BackgroundVenous stenosis is a common complication of transvenous lead implantation, but the risk factors for venous stenosis have not been well defined to date. This study was designed to evaluate the incidence of and risk factors for venous stenosis in a large consecutive cohort.Methods and ResultsA total of 212 consecutive patients (136 male, 76 female; mean age 69 years) with existing pacing or implantable cardioverter-defibrillator systems presented for generator replacement, lead revision, or device upgrade with a mean time since implantation of 6.2 years. Venograms were performed and percentage of stenosis was determined. Variables studied included age, sex, number of leads, lead diameter, implant duration, insulation material, side of implant, and anticoagulant use. Overall, 56 of 212 patients had total occlusion of the subclavian or innominate vein (26%). There was a significant association between the number of leads implanted and percentage of venous stenosis (P =0.012). Lead diameter, as an independent variable, was not a risk factor; however, greater sum of the lead diameters implanted was a predictor of subsequent venous stenosis (P =0.009). Multiple lead implant procedures may be associated with venous stenosis (P =0.057). No other variables approached statistical significance.ConclusionsA significant association exists between venous stenosis and the number of implanted leads and also the sum of the lead diameters. When combined with multiple implant procedures, the incidence of venous stenosis is increased.

Cardiac resynchronization therapy (CRT) using a biventricular pacemaker is an invasive and expensive treatment option for left ventricular mechanical dyssynchrony (LVMD). The CRT candidate selection is a crucial issue due to the unreliability of the current standard CRT indicators. Real-time 3D echocardiography (RT3DE) provides 4D (3D+time) information about the LV and is suitable for LVMD assessment. In this paper, the complex LV shape and motion of 50 RT3DE datasets are represented by novel 4D descriptors—4D sphericity, volume, and shape, from which novel indices were derived by principal component analysis (PCA) and subsequently analyzed by a support vector machine (SVM) classifier to assess their capability of LVMD characterization and CRT outcome prediction. These novel indices outperformed clinical indices and have promising capabilities in disease characterization and great potential in CRT outcome prediction. To enable efficient quantitative RT3DE analysis, a segmentation method was developed to combine the powers of active shape models and optimal graph search. Various aspects of the method were designed to handle varying RT3DE image quality among datasets and LV segments. An application with graphical user interface was developed to provide the user with simple and intuitive control. The developed method was robust to inter-observer variability and produced very good accuracy—3.2±1.1mm absolute surface positioning error, <1 mm mean signed error, and <5% mean volume difference. The computer method’s classification performance was compared with the independent standard, showing that the 4D shape modal indices were not only the most capable of all tested options when employed for disease characterization but also the least sensitive to segmentation imperfections.

Quantitative analysis of the left ventricular shape and motion patterns associated with left ventricular mechanical dyssynchrony (LVMD) is essential for diagnosis and treatment planning in congestive heart failure. Real-time 3D echocardiography (RT3DE) used for LVMD analysis is frequently limited by heavy speckle noise or partially incomplete data, thus a segmentation method utilizing learned global shape knowledge is beneficial. In this study, the endocardial surface of the left ventricle (LV) is segmented using a hybrid approach combining active shape model (ASM) with optimal graph search. The latter is used to achieve landmark refinement in the ASM framework. Optimal graph search translates the 3D segmentation into the detection of a minimum-cost closed set in a graph and can produce a globally optimal result. Various information -gradient, intensity distributions, and regional-property terms -are used to define the costs for the graph search. The developed method was tested on 44 RT3DE datasets acquired from 26 LVMD patients. The segmentation accuracy was assessed by surface positioning error and volume overlap measured for the whole LV as well as 16 standard LV regions. The segmentation produced very good results that were not achievable using ASM or graph search alone.

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A 24-year-old male with Wolff-Parkinson-White syndrome developed systolic cardiomyopathy and severe heart failure following membranous ventricular septal defect repair and tricuspid valve replacement. Following successful catheter ablation of a right anterolateral accessory pathway (AP), complete AV block with junctional escape rhythm was noted. Patient subsequently underwent implantation of a biventricular ICD. Heart failure symptoms significantly improved soon after and left ventricular systolic function normalized 3 months post-procedure. In this case, surgically acquired AV block likely explains development of postoperative cardiomyopathy by facilitating ventricular activation solely via the AP and thereby increasing the degree of ventricular dyssynchrony.