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Background: We hypothesized that computerized morphological analysis of the left atrium (LA) and pulmonary veins (PVs) via fractal measurements of shape and texture features of the LA myocardial wall could predict atrial fibrillation (AF) recurrence after ablation. Methods: Preablation contrast computed tomography 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 postablation 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 (D1 ) of 137 patients; classifiers were subsequently validated on an independent set (D2 ) of 66 patients. Dedicated classifiers to capture the fractal and morphological properties of LA body (CLA ), PVs (CPV ), and LA myocardial (CLAM ) tissue were constructed, as well as a model (CAll ) 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 (Cclin ) was also compared against CAll .Results: Statistically significant differences were observed for fractal features of CLA , CLAM , and CAll in distinguishing AF recurrence (P &lt;0.001) on D1 . Using the 5 top features, CAll had the best prediction performance (area under the receiver operating characteristic curve [AUROC], 0.81 [95% CI, 0.78–0.85]), followed by CPV (AUROC, 0.78 [95% CI, 0.74–0.80]), and CLA (AUROC, 0.70 [95% CI, 0.63–0.78]) on D2 . The clinical parameter model Cclin yielded an AUROC, 0.70 (95% CI, 0.65–0.77), while the atrial volume model yielded an AUROC, 0.59. Combining CAll and Cclin on D2 improved the AUROC to 0.87 (95% CI, 0.82–0.93).Conclusions: Fractal measurements of the LA, PVs, and atrial myocardium on computed tomography scans were associated with likelihood of postablation AF recurrence.

circulation. arrhythmia and electrophysiology

Machine Learning–Derived Fractal Features of Shape and Texture of the Left Atrium and Pulmonary Veins From Cardiac Computed Tomography Scans Are Associated With Risk of Recurrence of Atrial Fibrillation Postablation