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Cardiovascular diseases represent the leading global cause of death, typically diagnosed and addressed through electrocardiograms (ECG), which record the heart's electrical activity. In recent years, there has been a notable surge in ECG recordings, driven by the widespread use of wearable devices. However, the limited availability of medical experts to analyze these recordings underscores the necessity for automated ECG analysis using computer-aided methods. In this study, we introduced 3DECG-Net, a deep learning model designed to detect and classify seven distinct heart states through the analysis of data fusion from 12-lead ECG in a multi-label framework. Our model leverages a residual architecture with a multi-head attention mechanism, undergoing training within a five-fold cross-validation scheme. By transforming 12-lead ECG signals into 3D data with the help of Recurrent Plot technique, 3DECG-Net achieves a noteworthy micro F1-score of 80.3 %, surpassing the performance of other state-of-the-art deep learning models developed for this specific task. Also, we present an ECG preprocessing framework to generate compact, high-quality ECG signals for potential application in future studies within this domain. We conduct an explainable AI experiment using Local Interpretable Model-agnostic Explanations (LIME) to elucidate the significance of each lead in accurately diagnosing specific arrhythmias, ensuring the logical processing of ECG data by 3DECG-Net. The findings of this study suggest that the proposed model is trustworthy and has the potential to be used as an effective diagnostic toolset for identifying heart arrhythmias. Its effectiveness can improve the diagnostic process, facilitate early treatment, and enhance overall efficiency in medical settings.

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Sleep duration is a substantial risk factor for several cardiovascular diseases, including atrial fibrillation (AF). Despite much research, the precise nature of the relationship between the amount of sleep and AF remains unclear. This narrative review explores the relationship between AF and sleep duration, looking at genetic, mechanistic, and epidemiological data to explain this association. A U-shaped association (nonlinear relationship or curvilinear association) between sleep duration and AF has been seen, where longer and shorter sleep duration, more or less than seven to eight hours, have been associated with increased AF risk. Multiple mechanisms such as autonomic dysfunction, inflammation, and structural atrial remodeling have been proposed linking sleep disturbances to AF. Moreover, confounding factors such as individual lifestyle, comorbidities, and sleep quality could affect this association. Additionally, the interpretation of study results is further impacted by methodological limitations, including self-reported sleep duration and observational study designs. It is imperative to comprehend the complex relationship between sleep duration and AF to develop effective preventive and therapeutic methods. The main goals of future research should focus on prospective cohort studies with objective sleep metrics, exploring the mechanistic pathways, and comprehensive confounder adjustments that link sleep disturbances to AF. In summary, addressing sleep disturbances may represent one of the novel approaches to AF prevention and management, with potential implications for improving cardiovascular health and reducing AF-related morbidity and mortality.

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Background: Sarcoidosis is a granulomatous multi-organ disease of unknown aetiology. Despite being relatively rare, cardiac sarcoidosis constitutes a very important manifestation of sarcoidosis, as its symptoms regularly precede or occur in isolation of more prevalent ones, and as it is the main driver of mortality in systemic sarcoidosis. Case summary: We present the case of a 37-year-old woman, in which clinically isolated cardiac sarcoidosis revealed widespread systemic sarcoidosis. Apart from constitutional symptoms and strong recurrent dizziness (i.e. near-syncopes), which persisted for multiple years already, our patient initially presented with complex conduction abnormalities, including a right bundle branch block, left anterior hemi-block, and atrioventricular block °1. Following inconclusive endomyocardial biopsies, performed due to detection of focal septal scarring on cardiac magnetic resonance imaging, an 18F-FDG-PET-CT, performed upon admission to our clinic, showed distinct hypermetabolic lesions indicative of active inflammation in various organs and raised suspicion of systemic sarcoidosis. Eventually, histopathological evidence of non-caseating granulomas in affected lymph nodes, extracted by bronchoscopy, confirmed the diagnosis of systemic sarcoidosis after reasonable exclusion of other granulomatous diseases. Immediate initiation of long-term immunosuppressive therapy led to almost complete remission, as monitored by consequential 18F-FDG-PET-CT scans. Discussion: Unexplained complex conduction abnormalities in young patients may be a sign of sarcoidosis, even in isolation of more prevalent symptoms. Correct interpretation and prompt initiation of a structured interdisciplinary diagnostic workup, including 18F-FDG-PET-CT as the imaging modality of choice, are essential to initiate specific treatment and obviate the major risk of mortality resulting from cardiac sarcoidosis.

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Coffee, next to water, is the most consumed drink in the world. Coffee contains over 1000 chemical compounds, the most popular of which are caffeine, chlorogenic acid, kahweol, cafestol and trigonelline. Numerous studies have shown the beneficial effects of coffee on the cardiovascular system, nervous system, digestive system and kidneys. Due to the high incidence of cardiac arrhythmias, especially atrial fibrillation, the influence of coffee consumption on arrhythmogenesis remains a controversial and clinically important issue. Many mechanisms by which coffee can increase and decrease the risk of arrhythmias have been described. Habitual consumption of moderate amounts of coffee seems to lead to less arrhythmias, which is reflected in the results of many clinical trials and meta-analyzes. This review summarizes the mechanisms of coffee action on the heart muscle and the results of the most recent important clinical trials assessing the impact of coffee consumption on the risk of various cardiac arrhythmias.

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Cardiovascular diseases, like arrhythmia, as the leading causes of death in the world, can be automatically diagnosed using an electrocardiogram (ECG). The ECG-based diagnostic has notably resulted in reducing human errors. The main aim of this study is to increase the accuracy of arrhythmia diagnosis and classify various types of arrhythmias in individuals (suffering from cardiovascular diseases) using a novel graph convolutional network (GCN) benefitting from mutual information (MI) indices extracted from the ECG leads. In this research, for the first time, the relationships of 12 ECG leads measured using MI as an adjacency matrix were illustrated by the developed GCN and included in the ECG-based diagnostic method. Cross-validation methods were applied to select both training and testing groups. The proposed methodology was validated in practice by applying it to the large ECG database, recently published by Chapman University. The GCN-MI structure with 15 layers was selected as the best model for the selected database, which illustrates a very high accuracy in classifying different types of rhythms. The classification indicators of sensitivity, precision, specificity, and accuracy for classifying heart rhythm type, using GCN-MI, were computed as 98.45%, 97.89%, 99.85%, and 99.71%, respectively. The results of the present study and its comparison with other studies showed that considering the MI index to measure the relationship between cardiac leads has led to the improvement of GCN performance for detecting and classifying the type of arrhythmias, in comparison to the existing methods. For example, the above classification indicators for the GCN with the identity adjacency matrix (or GCN-Id) were reported to be 68.24%, 72.83%, 95.24%, and 92.68%, respectively.

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Vulvar cancers make up just 3% to 5% of all gynecological cancers, and they are most typically found in postmenopausal women. Vulvar cancer distant metastases are uncommon and usually arise late. Only six cases of vulvar cancer metastasizing to the heart have been reported in the literature, and none of them included both the left and right ventricles. We describe the case of a 68-year-old patient diagnosed with vulvar cancer arising from lichen sclerosus, initially localized, treated with chemotherapy, surgery, and radiation therapy. Less than two months after the end of the treatment sequence, the patient returned to our clinic with bone pain. Imaging investigations have shown multiple disseminated metastases, but not in the heart at that moment. Chemotherapy was initiated, and after two cycles, the patient developed an arrhythmia (atrial fibrillation with rapid ventricular rate), which was later determined to be caused by cardiac metastases discovered by echocardiography and computed tomography. Vulvar cancer metastatic to the heart represents a rare clinical condition, requiring multidisciplinary care. The case's uniqueness is the biventricular metastasis, which resulted in STEMI despite angiographically normal epicardial coronary arteries.

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ß-blockers is a vast group of antiarrhythmic drugs which differ in their pharmacokinetic and chemical properties. Some of them block ß-adrenergic receptors selectively while the others work non-selectively. Consequently, they reduce the influence of the sympathetic nervous system on the heart, acting negatively inotropic, chronotropic, bathmotropic and dromotropic. Although they have been present in medicine since the beginning of the 1960s, they still play a crucial role in the treatment of cardiac arrhythmias. They are also first-line group of drugs used to control the ventricular rate in patients with the most common arrhythmia-atrial fibrillation. Previous reports indicate that infection with SARS-CoV-2 virus may constitute an additional risk factor for arrhythmia. Due to the aging of the population in developed countries and the increase in the number of patients with cardiac burden, the number of people suffering from cardiac arrhythmias will increase in the upcoming years. As a result the role of above-mentioned beta-blockers will remain significant. Particularly noteworthy is propranolol-the oldest beta adrenergic antagonist, which in recent years has found additional applications due to its unique properties. In this article, we reviewed the accessible literature and summarized the current guidelines on the use of beta-blockers in the treatment of cardiac arrhythmias.

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Dysregulated circadian functions contribute to various diseases, including cardiovascular disease. Much progress has been made on chronotherapeutic applications of drugs against cardiovascular disease (CVD); however, the direct effects of various medications on the circadian system are not well characterized. We previously conducted high-throughput chemical screening for clock modulators and identified an off-patent anti-arrhythmic drug, moricizine, as a clock-period lengthening compound. In Per2:LucSV reporter fibroblast cells, we showed that under both dexamethasone and forskolin synchronization, moricizine was able to increase the circadian period length, with greater effects seen with the former. Titration studies revealed a dose-dependent effect of moricizine to lengthen the period. In contrast, flecainide, another Class I anti-arrhythmic, showed no effects on circadian reporter rhythms. Real-time qPCR analysis in fibroblast cells treated with moricizine revealed significant circadian time- and/or treatment-dependent expression changes in core clock genes, consistent with the above period-lengthening effects. Several clock-controlled cardiac channel genes also displayed altered expression patterns. Using tissue explant culture, we showed that moricizine was able to significantly prolong the period length of circadian reporter rhythms in atrial ex vivo cultures. Using wild-type C57BL/6J mice, moricizine treatment was found to promote sleep, alter circadian gene expression in the heart, and show a slight trend of increasing free-running periods. Together, these observations demonstrate novel clock-modulating activities of moricizine, particularly the period-lengthening effects on cellular oscillators, which may have clinical relevance against heart diseases.

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BACKGROUND: A language is constructed of a finite/infinite set of sentences composing of words. Similar to natural languages, the Electrocardiogram (ECG) signal, the most common noninvasive tool to study the functionality of the heart and diagnose several abnormal arrhythmias, is made up of sequences of three or four distinct waves, including the P-wave, QRS complex, T-wave, and U-wave. An ECG signal may contain several different varieties of each wave (e.g., the QRS complex can have various appearances). For this reason, the ECG signal is a sequence of heartbeats similar to sentences in natural languages) and each heartbeat is composed of a set of waves (similar to words in a sentence) of different morphologies. METHODS: Analogous to natural language processing (NLP), which is used to help computers understand and interpret the human's natural language, it is possible to develop methods inspired by NLP to aid computers to gain a deeper understanding of Electrocardiogram signals. In this work, our goal is to propose a novel ECG analysis technique, ECG language processing (ELP), focusing on empowering computers to understand ECG signals in a way physicians do. RESULTS: We evaluated the proposed approach on two tasks, including the classification of heartbeats and the detection of atrial fibrillation in the ECG signals. Overall, our technique resulted in better performance or comparable performance with smaller neural networks compared to other deep neural networks and existing algorithms. CONCLUSION: Experimental results on three databases (i.e., PhysioNet's MIT-BIH, MIT-BIH AFIB, and PhysioNet Challenge 2017 AFIB Dataset databases) reveal that the proposed approach as a general idea can be applied to a variety of biomedical applications and can achieve remarkable performance.

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Gelsolin amyloidosis typically presents with corneal lattice dystrophy and is most frequently associated with pathogenic GSN variant p.Asp214Asn. Here we report clinical and histopathological features of gelsolin amyloidosis associated with a novel GSN variant p.Glu580Lys. We studied DNA samples of seven members of a two-generation family. Exome sequencing was performed in the proband, and targeted Sanger sequencing in the others. The heterozygous GSN variant p.Glu580Lys was identified in six patients. The patients exhibited corneal dystrophy (5/6), loose skin (5/6) and/or heart arrhythmia (3/6) and one presented with bilateral optic neuropathy. The impact of the mutation on the protein structure was evaluated in silico. The substitution is located in the fifth domain of gelsolin protein, homologous to the second domain harboring the most common pathogenic variant p.Asp214Asn. Structural investigation revealed that the mutation might affect protein folding. Histopathological analysis showed amyloid deposits in the skin. The p.Glu580Lys is associated with corneal dystrophy, strengthening the association of the fifth domain of gelsolin protein with the typical amyloidosis phenotype. Furthermore, optic neuropathy may be related to the disease and is essential to identify before discussing corneal transplantation.

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Cardiovascular complications including arrhythmias and cardiac conduction disorders are one of the main reasons of high mortality rate in acromegaly, while they have not been well explored. AIM: To estimate arrhythmias frequency in acromegaly, identify risk factors leading to the development of arrhythmia and cardiac conduction disorder, to determine the role of cardiac MRI in detecting structural and functional changes. MATERIALS AND METHODS: A single-center prospective cohort study, which included 461 patients (151 men and 310 women) with acromegaly, was conducted. All the patients underwent a standard medical examination, including hormonal blood test, electrocardiogram, echocardiography, electrocardiogram daily monitoring. 18 patients with arrhythmias (11 men and 7 women) had cardiac MRI with gadolinium-based contrast. RESULTS: The results of our research show high frequency of arrhythmias and cardiac conduction disorders in patients with acromegaly 42%. Most frequent kinds of arrhythmias and cardiac conduction disorders were sinus bradycardia 19.1% of the cases and conduction disorders of bundle branch blocks 14.5%. Men were more likely to suffer from arrhythmias and cardiac conduction disorders than women (54.2% and 37.4%, respectively,p=0.0005). Not acromegaly activity but duration of the disease was a main risk factor of arrhythmias and cardiac conduction disorders. Patients with arrhythmias had a long anamnesis of acromegaly (10 and 7 years, respectively, p=0.04). Meanwhile, cardiac conduction disorders were commonly observed in the patients who were treated with somatostatin analogs comparing to the patients who didnt undergo this therapy (50% and 38.6% respectively,p=0.004). We showed that 61% of patients with acromegaly and cardiac conduction disorders who underwent magnetic resonance imaging (MRI) had the signs of myocardial fibrosis. The value of the ejection fraction of the left ventricle according to MRI was higher than with echocardiography (p=0.04). CONCLUSION: Arrhythmias and cardiac conduction disorders are often observed in patients with acromegaly even with remission of the disease. High risk group need careful diagnostic and monitoring approaches. Cardiac MRI is the gold standard for visualization of structural and morphological changes in the heart. Use of cardiac MRI in acromegalic patients expands our understanding of arrhythmias and cardiac conduction disorders in this disease. There are no specific laboratory markers of diffuse myocardial fibrosis, and the role of myocardial fibrosis in the occurrence of cardiac arrhythmias and conduction disorders needs further studying.

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Atrial fibrillation (AF) is one of the most prevalent cardiac arrhythmias that affects the lives of many people around the world and is associated with a five-fold increased risk of stroke and mortality. Like other problems in the healthcare domain, artificial intelligence (AI)-based models have been used to detect AF from patients' ECG signals. The cardiologist level performance in detecting this arrhythmia is often achieved by deep learning-based methods, however, they suffer from the lack of interpretability. In other words, these approaches are unable to explain the reasons behind their decisions. The lack of interpretability is a common challenge toward a wide application of machine learning (ML)-based approaches in the healthcare which limits the trust of clinicians in such methods. To address this challenge, we propose HAN-ECG, an interpretable bidirectional-recurrent-neural-network-based approach for the AF detection task. The HAN-ECG employs three attention mechanism levels to provide a multi-resolution analysis of the patterns in ECG leading to AF. The detected patterns by this hierarchical attention model facilitate the interpretation of the neural network decision process in identifying the patterns in the signal which contributed the most to the final detection. Experimental results on two AF databases demonstrate that our proposed model performs better than the existing algorithms. Visualization of these attention layers illustrates that our proposed model decides upon the important waves and heartbeats which are clinically meaningful in the detection task (e.g., absence of P-waves, and irregular R-R intervals for the AF detection task).

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Gap junctions consist of arrays of intercellular channels that enable adjacent cells to communicate both electrically and metabolically. Gap junctions have a wide diversity of physiological functions, playing critical roles in both excitable and non-excitable tissues. Gap junction channels are formed by integral membrane proteins called connexins. Inherited or acquired alterations in connexins are associated with numerous diseases, including heart failure, neuropathologies, deafness, skin disorders, cataracts and cancer. Gap junctions are highly dynamic structures and by modulating the turnover rate of connexins, cells can rapidly alter the number of gap junction channels at the plasma membrane in response to extracellular or intracellular cues. Increasing evidence suggests that ubiquitination has important roles in the regulation of endoplasmic reticulum-associated degradation of connexins as well as in the modulation of gap junction endocytosis and post-endocytic sorting of connexins to lysosomes. In recent years, researchers have also started to provide insights into the physiological roles of connexin ubiquitination in specific tissue types. This review provides an overview of the advances made in understanding the roles of connexin ubiquitination in the regulation of gap junction intercellular communication and discusses the emerging physiological and pathophysiological implications of these processes.

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The potent hERG channel blocking drug ondansetron is used off-label for treatment of nausea and vomiting in early pregnancy. Some human epidemiological studies have associated ondansetron with fetal cardiovascular defects and orofacial clefts. This study investigated the effects of ondanestron on embryonic heart rhythm of gestational day (GD) 13 rat embryos in vitro and then integrated the results with published animal teratology, and animal and human pharmacokinetic studies to perform a risk evaluation. Ondansetron caused concentration dependent bradycardia and arrhythmia. Cardiovascular malformations in rats occurred at exposures slightly higher than those in early human pregnancy. Together the results suggest that ondansetron can have teratogenic potential in rats and humans mediated via hERG block and severe heart rhythm disturbances in the embryo. The risk may be increased in human pregnancy if additional risk factors are present such as hypokalemia.

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Evaluar la presencia de disfunción tiroidea en pacientes con arritmias cardíacas tratados con Amiodarona (AMD) Métodos: se realizó el estudio en 24 pacientes que presentaron arritmias supraventriculares o ventriculares tratados con AMD, atendidos en el Servicio de Medicina Interna de la Ciudad Hospitalaria "Dr. Enrique Tejera" durante el período julio 2015 ­ abril 2016. Se les determinaron T3L, T4L y TSH a manera de tamizaje previo a la administración de AMD y fueron citados y divididos en 3 grupos de 3, 6 y 12 meses de tratmiento de AMD con determinación del perfil tiroideo en la consulta. Resultados: El hipotiroidismo inducido por AMD (HIA) se presentó en 20,83% (n=5), siendo más frecuente en aquellos pacientes asculinos que tenían 3 meses de tratamiento y que recibían una dosis de 1400 mg/semanal. La tirotoxicosis inducida por AMD (TIA) se presentó en 8,33% (n=2) ambos masculinos con dosis de 1400 mg/semanal. No se encontró asociación entre HIA y TIA con el tiempo, dosis, grupo etario ni género (P>0,05). T3L, T4L y TSH registraron el mayor y menor promedio a los 12 y 3 meses (P < 0,05); 12 y 6 meses; 3 y 12 meses respectivamente. Conclusión: La frecuencia de HIA fue de 20,83 % y TIA de 8,33 %. No hubo asociación estadísticamente significativa entre la HIA o TIA con la duración de consumo, dosis, grupo etario ni género. La TSH presentó el mayor promedio a los 3 meses, la T3L y T4L a los 12 meses (AU)

to evaluate the presence of thyroid dysfunction in patients with cardiac arrhythmia who were treated with Amiodarone (AMD). Methods: the study was done in 24 patients who were treated for supraventricular or ventricular arrhythmia at the Department of Internal Medicine of Hospital "Dr. Enrique Tejera" in Valencia, Venezuela from July 2015 to April 2016. FT3, FT4 and TSH were measured to the administration of AMD. The patients were divided in 3 groups according to time of use of the drug as follows: 3, 6 and 12 months, and their thyroid function was measured at each of these periods. Results: 20.83 % (n=5) presented Amiodarone induced hypothyroidism (AIH), which was more frequent in males at 3 months of treatment and who received 1400 mg weekly. Amiodarone induced thyrotoxicosis (AIT) was found in 8.33% (n=2) also in male patients using 1400mg weekly. There was no association between AIH or AIT and duration, dose of AMD, age or gender. (p>0.05) FT3, FT4 and TSH registered their higher and lower averages on 12 and 3 months (P < 0,05); 12 and 6 months; 3 and 12 months respectively. Conclusion: AIH's frequency was 20.83 % and 8.33% for AIT. There was no statistically significant association between AIH or AIT and duration, dose of AMD, age or gender TSH average measure was higher at 3 months and the FT3 and FT4 at 12 months(AU)

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In this study, Random Forests (RF) classifier is proposed for ECG heartbeat signal classification in diagnosis of heart arrhythmia. Discrete wavelet transform (DWT) is used to decompose ECG signals into different successive frequency bands. A set of different statistical features were extracted from the obtained frequency bands to denote the distribution of wavelet coefficients. This study shows that RF classifier achieves superior performances compared to other decision tree methods using 10-fold cross-validation for the ECG datasets and the obtained results suggest that further significant improvements in terms of classification accuracy can be accomplished by the proposed classification system. Accurate ECG signal classification is the major requirement for detection of all arrhythmia types. Performances of the proposed system have been evaluated on two different databases, namely MIT-BIH database and St. -Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database. For MIT-BIH database, RF classifier yielded an overall accuracy 99.33 % against 98.44 and 98.67 % for the C4.5 and CART classifiers, respectively. For St. -Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database, RF classifier yielded an overall accuracy 99.95 % against 99.80 % for both C4.5 and CART classifiers, respectively. The combined model with multiscale principal component analysis (MSPCA) de-noising, discrete wavelet transform (DWT) and RF classifier also achieves better performance with the area under the receiver operating characteristic (ROC) curve (AUC) and F-measure equal to 0.999 and 0.993 for MIT-BIH database and 1 and 0.999 for and St. -Petersburg Institute of Cardiological Technics 12-lead Arrhythmia Database, respectively. Obtained results demonstrate that the proposed system has capacity for reliable classification of ECG signals, and to assist the clinicians for making an accurate diagnosis of cardiovascular disorders (CVDs).

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Long QT Syndrome is characterized by syncope and fatal ventricular arrhythmia. Monotherapy with beta blockers is the first-line therapy. In patients with recurrent syncope despite therapy with beta blockers, combinations of the following modalities of treatment may be considered: pacemakers, left cervicothoracic sympathectomy, and implantable cardioverter defibrillators. Recently, we anesthetized a patient with Long QT Syndrome who underwent thoracoscopic left upper ganglionectomy for recurrent episodes of syncope and ventricular arrhythmia despite aggressive use of propranolol. Because of the increased risk of developing fatal ventricular arrhythmias during anesthesia and surgery, we performed a left stellate ganglion block prior to induction of anesthesia to prevent the ventricular arrhythmia that may be triggered by stimulation of the sympathetic nervous system and to assess the effect of surgical ganglionectomy on the QT interval. Following the block, the QT interval was shortened, and anesthesia and surgery was uneventful though anesthetic induction caused serious sympathetic responses. We recommend a left stellate ganglion block prior to induction of anesthesia in patients with Long QT Syndrome resistant to beta blocker to prevent fatal arrhythmia and to predict the efficacy of the surgical sympathectomy on the QT interval.

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Transient Complete left bundle branch block (CLBBB) is defined as an intraventricular conduction defect that subsequently returns, if only temporarily, to normal conduction. CLBBB is usually permanent and associated with a structurally abnormal heart, especially the heart with artherosclerotic, hypertensive, or valvular disease. However, CLBBB may appear transiently and intermittently during anesthesia, although it is uncommon.It may be related to the changes in heart rate or blood pressure without any heart disease. Also, transient CLBBB may develop during anesthesia in the absence of associated tachycardia or hypertension. We report a case of transient CLBBB which developed without apparent associated hypertension or tachycardia during general endotracheal anesthesia.

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PURPOSE: To evaluate the usefulness of cardiac MRI in the diagnosis of clinically suspected arrhythmogenic right ventricular dysplasia (ARVD). MATERIALS AND METHODS: Between February 1991 and January 1999, 15 patients [M:F=13:2, aged 2 -60 (mean, 37 -7) years] with clinically suspected ventricular arrhythmia due to unknown causes underwent MR imaging. Using a CP body array coil and the single slice breath hold technique, ECG-gated T1-weighted images were obtained. In all patients, these were acquired transaxially from the diaphragm to the aortic arch and along the true short and long axis, and in two, coronal images were obtained. On the basis of clinical and MRI diagnostic criteria, ARVD was classified as one of four types. The significance of differences in diagnostic grades between clinical and MRI criteria was determined using Wilcoxon's signed rank test. RESULTS: According to both clinical and MRI criteria, it was highly probable that three of the 15 patients had ARVD. In eleven, both sets of criteria indicated the same diagnostic grade. Wilcoxon's signed rank test indicated no significant differences in diagnostic grades between clinical and MRI criteria (p > 0.05). CONCLUSION: For the diagnosis or exclusion of ARVD, MR imaging is a useful modality.

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PURPOSE: To evaluate the usefulness of cardiac MRI in the diagnosis of clinically suspected arrhythmogenic right ventricular dysplasia (ARVD). MATERIALS AND METHODS: Between February 1991 and January 1999, 15 patients [M:F=13:2, aged 2 -60 (mean, 37 -7) years] with clinically suspected ventricular arrhythmia due to unknown causes underwent MR imaging. Using a CP body array coil and the single slice breath hold technique, ECG-gated T1-weighted images were obtained. In all patients, these were acquired transaxially from the diaphragm to the aortic arch and along the true short and long axis, and in two, coronal images were obtained. On the basis of clinical and MRI diagnostic criteria, ARVD was classified as one of four types. The significance of differences in diagnostic grades between clinical and MRI criteria was determined using Wilcoxon's signed rank test. RESULTS: According to both clinical and MRI criteria, it was highly probable that three of the 15 patients had ARVD. In eleven, both sets of criteria indicated the same diagnostic grade. Wilcoxon's signed rank test indicated no significant differences in diagnostic grades between clinical and MRI criteria (p > 0.05). CONCLUSION: For the diagnosis or exclusion of ARVD, MR imaging is a useful modality.

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