提高细微性内侧颞叶硬化的检测：商业化自动海马体积分割软件的验证。
Improved Detection of Subtle Mesial Temporal Sclerosis: Validation of a Commercially Available Software for Automated Segmentation of Hippocampal Volume.
机构信息
From the Departments of Radiology (J.M.M., B.F.B.,)
From the Departments of Radiology (J.M.M., B.F.B.,).
出版信息
AJNR Am J Neuroradiol. 2019 Mar;40(3):440-445. doi: 10.3174/ajnr.A5966. Epub 2019 Feb 7.
BACKGROUND AND PURPOSE
Identification of mesial temporal sclerosis is critical in the evaluation of individuals with temporal lobe epilepsy. Our aim was to assess the performance of FDA-approved software measures of hippocampal volume to identify mesial temporal sclerosis in patients with medically refractory temporal lobe epilepsy compared with the initial clinical interpretation of a neuroradiologist.
MATERIALS AND METHODS
Preoperative MRIs of 75 consecutive patients who underwent a temporal resection for temporal lobe epilepsy from 2011 to 2016 were retrospectively reviewed, and 71 were analyzed using Neuroreader, a commercially available automated segmentation and volumetric analysis package. Volume measures, including hippocampal volume as a percentage of total intracranial volume and the Neuroreader Index, were calculated. Radiologic interpretations of the MR imaging and pathology from subsequent resections were classified as either mesial temporal sclerosis or other, including normal findings. These measures of hippocampal volume were evaluated by receiver operating characteristic curves on the basis of pathologic confirmation of mesial temporal sclerosis in the resected temporal lobe. Sensitivity and specificity were calculated for each method and compared by means of the McNemar test using the optimal threshold as determined by the Youden J point.
RESULTS
Optimized thresholds of hippocampal percentage of a structural volume relative to total intracranial volume (<0.19%) and the Neuroreader Index (≤-3.8) were selected to optimize sensitivity and specificity (89%/71% and 89%/78%, respectively) for the identification of mesial temporal sclerosis in temporal lobe epilepsy compared with the initial clinical interpretation of the neuroradiologist (50% and 87%). Automated measures of hippocampal volume predicted mesial temporal sclerosis more accurately than radiologic interpretation (McNemar test, < .0001).
CONCLUSIONS
Commercially available automated segmentation and volume analysis of the hippocampus accurately identifies mesial temporal sclerosis and performs significantly better than the interpretation of the radiologist.
背景与目的
在评估颞叶癫痫患者时，明确是否存在海马硬化至关重要。本研究旨在评估经美国食品药品监督管理局（FDA）批准的海马体积测量软件在识别药物难治性颞叶癫痫患者海马硬化方面的性能，并与神经放射科医师的初始临床解读进行比较。
材料与方法
回顾性分析了 2011 年至 2016 年间 75 例因颞叶癫痫行颞叶切除术患者的术前 MRI 资料，其中 71 例使用神经阅读器（一款商业化的自动分割和容积分析软件包）进行分析。计算海马体积（占颅内总体积的百分比）和神经阅读器指数等容积测量指标。根据术后切除标本的影像学和病理学结果，将 MRI 解读分为海马硬化和其他（包括正常发现）。基于术后颞叶标本病理证实的海马硬化，使用受试者工作特征曲线评估这些海马体积测量指标。使用 Youden J 点确定的最佳阈值，通过 McNemar 检验比较每种方法的敏感性和特异性。
结果
选择相对颅内总体积的海马结构容积百分比（<0.19%）和神经阅读器指数（≤-3.8）的优化阈值，以优化用于识别颞叶癫痫中海马硬化的敏感性和特异性（分别为 89%/71%和 89%/78%），并与神经放射科医师的初始临床解读（50%和 87%）进行比较。海马体积的自动测量较影像学解读更能准确预测海马硬化（McNemar 检验，<.0001）。
结论
商业化的海马自动分割和容积分析能准确识别海马硬化，其性能明显优于放射科医师的解读。
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