Investigation of the hyperperfusion phenomenon following carotid artery stenting using preoperative computed tomography perfusion imaging

Purpose This study aimed to identify the most effective parameters of computed tomography perfusion imaging (CTP) using the Bayesian estimation to predict hyperperfusion phenomenon (HPP) risk after carotid artery stenting (CAS). Methods We retrospectively analyzed 46 patients who underwent CAS with preoperative CTP and preoperative and postoperative 123 I-labeled N-isopropyl-p-iodoamphetamine ( 123 I-IMP) single photon emission computed tomography (SPECT) at rest, between April 2019 and March 2024. Patients were categorized into the HPP and non-HPP groups based on the postoperative asymmetry index (AI) of cerebral blood flow (CBF) on 123 I-IMP SPECT. Relative ratios of CBF, cerebral blood volume (CBV), mean transit time (MTT), and time-to-peak (TTP) were calculated from preoperative CTP and compared between the two groups. Correlations among each CTP parameter, preoperative AI, and postoperative AI were assessed. Receiver operating characteristic (ROC) analysis identified the most accurate CTP parameters for predicting HPP. Results HPP occurred in four patients, with one developing cerebral hemorrhage. Significant differences were observed between the HPP and non-HPP groups in CBV ( p = 0.001), MTT ( p = 0.003), and TTP ratio ( p = 0.011), and preoperative AI ( p = 0.021). Among the CTP parameters and preoperative AI, the CBV ratio showed a positive correlation with the postoperative AI ( r = 0.63, p < 0.01). The CBV ratio demonstrated the highest area under the curve (AUC) for predicting HPP (AUC = 0.95). However, after Benjamini–Hochberg correction, statistical significance was lost (adjusted p = 0.07). Conclusion This study evaluated the predictive value of preoperative CTP using the Bayesian estimation method for identifying HPP risk after CAS. CBV ratio may serve as a potential parameter for predicting HPP.