Abstract
BACKGROUND: This multicenter study aimed to develop and validate a hemodynamics-based nomogram for predicting incomplete occlusion (ICO) of intracranial aneurysms (IAs) after pipeline embolization device (PED) treatment. METHODS: 426 IAs from 362 patients were analyzed and divided into a training set (n = 298) and a validation set (n = 128). Morphological and hemodynamic parameters of the IAs were calculated using AneuFlow Pro. Independent predictors of ICO were identified using least absolute shrinkage and selection operator (LASSO) regression and logistic regression to develop a predictive nomogram. The nomogram's performance was evaluated using area under the curve (AUC), calibration curves, and decision curve analysis (DCA). RESULTS: The aneurysm occlusion rate of the overall cohort was 79.8% with a median angiographic follow-up time of 199 days. No significant differences were observed in patient and aneurysm characteristics between the training and validation sets. Through LASSO and logistic regression analyses, we identified smoking (OR = 0.32, 95% CI 0.14-0.68, p = 0.005), flow complexity (OR = 3.03, 95% CI 1.58-5.89, p < 0.001), device migration (OR = 11.03, 95% CI 1.51-105.55, p = 0.021), poor wall apposition (OR = 3.21, 95% CI 1.37-7.53, p = 0.007), aneurysm angle (OR = 3.46, 95% CI 1.79-6.93, p < 0.001), and low wall shear stress area ratio (LSAR; OR = 2.78, 95% CI 1.46-5.50, p = 0.002) as independent predictors of ICO. A nomogram developed based on these factors showed an AUC of 0.785 (95% CI 0.719-0.850) in the training set and 0.809 (95% CI 0.695-0.923) in the validation set, demonstrating consistent calibration and excellent clinical use. CONCLUSION: The hemodynamics-based nomogram developed in this study effectively predicted ICO of IAs after PED treatment.