Background: Partial anomalous venous connections (PAPVC) are associated with left to right shunting and right heart dilatation. Identification of PAPVC has increased with widespread use of cross-sectional imaging modalities. However, management strategies are mostly based on expert opinion given the scarcity of data from large series. We aimed to define types and significance of isolated and atrial septal defect (ASD) associated PAPVC detected by cardiovascular magnetic resonance. Methods: We retrospectively reviewed our cardiovascular magnetic resonance database from 2002 to 2018 to identify isolated or ASD-associated PAPVC cases. Results: A total of 215 patients (median age 46 years; range, 6–83) with isolated or ASD-associated PAPVC were identified among 102 135 clinical cardiovascular magnetic resonance studies. Of these, 104 were isolated and 111 were associated with an ASD. Anomalous connection of right upper pulmonary vein was the most common single venous anomaly (99/215), but in the isolated PAPVC group there were more anomalous left than right upper pulmonary veins (39 versus 34). The Qp/Qs was significantly higher for isolated anomalous single right upper pulmonary vein than left upper pulmonary vein (1.6 versus 1.4 respectively; P =0.01) as were right ventricular end-diastolic volumes (113.7±30.9 versus 90 [57–157] mL/m ² , P =0.004). In the PAPVC with an ASD group, sinus venosus ASDs (82%) were associated with right-sided PAPVCs while both right and left-sided venous anomalies were seen in secundum ASDs (18%). In a substantial number of patients (30 out of 91) with sinus venosus ASDs, PAPVCs were more complex and involved more than a single anomalous right upper pulmonary vein; and in 5 patients with ASD, PAPVC was identified only after the ASD closure. Conclusions: This large series provides descriptive and hemodynamic features for isolated and ASD-associated PAPVCs. Anomalous isolated right upper pulmonary vein may cause a significant shunt (Qp/Qs >1.5). PAPVC associated with sinus venosus and secundum ASDs might be more complex than a single anomalous pulmonary vein and missed before ASD correction.

This study sought to investigate whether shape-based late gadolinium enhancement (LGE) metrics and simulations of re-entrant electrical activity are associated with arrhythmic events in patients with nonischemic dilated cardiomyopathy (NIDCM). The presence of LGE predicts life-threatening ventricular arrhythmias in NIDCM; however, risk stratification remains imprecise. LGE shape and simulations of electrical activity may be able to provide additional prognostic information. Cardiac magnetic resonance (CMR)-LGE shape metrics were computed for a cohort of 156 patients with NIDCM and visible LGE and tested retrospectively for an association with an arrhythmic composite endpoint of sudden cardiac death and ventricular tachycardia. Computational models were created from images and used in conjunction with simulated stimulation protocols to assess the potential for re-entry induction in each patient's scar morphology. A mechanistic analysis of the simulations was carried out to explain the associations. During a median follow-up of 1,611 (interquartile range: 881 to 2,341) days, 16 patients (10.3%) met the primary endpoint. In an inverse probability weighted Cox regression, the LGE-myocardial interface area (hazard ratio [HR]: 1.75; 95% confidence interval [CI]: 1.24 to 2.47; p = 0.001), number of simulated re-entries (HR: 1.40; 95% CI: 1.23 to 1.59; p < 0.01) and LGE volume (HR: 1.44; 95% CI: 1.07 to 1.94; p = 0.02) were associated with arrhythmic events. Computational modeling revealed repolarization heterogeneity and rate-dependent block of electrical wavefronts at the LGE-myocardial interface as putative arrhythmogenic mechanisms directly related to the LGE interface area. The area of interface between scar and surviving myocardium, as well as simulated re-entrant activity, are associated with an elevated risk of major arrhythmic events in patients with NIDCM and LGE and represent novel risk predictors.

Three-directional cine multi-slice left ventricular myocardial velocity mapping (3Dir MVM) is a cardiac magnetic resonance (CMR) technique that allows the assessment of cardiac motion in three orthogonal directions. Accurate and reproducible delineation of the myocardium is crucial for accurate analysis of peak systolic and diastolic myocardial velocities. In addition to the conventionally available magnitude CMR data, 3Dir MVM also provides three orthogonal phase velocity mapping datasets, which are used to generate velocity maps. These velocity maps may also be used to facilitate and improve the myocardial delineation. Based on the success of deep learning in medical image processing, we propose a novel fast and automated framework that improves the standard U-Net-based methods on these CMR multi-channel data (magnitude and phase velocity mapping) by cross-channel fusion with an attention module and the shape information-based post-processing to achieve accurate delineation of both epicardial and endocardial contours. To evaluate the results, we employ the widely used Dice Scores and the quantification of myocardial longitudinal peak velocities. Our proposed network trained with multi-channel data shows superior performance compared to standard U-Net-based networks trained on single-channel data. The obtained results are promising and provide compelling evidence for the design and application of our multi-channel image analysis of the 3Dir MVM CMR data.

In patients presenting with ST-elevation myocardial infarction (STEMI), we investigated the relation of left atrial (LA) deformational parameters evaluated by two-dimensional speckle tracking imaging (2D-STI) with conventional echocardiographic diastolic dysfunction parameters and B-type natriuretic peptide (BNP) level.

Anadolu Kardiyoloji Dergisi, Anadolu Kardiyol Derg, The Anatolian Journal of Cardiology, Anatol J Cardiol, Cardiology, Cardiovascular Medicine, Surgery, Pediatric Cardiology, Angiology

Cardiovascular magnetic resonance (CMR) derived ventricular volumes and function guide clinical decision-making for various cardiac pathologies. We aimed to evaluate the efficiency and clinical applicability of a commercially available artificial intelligence (AI) method for performing biventricular volumetric analysis. Three-hundred CMR studies (100 with normal CMR findings, 50 dilated cardiomyopathy, 50 hypertrophic cardiomyopathy, 50 ischaemic heart disease and 50 congenital or valvular heart disease) were randomly selected from database. Manual biventricular volumetric analysis (CMRtools) results were derived from clinical reports and automated volumetric analyses were performed using short axis volumetry AI function of CircleCVI⁴² v5.12 software. For 20 studies, a combined method of manually adjusted AI contours was tested and all three methods were timed. Clinicians` confidence in AI method was assessed using an online survey. Although agreement was better for left ventricle than right ventricle, AI analysis results were comparable to manual method. Manual adjustment of AI contours further improved agreement: within subject coefficient of variation decreased from 5.0% to 4.5% for left ventricular ejection fraction (EF) and from 9.9% to 7.1% for right ventricular EF. Twenty manual analyses were performed in 250 min 12 s whereas same task took 5 min 48 s using AI method. Clinicians were open to adopt AI but concerns about accuracy and validity were raised. The AI method provides clinically valid outcomes and saves significant time. To address concerns raised by survey participants and overcome shortcomings of the automated myocardial segmentation, visual assessment of contours and performing manual corrections where necessary appears to be a practical approach.