@inproceedings{2f0b62ca61b74d66ac3c78a4baa1b0b4,
title = "Predicting Activation Patterns in Cardiac Resynchronization Therapy Patients",
abstract = "Cardiac resynchronization therapy (CRT) is an effective treatment for heart failure patients. Suboptimal pacing timings and locations have been identified as causes for nonresponse to CRT. Patient specific computer models allow for the prediction of the electrical activation pattern on the ventricles, which can then be used to optimise CRT lead location.The electrical activation of the heart depends on the underlying cardiac substrate. The electrical properties of the heart have been found to be heterogeneous, with scar, functional block, septal slowing, and fast endocardial conduction impacting the electrical activation across the ventricles.Non-invasive data from 14 patients were used to create computer models of the heart. The patient specific models were then used to assess the importance of the heterogeneous cardiac substrates on accurately predicting the electrical activation pattern of the ventricles. Fast endocardial conduction was found to be the most important factor in accurately predicting the electrical activation of the heart in CRT patients.",
keywords = "HEART-FAILURE, OPTIMIZATION, INSIGHTS",
author = "A.W.C. Lee and U.C. Nguyen and J. Gould and B. Sidhu and B. Sieniewicz and C.M. Costa and F. Prinzen and G. Plank and C.A. Rinaldi and K. Vernooy and S.A. Niederer",
year = "2018",
month = sep,
doi = "10.22489/CinC.2018.079",
language = "English",
isbn = "9781728109589",
volume = "45",
series = "Computing in Cardiology Conference",
publisher = "IEEE",
booktitle = "Computing in Cardiology Conference, CinC 2018",
address = "United States",
note = "45th Computing in Cardiology Conference (CinC) ; Conference date: 23-09-2018 Through 26-09-2018",
}