School of Pharmacy and Bioengineering, Chongqing University of Technology, Chongqing, 400054, China.
College of Artificial Intelligence, Chongqing University of Technology, Chongqing, 401135, China.
Biomed Eng Online. 2023 Aug 15;22(1):80. doi: 10.1186/s12938-023-01145-4.
Cerebral edema is an extremely common secondary disease in post-stroke. Point-of-care testing for cerebral edema types has important clinical significance for the precise management to prevent poor prognosis. Nevertheless, there has not been a fully accepted bedside testing method for that.
A symmetric cancellation near-field coupling phase shift (NFCPS) monitoring system is established based on the symmetry of the left and right hemispheres and the fact that unilateral lesions do not affect healthy hemispheres. For exploring the feasibility of this system to reflect the occurrence and development of cerebral edema, 13 rabbits divided into experimental group (n = 8) and control group (n = 5) were performed 24-h NFCPS continuous monitoring experiments. After time difference offset and feature band averaging processing, the changing trend of NFCPS at the stages dominated by cytotoxic edema (CE) and vasogenic edema (VE), respectively, was analyzed. Furthermore, the features under the different time windows were extracted. Then, a discriminative model of cerebral edema types based on support vector machines (SVM) was established and performance of multiple feature combinations was compared.
The NFCPS monitoring outcomes of experimental group endured focal ischemia modeling by thrombin injection show a trend of first decreasing and then increasing, reaching the lowest value of - 35.05° at the 6th hour. Those of control group do not display obvious upward or downward trend and only fluctuate around the initial value with an average change of - 0.12°. Furthermore, four features under the 1-h and 2-h time windows were extracted. Based on the discriminative model of cerebral edema types, the classification accuracy of 1-h window is higher than 90% and the specificity is close to 1, which is almost the same as the performance of the 2-h window.
This study proves the feasibility of NFCPS technology combined with SVM to distinguish cerebral edema types in a short time, which is promised to become a new solution for immediate and precise management of dehydration therapy after ischemic stroke.
脑水肿是中风后极为常见的继发性疾病。即时检测脑水肿类型对于预防不良预后的精确管理具有重要的临床意义。然而，目前还没有一种完全被接受的床边检测方法。
基于左右半球的对称性和单侧病变不会影响健康半球的事实，建立了一种对称消近场耦合相移（NFCPS）监测系统。为了探索该系统反映脑水肿发生和发展的可行性，将 13 只兔子分为实验组（n=8）和对照组（n=5），进行了 24 小时 NFCPS 连续监测实验。在时差偏移和特征频带平均处理后，分析了分别以细胞毒性水肿（CE）和血管源性水肿（VE）为主导阶段的 NFCPS 的变化趋势。此外，还提取了不同时间窗下的特征。然后，建立了基于支持向量机（SVM）的脑水肿类型判别模型，并比较了多种特征组合的性能。
实验组通过凝血酶注射进行局灶性缺血建模后的 NFCPS 监测结果显示出先下降后上升的趋势，在第 6 小时达到最低值-35.05°。对照组没有显示出明显的上升或下降趋势，仅在初始值附近波动，平均变化为-0.12°。此外，在 1 小时和 2 小时时间窗下提取了四个特征。基于脑水肿类型的判别模型，1 小时窗口的分类准确率高于 90%，特异性接近 1，与 2 小时窗口的性能几乎相同。
本研究证明了 NFCPS 技术结合 SVM 区分短时间内脑水肿类型的可行性，有望成为缺血性中风后立即精确管理脱水治疗的新方法。
