Automatic Segmentation of Left Atrial Scar from Delayed-Enhancement Magnetic Resonance Imaging

Karim, Rashed; Arujuna, Aruna; Brazier, Alex; Gill, Jaswinder; Rinaldi, Christopher Aldo; O’Neill, Mark; Razavi, Reza; Schaeffter, Tobias; Rueckert, Daniel; Rhode, Kawal

doi:10.1007/978-3-642-21028-0_8

Cited by 9 publications

(6 citation statements)

References 9 publications

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“…A background of the techniques used in this work is described above in Sections 'Algorithm 3: Sunnybrook - Graph-cuts with fuzzy c-means clustering (SY)’ (Graph-cuts) and 'Algorithm 4: Harvard/Boston University - Active contours and mixture model fitting (HB)’ (EM-algorithm). More details can be found in [ 28 ].…”

Section: Methodsmentioning

confidence: 99%

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

Karim

Housden

Balasubramaniam

et al. 2013

Journal of Cardiovascular Magnetic Resonance

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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.

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Section: Methodsmentioning

confidence: 99%

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

Karim

Housden

Balasubramaniam

et al. 2013

Journal of Cardiovascular Magnetic Resonance

Self Cite

156

165

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“…Knowles et al (2010) and Tao et al (2016a) performed at ±3 mm and ±2 mm along each normal vector of the LA surface respectively, to consider the potential errors of LA segmentation. Karim et al (2011) proposed a probabilistic tissue intensity model which was formulated as Markov random field and solved using graph-cuts. In their following work (Karim et al, 2014), they presented a scar quantification method by combining the scar intensity model priors and Gaussian mixture model (GMM).…”

Section: La Scar Segmentation and Quantificationmentioning

confidence: 99%

Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review

Li¹,

Zimmer²,

Schnabel³

et al. 2021

Preprint

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Late gadolinium enhancement magnetic resonance imaging (LGE MRI) is commonly used to visualize and quantify left atrial (LA) scars. The position and extent of scars provide important information of the pathophysiology and progression of atrial fibrillation (AF). Hence, LA scar segmentation and quantification from LGE MRI can be useful in computerassisted diagnosis and treatment stratification of AF patients. Since manual delineation can be time-consuming and subject to intra-and inter-expert variability, automating this computing is highly desired, which nevertheless is still challenging and under-researched.This paper aims to provide a systematic review on computing methods for LA cavity, wall, scar and ablation gap segmentation and quantification from LGE MRI, and the related literature for AF studies. Specifically, we first summarize AF-related imaging techniques, particularly LGE MRI. Then, we review the methodologies of the four computing tasks in detail, and summarize the validation strategies applied in each task. Finally, the possible future developments are outlined, with a brief survey on the potential clinical applications of the aforementioned methods. The review shows that the research into this topic is still in early stages. Although several methods have been proposed, especially for LA segmentation, there is still large scope for further algorithmic developments due to performance issues related to the high variability of enhancement appearance and differences in image acquisition.

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“…Так, размер вокселя в новых МР-импульсных последовательностях был не более 1,3×1,3×5 мм. Кроме того, на полученных МР-изображениях каждый воксель автоматически разделяется пополам до размера около 0,6×0,6×5 мм [30]. Третьим достижением, реализованным в усовершенствованных МР-последовательностях, является возможность коррекции артефактов движения предсердий в сердечном и дыхательном циклах, а также артефактов тока крови в легочных венах.…”

Section: обзоры §unclassified

Cardiac magnetic resonance imaging with contrast enhancement in treatment of atrial fibrillation

et al. 2020

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Catheter ablation is presently the main method for interventional treatment of atrial fibrillation (AF). Despite improvements of the method and accumulation of personnel’s experience, incidence of recurrent AF following catheter interventions remains high. This review addresses a possibility of using contrast-enhanced cardiac magnetic resonance imaging to increase the effectiveness of interventional treatment of arrhythmia.

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Automatic Segmentation of Left Atrial Scar from Delayed-Enhancement Magnetic Resonance Imaging

Cited by 9 publications

References 9 publications

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

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

Medical Image Analysis on Left Atrial LGE MRI for Atrial Fibrillation Studies: A Review

Cardiac magnetic resonance imaging with contrast enhancement in treatment of atrial fibrillation

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