Intracranial atherosclerotic stenosis (ICAS) is one of the main causes of large vessel occlusion (LVO). However, it is challenging to diagnose ICAS-related LVO.
Endovascular thrombectomy (EVT) has become the standard of care for acute stroke patients with LVO. But, EVT is less efficacious in patients with underlying ICAS, making it essential to diagnose ICAS as quickly as possible before proceeding to treatment. Currently, there are no biomarkers to predict ICAS with high accuracy.
CT perfusion (CTP), which is now part of stroke workflow, provides essential information on collateral status using biomarkers such as hypoperfusion intensity ratio (HIR) and cerebral blood volume (CBV) index. Patients with ICAS are known to have better collateral flow than those with other stroke subtypes.
Can HIR and CBV index, therefore, help diagnose underlying ICAS?
Dr. Yukihiro Imaoka and co-authors hypothesized that lower HIR and higher CBV index would be helpful to biomarkers to predict underlying ICAS before EVT.
In an ROC analysis (receiver operating characteristic analysis), HIR showed good discrimination with a cutoff value of 0.22 (area under the curve, 0.85; 95%CI, 0.75−0.96; sensitivity, 0.84; specificity, 0.80) for underlying ICAS.
CBV index showed excellent discrimination with a cutoff value of 0.90 (area under the curve, 0.92; 95%CI, 0.81−0.98; sensitivity, 0.92; specificity, 0.79) for underlying ICAS.
This retrospective study was based on a single-site registry of consecutive LVO-acute ischemic stroke patients receiving EVT between October 2019 and December 2021.
Patients with anterior circulation LVO (ICA, M1, and M2 proximal)
Patients who received CTP imaging before EVT.
CTP images were automatically analyzed using Rapid CTP.
HIR: Defined as the ratio of the volume of the Tmax >10 s lesion divided by the volume of the Tmax >6 s lesion.
CBV index: Defined as the ratio of the mean CBV within the "Tmax > 6 s lesion" in the ipsilateral hemisphere over the mean CBV of the ipsilateral area.
Among the 238 patients who underwent thrombectomy in this period, 47 met the inclusion criteria. Out of the 47 patients, 10 (21%) had ICAS, and 37 (79%) had an embolism.
Patients in the ICAS group had:
A smaller ischemic core (0 ml vs. 18 ml; p = 0.002)
Smaller Tmax > 10 s lesion (14 ml vs. 51 ml; P = 0.005)
Lower HIR (0.12 vs. 0.50; p = 0.001)
Higher CBV index (0.9 vs. 0.7; P < 0.001) than the embolism group
In a receiver operating characteristic (ROC) curve analysis, HIR showed good discrimination with a cutoff value of 0.22 (area under the curve, 0.85; 95%CI, 0.75−0.96; sensitivity, 0.84; specificity, 0.80) for underlying ICAS.
CBV index showed excellent discrimination with a cutoff value of 0.90 (area under the curve, 0.92; 95%CI, 0.81−0.98; sensitivity, 0.92; specificity, 0.79) for ICAS.
Multivariable logistic regression analysis showed that an HIR ≤ 0.22 (OR, 22.5; 95%CI, 2.9 −177.0; P = 0.003) and a CBV index ≥ 0.9 (OR, 75.7; 95%CI, 5.8−994.0; P < 0.001) were significantly associated with underlying ICAS.
Therefore, an HIR ≤ 0.22 and a CBV index ≥ 0.9 could help predict ICAS.
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