Background: Hemodynamic factors play a crucial role in the recurrence of intracranial aneurysms after coiling. However, the strongest factor for predicting recurrence remains unclear because each risk factor has been investigated and reported separately.
Objective: To clarify the strongest predictor of recurrence with computational fluid dynamics (CFD).
Methods: Using pretreatment patient-specific 3-dimensional rotational angiography data of 50 internal carotid artery (ICA) aneurysms (7 recanalized, 43 stable) treated with endovascular coiling, we created a precoiling model and a virtual postcoiling model produced by manually cutting the aneurysm by the flat plane corresponding to the virtual coil surface. We conducted CFD analysis to investigate inflow dynamics in the precoiling model and pressure difference and wall shear stress on the virtual coil surface. The pressure difference was calculated by subtracting average pressure at the proximal ICA from the maximum pressure at the coil surface and dividing by dynamic pressure at the proximal ICA for normalization. We compared hemodynamic parameters in both models between recanalized and stable aneurysms.
Results: Compared with stable aneurysms, recanalized aneurysms showed a significantly larger inflow area and higher inflow rate in the precoiling model (P = .016, .028), and higher pressure difference at the coil surface in the postcoiling model (P < .001). The receiver-operating characteristic analysis showed that the area under the curve value for the pressure difference (0.967) was superior to that of other evaluated parameters.
Conclusion: The pressure difference in the virtual postcoiling model may be a strong predictor of recurrence after coiling.
Keywords: Cerebral aneurysm; Coil embolization; Computational fluid dynamics; Inflow rate ratio; Pressure difference; Recurrence after coil embolization.
Copyright © 2018 by the Congress of Neurological Surgeons.