Background - We hypothesized that computerized morphologic analysis of the LA and pulmonary veins (PVs) via fractal measurements of shape and texture features of the LA myocardial wall could predict AF recurrence after ablation. Methods - Pre-ablation contrast CT scans were collected for 203 patients who underwent AF ablation. The LA body, PVs, and myocardial wall were segmented using a semi-automated region growing method. Twenty-eight fractal-based shape and texture-based features were extracted from resulting segments. The top features most associated with post-ablation recurrence were identified using feature selection and subsequently evaluated with a Random Forest classifier. Feature selection and classifier construction were performed on a discovery cohort (D 1 ) of 137 patients; classifiers were subsequently validated on an independent set (D 2 ) of 66 patients. Dedicated classifiers to capture the fractal and morphologic properties of LA body (C LA ), PVs (C PV ), and LA myocardial (C LAM ) tissue were constructed, as well as a model (C All ) capturing properties of all segmented compartments. Fractal-based models were also compared against a model employing machine estimation of LA volume. To assess the effect of clinical parameters, such as AF type and catheter technique, a clinical model (C clin ) was also compared against C All . Results - Statistically significant differences were observed for fractal features of C LA , C LAM and C All in distinguishing AF recurrence (p<0.001) on D 1 . Using the five top features, C All had the best prediction performance (AUC=0.81 [95% Confidence Interval (CI): 0.78-0.85]), followed by C PV (AUC=0.78 [95% CI: 0.74-0.80]) and C LA (AUC=0.70 [95% CI: 0.63-0.78]) on D 2 . The clinical parameter model C clin yielded an AUC=0.70 [95% CI: 0.65-0.77], while the atrial volume model yielded an AUC=0.59. Combining C All and C clin on D 2 improved the AUC to 0.87 [95% CI: 0.82-0.93]. Conclusions - Fractal measurements of the LA, PVs, and atrial myocardium on CT scans were associated with likelihood of post-ablation AF recurrence.
Objective: To identify radiomic and clinical features associated with post-ablation recurrence of AF, given that cardiac morphologic changes are associated with persistent atrial fibrillation (AF), and initiating triggers of AF often arise from the pulmonary veins which are targeted in ablation. Methods: Subjects with pre-ablation contrast CT scans prior to first-time catheter ablation for AF between 2014–2016 were retrospectively identified. A training dataset (D 1 ) was constructed from left atrial and pulmonary vein morphometric features extracted from equal numbers of consecutively included subjects with and without AF recurrence determined at 1 year. The top-performing combination of feature selection and classifier methods based on C-statistic was evaluated on a validation dataset (D 2 ), composed of subjects retrospectively identified between 2005–2010. Clinical models ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\text{M}_{\mathrm {C}}$ \end{document} ) were similarly evaluated and compared to radiomic ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\text{M}_{\mathrm {R}}$ \end{document} ) and radiomic-clinical models ( \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$\text{M}_{\mathrm {RC}}$ \end{document} ), each independently validated on D 2 . Results: Of 150 subjects in D 1 , 108 received radiofrequency ablation and 42 received cryoballoon. Radiomic features of recurrence included greater right carina angle, reduced anterior-posterior atrial diameter, greater atrial volume normalized to height, and steeper right inferior pulmonary vein angle. Clinical features predicting recurrence included older age, greater BMI, hypertension, and warfarin use; apixaban use was associated with reduced recurrence. AF recurrence was predicted with radio-frequency ablation models on D 2 subjects with C-statistics of 0.68, 0.63, and 0.70 for radiomic, clinical, and combined feature models, though these were not prognostic in patients treated with cryoballoon. Conclusions: Pulmonary vein morphology associated with increased likelihood of AF recurrence within 1 year of catheter ablation was identified on cardiac CT. Significance: Radiomic and clinical features-based predictive ...
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