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

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-proces...

Full description

Bibliographic Details
Main Authors: Wen-han Hu, Li-na Liu, Bao-tian Zhao, Xiu Wang, Chao Zhang, Xiao-qiu Shao, Kai Zhang, Yan-Shan Ma, Lin Ai, Jun-ju Li, Jian-guo Zhang
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-10-01
Series:Frontiers in Neurology
Subjects:
MRI
Online Access:https://www.frontiersin.org/article/10.3389/fneur.2018.00820/full
id doaj-72227842e5f848cb9abeb9c6a88fad64
record_format Article
spelling doaj-72227842e5f848cb9abeb9c6a88fad642020-11-25T00:37:13ZengFrontiers Media S.A.Frontiers in Neurology1664-22952018-10-01910.3389/fneur.2018.00820392409Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal SclerosisWen-han Hu0Li-na Liu1Bao-tian Zhao2Xiu Wang3Chao Zhang4Xiao-qiu Shao5Kai Zhang6Yan-Shan Ma7Lin Ai8Jun-ju Li9Jian-guo Zhang10Jian-guo Zhang11Beijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Pathology, Beijing Fengtai Hospital, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurology, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Fengtai Hospital, Beijing, ChinaNuclear Medicine, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Hainan General Hospital, Haikou, ChinaBeijing Neurosurgical Institute, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaDepartment of Neurosurgery, Beijing Tiantan Hospital, Capital Medical University, Beijing, ChinaPurpose: 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.https://www.frontiersin.org/article/10.3389/fneur.2018.00820/fullmesial temporal lobe epilepsyhippocampal sclerosisMRI18FDG-PETquantitative analysis
collection DOAJ
language English
format Article
sources DOAJ
author Wen-han Hu
Li-na Liu
Bao-tian Zhao
Xiu Wang
Chao Zhang
Xiao-qiu Shao
Kai Zhang
Yan-Shan Ma
Lin Ai
Jun-ju Li
Jian-guo Zhang
Jian-guo Zhang
spellingShingle Wen-han Hu
Li-na Liu
Bao-tian Zhao
Xiu Wang
Chao Zhang
Xiao-qiu Shao
Kai Zhang
Yan-Shan Ma
Lin Ai
Jun-ju Li
Jian-guo Zhang
Jian-guo Zhang
Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis
Frontiers in Neurology
mesial temporal lobe epilepsy
hippocampal sclerosis
MRI
18FDG-PET
quantitative analysis
author_facet Wen-han Hu
Li-na Liu
Bao-tian Zhao
Xiu Wang
Chao Zhang
Xiao-qiu Shao
Kai Zhang
Yan-Shan Ma
Lin Ai
Jun-ju Li
Jian-guo Zhang
Jian-guo Zhang
author_sort Wen-han Hu
title Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis
title_short Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis
title_full Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis
title_fullStr Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis
title_full_unstemmed Use of an Automated Quantitative Analysis of Hippocampal Volume, Signal, and Glucose Metabolism to Detect Hippocampal Sclerosis
title_sort use of an automated quantitative analysis of hippocampal volume, signal, and glucose metabolism to detect hippocampal sclerosis
publisher Frontiers Media S.A.
series Frontiers in Neurology
issn 1664-2295
publishDate 2018-10-01
description 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.
topic mesial temporal lobe epilepsy
hippocampal sclerosis
MRI
18FDG-PET
quantitative analysis
url https://www.frontiersin.org/article/10.3389/fneur.2018.00820/full
work_keys_str_mv AT wenhanhu useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT linaliu useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT baotianzhao useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT xiuwang useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT chaozhang useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT xiaoqiushao useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT kaizhang useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT yanshanma useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT linai useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT junjuli useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT jianguozhang useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
AT jianguozhang useofanautomatedquantitativeanalysisofhippocampalvolumesignalandglucosemetabolismtodetecthippocampalsclerosis
_version_ 1725301922948186112