Department of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, China.
Department of Neurosurgery, Beijing Neurosurgical Institute, Capital Medical University, Beijing, China.
J Magn Reson Imaging. 2021 Sep;54(3):925-935. doi: 10.1002/jmri.27615. Epub 2021 Apr 23.
Focal cortical dysplasia IIIa (FCD IIIa) is a common histopathological finding in temporal lobe epilepsy. However, subtle alterations in the temporal neocortex of FCD IIIa renders presurgical diagnosis and definition of the resective range challenging.
To explore neuroimaging phenotyping and structural-metabolic-electrophysiological alterations in FCD IIIa.
Retrospective.
One hundred and sixty-seven subjects aged 4-39 years, including 64 FCD IIIa patients, 89 healthy controls and 14 FCD I patients as disease controls.
FIELD STRENGTH/SEQUENCE: 3 T, fast-spin-echo T -weighted fluid-attenuated inversion recovery (FLAIR), synthetic T -weighted magnetization prepared rapid acquisition gradient echo (MPRAGE).
Surface-based linear model was applied to reveal neuroimaging phenotyping in FCD IIIa and assess its relationship with clinical variables. Logistic regression was implemented to identify FCD IIIa patients. Epileptogenicity mapping (EM) was conducted to explore the structural-metabolic-electrophysiological alterations in temporal neocortex of FCD IIIa.
Student's t-test was applied to determine the significance of paired differences. Calibration curves were plotted to assess the goodness-of-fit (GOF) of the models, combined with the Hosmer-Lemeshow test.
FCD IIIa exhibited widespread hyperintensities in temporal neocortex, and these alterations correlated with disease duration (P < 0.01). Machine learning model accurately identified 84.4% of FCD IIIa patients, 92.1% of healthy controls and 92.9% of FCD I patients. Cross-modality analysis showed a significant negative correlation between FLAIR hyperintensity and positron emission tomography hypometabolism P < 0.01). Furthermore, epileptogenic cortices were located predominantly in brain regions with FLAIR hyperintensity and hypometabolism.
FCD IIIa exhibited widespread temporal neocortex FLAIR hyperintensity. Automated machine learning of neuroimaging patterns is conducive for accurate identification of FCD IIIa. The degree and distribution of morphological alterations related to the extent of metabolic and epileptogenic abnormalities, lending support to its potential value for reduction of the radiative and invasive approaches during presurgical workup.
3 TECHNICAL EFFICACY STAGE: 2.
局灶性皮质发育不良 IIIa（FCD IIIa）是颞叶癫痫的常见组织病理学发现。然而，FCD IIIa 中颞叶新皮质的细微改变使得术前诊断和确定切除范围具有挑战性。
探讨 FCD IIIa 的神经影像学表型和结构-代谢-电生理改变。
回顾性研究。
167 名年龄在 4-39 岁的受试者，包括 64 名 FCD IIIa 患者、89 名健康对照者和 14 名 FCD I 患者作为疾病对照者。
磁场强度/序列：3T，快速自旋回波 T1 加权液体衰减反转恢复（FLAIR），合成 T1 加权磁化准备快速获取梯度回波（MPRAGE）。
采用基于表面的线性模型来揭示 FCD IIIa 的神经影像学表型，并评估其与临床变量的关系。实施逻辑回归以识别 FCD IIIa 患者。进行致痫性映射（EM）以探索 FCD IIIa 中颞叶新皮质的结构-代谢-电生理改变。
应用学生 t 检验确定配对差异的显著性。绘制校准曲线以评估模型的拟合优度（GOF），并结合 Hosmer-Lemeshow 检验。
FCD IIIa 在颞叶新皮质中显示出广泛的高信号，这些改变与疾病持续时间相关（P<0.01）。机器学习模型准确识别了 84.4%的 FCD IIIa 患者、92.1%的健康对照者和 92.9%的 FCD I 患者。跨模态分析显示 FLAIR 高信号与正电子发射断层扫描低代谢之间存在显著负相关（P<0.01）。此外，致痫皮质主要位于 FLAIR 高信号和低代谢的脑区。
FCD IIIa 在颞叶新皮质中显示出广泛的 FLAIR 高信号。神经影像学模式的自动化机器学习有助于准确识别 FCD IIIa。形态改变的程度和分布与代谢和致痫异常的程度相关，支持其在术前评估中减少放射性和侵袭性方法的潜在价值。
3 技术功效等级：2。
