NDLI: Three-dimensional quantification of regional left-ventricular dyssynchrony by magnetic resonance imaging

Content Provider	IEEE Xplore Digital Library
Author	Mischi, M. Kaklidou, F. Houthuizen, P. Aben, J. Prinzen, F.W. Bracke, F. van den Bosch, H. Korsten, H.H.M.
Copyright Year	2011
Description	Author affiliation: Catharina Hospital, Eindhoven, the Netherlands (Bracke, F.; van den Bosch, H.; Korsten, H.H.M.) \|\| Pie Medical Imaging, Maastricht, the Netherlands (Aben, J.) \|\| Department of Electrical Engineering, Eindhoven University of Technology, Eindhoven, the Netherlands (Mischi, M.; Kaklidou, F.) \|\| Department of Physiology, Maastricht University, Maastricht, the Netherlands (Houthuizen, P.; Prinzen, F.W.)
Abstract	Heart failure accounts for over five million patients in the United States alone. Many of them present dyssynchronous left ventricular (LV) contraction, whose treatment by cardiac resynchronization therapy (CRT) is until now guided by electrocardiographic analysis. One third of the selected patients, however, does not respond to the therapy. Aiming at improving the response rate, recent studies showed the importance of left bundle branch block (LBBB) configurations. Therefore, in order to detect motion patterns that relate to LBBB, this paper presents a novel method for three-dimensional quantification of regional LV mechanical dyssynchrony. LV wall-motion analysis is performed on magnetic resonance imaging (MRI) cines segmented by commercial software. Mutual delays between endocardial wall motion in different LV regions are estimated by cross correlation followed by phase difference analysis in frequency domain, achieving unlimited time resolution. Rather than focusing on the systolic phase, the full cardiac cycle is used to estimate the contraction timing. The method was successfully validated against MRI tagging in five dogs before and after LBBB induction. Preliminary validation in humans with 10 LBBB patients and 7 healthy subjects showed the method feasibility and reproducibility, with sensitivity and specificity in LBBB detection equal to 95.1% and 99.4%, respectively.
Starting Page	2646
Ending Page	2649
File Size	1102373
Page Count	4
File Format	PDF
ISBN	9781424441211
ISSN	1557170X
e-ISBN	9781457715891
e-ISBN	9781424441228
DOI	10.1109/IEMBS.2011.6090728
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-08-30
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Delay Tagging Heart Dogs Medical treatment
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

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