Theodore William H, Inati Sara K, Adler Sophie, Pearl Philip L, Mcdonald Carrie R
National Institutes of Health, Bethesda, MD, USA.
Developmental Neurosciences, UCL Great Ormond Street Institute of Child Health, London, UK.
Epilepsy Curr. 2025 Jun 18:15357597251332191. doi: 10.1177/15357597251332191.
New imaging techniques appearing over the last few decades have replaced procedures that were uncomfortable, of low specificity, and prone to adverse events. While computed tomography remains useful for imaging patients with seizures in acute settings, structural magnetic resonance imaging (MRI) has become the most important imaging modality for epilepsy evaluation, with adjunctive functional imaging also increasingly well established in presurgical evaluation, including positron emission tomography (PET), single photon ictal-interictal subtraction computed tomography co-registered to MRI and functional MRI for preoperative cognitive mapping. Neuroimaging in inherited metabolic epilepsies is integral to diagnosis, monitoring, and assessment of treatment response. Neurotransmitter receptor PET and magnetic resonance spectroscopy can help delineate the pathophysiology of these disorders. Machine learning and artificial intelligence analyses based on large MRI datasets composed of healthy volunteers and people with epilepsy have been initiated to detect lesions that are not found visually, particularly focal cortical dysplasia. These methods, not yet approved for patient care, depend on careful clinical correlation and training sets that fully sample broad populations.
过去几十年出现的新成像技术已经取代了那些让人不适、特异性低且容易引发不良事件的检查方法。虽然计算机断层扫描在急性发作期癫痫患者的成像中仍有作用,但结构磁共振成像(MRI)已成为癫痫评估最重要的成像方式,辅助功能成像在术前评估中也越来越成熟,包括正电子发射断层扫描(PET)、与MRI联合登记的单光子发作期 - 发作间期减影计算机断层扫描以及用于术前认知图谱的功能MRI。遗传性代谢性癫痫的神经成像对于诊断、监测和治疗反应评估至关重要。神经递质受体PET和磁共振波谱有助于明确这些疾病的病理生理学。基于由健康志愿者和癫痫患者组成的大型MRI数据集的机器学习和人工智能分析已经启动,以检测肉眼无法发现的病变,特别是局灶性皮质发育不良。这些方法尚未被批准用于患者护理,依赖于仔细的临床关联和能充分代表广泛人群的训练集。