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Mapping Cortical Dynamics Using Simultaneous MEG/EEG and Anatomically-constrained Minimum-norm Estimates: an Auditory Attention Example
Published on: October 24, 2012
Accessory pathway localization with probabilistic density maps generated by a mobile application: Assessment of a
Marek Jastrzębski1, Kamil Fijorek2, Piotr Futyma3
1First Department of Cardiology, Interventional Electrocardiology and Hypertension, Medical College, Jagiellonian University, Kraków, Poland.
Introduction:
Precise electrocardiographic localization of accessory pathways (AP) can be challenging. Seminal AP localization studies were limited by complexity of algorithms and sample size. We aimed to create a nonalgorithmic method for AP localization based on color-coded maps of AP distribution generated by a web-based application.
Methods:
APs were categorized into 19 regions/types based on invasive electrophysiologic mapping. Preexcited QRS complexes were categorized into 6 types based on polarity and notch/slur. For each QRS type in each lead the distribution of APs was visualized on a gradient map. The principle of common set was used to combine the single lead maps to create the distribution map for AP with any combination of QRS types in several leads. For the validation phase, a separate cohort of APs was obtained.
Results:
A total of 800 patients with overt APs were studied. The application used the exploratory data set of 553 consecutive APs and the corresponding QRS complexes to generate AP localization maps for any possible combination of QRS types in 12 leads. Optimized approach (on average 3 steps) for evaluation of preexcited electrcardiogram was developed. The area of maximum probability of AP localization was pinpointed by providing the QRS type for the subsequent leads. The exploratory data set was validated with the separate cohort of APs (n = 256); p = .23 for difference in AP distribution.
Conclusions:
In the largest data set of APs to-date, a novel probabilistic and semi-automatic approach to electrocardiographic localization of APs was highly predictive for anatomic localization.
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