Evaluation of current algorithms for segmentation of scar tissue from late Gadolinium enhancement cardiovascular magnetic resonance of the left atrium: an open-access grand challenge

Journal of Cardiovascular Magnetic Resonance

Research

Wenzhe Shi¹  Wenjia Bai¹  Daniel Rueckert¹  R James Housden²  Rashed Karim²  Zhong Chen²  Ebrahim Palkhi²  Reza Razavi²  Tobias Schaeffter²  Yosra Al-Beyatti²  Mayuragoban Balasubramaniam²  Ayesha Uddin²  Kawal Rhode²  Samantha Obom²  Prince Acheampong²  Heinz-Otto Peitgen³  Anja Hennemuth³  Perry Radau⁴  YingLi Lu⁴  Dana Peters⁵  Yi Gao⁶  Allen Tannenbaum⁷  Rob MacLeod⁸  Daniel Perry⁸  Josh Cates⁸ 

[1] Department of Computing, Imperial College London, London, UK;Department of Imaging Sciences & Biomedical Engineering, King’s College London, London, UK;Fraunhofer Institute for Medical Image Computing, Fraunhofer MEVIS, Bremen, Germany;Imaging Research, Sunnybrook Health Sciences Centre, Toronto, Canada;Magnetic Resonance Research Centre, Yale School of Medicine, Yale University, New Haven, USA;Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, USA;Psychiatry Neuroimaging Lab, Harvard Medical School, Boston, USA;School of Electrical and Computer Engineering, Boston University, Boston, USA;Utah Center for Advanced Imaging Research, University of Utah, Salt Lake City, Utah, USA;

关键词: Late gadolinium enhancement;    Cardiovascular magnetic resonance;    Atrial fibrillation;    Segmentation;    Algorithm benchmarking;   

DOI  :  10.1186/1532-429X-15-105

 received in 2013-08-12, accepted in 2013-12-10,  发布年份 2013

来源: Springer

【 摘 要 】

BackgroundLate Gadolinium enhancement (LGE) cardiovascular magnetic resonance (CMR) imaging can be used to visualise regions of fibrosis and scarring in the left atrium (LA) myocardium. This can be important for treatment stratification of patients with atrial fibrillation (AF) and for assessment of treatment after radio frequency catheter ablation (RFCA). In this paper we present a standardised evaluation benchmarking framework for algorithms segmenting fibrosis and scar from LGE CMR images. The algorithms reported are the response to an open challenge that was put to the medical imaging community through an ISBI (IEEE International Symposium on Biomedical Imaging) workshop.MethodsThe image database consisted of 60 multicenter, multivendor LGE CMR image datasets from patients with AF, with 30 images taken before and 30 after RFCA for the treatment of AF. A reference standard for scar and fibrosis was established by merging manual segmentations from three observers. Furthermore, scar was also quantified using 2, 3 and 4 standard deviations (SD) and full-width-at-half-maximum (FWHM) methods. Seven institutions responded to the challenge: Imperial College (IC), Mevis Fraunhofer (MV), Sunnybrook Health Sciences (SY), Harvard/Boston University (HB), Yale School of Medicine (YL), King’s College London (KCL) and Utah CARMA (UTA, UTB). There were 8 different algorithms evaluated in this study.ResultsSome algorithms were able to perform significantly better than SD and FWHM methods in both pre- and post-ablation imaging. Segmentation in pre-ablation images was challenging and good correlation with the reference standard was found in post-ablation images. Overlap scores (out of 100) with the reference standard were as follows: Pre: IC = 37, MV = 22, SY = 17, YL = 48, KCL = 30, UTA = 42, UTB = 45; Post: IC = 76, MV = 85, SY = 73, HB = 76, YL = 84, KCL = 78, UTA = 78, UTB = 72.ConclusionsThe study concludes that currently no algorithm is deemed clearly better than others. There is scope for further algorithmic developments in LA fibrosis and scar quantification from LGE CMR images. Benchmarking of future scar segmentation algorithms is thus important. The proposed benchmarking framework is made available as open-source and new participants can evaluate their algorithms via a web-based interface.

【 授权许可】

CC BY   
© Karim et al.; licensee BioMed Central Ltd. 2013