Literature DB >> 24239989

A novel skeleton based quantification and 3-D volumetric visualization of left atrium fibrosis using late gadolinium enhancement magnetic resonance imaging.

Daniele Ravanelli, Elena Costanza dal Piaz, Maurizio Centonze, Giulia Casagranda, Massimiliano Marini, Maurizio Del Greco, Rashed Karim, Kawal Rhode, Aldo Valentini.   

Abstract

This work presents the results of a new tool for 3-D segmentation, quantification and visualization of cardiac left atrium fibrosis, based on late gadolinium enhancement magnetic resonance imaging (LGE-MRI), for stratifying patients with atrial fibrillation (AF) that are candidates for radio-frequency catheter ablation. In this study 10 consecutive patients suffering AF with different grades of atrial fibrosis were considered. LGE-MRI and magnetic resonance angiography (MRA) images were used to detect and quantify fibrosis of the left atrium using a threshold and 2-D skeleton based approach. Quantification and 3-D volumetric views of atrial fibrosis were compared with quantification and 3-D bipolar voltage maps measured with an electro-anatomical mapping (EAM) system, the clinical reference standard technique for atrial substrate characterization. Segmentation and quantification of fibrosis areas proved to be clinically reliable among all different fibrosis stages. The proposed tool obtains discrepancies in fibrosis quantification less than 4% from EAM results and yields accurate 3-D volumetric views of fibrosis of left atrium. The novel 3-D visualization and quantification tool based on LGE-MRI allows detection of cardiac left atrium fibrosis areas. This noninvasive method provides a clinical alternative to EAM systems for quantification and localization of atrial fibrosis.

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Year:  2013        PMID: 24239989     DOI: 10.1109/TMI.2013.2290324

Source DB:  PubMed          Journal:  IEEE Trans Med Imaging        ISSN: 0278-0062            Impact factor:   10.048


  8 in total

1.  Fully Automatic Left Atrium Segmentation From Late Gadolinium Enhanced Magnetic Resonance Imaging Using a Dual Fully Convolutional Neural Network.

Authors:  Zhaohan Xiong; Vadim V Fedorov; Xiaohang Fu; Elizabeth Cheng; Rob Macleod; Jichao Zhao
Journal:  IEEE Trans Med Imaging       Date:  2019-02       Impact factor: 10.048

2.  A Method to Standardize Quantification of Left Atrial Scar From Delayed-Enhancement MR Images.

Authors:  Rashed Karim; Aruna Arujuna; Richard James Housden; Jaspal Gill; Hannah Cliffe; Kavir Matharu; Jaswinder Gill; Christopher Aldo Rindaldi; Mark O'Neill; Daniel Rueckert; Reza Razavi; Tobias Schaeffter; Kawal Rhode
Journal:  IEEE J Transl Eng Health Med       Date:  2014-03-18       Impact factor: 3.316

Review 3.  How to detect atrial fibrosis.

Authors:  Juan Lacalzada-Almeida; Javier García-Niebla
Journal:  J Geriatr Cardiol       Date:  2017-03       Impact factor: 3.327

4.  Extensive atrial fibrosis in a patient with systemic lupus erythematosus and atrial fibrillation.

Authors:  Elena Costanza Dal Piaz; Giulia Casagranda; Daniele Ravanelli; Massimiliano Marini; Aldo Valentini; Maurizio Del Greco
Journal:  HeartRhythm Case Rep       Date:  2015-03-11

5.  Simultaneous left atrium anatomy and scar segmentations via deep learning in multiview information with attention.

Authors:  Guang Yang; Jun Chen; Zhifan Gao; Shuo Li; Hao Ni; Elsa Angelini; Tom Wong; Raad Mohiaddin; Eva Nyktari; Ricardo Wage; Lei Xu; Yanping Zhang; Xiuquan Du; Heye Zhang; David Firmin; Jennifer Keegan
Journal:  Future Gener Comput Syst       Date:  2020-06       Impact factor: 7.187

6.  Atrial scar quantification via multi-scale CNN in the graph-cuts framework.

Authors:  Lei Li; Fuping Wu; Guang Yang; Lingchao Xu; Tom Wong; Raad Mohiaddin; David Firmin; Jennifer Keegan; Xiahai Zhuang
Journal:  Med Image Anal       Date:  2019-11-16       Impact factor: 8.545

7.  Rapid automatic segmentation of abnormal tissue in late gadolinium enhancement cardiovascular magnetic resonance images for improved management of long-standing persistent atrial fibrillation.

Authors:  Archontis Giannakidis; Eva Nyktari; Jennifer Keegan; Iain Pierce; Irina Suman Horduna; Shouvik Haldar; Dudley J Pennell; Raad Mohiaddin; Tom Wong; David N Firmin
Journal:  Biomed Eng Online       Date:  2015-10-07       Impact factor: 2.819

8.  Fully automatic segmentation and objective assessment of atrial scars for long-standing persistent atrial fibrillation patients using late gadolinium-enhanced MRI.

Authors:  Guang Yang; Xiahai Zhuang; Habib Khan; Shouvik Haldar; Eva Nyktari; Lei Li; Ricardo Wage; Xujiong Ye; Greg Slabaugh; Raad Mohiaddin; Tom Wong; Jennifer Keegan; David Firmin
Journal:  Med Phys       Date:  2018-03-15       Impact factor: 4.071

  8 in total

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