P
Phani Chinchapatnam
Researcher at King's College London
Publications - 36
Citations - 1527
Phani Chinchapatnam is an academic researcher from King's College London. The author has contributed to research in topics: Regularized meshless method & Cardiac resynchronization therapy. The author has an hindex of 18, co-authored 36 publications receiving 1404 citations. Previous affiliations of Phani Chinchapatnam include Rolls-Royce Holdings & University of Southampton.
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Journal ArticleDOI
Patient-specific electromechanical models of the heart for the prediction of pacing acute effects in CRT: A preliminary clinical validation
Maxime Sermesant,Radomir Chabiniok,Phani Chinchapatnam,Tommaso Mansi,Florence Billet,Philippe Moireau,Jean-Marc Peyrat,Kitty Wong,Jatin Relan,Kawal Rhode,Matthew Ginks,Pier D. Lambiase,Hervé Delingette,Michel Sorine,Christopher A. Rinaldi,Dominique Chapelle,Reza Razavi,Nicholas Ayache +17 more
TL;DR: How the personalisation of an electromechanical model of the myocardium can predict the acute haemodynamic changes associated with CRT is presented, demonstrating the potential of physiological models personalised from images and electrophysiology signals to improve patient selection and plan CRT.
Journal ArticleDOI
Length-dependent tension in the failing heart and the efficacy of cardiac resynchronization therapy.
Steven A. Niederer,Gernot Plank,Phani Chinchapatnam,Matthew Ginks,Matthew Ginks,Pablo Lamata,Kawal Rhode,Christopher A. Rinaldi,Christopher A. Rinaldi,Reza Razavi,Reza Razavi,Nicolas P. Smith,Nicolas P. Smith +12 more
TL;DR: In individuals with effective Frank-Starling mechanism, the length dependence of tension facilitates the homogenization of stress and strain, and in these individuals, synchronizing electrical activation through CRT may have minimal benefit.
Journal ArticleDOI
Coupled personalization of cardiac electrophysiology models for prediction of ischaemic ventricular tachycardia
Jatin Relan,Phani Chinchapatnam,Maxime Sermesant,Kawal Rhode,Matthew Ginks,Hervé Delingette,C. Aldo Rinaldi,Reza Razavi,Nicholas Ayache +8 more
TL;DR: A coupled personalization framework is presented that combines the power of the two kinds of models while keeping the computational complexity tractable and opens up possibilities of using VT induction modelling in order to both assess the risk of VT for a given patient and also to plan a potential subsequent radio-frequency ablation strategy to treat VT.
Book ChapterDOI
An anisotropic multi-front fast marching method for real-time simulation of cardiac electrophysiology
Maxime Sermesant,Ender Konukoglu,Hervé Delingette,Yves Coudière,Phani Chinchapatnam,Kawal Rhode,Reza Razavi,Nicholas Ayache +7 more
TL;DR: A real-time method to simulate cardiac electrophysiology on triangular meshes based on a multi-front integration of the Fast Marching Method is proposed, which opens new possibilities, including the ability to directly integrate modelling in the interventional room.
Journal ArticleDOI
Efficient probabilistic model personalization integrating uncertainty on data and parameters: Application to eikonal-diffusion models in cardiac electrophysiology.
Ender Konukoglu,Jatin Relan,Ulas Cilingir,Bjoern H. Menze,Phani Chinchapatnam,Phani Chinchapatnam,Amir Jadidi,Hubert Cochet,Mélèze Hocini,Hervé Delingette,Pierre Jaïs,Michel Haïssaguerre,Nicholas Ayache,Maxime Sermesant +13 more
TL;DR: This work proposes an efficient Bayesian inference method for model personalization using polynomial chaos and compressed sensing and demonstrates how this can help in quantifying the impact of the data characteristics on the personalization (and thus prediction) results.