Ran Haifeng, Huang Kexin, Xie Yuxin, He Yulun, Chen Guiqin, Yu Qiane, Li Xuhong, Hu Jie, Zhang Tijiang
Department of Radiology, the Affiliated Hospital of Zunyi Medical University, Zunyi, China.
Intelligent Medical Imaging Engineering Research Center of Guizhou Higher Education Institutions, Zunyi, China.
Quant Imaging Med Surg. 2025 Jul 1;15(7):6501-6516. doi: 10.21037/qims-2024-2756. Epub 2025 Jun 30.
Drug refractory focal epilepsy (DRFE) often gives rise to structural and functional damage in the brain accompanied by neuronal activity and cerebral vascular hemodynamics changes, which may result in neurovascular decoupling. However, neuroimaging evidence on neurovascular decoupling remains scarce. This study aimed to assess the manifestation of neurovascular coupling (NVC) in childhood DRFE using resting-state functional magnetic resonance imaging (rs-fMRI) and arterial spin labeling imaging (ASL).
The rs-fMRI and ASL imaging data were obtained from 24 children with DRFE and 35 healthy controls (HC). Based on the collected data, degree centrality (DC) and cerebral blood flow (CBF) were calculated respectively. Across voxel CBF-DC correlations were calculated to evaluate the NVC within whole gray matter (GM), and NVC of brain region was assessed by the CBF/DC ratio, the whole-brain GM across voxel CBF-DC correlations and CBF/DC ratio of the 2 groups were compared. We further analyzed the relationships between the changed CBF, DC and CBF/DC ratio values and cognitive performance, clinical variables. Finally, we explored the value of machine learning methods for classifying DRFE and HC.
Compared with the HC group, the DRFE children showed higher across voxel CBF-DC correlations. Increased CBF/DC ratio located in the orbital part of the superior frontal gyrus, superior parietal lobule, and lower in the left inferior temporal gyrus and precuneus in the DRFE group. The brain regions of abnormal CBF, DC, and CBF/DC ratio were predominantly in regions in the default mode network, and the executive control network, and the abnormally CBF, DC values in some brain regions were significantly correlated to cognitive function. The classification model using CBF/DC ratio as features achieved the 72.8% accuracy, 0.764 area under the curve (AUC), 68.5% sensitivity and 87.5% specificity. The classification accuracy was higher than the model with other feature type (CBF: 67.8% accuracy; DC: 66.1% accuracy).
The study reveals the cerebral blood perfusion, neuronal activity, global and regional NVC alteration in children with magnetic resonance imaging (MRI)-negative DRFE non-invasively, associated with lower cognitive performance. These findings indicate that NVC-based study can better integrate information of neuronal activity and cerebral hemodynamics, offering a new insight into the neuropathological mechanisms of DRFE and providing potential imaging biomarkers, and neurovascular decoupling may help clinical classification for childhood DRFE.
药物难治性局灶性癫痫（DRFE）常导致大脑结构和功能损伤，伴有神经元活动及脑血管血流动力学改变，这可能导致神经血管解耦。然而，关于神经血管解耦的神经影像学证据仍然匮乏。本研究旨在使用静息态功能磁共振成像（rs-fMRI）和动脉自旋标记成像（ASL）评估儿童DRFE中神经血管耦合（NVC）的表现。
从24例DRFE儿童和35例健康对照（HC）中获取rs-fMRI和ASL成像数据。基于收集的数据，分别计算度中心性（DC）和脑血流量（CBF）。计算体素间CBF-DC相关性以评估全脑灰质（GM）内的NVC，并通过CBF/DC比值评估脑区的NVC，比较两组全脑GM体素间CBF-DC相关性和CBF/DC比值。我们进一步分析了CBF、DC和CBF/DC比值变化值与认知表现、临床变量之间的关系。最后，我们探索了机器学习方法对DRFE和HC进行分类的价值。
与HC组相比，DRFE儿童表现出更高的体素间CBF-DC相关性。DRFE组中，CBF/DC比值增加位于额上回眶部、顶上小叶，而在左侧颞下回和楔前叶较低。CBF、DC和CBF/DC比值异常的脑区主要位于默认模式网络和执行控制网络区域，一些脑区异常的CBF、DC值与认知功能显著相关。以CBF/DC比值为特征的分类模型准确率达到72.8%，曲线下面积（AUC）为0.764，敏感性为68.5%，特异性为87.5%。分类准确率高于其他特征类型的模型（CBF：准确率67.8%；DC：准确率66.1%）。
本研究无创地揭示了磁共振成像（MRI）阴性的儿童DRFE中的脑血流灌注、神经元活动、整体和局部NVC改变，这些改变与较低的认知表现相关。这些发现表明基于NVC的研究能够更好地整合神经元活动和脑血流动力学信息，为DRFE的神经病理机制提供新的见解，并提供潜在的影像学生物标志物，神经血管解耦可能有助于儿童DRFE的临床分类。
