OBJECTIVE: Cardiac mapping is an important diagnostic step in cardiac electrophysiology. One of its purposes is to generate a map of the depolarization sequence. This map is constructed in clinical routine either by directly analyzing cardiac electrograms (EGMs) recorded invasively or an estimate of these EGMs obtained by a noninvasive technique. Activation maps based on noninvasively estimated EGMs often show artefactual jumps in activation times. To overcome this problem, we present a new method to construct the activation maps from reconstructed unipolar EGMs. METHODS: On top of the standard estimation of local activation time from unipolar intrinsic deflections, we propose to mutually compare the EGMs in order to estimate the delays in activation for neighboring recording locations. We then describe a workflow to construct a spatially coherent activation map from local activation times and delay estimates in order to create more accurate maps. The method is optimized using simulated data and evaluated on clinical data from 12 different activation sequences. RESULTS: We found that the standard methodology created lines of artificially strong activation time gradient. The proposed workflow enhanced these maps significantly. CONCLUSION: Estimating delays between neighbors is an interesting option for activation map computation in electrocardiographic imaging.
OBJECTIVE: Cardiac mapping is an important diagnostic step in cardiac electrophysiology. One of its purposes is to generate a map of the depolarization sequence. This map is constructed in clinical routine either by directly analyzing cardiac electrograms (EGMs) recorded invasively or an estimate of these EGMs obtained by a noninvasive technique. Activation maps based on noninvasively estimated EGMs often show artefactual jumps in activation times. To overcome this problem, we present a new method to construct the activation maps from reconstructed unipolar EGMs. METHODS: On top of the standard estimation of local activation time from unipolar intrinsic deflections, we propose to mutually compare the EGMs in order to estimate the delays in activation for neighboring recording locations. We then describe a workflow to construct a spatially coherent activation map from local activation times and delay estimates in order to create more accurate maps. The method is optimized using simulated data and evaluated on clinical data from 12 different activation sequences. RESULTS: We found that the standard methodology created lines of artificially strong activation time gradient. The proposed workflow enhanced these maps significantly. CONCLUSION: Estimating delays between neighbors is an interesting option for activation map computation in electrocardiographic imaging.
Authors: Matthew R Schill; Phillip S Cuculich; Christopher M Andrews; Ramya Vijayakumar; Chawannuch Ruaengsri; Matthew C Henn; Timothy S Lancaster; Spencer J Melby; Richard B Schuessler; Yoram Rudy; Ralph J Damiano Journal: J Atr Fibrillation Date: 2020-08-31
Authors: Matthijs Cluitmans; Dana H Brooks; Rob MacLeod; Olaf Dössel; María S Guillem; Peter M van Dam; Jana Svehlikova; Bin He; John Sapp; Linwei Wang; Laura Bear Journal: Front Physiol Date: 2018-09-20 Impact factor: 4.566
Authors: Laura R Bear; Richard D Walton; Emma Abell; Yves Coudière; Michel Haissaguerre; Olivier Bernus; Rémi Dubois Journal: Front Physiol Date: 2019-02-26 Impact factor: 4.566
Authors: Pavel Jurak; Laura R Bear; Uyên Châu Nguyên; Ivo Viscor; Petr Andrla; Filip Plesinger; Josef Halamek; Vlastimil Vondra; Emma Abell; Matthijs J M Cluitmans; Rémi Dubois; Karol Curila; Pavel Leinveber; Frits W Prinzen Journal: Sci Rep Date: 2021-06-01 Impact factor: 4.379
Authors: Simone Pezzuto; Frits W Prinzen; Mark Potse; Francesco Maffessanti; François Regoli; Maria Luce Caputo; Giulio Conte; Rolf Krause; Angelo Auricchio Journal: Europace Date: 2021-04-06 Impact factor: 5.214