Abstract 23: Results of CRISP2: CTP and CTA Assessment of Collaterals Predicts Inter-Hospital Infarct Growth

Abstract

Background: Acute ischemic stroke patients with a large vessel occlusion (LVO) who present in a primary stroke center (PSC) without endovascular treatment capability, are often transferred to a comprehensive stroke center (CSC) for thrombectomy. CRISP2 was a prospective NIH funded multi-center study that aimed to determine characteristics associated with infarct growth during inter-hospital transfer. Methods: Data from patients with an anterior circulation LVO transferred to two CSCs were collected. A CT perfusion (CTP) was obtained at the PSC followed by an MRI at the CSC, before consideration of thrombectomy. The inter-hospital infarct growth rate was defined as the difference between the co-registered infarct volumes on MRI and CTP, divided by the time between the two scans. Multivariable logistic regression was used to determine characteristics associated with fast inter-hospital progression, defined as a growth rate ≥ 5ml/h. The hypoperfusion intensity ratio (HIR) was calculated automatically from the CTP, while the Tan collateral score was visually rated on baseline CT angiography. Results: A total of 183 patients, of whom 45% were fast progressors, were included. Baseline characteristics are presented in Table 1 . An HIR ≥0.40 identified fast infarct growth with a sensitivity of 0.76 (95%CI 0.65-0.84) and a specificity of 0.55 (95%CI 0.44-0.65), whereas for Tan 0-1 sensitivity was 0.37 (95%CI 0.27-0.48) and specificity 0.93 (95%CI 0.86-0.97). In multivariable models, baseline core volume and poor collaterals defined as either an HIR ≥ 0.40 (aOR = 2.18 (95%CI 1.10-4.42); p = 0.03) or a Tan score of 0-1 (aOR = 4.74 (95%CI 1.90-13.07); p=0.001), remained independently associated with fast infarct growth. Conclusion: An HIR ≥ 0.40 is a predictor of fast inter-hospital infarct growth with high sensitivity and a Tan score of 0-1 predicts fast growth with high specificity. These are promising imaging markers for patient selection in future neuroprotective trials.