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Journal articleJarman JWE, Wong T, Kojodjojo P, et al., 2014,
Organizational Index Mapping to Identify Focal Sources During Persistent Atrial Fibrillation
, JOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY, Vol: 25, Pages: 355-363, ISSN: 1045-3873- Author Web Link
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- Citations: 26
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Journal articleDias P, Desplantez T, El-Harasis MA, et al., 2014,
Characterisation of Connexin Expression and Electrophysiological Properties in Stable Clones of the HL-1 Myocyte Cell Line
, PLOS ONE, Vol: 9, ISSN: 1932-6203- Author Web Link
- Open Access Link
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- Citations: 26
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Journal articleKyriacou A, Pabari PA, Mayet J, et al., 2014,
Cardiac resynchronization therapy and AV optimization increase myocardial oxygen consumption, but increase cardiac function more than proportionally
, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 171, Pages: 144-152, ISSN: 0167-5273- Author Web Link
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- Citations: 12
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Journal articleCantwell CD, Yakovlev S, Kirby RM, et al., 2014,
High-order spectral/hp element discretisation for reaction-diffusion problems on surfaces: application to cardiac electrophysiology
, Journal of Computational Physics, Vol: 257, Pages: 813-829, ISSN: 0021-9991We present a numerical discretisation of an embedded two-dimensional manifold using high-order continuous Galerkin spectral/hp elements, which provide exponential convergence of the solution with increasing polynomial order, while retaining geometric flexibility in the representation of the domain. Our work is motivated by applications in cardiac electrophysiology where sharp gradients in the solution benefit from the high-order discretisation, while the compu- tational cost of anatomically-realistic models can be reduced through the surface representation. We describe and validate our discretisation and provide a demonstration of its application to modeling electrochemical propagation across a human left atrium.
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Journal articleJamil-Copley S, Linton N, Koa-Wing M, et al., 2013,
Application of Ripple Mapping with an Electroanatomic Mapping System for Diagnosis of Atrial Tachycardias
, JOURNAL OF CARDIOVASCULAR ELECTROPHYSIOLOGY, Vol: 24, Pages: 1361-1369, ISSN: 1045-3873- Author Web Link
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- Citations: 25
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Journal articleDhillon PS, Gray R, Kojodjojo P, et al., 2013,
Relationship Between Gap-Junctional Conductance and Conduction Velocity in Mammalian Myocardium
, CIRCULATION-ARRHYTHMIA AND ELECTROPHYSIOLOGY, Vol: 6, Pages: 1208-1214, ISSN: 1941-3149- Author Web Link
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- Citations: 50
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Journal articleWalsh R, Peters NS, Cook SA, et al., 2013,
Paralogue annotation identifies novel pathogenic variants in patients with Brugada syndrome and catecholaminergic polymorphic ventricular tachycardia
, Journal of Medical Genetics, Vol: 51, Pages: 35-44, ISSN: 1468-6244Background Distinguishing genetic variants that causedisease from variants that are rare but benign is one ofthe principal challenges in contemporary clinicalgenetics, particularly as variants are identified at a paceexceeding the capacity of researchers to characterisethem functionally.Methods We previously developed a novel method,called paralogue annotation, which accurately andspecifically identifies disease-causing missense variants bytransferring disease-causing annotations across families ofrelated proteins. Here we refine our approach, and applyit to novel variants found in 2266 patients across twolarge cohorts with inherited sudden death syndromes,namely catecholaminergic polymorphic ventriculartachycardia (CPVT) or Brugada syndrome (BrS).Results Over one third of the novel non-synonymousvariants found in these studies, which would otherwisebe reported in a clinical diagnostics setting as ‘variants ofunknown significance’, are categorised by our method aslikely disease causing (positive predictive value 98.7%).This identified more than 500 new disease loci for BrSand CPVT.Conclusions Our methodology is widely transferableacross all human disease genes, with an estimated150 000 potentially informative annotations in more than1800 genes. We have developed a web resource thatallows researchers and clinicians to annotate variantsfound in individuals with inherited arrhythmias,comprising a referenced compendium of known missensevariants in these genes together with a user-friendlyimplementation of our approach. This tool will facilitatethe interpretation of many novel variants that mightotherwise remain unclassified.
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Journal articleKyriacou A, Wa MELK, Pabari PA, et al., 2013,
A systematic approach to designing reliable VV optimization methodology: Assessment of internal validity of echocardiographic, electrocardiographic and haemodynamic optimization of cardiac resynchronization therapy
, INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 167, Pages: 954-964, ISSN: 0167-5273- Author Web Link
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- Citations: 7
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Journal articleMalcolme-Lawes LC, Juli C, Karim R, et al., 2013,
Automated analysis of atrial late gadolinium enhancement imaging that correlates with endocardial voltage and clinical outcomes: A 2-center study
, HEART RHYTHM, Vol: 10, Pages: 1184-1191, ISSN: 1547-5271- Author Web Link
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- Citations: 104
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Journal articleBai W, Shi W, O'Regan DP, et al., 2013,
A probabilistic patch-based label fusion model for multi-atlas segmentation with registration refinement: application to cardiac MR images
, IEEE Transactions on Medical Imaging, Vol: 32, Pages: 1302-1315, ISSN: 0278-0062The evaluation of ventricular function is important for the diagnosis of cardiovascular diseases. It typically involves measurement of the left ventricular (LV) mass and LV cavity volume. Manual delineation of the myocardial contours is time-consuming and dependent on the subjective experience of the expert observer. In this paper, a multi-atlas method is proposed for cardiac magnetic resonance (MR) image segmentation. The proposed method is novel in two aspects. First, it formulates a patch-based label fusion model in a Bayesian framework. Second, it improves image registration accuracy by utilizing label information, which leads to improvement of segmentation accuracy. The proposed method was evaluated on a cardiac MR image set of 28 subjects. The average Dice overlap metric of our segmentation is 0.92 for the LV cavity, 0.89 for the right ventricular cavity and 0.82 for the myocardium. The results show that the proposed method is able to provide accurate information for clinical diagnosis.
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