Preliminary application of CT perfusion source images for evaluating regional collateral circulation in unilateral Moyamoya disease.

Abstract

BACKGROUND:

Collateral flow is associated with clinical outcomes for patients with Moyamoya disease and served as a parameter for patient selection of therapeutic strategies. Therefore, we explored whether a noninvasive imaging modality, computed tomography perfusion (CTP) source images (CTP-Sis), could be used to identify the presence and intensity of collateral flow using digital subtraction angiography (DSA) as a gold standard for collateral flow.

METHODS:

CTP-Sis and DSA were performed for 24 patients with unilateral Moyamoya disease. A collateral grading system was developed based on arterial and venous phase CTP-Sis, imitating the DSA score system. Two neuroradiologists scored the DSA images using a collateral grading scale for the regions of interest corresponding to the Alberta Stroke Program Early computed tomography Score (ASPECTS) methodology. Another two neuroradiologists scored CTP-Sis in a similar manner. Agreement between the CTP-Sis and DSA consensus scores was determined, including kappa statistics.

RESULTS:

The agreement between the CTP-Sis and DSA consensus readings was moderate to strong, with a weighted kappa value of 0.768 [95% confidence interval (CI), 0.703-0.832], but there was a better agreement for readers of CTP-Sis, as compared with those of DSA. The sensitivity and specificity for identifying collaterals with CTP-Sis were 0.714 (95% CI, 0.578-0.851) and 0.995 (95% CI, 0.985-1.000), respectively.

CONCLUSIONS:

CTP-Sis could help identify in a noninvasive manner the presence and intensity of collateral flow in patients with unilateral Moyamoya disease using DSA as a gold standard. Further study with a large number of cases is warranted. Further application of this method to other cerebrovascular diseases including acute ischemic stroke can also be warranted.

• Authors: Jing Xue, Yujing Peng, Yanan Zhang, Weiqi Chen, Yuesong Pan, Yu Qi, Lina Hao, Weibin Gu, Ning Wang, Peiyi Gao
• Journal: Quantitative imaging in medicine and surgery (Quant Imaging Med Surg) Vol. 9 Issue 4 Pg. 615-624 (Apr 2019) ISSN: 2223-4292 [Print] China
• PMID: 31143652 (Publication Type: Journal Article)