title: Fully automatic segmentation of left atrium and pulmonary veins in late gadolinium-enhanced MRI: Towards objective atrial scar assessment.
abstract: 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.
  
  
  
  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.
  
  
  
  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).
  
  
  
  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.
authors.affiliation: LKEB, Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Qian
authors.initials: Q
authors.lastname: Tao
authors.affiliation: Department of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
authors.forename: Esra Gucuk
authors.initials: EG
authors.lastname: Ipek
authors.affiliation: LKEB, Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Rahil
authors.initials: R
authors.lastname: Shahzad
authors.affiliation: LKEB, Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Floris F
authors.initials: FF
authors.lastname: Berendsen
authors.affiliation: Department of Cardiology, Johns Hopkins University School of Medicine, Baltimore, Maryland, USA.
authors.forename: Saman
authors.initials: S
authors.lastname: Nazarian
authors.affiliation: LKEB, Division of Image Processing, Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands.
authors.forename: Rob J
authors.initials: RJ
authors.lastname: van der Geest
mesh_terms: D000465:Algorithms; D001281:Atrial Fibrillation / Q000000981:diagnostic imaging* / Q000209:etiology; D002921:Cicatrix / Q000150:complications / Q000000981:diagnostic imaging*; D003287:Contrast Media / Q000008:administration & dosage; D019786:Gadolinium DTPA / Q000008:administration & dosage*; D006325:Heart Atria / Q000000981:diagnostic imaging*; D006801:Humans; D007089:Image Enhancement; D007090:Image Interpretation, Computer-Assisted; D021621:Imaging, Three-Dimensional; D018810:Magnetic Resonance Angiography / Q000379:methods*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011667:Pulmonary Veins / Q000000981:diagnostic imaging*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity
chemical_list: D003287:Contrast Media; D019786:Gadolinium DTPA
keywords: LGE-MRI; MRA; automatic segmentation; left atrium; pulmonary veins