Department of Neuroradiology, Heidelberg University Hospital, Heidelberg, Germany.
Institute of Diagnostic and Interventional Neuroradiology, Inselspital Bern University Hospital, Bern, Switzerland.
Clin Neuroradiol. 2022 Mar;32(1):133-140. doi: 10.1007/s00062-021-01110-5. Epub 2021 Oct 28.
We hypothesize that the detectability of early ischemic changes on non-contrast computed tomography (NCCT) is limited in hyperacute stroke for both human and machine-learning based evaluation. In short onset-time-to-imaging (OTI), the CT angiography collateral status may identify fast stroke progressors better than early ischemic changes quantified by ASPECTS.
In this retrospective, monocenter study, CT angiography collaterals (Tan score) and ASPECTS on acute and follow-up NCCT were evaluated by two raters. Additionally, a machine-learning algorithm evaluated the ASPECTS scale on the NCCT (e-ASPECTS). In this study 136 patients from 03/2015 to 12/2019 with occlusion of the main segment of the middle cerebral artery, with a defined symptom-onset-time and successful mechanical thrombectomy (MT) (modified treatment in cerebral infarction score mTICI = 2c or 3) were evaluated.
Agreement between acute and follow-up ASPECTS were found to depend on OTI for both human (Intraclass correlation coefficient, ICC = 0.43 for OTI < 100 min, ICC = 0.57 for OTI 100-200 min, ICC = 0.81 for OTI ≥ 200 min) and machine-learning based ASPECTS evaluation (ICC = 0.24 for OTI < 100 min, ICC = 0.61 for OTI 100-200 min, ICC = 0.63 for OTI ≥ 200 min). The same applied to the interrater reliability. Collaterals were predictors of a favorable clinical outcome especially in hyperacute stroke with OTI < 100 min (collaterals: OR = 5.67 CI = 2.38-17.8, p < 0.001; ASPECTS: OR = 1.44, CI = 0.91-2.65, p = 0.15) while ASPECTS was in prolonged OTI ≥ 200 min (collaterals OR = 4.21,CI = 1.36-21.9, p = 0.03; ASPECTS: OR = 2.85, CI = 1.46-7.46, p = 0.01).
The accuracy and reliability of NCCT-ASPECTS are time dependent for both human and machine-learning based evaluation, indicating reduced detectability of fast stroke progressors by NCCT. In hyperacute stroke, collateral status from CT-angiography may help for a better prognosis on clinical outcome and explain the occurrence of futile recanalization.
我们假设，在超急性期卒中患者中，基于人类和基于机器学习的评估均显示，非对比 CT（NCCT）上早期缺血性改变的检出率有限。在起病至影像学检查时间（OTI）较短的情况下，CT 血管造影侧支循环状态可能比 ASPECTS 量化的早期缺血性改变更好地识别快速进展的卒中患者。
在这项回顾性单中心研究中，两名评估者评估了急性和随访期 NCCT 的 CT 血管造影侧支循环（Tan 评分）和 ASPECTS。此外，机器学习算法还评估了 NCCT 上的 ASPECTS 量表（e-ASPECTS）。本研究纳入了 2015 年 3 月至 2019 年 12 月期间因大脑中动脉主干闭塞、明确起病时间且成功接受机械血栓切除术（MT）（改良脑梗死治疗评分 mTICI=2c 或 3）的 136 例患者。
发现急性和随访期 ASPECTS 的一致性取决于 OTI，人类评估的 ICC 值为 OTI＜100min 时为 0.43，OTI 为 100-200min 时为 0.57，OTI≥200min 时为 0.81；基于机器学习的 ASPECTS 评估的 ICC 值为 OTI＜100min 时为 0.24，OTI 为 100-200min 时为 0.61，OTI≥200min 时为 0.63。两名评估者之间的可靠性也是如此。侧支循环是临床结局良好的预测因素，尤其是在 OTI＜100min 的超急性期卒中患者中（侧支循环：OR=5.67，CI=2.38-17.8，p＜0.001；ASPECTS：OR=1.44，CI=0.91-2.65，p=0.15），而在 OTI≥200min 时，ASPECTS 则是（侧支循环：OR=4.21，CI=1.36-21.9，p=0.03；ASPECTS：OR=2.85，CI=1.46-7.46，p=0.01）。
基于人类和基于机器学习的评估均表明，NCCT-ASPECTS 的准确性和可靠性均与 OTI 时间相关，提示 NCCT 对快速进展的卒中患者的检出率降低。在超急性期卒中患者中，CT 血管造影的侧支循环状态可能有助于更好地预测临床结局，并解释无效再通的发生。
