Key result
Fully automatic segmentation of the left atrium using both MRA and LGE-MRI yielded a surface-to-surface distance of 1.49 mm compared to manual segmentation, outperforming LGE alone (1.80 mm, P<0.05).
Why the study?
Does a fully automatic segmentation method accurately segment the left atrium and pulmonary veins from LGE-MRI compared to manual segmentation in patients with atrial fibrillation?
Observational (n=46)
Does a fully automatic segmentation method accurately segment the left atrium and pulmonary veins from LGE-MRI compared to manual segmentation in patients with atrial fibrillation?
A fully automatic segmentation method for the left atrium and pulmonary veins from LGE-MRI performs comparably to human observers, potentially enabling objective atrial scar assessment for AF patients.
Answers are grounded in this paper and cite their sources.
May support automated LA segmentation for AF scar analysis; leaves open outcome-based validation before clinical use.
PURPOSE: To realize objective atrial scar assessment, this study aimed to develop a fully automatic method to segment the left atrium (LA) and pulmonary veins (PV) from late gadolinium-enhanced (LGE) magnetic resonance imaging (MRI). The extent and distribution of atrial scar, visualized by LGE-MRI, provides important information for clinical treatment of atrial fibrillation (AF) patients. MATERIALS AND METHODS: Forty-six AF patients (age 62 ± 8, 14 female) who underwent cardiac MRI prior to RF ablation were included. A contrast-enhanced MR angiography (MRA) sequence was acquired for anatomy assessment followed by an LGE sequence for LA scar assessment. A fully automatic segmentation method was proposed consisting of two stages: 1) global segmentation by multiatlas registration; and 2) local refinement by 3D level-set. These automatic segmentation results were compared with manual segmentation. RESULTS: The LA and PVs were automatically segmented in all subjects. Compared with manual segmentation, the method yielded a surface-to-surface distance of 1.49 ± 0.65 mm in the LA region when using both MRA and LGE, and 1.80 ± 0.93 mm when using LGE alone (P < 0.05). In the PV regions, the distance was 2.13 ± 0.67 mm and 2.46 ± 1.81 mm (P < 0.05), respectively. The difference between automatic and manual segmentation was comparable to the interobserver difference (P = 0.8 in LA region and P = 0.7 in PV region). CONCLUSION: We developed a fully automatic method for LA and PV segmentation from LGE-MRI, with comparable performance to a human observer. Inclusion of an MRA sequence further improves the segmentation accuracy. The method leads to automatic generation of a patient-specific model, and potentially enables objective atrial scar assessment for AF patients. J. Magn. Reson. Imaging 2016;44:346-354.
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Tao et al. (2016) conducted an observational in Atrial fibrillation (n=46). Fully automatic segmentation using both MRA and LGE vs. Fully automatic segmentation using LGE alone was evaluated on Surface-to-surface distance in the left atrium region compared with manual segmentation (mm) (p=<0.05). Fully automatic segmentation of the left atrium using both MRA and LGE-MRI yielded a surface-to-surface distance of 1.49 mm compared to manual segmentation, outperforming LGE alone (1.80 mm, P<0.05).
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