Is heart failure with mid range ejection fraction (HFmrEF) a distinct clinical entity or an overlap group?

Autor: Jessica Webb, Jane Draper, Lauren Fovargue, Ben Sieniewicz, Justin Gould, Simon Claridge, Carys Barton, Silapiya Smith, Kristin Tondel, Ronak Rajani, Stamatis Kapetanakis, Christopher A. Rinaldi, Theresa A. McDonagh, Reza Razavi, Gerald Carr-White

Publikováno v: International Journal of Cardiology: Heart & Vasculature, Vol 21, Iss , Pp 1-6 (2018)

Background: The new category of heart failure (HF), Heart Failure with mid range Ejection Fraction (HFmrEF) has recently been proposed with recent publications reporting that HFmrEF represents a transitional phase. The aim of this study was to determ

Externí odkaz: https://doaj.org/article/3a6a505c8d844e4294a7b7561f174b98

Transfer learning from simulations on a reference anatomy for ECGI in personalized cardiac resynchronization therapy

Autor: Jessica Webb, Jack Lee, Lauren Fovargue, Sophie Giffard-Roisin, Nicholas Ayache, Reza Razavi, Tom Jackson, Christopher A. Rinaldi, Hervé Delingette, Maxime Sermesant

Publikováno v: Giffard-Roisin, S, Delingette, H, Jackson, T, Webb, J, Fovargue, L, Lee, J, Rinaldi, C A, Razavi, R, Ayache, N & Sermesant, M 2019, ' Transfer learning from simulations on a reference anatomy for ECGI in personalized cardiac resynchronization therapy ', IEEE Transactions on Biomedical Engineering, vol. 66, no. 2, 8362988, pp. 343-353 . https://doi.org/10.1109/TBME.2018.2839713
IEEE Transactions on Biomedical Engineering
IEEE Transactions on Biomedical Engineering, Institute of Electrical and Electronics Engineers, In press, 20, ⟨10.1109/TBME.2018.2839713⟩
IEEE Transactions on Biomedical Engineering, In press, 20, ⟨10.1109/TBME.2018.2839713⟩

International audience; Goal: Non-invasive cardiac electrophysiology (EP) model personalisation has raised interest for instance in the scope of predicting EP cardiac resynchronization therapy (CRT) response. However, the restricted clinical applicab

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::dd56005fc96d8164d060f77d36ba05ad
https://kclpure.kcl.ac.uk/en/publications/184359eb-0187-4104-b8e5-a48d9e26a98f

Non-Invasive Personalisation of a Cardiac Electrophysiology Model from Body Surface Potential Mapping

Autor: Tom Jackson, Reza Razavi, Jack Lee, Sophie Giffard-Roisin, Lauren Fovargue, Hervé Delingette, Maxime Sermesant, Nicholas Ayache

Publikováno v: IEEE Transactions on Biomedical Engineering
IEEE Transactions on Biomedical Engineering, 2017, IEEE Transactions on Biomedical Engineering, 64 (9), pp.2206-2218. ⟨10.1109/TBME.2016.2629849⟩
Giffard-Roisin, S, Jackson, T, Fovargue, L, Lee, J, Delingette, H, Razavi, R, Ayache, N & Sermesant, M 2017, ' Noninvasive Personalization of a Cardiac Electrophysiology Model from Body Surface Potential Mapping ', IEEE Transactions on Biomedical Engineering, vol. 64, no. 9, 7745951, pp. 2206-2218 . https://doi.org/10.1109/TBME.2016.2629849

Selected for the TBME highlights, sept. 2017\url{https://tbme.embs.org/2017/08/24/non-invasive-personalisation-cardiac-electrophysiology-model-body-surface-potential-mapping/}; International audience; Goal: We use non-invasive data (body surface pote

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6f8e3e7d52ec61782775a14212be2d5c
https://hal.inria.fr/hal-01397393/file/TBME_acceptedversion.pdf

Estimation of Purkinje Activation from ECG: an Intermittent Left Bundle Branch Block Study

Autor: Nicholas Ayache, Reza Razavi, Jessica Webb, Jack Lee, Roch Molléro, Hervé Delingette, Maxime Sermesant, Sophie Giffard-Roisin, Lauren Fovargue

Publikováno v: 7th International Statistical Atlases and Computational Modeling of the Heart (STACOM) Workshop, Held in Conjunction with MICCAI 2016
7th International Statistical Atlases and Computational Modeling of the Heart (STACOM) Workshop, Held in Conjunction with MICCAI 2016, Oct 2016, Athens, Greece
Statistical Atlases and Computational Models of the Heart. Imaging and Modelling Challenges ISBN: 9783319527178

In press; International audience; Modelling the cardiac electrophysiology (EP) can help understand pathologies and predict the response to therapies such as cardiac resynchronization. To this end, estimating patient-specific model parameters is cruci

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=doi_dedup___::a1e161818d5be0b0d6a7f6bf36dd1d2b
https://inria.hal.science/hal-01372924