LV Dyssynchrony Assessed With Phase Analysis on Gated Myocardial Perfusion SPECT Can Predict Response to CRT in Patients With End-Stage Heart Failure.

BACKGROUND: Cardiac resynchronization therapy (CRT) is an established treatment in patients with end-stage heart failure and wide QRS complex. However, about 30% of patients do not benefit from CRT (non-responder). Recent studies with tissue Doppler imaging yielded disappointing results in predicting CRT responders. Phase analysis was developed to allow assessment of LV dyssynchrony by gated single photon emission computed tomography (SPECT) myocardial perfusion imaging (GMPS). OBJECTIVES: The aim of present study was to investigate the role of quantitative GMPS-derived LV dyssynchrony data to predict CRT responder. PATIENTS AND METHODS: Thirty eligible patients for CRT implantation underwent GMPS and echocardiography. Response to CRT was evaluated six months after the device implantation. Clinical response to CRT was defined as 50 meters increase in 6-minute walking test (6-MWT) distance. Echocardiographic response to CRT was defined as ≥ 15% decrease in left ventricular end-systolic volume (LVESV). The lead position was considered concordant if it was positioned at the area of latest mechanical activation, and discordant if located outside the area of latest mechanical activation. RESULTS: Clinical response to CRT was observed in 74% of patients. However, only 57% of patients were responder according to the echo criteria. There were statistically significant differences between CRT responders and non-responders for GMPS-derived variables, including phased histogram bandwidth (PHB), phase SD (PSD), and Entropy. Moreover, a cutoff value of 112° for PHB with a sensitivity of 72% and specificity of 70%, a cutoff value of 21° for PSD with a sensitivity of 90% and specificity of 74%, and a cutoff of 52% for Entropy with a sensitivity of 90% and a specificity of 80% were considered to discriminate responders and non-responders. CRT response was more likely in patients with concordant LV lead position compared to those with discordant LV lead position. CONCLUSIONS: GMPS-derived LV dyssynchrony variables can predict response to CRT with good sensitivity and specificity.

A data mining approach for diagnosis of coronary artery disease.

Cardiovascular diseases are very common and are one of the main reasons of death. Being among the major types of these diseases, correct and in-time diagnosis of coronary artery disease (CAD) is very important. Angiography is the most accurate CAD diagnosis method; however, it has many side effects and is costly. Existing studies have used several features in collecting data from patients, while applying different data mining algorithms to achieve methods with high accuracy and less side effects and costs. In this paper, a dataset called Z-Alizadeh Sani with 303 patients and 54 features, is introduced which utilizes several effective features. Also, a feature creation method is proposed to enrich the dataset. Then Information Gain and confidence were used to determine the effectiveness of features on CAD. Typical Chest Pain, Region RWMA2, and age were the most effective ones besides the created features by means of Information Gain. Moreover Q Wave and ST Elevation had the highest confidence. Using data mining methods and the feature creation algorithm, 94.08% accuracy is achieved, which is higher than the known approaches in the literature.

Eosinophilic Endomyocardial Fibrosis and Strongyloides stercoralis: A Case Report.

A 64-year-old female with history of previous aortoiliac occlusion and aortoiliac bypass operation four months ago presented with dyspnea, ascites and leg edema. She has been suffering from bloody diarrhea since two weeks earlier. Laboratory data showed important eosinophilia and stool examination was positive for Strongyloides stercoralis. Patient had clinical signs of heart failure. A cardiac MRI revealed hypersignal subendocardium in favor of endomyocardial fibrosis. Hypereosinophilic syndrome is defined by persistent hypereosinophilia for more than 6 months. The association with different etiologies is known but the report of cardiac involvement due to S. stercoralis infection is not very common. Cardiac manifestation is characterized by a restrictive cardiomyopathy due to toxic damage produced by activated eosinophils.

Diagnosis of coronary arteries stenosis using data mining.

Cardiovascular diseases are one of the most common diseases that cause a large number of deaths each year. Coronary Artery Disease (CAD) is the most common type of these diseases worldwide and is the main reason of heart attacks. Thus early diagnosis of CAD is very essential and is an important field of medical studies. Many methods are used to diagnose CAD so far. These methods reduce cost and deaths. But a few studies examined stenosis of each vessel separately. Determination of stenosed coronary artery when significant ECG abnormality exists is not a difficult task. Moreover, ECG abnormality is not common among CAD patients. The aim of this study is to find a way for specifying the lesioned vessel when there is not enough ECG changes and only based on risk factors, physical examination and Para clinic data. Therefore, a new data set was used which has no missing value and includes new and effective features like Function Class, Dyspnoea, Q Wave, ST Elevation, ST Depression and Tinversion. These data was collected from 303 random visitor of Tehran's Shaheed Rajaei Cardiovascular, Medical and Research Centre, in 2011 fall and 2012 winter. They processed with C4.5, Naïve Bayes, and k-nearest neighbour (KNN) algorithms and their accuracy were measured by tenfold cross validation. In the best method the accuracy of diagnosis of stenosis of each vessel reached to 74.20 ± 5.51% for Left Anterior Descending (LAD), 63.76 ± 9.73% for Left Circumflex and 68.33 ± 6.90% for Right Coronary Artery. The effective features of stenosis of each vessel were found too.