Fuzong Clinical Medical College of Fujian Medical University, Fuzhou, Fujian Province, China; Department of Radiology, 900TH Hospital of Joint Logistics Support Force, Fuzhou, Fujian Province, China.
Department of Radiology, the First Affiliated Hospital of Xiamen University, Xiamen, Fujian Province, China.
Eur J Radiol. 2023 Oct;167:111082. doi: 10.1016/j.ejrad.2023.111082. Epub 2023 Sep 9.
Preoperative identification of hippocampal sclerosis (HS) is crucial to successful surgery for mesial temporal lobe epilepsy (MTLE). We aimed to investigate the diagnostic performance of hippocampal radiomics models based on T2 fluid-attenuated inversion recovery (FLAIR) images in MTLE with HS.
We analysed 210 cases, including 172 HS pathology-confirmed cases (100 magnetic resonance imaging [MRI]-positive cases [MRI + HS], 72 MRI-negative HS cases [MRI - HS]), and 38 healthy controls (HC). The hippocampus was delineated slice by slice on an oblique coronal plane by a T2-FLAIR sequence, perpendicular to the hippocampus's long axis, to obtain a three-dimensional region of interest. Radiomics were processed using Artificial Intelligence Kit software; logistic regression radiomics models were constructed. The model evaluation indexes included the area under the curve (AUC), accuracy, sensitivity, and specificity.
The respective AUC, accuracy, sensitivity, and specificity were 0.863, 81.4%, 78.0%, and 84.6% between the MRI - HS and HC groups in the training set and 0.855, 75.0%, 68.2%, and 81.8% in the test set; 0.975, 95.0%, 92.9%, and 98.0% between the MRI + HS and HC groups in the training set and 0.954, 88.7%, 90.0%, and 87.0% in the test set; and 0.912, 84.3%, 83.3%, and 86.5% between the MTLE and HC groups in the training set and 0.854, 79.7%, 80.8%, and 77.3% in the test set. The AUC values of the comparative radiomics models were > 0.85, indicating good diagnostic efficiency.
The hippocampal radiomics models based on T2-FLAIR images can help diagnose MTLE with HS. They can be used as biological markers for MTLE diagnosis.
术前识别海马硬化（HS）对于内侧颞叶癫痫（MTLE）的手术成功至关重要。本研究旨在探讨基于 T2 液体衰减反转恢复（FLAIR）图像的海马放射组学模型在 HS 所致 MTLE 中的诊断性能。
我们分析了 210 例患者，包括 172 例 HS 病理证实病例（100 例 MRI 阳性病例[MRI+HS]，72 例 MRI 阴性 HS 病例[MRI-HS]）和 38 例健康对照者（HC）。采用 T2-FLAIR 斜冠状位序列对海马进行逐层勾画，垂直于海马长轴，获得三维感兴趣区。使用人工智能套件软件进行放射组学处理；构建逻辑回归放射组学模型。模型评估指标包括曲线下面积（AUC）、准确性、敏感性和特异性。
在训练集中，MRI-HS 与 HC 组之间的 AUC、准确性、敏感性和特异性分别为 0.863、81.4%、78.0%和 84.6%，在测试集中分别为 0.855、75.0%、68.2%和 81.8%；MRI+HS 与 HC 组之间的 AUC、准确性、敏感性和特异性分别为 0.975、95.0%、92.9%和 98.0%，在测试集中分别为 0.954、88.7%、90.0%和 87.0%；MTLE 与 HC 组之间的 AUC、准确性、敏感性和特异性分别为 0.912、84.3%、83.3%和 86.5%，在测试集中分别为 0.854、79.7%、80.8%和 77.3%。比较放射组学模型的 AUC 值均>0.85，提示具有较好的诊断效率。
基于 T2-FLAIR 图像的海马放射组学模型有助于诊断 HS 所致 MTLE，可以作为 MTLE 诊断的生物学标志物。
