Echocardiographic aspects of hypertrophic cardiomyopathy in a Persian cat: case report

Hypertrophic cardiomyopathy (HCM) is a primary myocardial abnormality characterized by diastolic dysfunction and congestive heart failure of unknown etiology. It is a cardiac disorder most common in cats (Felis catus), and is reported as a rare condition in dogs. There are racial, sex and age predisposition in cats. Clinical signs commonly found are anorexia, nausea, vomiting, acute dyspnea, paresis or paralysis of hind limbs. Radiographic and electrocardiographic exams are critical to understanding the disease, but Doppler echocardiographic imaging is the definitive method for diagnosis. Our objective is to report the appearance and Doppler ultrasonography in a case of hypertrophic cardiomyopathy in a 3-year-old Persian cat.

Relationship between aetiology and left ventricular systolic dysfunction in hypertrophic cardiomyopathy

Background: Hypertrophic cardiomyopathy (HCM) is a common cardiac disease caused by a range of genetic and acquired disorders. The most common cause is genetic variation in sarcomeric proteins genes. Current ESC guidelines suggest that particular clinical features (‘red flags’) assist in differential diagnosis. Aims: To test the hypothesis that left ventricular (LV) systolic dysfunction in the presence of increased wall thickness is an age-specific ‘red flag’ for aetiological diagnosis and to determine long-term outcomes in adult patients with various types of HCM. Methods: A cohort of 1697 adult patients with HCM followed at two European referral centres were studied. Aetiological diagnosis was based on clinical examination, cardiac imaging and targeted genetic and biochemical testing. Main outcomes were: all-cause mortality or heart transplantation (HTx) and heart failure (HF) related-death. All-cause mortality included sudden cardiac death or equivalents, HF and stroke-related death and non-cardiovascular death. Results: Prevalence of different aetiologies was as follows: sarcomeric HCM 1288 (76%); AL amyloidosis 115 (7%), hereditary TTR amyloidosis 86 (5%), Anderson-Fabry disease 85 (5%), wild-type TTR amyloidosis 48 (3%), Noonan syndrome 15 (0.9%), mitochondrial disease 23 (1%), Friedreich’s ataxia 11 (0.6%), glycogen storage disease 16 (0.9%), LEOPARD syndrome 7 (0.4%), FHL1 2 (0.1%) and CPT II deficiency 1 (0.1%). Systolic dysfunction at first evaluation was significantly more frequent in phenocopies than sarcomeric HCM [105/409 (26%) versus 40/1288 (3%), (p<0.0001)]. All-cause mortality/HTx and HF-related death were higher in phenocopies compared to sarcomeric HCM (p<0.001, respectively). When considering specific aetiologies, all-cause mortality and HF-related death were higher in cardiac amyloidosis (p<0.001, respectively). Conclusion: Systolic dysfunction at first evaluation is more common in phenocopies compared to sarcomeric HCM representing an age-specific ‘red flag’ for differential diagnosis. Long-term prognosis was more severe in phenocopies compared to sarcomeric HCM and when comparing specific aetiologies, cardiac amyloidosis showed the worse outcomes.

Substrate characterization and catheter ablation for monomorphic ventricular tachycardia in patients with apical hypertrophic cardiomyopathy

VT Ablation in Apical Hypertrophic Cardiomyopathy.

Termination of Ventricular Tachycardia with Antitachycardia Pacing after Ineffective Shock Therapy in an ICD Recipient with Hypertrophic Cardiomyopathy

Implantable Cardioverter Defibrillator (ICD) implantation is the only established therapy for primary or secondary prevention of sudden cardiac death in patients with Hypertrophic Cardiomyopathy (HCM). Ineffectiveness of shock therapy for the termination of potentially fatal ventricular arrhythmias in ICD recipients is rare in the presence of appropriate arrhythmia detection by the device. We report the case of a 48-year-old woman with HCM and a single chamber ICD, who received five inefficient high-energy (35 Joules) shocks for the termination of an appropriately detected episode of Ventricular Tachycardia (VT). The episode was safely terminated with a subsequent application of Antitachycardia Pacing (ATP) by the device. At the following ICD control, an acceptable defibrillation threshold was detected.

Myocardial contrast echocardiography for the distinction of hypertrophic cardiomyopathy from athlete's heart and hypertensive heart disease

BACKGROUND: Myocardial contrast echocardiography (MCE) is able to measure in vivo relative blood volume (rBV, i.e., capillary density), and its exchange frequency b, the constituents of myo-cardial blood flow (MBF, ml min-1 g-1). This study aimed to assess, by MCE, whether left ventricular hypertrophy (LVH) in hypertrophic cardiomyopathy (HCM) can be differentiated from LVH in triathletes (athlete's heart, AH) or from hypertensive heart disease patients (HHD). METHODS: Sixty individuals, matched for age (33 +/- 10 years) and gender, and subdivided into four groups (n = 15) were examined: HCM, AH, HHD and a group of sedentary individuals without LVH (S). rBV (ml ml-1), b (min-1) and MBF, at rest and during adenosine-induced hyperaemia, were derived by MCE in mid septal, lateral and inferior regions. The ratio of MBF during hyperaemia and MBF at rest yielded myocardial blood flow reserve (MBFR). RESULTS: Septal wall rBV at rest was lower in HCM (0.084 +/- 0.023 ml ml-1) than in AH (0.151 +/- 0.024 ml ml-1, p <0.01) and in S (0.129 +/- 0.026 ml ml-1, p <0.01), but was similar to HHD (0.097 +/- 0.016 ml ml-1). Conversely, MBFR was lowest in HCM (1.67 +/- 0.93), followed by HHD (2.8 +/- 0.93, p <0.01), by S (3.36 +/- 1.03, p <0.001) and by AH (4.74 +/- 1.46, p <0.0001). At rest, rBV <0.11 ml ml-1 accurately distinguished between HCM and AH (sensitivity 99%, specificity 99%), similarly MBFR < or =1.8 helped to distinguish between HCM and HHD (sensitivity 100%, specificity 77%). CONCLUSIONS: rBV at rest, most accurately distinguishes between pathological LVH due to HCM and physiological, endurance-exercise induced LVH.

Phenotypes and echocardiographic characteristics of a European population of domestic shorthair cats with idiopathic hypertrophic cardiomyopathy

111 Domestic Shorthair cats with idiopathic hypertrophic cardiomyopathy were reviewed retrospectively. Two-dimensional echocardiography was used to classify cases in 6 established phenotypes. Hypertrophy was diffuse in 61 % of cats and involved major portions of the ventricular septum and the left ventricular free wall (phenotype D). In the remaining cats, distribution of hypertrophy was more segmental and was identified on the papillary muscles exclusively (phenotype A, 6 %), on the anterior and basal portion of the ventricular septum (phenotype B, 12 %), on the entire septum (phenotype C, 14 %), or on the left ventricular free wall (phenotype E, 7 %). Echocardiographic characteristics and clinical findings were determined for each phenotype to study the correlation between distribution of hypertrophy and clinical implications. 31 cats demonstrated systolic anterior motion of the mitral valve, 75 % of them belonged to phenotype C of hypertrophy. Left ventricular-outflow turbulences were identified more frequently with patterns of hypertrophy involving the ventricular septum (65.5 %), while prevalence of mitral regurgitation was higher when hypertrophy included the papillary muscles (phenotypes A and E, 85 % and 87 %, respectively). Left atrial dilatation occurred more frequently when hypertrophy was diffuse or confined to the left ventricular free wall (61 % of cats with phenotype D or E) rather than to the ventricular septum (31 % of cats with phenotype B or C).

Relaxation in hypertrophic cardiomyopathy and hypertensive heart disease: relations between hypertrophy and diastolic function

AIM To determine the relation between the extent and distribution of left ventricular hypertrophy and the degree of disturbance of regional relaxation and global left ventricular filling. METHODS Regional wall thickness (rWT) was measured in eight myocardial regions in 17 patients with hypertrophic cardiomyopathy, 12 patients with hypertensive heart disease, and 10 age matched normal subjects, and an asymmetry index calculated. Regional relaxation was assessed in these eight regions using regional isovolumetric relaxation time (rIVRT) and early to late peak filling velocity ratio (rE/A) derived from Doppler tissue imaging. Asynchrony of rIVRT was calculated. Doppler left ventricular filling indices were assessed using the isovolumetric relaxation time, the deceleration time of early diastolic filling (E-DT), and the E/A ratio. RESULTS There was a correlation between rWT and both rIVRT and rE/A in the two types of heart disease (hypertrophic cardiomyopathy: r = 0.47, p < 0.0001 for rIVRT; r = -0.20, p < 0.05 for rE/A; hypertensive heart disease: r = 0.21, p < 0.05 for rIVRT; r = -0.30, p = 0.003 for rE/A). The degree of left ventricular asymmetry was related to prolonged E-DT (r = 0. 50, p = 0.001) and increased asynchrony (r = 0.42, p = 0.002) in all patients combined, but not within individual groups. Asynchrony itself was associated with decreased E/A (r = -0.39, p = 0.01) and protracted E-DT (r = 0.69, p < 0.0001) and isovolumetric relaxation time (r = 0.51, p = 0.001) in all patients. These correlations were still significant for E-DT in hypertrophic cardiomyopathy (r = 0.56, p = 0.02) and hypertensive heart disease (r = 0.59, p < 0.05) and for isovolumetric relaxation time in non-obstructive hypertrophic cardiomyopathy (n = 8, r = 0.87, p = 0.005). CONCLUSIONS Non-invasive ultrasonographic examination of the left ventricle shows that in both hypertrophic cardiomyopathy and hypertensive heart disease, the local extent of left ventricular hypertrophy is associated with regional left ventricular relaxation abnormalities. Asymmetrical distribution of left ventricular hypertrophy is indirectly related to global left ventricular early filling abnormalities through regional asynchrony of left ventricular relaxation.

Functional analyses of troponin T mutations that cause hypertrophic cardiomyopathy: Insights into disease pathogenesis and troponin function

Mutations in a number of cardiac sarcomeric protein genes cause hypertrophic cardiomyopathy (HCM). Previous findings indicate that HCM-causing mutations associated with a truncated cardiac troponin T (TnT) and missense mutations in the β-myosin heavy chain share abnormalities in common, acting as dominant negative alleles that impair contractile performance. In contrast, Lin et al. [Lin, D., Bobkova, A., Homsher, E. & Tobacman, L. S. (1996) J. Clin. Invest. 97, 2842–2848] characterized a TnT point mutation (Ile79Asn) and concluded that it might lead to hypercontractility and, thus, potentially a different mechanism for HCM pathogenesis. In this study, three HCM-causing cardiac TnT mutations (Ile79Asn, Arg92Gln, and ΔGlu160) were studied in a myotube expression system. Functional studies of wild-type and mutant transfected myotubes revealed that all three mutants decreased the calcium sensitivity of force production and that the two missense mutations (Ile79Asn and Arg92Gln) increased the unloaded shortening velocity nearly 2-fold. The data demonstrate that TnT can alter the rate of myosin cross-bridge detachment, and thus the troponin complex plays a greater role in modulating muscle contractile performance than was recognized previously. Furthermore, these data suggest that these TnT mutations may cause disease via an increased energetic load on the heart. This would represent a second paradigm for HCM pathogenesis.

Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG

Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease where the heart muscle is partially thickened and blood flow is - potentially fatally - obstructed. It is one of the leading causes of sudden cardiac death in young people. Electrocardiography (ECG) and Echocardiography (Echo) are the standard tests for identifying HCM and other cardiac abnormalities. The American Heart Association has recommended using a pre-participation questionnaire for young athletes instead of ECG or Echo tests due to considerations of cost and time involved in interpreting the results of these tests by an expert cardiologist. Initially we set out to develop a classifier for automated prediction of young athletes’ heart conditions based on the answers to the questionnaire. Classification results and further in-depth analysis using computational and statistical methods indicated significant shortcomings of the questionnaire in predicting cardiac abnormalities. Automated methods for analyzing ECG signals can help reduce cost and save time in the pre-participation screening process by detecting HCM and other cardiac abnormalities. Therefore, the main goal of this dissertation work is to identify HCM through computational analysis of 12-lead ECG. ECG signals recorded on one or two leads have been analyzed in the past for classifying individual heartbeats into different types of arrhythmia as annotated primarily in the MIT-BIH database. In contrast, we classify complete sequences of 12-lead ECGs to assign patients into two groups: HCM vs. non-HCM. The challenges and issues we address include missing ECG waves in one or more leads and the dimensionality of a large feature-set. We address these by proposing imputation and feature-selection methods. We develop heartbeat-classifiers by employing Random Forests and Support Vector Machines, and propose a method to classify full 12-lead ECGs based on the proportion of heartbeats classified as HCM. The results from our experiments show that the classifiers developed using our methods perform well in identifying HCM. Thus the two contributions of this thesis are the utilization of computational and statistical methods for discovering shortcomings in a current screening procedure and the development of methods to identify HCM through computational analysis of 12-lead ECG signals.

Apical hypertrophic cardiomyopathy : a review

Trabalho Final do Curso de Mestrado Integrado em Medicina, Faculdade de Medicina, Universidade de Lisboa, 2014

Understanding hypertrophic cardiomyopathy /

Mode of access: Internet.

Tick paralysis in a cat with sub-clinical hypertrophic cardiomyopathy

A three-year-old male neutered British Shorthair cat was treated for tick paralysis caused by L holocyclus. Ten days after discharge, the cat represented with left-sided congestive heart failure and was diagnosed with hypertrophic cardiomyopathy, characterised by diastolic dysfunction. It has been proposed that tick toxicity is associated with diastolic dysfunction and it is possible that residual toxin effects were a contributing factor to the development of left-sided congestive heart failure in this case.

Computational Methods for Identifying Hypertrophic Cardiomyopathy using 12-lead ECG

Hypertrophic cardiomyopathy (HCM) is a cardiovascular disease where the heart muscle is partially thickened and blood flow is - potentially fatally - obstructed. It is one of the leading causes of sudden cardiac death in young people. Electrocardiography (ECG) and Echocardiography (Echo) are the standard tests for identifying HCM and other cardiac abnormalities. The American Heart Association has recommended using a pre-participation questionnaire for young athletes instead of ECG or Echo tests due to considerations of cost and time involved in interpreting the results of these tests by an expert cardiologist. Initially we set out to develop a classifier for automated prediction of young athletes’ heart conditions based on the answers to the questionnaire. Classification results and further in-depth analysis using computational and statistical methods indicated significant shortcomings of the questionnaire in predicting cardiac abnormalities. Automated methods for analyzing ECG signals can help reduce cost and save time in the pre-participation screening process by detecting HCM and other cardiac abnormalities. Therefore, the main goal of this dissertation work is to identify HCM through computational analysis of 12-lead ECG. ECG signals recorded on one or two leads have been analyzed in the past for classifying individual heartbeats into different types of arrhythmia as annotated primarily in the MIT-BIH database. In contrast, we classify complete sequences of 12-lead ECGs to assign patients into two groups: HCM vs. non-HCM. The challenges and issues we address include missing ECG waves in one or more leads and the dimensionality of a large feature-set. We address these by proposing imputation and feature-selection methods. We develop heartbeat-classifiers by employing Random Forests and Support Vector Machines, and propose a method to classify full 12-lead ECGs based on the proportion of heartbeats classified as HCM. The results from our experiments show that the classifiers developed using our methods perform well in identifying HCM. Thus the two contributions of this thesis are the utilization of computational and statistical methods for discovering shortcomings in a current screening procedure and the development of methods to identify HCM through computational analysis of 12-lead ECG signals.

Noncompaction in Healthy Subjects, Dilated and Hypertrophic Cardiomyopathy, and Neuromuscular Disorders Is the Same Entity

With interest we read the article by Khosroshahi et al. about a novel method for quantification of left ventricular hypertrabeculation/noncompaction (LVHT) using two-dimensional echocardiography in children (1). We appreciate their efforts to contribute to an improvement and unification of echocardiographic diagnostic criteria for LVHT, which is urgently needed. Concerning their proposed method, we have the following questions and concerns: