Elisevich Kost, Davoodi-Bojd Esmaeil, Heredia John G, Soltanian-Zadeh Hamid
Department of Clinical Neurosciences, Spectrum Health, Grand Rapids, MI, United States.
Department of Surgery, College of Human Medicine, Michigan State University, Grand Rapids, MI, United States.
Front Neurol. 2021 Nov 5;12:747580. doi: 10.3389/fneur.2021.747580. eCollection 2021.
A prospective study of individual and combined quantitative imaging applications for lateralizing epileptogenicity was performed in a cohort of consecutive patients with a putative diagnosis of mesial temporal lobe epilepsy (mTLE). Quantitative metrics were applied to MRI and nuclear medicine imaging studies as part of a comprehensive presurgical investigation. The neuroimaging analytics were conducted remotely to remove bias. All quantitative lateralizing tools were trained using a separate dataset. Outcomes were determined after 2 years. Of those treated, some underwent resection, and others were implanted with a responsive neurostimulation (RNS) device. Forty-eight consecutive cases underwent evaluation using nine attributes of individual or combinations of neuroimaging modalities: 1) hippocampal volume, 2) FLAIR signal, 3) PET profile, 4) multistructural analysis (MSA), 5) multimodal model analysis (MMM), 6) DTI uncertainty analysis, 7) DTI connectivity, and 9) fMRI connectivity. Of the 24 patients undergoing resection, MSA, MMM, and PET proved most effective in predicting an Engel class 1 outcome (>80% accuracy). Both hippocampal volume and FLAIR signal analysis showed 76% and 69% concordance with an Engel class 1 outcome, respectively. Quantitative multimodal neuroimaging in the context of a putative mTLE aids in declaring laterality. The degree to which there is disagreement among the various quantitative neuroimaging metrics will judge whether epileptogenicity can be confined sufficiently to a particular temporal lobe to warrant further study and choice of therapy. Prediction models will improve with continued exploration of combined optimal neuroimaging metrics.
对一组初步诊断为内侧颞叶癫痫（mTLE）的连续患者进行了一项关于个体化和联合定量成像应用以定位致痫灶的前瞻性研究。作为全面术前检查的一部分，将定量指标应用于MRI和核医学成像研究。远程进行神经影像分析以消除偏差。所有定量定位工具均使用单独的数据集进行训练。2年后确定结果。在接受治疗的患者中，一些人接受了切除术，另一些人植入了反应性神经刺激（RNS）装置。连续48例患者使用神经影像模态的九个个体属性或组合进行评估：1）海马体积，2）FLAIR信号，3）PET特征，4）多结构分析（MSA），5）多模态模型分析（MMM），6）DTI不确定性分析，7）DTI连通性，以及9）fMRI连通性。在接受切除术的24例患者中，MSA、MMM和PET在预测Engel 1级结果（准确率>80%）方面最为有效。海马体积和FLAIR信号分析与Engel 1级结果的一致性分别为76%和69%。在疑似mTLE的情况下，定量多模态神经影像有助于确定病变侧别。各种定量神经影像指标之间的不一致程度将判断致痫性是否能够充分局限于特定颞叶，以保证进一步研究和治疗选择。随着对联合最佳神经影像指标的持续探索，预测模型将会得到改进。
