic resonance imaging and risk of stroke recurrence similar to AF-related stroke despite being on appropriate antiplatelet medications. Further studies with anticoagulation therapy may be required in this group of patients to improve the high risk of recurrent stroke.

Takotsubo Cardiomyopathy-Acute Cardiac Dysfunction Associated With Neurological and Psychiatric Disorders.

Takotsubo cardiomyopathy (TTC) is an acute and reversible cardiac wall motion abnormality of the left myocardium. Although many studies focused on etiology, diagnostic and treatment of TTC, precise clinical guidelines on TTC are not available. Research revealed emotional and physical triggering factors of TTC and emphasized the association of TTC with psychiatric and particularly acute neurological disorders. Similar clinical presentation of acute coronary syndrome (ACS) and TTC patients, makes an anamnestic screening for TTC risk factors necessary. In psychiatric anamnesis affective disorders and chronic anxiety disorders are presumably for TTC. Subarachnoid hemorrhages and status epilepticus are typical acute neurological associated with a higher risk for TTC. Moreover, magnetic resonance imaging (MRI) studies reveled brain alterations of the limbic system and reduced connectivity of central autonomic nervous system structures. Diagnosis of TTC is made by elevation of cardiac enzymes, electrocardiogram (ECG) and visualization of myocardial wall motion. Major differential diagnoses like acute coronary syndrome and myocarditis are hereby in synopsis with anamnesis with respect of possible emotional and physical triggering factors of TTC ruled out. In most cases the TTC typical wall motion abnormalities resolve in weeks and therapy is only necessary in hemodynamic instable patients and if rare complications, like cardiac wall ruptures occur. Recently, the two-parted International expert consensus document on Takotsubo syndrome was published, providing a detailed characterization of TTC and allows clinicians to understand this cardiac dysfunction with a multidisciplinary view.

The effect of biventricular pacing on cardiac function after open heart surgery

Background: Temporary postoperative pacing could enhance recovery of the cardiac function. The right ventricular pacing (RV) is commonly used, but it can cause dyssynchronous contraction of both ventricles. Biventricular pacing (BV) could improve the systolic function by synchronizing the ventricular contraction. The aim of this study is to evaluate the effectiveness of biventricular pacing in improving the hemodynamics in the early postoperative period compared to other pacing modes.&#x0D; Methods: This is a clinical crossover trial including 50 patients who underwent open cardiac surgery in the period from September 2017 to September 2018. Mean age was 46.78± 12.09 years, and 50% were males. Temporary pacing leads were attached to the anterior wall of the right ventricle 1-2 cm paraseptally and the lateral wall of left ventricle 1-2 cm paraseptally. Each patient was paced for 3 minutes in the first 1-4 postoperative hours with 20 minutes washout period between different pacing modes. Study endpoints included cardiac output, ejection fraction (EF) and wall motion abnormality.&#x0D; Results: Biventricular and right ventricular pacing increased postoperative cardiac output (6.31± 1.28 and 5.2±0.72 L/min; respectively), but BV pacing was superior to RV pacing (P-value &lt;0.001). The effect of BV pacing was more evident in patients with EF &lt; 50% (7.27± 0.895 vs. 5.26 ± 0.634 L/min; p&lt; 0.001). The postoperative EF improved during BV pacing (53.16± 4.71%) compared to RV pacing (49.4± 4.07%; P-value &lt;0.001). Both BV and RV pacing were associated with less paradoxical septal wall motion abnormality (P-value &lt;0.001).&#x0D; Conclusions: Temporary postoperative biventricular pacing improves hemodynamics compared to right ventricular and no pacing. Routine BV pacing is recommended especially in patients with low ejection fraction.

The Role of Phase Image in the Detection of Myocardial Dyskinesia by Magnetic Resonance Imaging (MRI).

The assessment of cardiac wall motion abnormalities plays an important role in the evaluation of many cardiovascular diseases and the prediction of functional recovery. Most of the methods dedicated to identifying the location of wall motion abnormalities have been restricted to study hypokinesia while an accurate way to assess dyskinesia is still needed in Cardiac Magnetic Resonance Imaging (CMRI). The aim of this study is to propose a phase image based on the analytic signal able to assess the extent of the myocardial dyskinetic segments in Cardiac Magnetic Resonance Imaging (CMRI). 22 subjects were retrospectively enrolled in this study (age 46 ± 11): 15 presenting an aneurysm and 7 control subjects with normal wall motion. For each patient, three standard views (short axis view, 2 chamber and 4 chamber views) were acquired using 3 Tesla Siemens Avanto MRI scanner and a segmented True FISP sequence. All the cine MRI images were analyzed by two experimented observers who were blinded to the diagnostic results. The outcomes of this study show that using the proposed phase image in MRI clinical routine can increase the accuracy of the detection of myocardial dyskinetic segments from 77.23 % to 86.38 %, the sensitivity from 67.48 % to 78.86 % as well the specificity from 80.92 % to 89.23 % compared to the standard method based on cine MRI interpretation. The phase image is a promising tool in CMRI for the assessment of dyskinetic segments and the degree of myocardial asynchronism.

Electrocadiographic Scoring Helps Predict Left Ventricular Wall Motion Abnormality Commonly Observed after Subarachnoid Hemorrhage

Background: Cardiac wall motion abnormality (WMA) is a common complication in patients with subarachnoid hemorrhage (SAH) and is one determinant of their prognosis. The aim of this study was to examine whether the electrocardiography (ECG) findings at admission could predict WMA commonly observed after SAH. Materials and methods: We studied 161 SAH patients with SAH who were hospitalized in our institution between April 2007 and November 2010. We performed bedside 2-dimensional transthoracic echocardiography and 12-lead surface ECG within 24hours of SAH onset. Each of the following ECG changes was scored as having 1 point: ST elevation, ST depression and T wave inversion. We summed up the points in every patient and compared with WMA evaluated by echocardiography. Results: The study subjects were classified into 2 groups based on the presence of WMA. Multivariate analysis revealed that ST elevation, ST depression and T wave inversion were strong independent predictors of WMA. Receiver operating characteristic curve determined that the threshold value to predict WMA was 4 points (sensitivity 86.5%, specificity 83.1%, AUC 0.94, P < .0001). Conclusions: In conclusion, a novel ECG score may well predict WMA after SAH which may associate with an increased risk of mortality.