Initial investigation of the use of angiographic parametric imaging for early prognosis of delayed cerebral ischemia in patients with subarachnoid hemorrhage.
Initial investigation of the use of angiographic parametric imaging for early prognosis of delayed cerebral ischemia in patients with subarachnoid hemorrhage.
复制标题
使用血管造影参数成像对蛛网膜下腔出血患者迟发性脑缺血早期预后的初步研究。
DOI：
10.1117/12.2612081
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Ionita,CiprianN
中科院分区：
文献类型：
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作者：
Price,RomanD;Bhurwani,MohammadMahdiShiraz;Sommer,KelseyN;Monteiro,Andrei;Baig,AmmadA;Davies,JasonM;Siddiqui,AdnanH;Ionita,CiprianN
蛛网膜下腔出血（Subarachnoid Hemorrhage，SAH）是一种致死性出血性脑卒中，占脑血管病死亡的25%.作为初始出血的结果，引发一系列生理事件，这可能导致迟发性脑缺血（DCI）。到目前为止，我们还没有诊断能力来识别可能在最初表现后几周出现DCI的患者。我们建议调查是否使用血管造影参数成像（API）的数据驱动的方法可以预测发生的DCI.Materials和MethodsDigital减影血管造影（DSA）序列从125 SAH患者进行回顾性分析，以执行API评估的整个大脑半球的出血被检测到。放置四个感兴趣区域（ROI）以提取侧向和AP DSA中的五个平均API生物标志物。使用逻辑回归对各种API参数和ROI进行数据驱动分析，以找到最佳配置，从而最大化预后准确性。每个模型的性能进行了评估，使用曲线下面积的受试者操作者特征（AUROC）。结果数据驱动的方法与API有60%的准确率预测DCI的发生。我们确定了用于提取API参数的ROI的位置对于数据驱动模型性能非常重要。使用每个患者的入口速度对值进行标准化可以产生更高和更一致的结果。单一的API生物标志物模型预测准确性差，勉强优于chance.ConclusionsThis有效性探索性研究表明，第一次，在SAH患者的DCI的预后，是可行的，值得更深入的调查。
PurposeSubarachnoid Hemorrhage (SAH) is a lethal hemorrhagic stroke that account for 25% of cerebrovascular deaths. As a result of the initial bleed, a chain of physiological events are initiated which may lead to Delayed Cerebral Ischemia (DCI). As of now we have no diagnostic capability to identify patients which may present DCI a few weeks after initial presentation. We propose to investigate whether a data driven approach using angiographic parametric imaging (API) may predict occurrence of the DCI.Materials and MethodsDigital Subtraction Angiographic (DSA) sequences from 125 SAH patients were used retrospectively to perform API assessment of the entire brain hemisphere where the hemorrhage was detected. Four Regions of Interests (ROIs) were placed to extract five average API biomarkers in the lateral and AP DSAs. Data driven analysis using Logistic Regression was performed for various API parameters and ROIs to find the optimal configuration to maximize the prognosis accuracy. Each model performance was evaluated using area under the curve of the receiver operator characteristic (AUROC).ResultsData driven approach with API has a 60% accuracy predicting DCI occurrence. We determined that location of the ROI for extraction of the API parameters is very important for the data driven model performance. Normalizing the values using the inlet velocities for each patient yield higher and more consistent results. Single API biomarkers models had poor prediction accuracies, barely better than chance.ConclusionsThis effectiveness exploratory study demonstrates for the first time, that prognosis of the DCI in SAH patients, is feasible and warrants a more in-depth investigation.