Diagnostic value of three-dimensional arterial spin labeling in patients with isolated vertigo due to posterior circulation ischemia
10.3760/cma.j.issn.1673-4165.2025.02.003
- VernacularTitle:三维动脉自旋标记技术评估孤立性眩晕患者的后循环缺血
- Author:
Qian LIU
1
;
Rongchao MA
;
Luna WANG
;
Xuan HE
;
Dujuan SHA
Author Information
1. 徐州医科大学鼓楼临床学院全科医学科，南京 210008
- Keywords:
Vertigo;
Brain ischemia;
Ischemic stroke;
Magnetic resonance imaging;
Spin labels;
Image processing, computer-assisted;
Cerebrovascular circulation
- From:
International Journal of Cerebrovascular Diseases
2025;33(2):93-100
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the predictive value of three-dimensional arterial spin labeling (3D-ASL) for posterior circulation ischemia (PCI) and posterior circulation stroke (PCS) in patients with isolated vertigo.Methods:Patients with isolated vertigo underwent 3D-ASL imaging at Drum Tower Hospital Affiliated to Nanjing University School of Medicine from January 1, 2022 to December 31, 2024 were included retrospectively. According to the imaging findings, the patients with isolated vertigo were divided into PCI group and non-PCI group. The PCI group was further divided into PCS group and non-PCS group. The baseline clinical data and laboratory examination data were collected. Cerebral blood flow (CBF) in different brain regions of the posterior circulation was obtained through 3D-ASL related parameters to evaluate the posterior circulation perfusion, including CBF at two post-labeling delay times (PLD) (1.5 s and 2.5 s), delayed perfusion CBF (ΔCBF), multisequence PLD (Multi-PLD) CBF, and CBF under arterial transit time (ATT). Multivariate logistic regression analysis was used to determine the association of different CBF values with PCI and PCS in patients with isolated vertigo. Receiver operating characteristic (ROC) curve was used to evaluate the predictive value of different CBF values for PCI and PCS. Results:A total of 81 patients with isolated vertigo were included, aged 63.0±12.1 years, 44 were males (54.3%); 58 (71.6%) had PCI and 27 (25.9%) had PCS. Multivariate logistic regression analysis showed that PLD 1.5 s-CBF (odds ratio [ OR] 1.372, 95% confidence interval [ CI] 1.169-1.611; P<0.001), ΔCBF ( OR 1.197, 95% CI 1.072-1.336; P=0.001), and Multi-PLD-CBF ( OR 2.099, 95% CI 1.257-3.504; P=0.005) were the independent predictive factors of PCI. ROC curve analysis showed that the area under the curve for predicting PCI using the above three parameters alone and in combination were 0.962 (95% CI 0.915-1.000), 0.683 (95% CI 0.543-0.823), 0.944 (95% CI 0.985-1.000), and 0.999 (95% CI 0.997-1.000), respectively. Multivariate logistic regression analysis showed that the PLD 1.5 s-CBF ( OR 1.246, 95% CI 1.030-2.089; P=0.002), ΔCBF ( OR 1.153, 95% CI 1.038-1.281; P=0.008), and multi-PLD-CBF ( OR 1.388, 95% CI 1.219-1.689; P=0.001) in cerebellar region were the independent predictors of PCS. ROC curve analysis showed that the area under the curve for predicting PCS using the above three parameters alone and in combination were 0.956 (95% CI 0.911-1.00), 0.802 (95% CI 0.685-0.920), 0.972 (95% CI 0.923-1.000), and 0.977 (95% CI 0.937-1.00), respectively. Conclusion:3D-ASL can predict PCI and PCS early, and combining multiple parameters can improve the predictive ability for PCI and PCS.
