Algorithms for left atrial wall segmentation and thickness – Evaluation on an open-source CT and MRI image database

• Published in: Medical image analysis Vol. 50; pp. 36 - 53
• Main Authors: Karim, Rashed, Blake, Lauren-Emma, Inoue, Jiro, Tao, Qian, Jia, Shuman, Housden, R. James, Bhagirath, Pranav, Duval, Jean-Luc, Varela, Marta, Behar, Jonathan M., Cadour, Loïc, van der Geest, Rob J., Cochet, Hubert, Drangova, Maria, Sermesant, Maxime, Razavi, Reza, Aslanidi, Oleg, Rajani, Ronak, Rhode, Kawal
• Format: Journal Article
• Language: English
• Published: Netherlands Elsevier B.V 01.12.2018; Elsevier BV; Elsevier
• Subjects: Accuracy; Algorithms; Artificial Intelligence; Atrial Fibrillation; Atrium; Benchmarks; Biostatistics; Cardiac arrhythmia; Change detection; Computed tomography; Computer Science; Databases, Factual; Evaluation; Fibrillation; Heart Atria - anatomy & histology; Humans; Image processing; Image resolution; Image segmentation; Left atrial wall thickness; Left atrium; Magnetic Resonance Imaging; Medical Imaging; Modeling and Simulation; Myocardium; NMR; Nuclear magnetic resonance; Observer Variation; State of the art; Tomography; Tomography, X-Ray Computed; Wall thickness; Myocardium; Left atrial wall thickness; Left atrium; Atrial fibrillation
• ISSN: 1361-8415; 1361-8423; 1361-8423
• DOI: 10.1016/j.media.2018.08.004

•An open-source atrial wall thickness CT and MRI dataset (n=20) with consensus ground truth obtained with statistical estimation from expert delineation (n=2).•Exploring a range of metrics for evaluating and ranking wall segmentation and thickness algorithms (n=6), and benchmarks were set on each metric.•New three-dimensional mean thickness atlases for atrial wall thickness derived from the consensus ground truth. The atlas was also transformed into a two-dimensional flat map of thickness. [Display omitted] Structural changes to the wall of the left atrium are known to occur with conditions that predispose to Atrial fibrillation. Imaging studies have demonstrated that these changes may be detected non-invasively. An important indicator of this structural change is the wall’s thickness. Present studies have commonly measured the wall thickness at few discrete locations. Dense measurements with computer algorithms may be possible on cardiac scans of Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). The task is challenging as the atrial wall is a thin tissue and the imaging resolution is a limiting factor. It is unclear how accurate algorithms may get and how they compare in this new emerging area. We approached this problem of comparability with the Segmentation of Left Atrial Wall for Thickness (SLAWT) challenge organised in conjunction with MICCAI 2016 conference. This manuscript presents the algorithms that had participated and evaluation strategies for comparing them on the challenge image database that is now open-source. The image database consisted of cardiac CT (n=10) and MRI (n=10) of healthy and diseased subjects. A total of 6 algorithms were evaluated with different metrics, with 3 algorithms in each modality. Segmentation of the wall with algorithms was found to be feasible in both modalities. There was generally a lack of accuracy in the algorithms and inter-rater differences showed that algorithms could do better. Benchmarks were determined and algorithms were ranked to allow future algorithms to be ranked alongside the state-of-the-art techniques presented in this work. A mean atlas was also constructed from both modalities to illustrate the variation in thickness within this small cohort.