Project description:We present the first imaging registry of the progressive isolation of an apical chamber of the right ventricle caused by the hypertrophy of the moderator band generated from the hemodynamic effect of a ventricular septal defect, leaving the apex of the right ventricle as an accessory chamber of the left ventricle. (Level of Difficulty: Advanced.) Central Illustration
Project description:VACTERL association is a non-random association of birth defects of unknown etiology derived from structures of embryonic mesoderm. The common cardiac defects seen with VACTERL association are ventricular septal defects, atrial septal defects, and tetralogy of Fallot. We present a 2-year-old child with VACTERL association in whom we detected double-chambered left ventricle on transthoracic echocardiography.
Project description:The rare case of an adult with a double-chambered left ventricle was revealed using multimodality imaging using echocardiography and cardiac magnetic resonance imaging in a 38-year-old asymptomatic male patient. The congenital malformation was dominated by a second, coarsely trabeculated muscular shelf dividing the left ventricle into 2 chambers without signs for left ventricular inflow or outflow tract obstruction. The partition wall did not show any signs for intramyocardial fibrosis in late gadolinium enhancement cardiovascular magnetic resonance imaging. Flow measurements excluded a relevant intracardial shunt across the additive perimembranous ventricular septal defect. There were no signs for global right and left ventricular dysfunction with left and right ventricular volumes and ejection fraction within normal limits. A conservative approach was recommended. In summary, we are able to present the case of an adult with a double-chambered left ventricle with a second muscular "septum" partially dividing the left ventricular cavity without causing a relevant impact on cardiac function or clinical signs for heart failure.
Project description:Deep neural networks (DNNs) have been extensively studied in medical image segmentation. However, existing DNNs often need to train shape models for each object to be segmented, which may yield results that violate cardiac anatomical structure when segmenting cardiac magnetic resonance imaging (MRI). In this paper, we propose a capsule-based neural network, named Seg-CapNet, to model multiple regions simultaneously within a single training process. The Seg-CapNet model consists of the encoder and the decoder. The encoder transforms the input image into feature vectors that represent objects to be segmented by convolutional layers, capsule layers, and fully-connected layers. And the decoder transforms the feature vectors into segmentation masks by up-sampling. Feature maps of each down-sampling layer in the encoder are connected to the corresponding up-sampling layers, which are conducive to the backpropagation of the model. The output vectors of Seg-CapNet contain low-level image features such as grayscale and texture, as well as semantic features including the position and size of the objects, which is beneficial for improving the segmentation accuracy. The proposed model is validated on the open dataset of the Automated Cardiac Diagnosis Challenge 2017 (ACDC 2017) and the Sunnybrook Cardiac Magnetic Resonance Imaging (MRI) segmentation challenge. Experimental results show that the mean Dice coefficient of Seg-CapNet is increased by 4.7% and the average Hausdorff distance is reduced by 22%. The proposed model also reduces the model parameters and improves the training speed while obtaining the accurate segmentation of multiple regions.Supplementary informationThe online version contains supplementary material available at 10.1007/s11390-021-0782-5.
Project description:ObjectivesTo determine the test-retest reproducibility and observer variability of CMR-derived LA function, using (i) LA strain (LAS) and strain rate (LASR), and (ii) LA volumes (LAV) and emptying fraction (LAEF).MethodsSixty participants with and without cardiovascular disease (aortic stenosis (AS) (n = 16), type 2 diabetes (T2D) (n = 28), end-stage renal disease on haemodialysis (n = 10) and healthy volunteers (n = 6)) underwent two separate CMR scans 7-14 days apart. LAS and LASR, corresponding to LA reservoir, conduit and contractile booster-pump function, were assessed using Feature Tracking software (QStrain v2.0). LAEF was calculated using the biplane area length method (QMass v8.1). Both were assessed using 4- and 2-chamber long-axis standard steady-state free precession cine images, and average values were calculated. Intra- and inter-observer variabilities were assessed in 10 randomly selected participants.ResultsThe test-retest reproducibility was moderate to poor for all strain and strain rate parameters. Overall, strain and strain rate corresponding to reservoir phase (LAS_r, LASR_r) were the most reproducible, yielding the smallest coefficient of variance (CoV) (29.9% for LAS_r, 28.9% for LASR_r). The test-retest reproducibility for LAVs and LAEF was good: LAVmax CoV = 19.6% ICC = 0.89, LAVmin CoV = 27.0% ICC = 0.89 and total LAEF CoV = 15.6% ICC = 0.78. The inter- and intra-observer variabilities were good for all parameters except for conduit function.ConclusionThe test-retest reproducibility of LA strain and strain rate assessment by CMR utilising Feature Tracking is moderate to poor across disease states, whereas LA volume and emptying fraction are more reproducible on CMR. Further improvements in LA strain quantification are needed before widespread clinical application.Key points• LA strain and strain rate assessment using Feature Tracking on CMR has moderate to poor test-retest reproducibility across disease states. • The test-retest reproducibility for the biplane method of assessing LA function is better than strain assessment, with lower coefficient of variances and narrower limits of agreement on Bland-Altman plots. • Biplane LA volumetric measurement also has better intra- and inter-observer variability compared to strain assessment.
Project description:A double-chambered right ventricle (DCRV) is a rare congenital heart disease and an uncommon cause of congestive heart failure. An anomalous muscle band divides the right ventricle into two cavities: the proximal high-pressure chamber and the distal low-pressure chamber. Most cases are diagnosed and treated during childhood. Furthermore, there is a tendency for progression, if not treated early. Echocardiography is considered useful for the diagnosis of this ailment. Most of the patients have associated congenital anomalies, such as ventricular septal defect, pulmonary stenosis, and subaortic stenosis. Isolated DCRV is a rare entity. Hence, we report a case of an isolated DCRV in an adult patient.
Project description:Isolated left ventricular apical hypoplasia (ILVAH) is an uncommon and likely congenital cardiac abnormality that has been described as relatively new. ILVAH is characterized by a truncated, globular-shaped left ventricle (LV) with bulging of the interventricular septum toward the right ventricle (RV), wrapping of an elongated and lengthened RV around the absent LV apex, thinning and fat replacement of apical myocardium of the LV, and abnormalities in the papillary muscle arrangement of the LV. In this report, we present the cardiac magnetic resonance imaging findings of a 22-year-old female patient with non-specific cardiac complaints that were compatible with ILVAH. Recognition of this rare cardiomyopathy is important for clinicians and radiologists in order to follow up on patients with ILVAH, as it may lead to severe complications, and to distinguish it from other cardiomyopathies.Learning objectiveIsolated left ventricular apical hypoplasia (ILVAH) is a rare congenital cardiomyopathy that has some serious complications, such as left-sided heart failure, severe pulmonary hypertension, and fatal arrhythmias. By recognizing and identifying the cardiac magnetic resonance imaging findings of ILVAH, clinicians and radiologists can take appropriate measures to manage and treat patients with this condition, potentially improving outcomes and reducing the risk of complications.