Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis

流体衰减反转恢复 核医学 磁共振成像 接收机工作特性 正电子发射断层摄影术 海马硬化 医学 海马结构 标准摄取值 神经影像学 放射科 颞叶 内科学 癫痫 精神科
作者
Wenhan Hu,Lina Liu,Baotian Zhao,Xiu Wang,Chao Zhang,Xiaoqiu Shao,Kai Zhang,Yulong Ma,Lin Ai,LI Jun-ju,Jianguo Zhang
出处
期刊:Frontiers in Neurology [Frontiers Media]
卷期号:9 被引量:7
标识
DOI:10.3389/fneur.2018.00820
摘要

Purpose: Magnetic resonance imaging (MRI) and positron emission tomography (PET) with 18F-fluorodeoxyglucose (18FDG) are valuable tools for evaluating hippocampal sclerosis (HS); however, bias may arise during visual analyses. The aim of this study was to evaluate and compare MRI and PET post-processing techniques, automated quantitative hippocampal volume (Q-volume), and fluid-attenuated inversion-recovery (FLAIR) signal (Q-FLAIR) and glucose metabolism (Q-PET) analyses in patients with HS. Methods: We collected MRI and 18FDG-PET images from 54 patients with HS and 22 healthy controls and independently performed conventional visual analyses (CVA) of PET (CVA-PET) and MRI (CVA-MRI) images. During the subsequent quantitative analyses, the hippocampus was segmented from the 3D T1 image, and the mean volumetric, FLAIR intensity and standardized uptake value ratio (SUVR) values of the left and right hippocampus were assessed in each subject. Threshold confidence levels calculated from the mean volumetric, FLAIR intensity and SUVR values of the controls were used to identify healthy subjects or subjects with HS. The performance of the three methods was assessed using receiver operating characteristic (ROC) curves, and the detection rates of CVA-MRI, CVA-PET, Q-volume, Q-FLAIR, and Q-PET were statistically compared. Results: The areas under the curves (AUCs) for the Q-volume, Q-FLAIR and Q-PET ROC analyses were 0.88, 0.41 and 0.98, which suggested a diagnostic method with moderate, poor, and high accuracy, respectively. Although Q-PET had the highest detection rate among the two CVA methods and three quantitative methods, the difference between Q-volume and Q-PET did not reach statistical significance. Regarding the HS subtypes, CVA-MRI, CVA-PET, Q-volume and Q-PET had similar detection rates for type 1 HS, and Q-PET was the most sensitive method for detecting types 2 and 3 HS. Conclusions: In MRI or 18FDG-PET images that have been visually assessed by experts, the quantification of hippocampal volume or glucose uptake can increase the detection of HS and appear to be additional valuable diagnostic tools for evaluating patients with epilepsy who are suspected of having HS.
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