• 文献检索
  • 文档翻译
  • 深度研究
  • 学术资讯
  • Suppr Zotero 插件Zotero 插件
  • 邀请有礼
  • 套餐&价格
  • 历史记录
应用&插件
Suppr Zotero 插件Zotero 插件浏览器插件Mac 客户端Windows 客户端微信小程序
定价
高级版会员购买积分包购买API积分包
服务
文献检索文档翻译深度研究API 文档MCP 服务
关于我们
关于 Suppr公司介绍联系我们用户协议隐私条款
关注我们

Suppr 超能文献

核心技术专利:CN118964589B侵权必究
粤ICP备2023148730 号-1Suppr @ 2026

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验

阿尔茨海默病早期活体 T1 加权 MRI 上内侧颞叶亚区的自动分割。

Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease.

机构信息

Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.

Department of Radiology, University of Pennsylvania, Philadelphia, Pennsylvania.

出版信息

Hum Brain Mapp. 2019 Aug 15;40(12):3431-3451. doi: 10.1002/hbm.24607. Epub 2019 Apr 29.

DOI:10.1002/hbm.24607
PMID:31034738
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC6697377/
Abstract

Medial temporal lobe (MTL) substructures are the earliest regions affected by neurofibrillary tangle pathology-and thus are promising biomarkers for Alzheimer's disease (AD). However, automatic segmentation of the MTL using only T1-weighted (T1w) magnetic resonance imaging (MRI) is challenging due to the large anatomical variability of the MTL cortex and the confound of the dura mater, which is commonly segmented as gray matter by state-of-the-art algorithms because they have similar intensity in T1w MRI. To address these challenges, we developed a novel atlas set, consisting of 15 cognitively normal older adults and 14 patients with mild cognitive impairment with a label explicitly assigned to the dura, that can be used by the multiatlas automated pipeline (Automatic Segmentation of Hippocampal Subfields [ASHS-T1]) for the segmentation of MTL subregions, including anterior/posterior hippocampus, entorhinal cortex (ERC), Brodmann areas (BA) 35 and 36, and parahippocampal cortex on T1w MRI. Cross-validation experiments indicated good segmentation accuracy of ASHS-T1 and that the dura can be reliably separated from the cortex (6.5% mislabeled as gray matter). Conversely, FreeSurfer segmented majority of the dura mater (62.4%) as gray matter and the degree of dura mislabeling decreased with increasing disease severity. To evaluate its clinical utility, we applied the pipeline to T1w images of 663 ADNI subjects and significant volume/thickness loss is observed in BA35, ERC, and posterior hippocampus in early prodromal AD and all subregions at later stages. As such, the publicly available new atlas and ASHS-T1 could have important utility in the early diagnosis and monitoring of AD and enhancing brain-behavior studies of these regions.

摘要

内侧颞叶(MTL)亚区是最早受到神经原纤维缠结病理影响的区域,因此是阿尔茨海默病(AD)的有前途的生物标志物。然而,由于 MTL 皮质的解剖结构变化较大,以及硬脑膜的混杂,仅使用 T1 加权(T1w)磁共振成像(MRI)对 MTL 进行自动分割是具有挑战性的,因为硬脑膜在 T1w MRI 中的强度与灰质相似,因此最先进的算法通常将其分割为灰质。为了解决这些挑战,我们开发了一个新的图谱集,其中包含 15 名认知正常的老年人和 14 名轻度认知障碍患者,这些图谱集明确标记了硬脑膜,可以由多图谱自动管道(海马亚区自动分割[ASHS-T1])用于 MTL 亚区的分割,包括前/后海马、内嗅皮质(ERC)、Brodmann 区(BA)35 和 36 以及 T1w MRI 上的旁海马皮质。交叉验证实验表明,ASHS-T1 的分割准确性较高,硬脑膜可以可靠地与皮质分离(6.5%错误标记为灰质)。相反,FreeSurfer 将大部分硬脑膜(62.4%)标记为灰质,并且随着疾病严重程度的增加,硬脑膜的错误标记程度降低。为了评估其临床应用价值,我们将该管道应用于 663 名 ADNI 受试者的 T1w 图像,在早期前驱 AD 中观察到 BA35、ERC 和后海马的体积/厚度明显丢失,并且在后期所有亚区都存在这种情况。因此,新的公共图谱和 ASHS-T1 可以在 AD 的早期诊断和监测以及增强这些区域的脑行为研究中具有重要的应用价值。

相似文献

1
Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease.阿尔茨海默病早期活体 T1 加权 MRI 上内侧颞叶亚区的自动分割。
Hum Brain Mapp. 2019 Aug 15;40(12):3431-3451. doi: 10.1002/hbm.24607. Epub 2019 Apr 29.
2
Clinical Application of Automatic Segmentation of Medial Temporal Lobe Subregions in Prodromal and Dementia-Level Alzheimer's Disease.内侧颞叶亚区域自动分割在前驱期和痴呆级阿尔茨海默病中的临床应用
J Alzheimers Dis. 2016 Oct 4;54(3):1027-1037. doi: 10.3233/JAD-160014.
3
Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-Weighted MRI.在T1加权磁共振成像中分割内嗅皮质和嗅周皮质时对脑膜混杂因素的考量
Med Image Comput Comput Assist Interv. 2016 Oct;9901:564-571. doi: 10.1007/978-3-319-46723-8_65. Epub 2016 Oct 2.
4
Validating ASHS-T1 automated entorhinal and transentorhinal cortical segmentation in Alzheimer's disease.验证 ASHS-T1 自动内侧颞叶和颞叶过渡区皮层分割在阿尔茨海默病中的应用。
Psychiatry Res Neuroimaging. 2023 Oct;335:111707. doi: 10.1016/j.pscychresns.2023.111707. Epub 2023 Aug 22.
5
Longitudinal atrophy in early Braak regions in preclinical Alzheimer's disease.早期 Braak 阶段临床前阿尔茨海默病中的纵向萎缩。
Hum Brain Mapp. 2020 Nov;41(16):4704-4717. doi: 10.1002/hbm.25151. Epub 2020 Aug 26.
6
Medial Temporal Lobe Subregional Atrophy in Aging and Alzheimer's Disease: A Longitudinal Study.衰老和阿尔茨海默病中的内侧颞叶亚区域萎缩:一项纵向研究。
Front Aging Neurosci. 2021 Oct 15;13:750154. doi: 10.3389/fnagi.2021.750154. eCollection 2021.
7
Automated volumetry and regional thickness analysis of hippocampal subfields and medial temporal cortical structures in mild cognitive impairment.轻度认知障碍中海马亚区及内侧颞叶皮质结构的自动容积测量和区域厚度分析
Hum Brain Mapp. 2015 Jan;36(1):258-87. doi: 10.1002/hbm.22627. Epub 2014 Sep 2.
8
Medial temporal lobe subregional morphometry using high resolution MRI in Alzheimer's disease.使用高分辨率磁共振成像对阿尔茨海默病进行内侧颞叶亚区域形态测量
Neurobiol Aging. 2017 Jan;49:204-213. doi: 10.1016/j.neurobiolaging.2016.09.011. Epub 2016 Sep 30.
9
Structural Alteration of Medial Temporal Lobe Subfield in the Amnestic Mild Cognitive Impairment Stage of Alzheimer's Disease.内侧颞叶亚区结构改变在阿尔茨海默病遗忘型轻度认知障碍阶段。
Neural Plast. 2022 Jan 24;2022:8461235. doi: 10.1155/2022/8461235. eCollection 2022.
10
Differential medial temporal lobe and default-mode network functional connectivity and morphometric changes in Alzheimer's disease.阿尔茨海默病患者内侧颞叶和默认模式网络功能连接及形态计量学的差异变化。
Neuroimage Clin. 2019;23:101860. doi: 10.1016/j.nicl.2019.101860. Epub 2019 May 18.

引用本文的文献

1
Regional deep atrophy: Using temporal information to automatically identify regions associated with Alzheimer's disease progression from longitudinal MRI.区域深度萎缩:利用时间信息从纵向磁共振成像中自动识别与阿尔茨海默病进展相关的区域。
Imaging Neurosci (Camb). 2024 Sep 18;2. doi: 10.1162/imag_a_00294. eCollection 2024.
2
Tau-Clinical Mismatch Identifies Individuals with Co-Pathology and Predicts Clinical Trajectory.tau蛋白临床不匹配可识别合并病理学特征的个体并预测临床病程。
medRxiv. 2025 Jul 25:2025.07.25.25332195. doi: 10.1101/2025.07.25.25332195.
3
Developing an Anatomically Valid Segmentation Protocol for Anterior Regions of the Medial Temporal Lobe for Neurodegenerative Diseases.为神经退行性疾病开发一种用于内侧颞叶前部区域的解剖学上有效的分割方案。
Hippocampus. 2025 Sep;35(5):e70027. doi: 10.1002/hipo.70027.
4
Tau, atrophy, and domain-specific cognitive impairment in typical Alzheimer's disease.典型阿尔茨海默病中的tau蛋白、萎缩与特定领域认知障碍
Alzheimers Dement. 2025 Jul;21(7):e70511. doi: 10.1002/alz.70511.
5
Disease stage-specific atrophy markers in Alzheimer's disease.阿尔茨海默病中疾病阶段特异性萎缩标志物。
Alzheimers Dement. 2025 Jul;21(7):e70482. doi: 10.1002/alz.70482.
6
Cardiovascular risk factors are associated with lower posterior-medial network functional connectivity in older adults.心血管危险因素与老年人后内侧网络功能连接性降低有关。
Alzheimers Res Ther. 2025 Jul 15;17(1):159. doi: 10.1186/s13195-025-01808-5.
7
Automated segmentation for cortical thickness of the medial perirhinal cortex.内侧嗅周皮质皮质厚度的自动分割
Sci Rep. 2025 Apr 28;15(1):14903. doi: 10.1038/s41598-025-98399-w.
8
Disease stage-specific atrophy markers in Alzheimer's disease.阿尔茨海默病中疾病阶段特异性萎缩标志物
medRxiv. 2025 Mar 14:2025.03.13.25323904. doi: 10.1101/2025.03.13.25323904.
9
Mesoscale connectivity of the human hippocampus and fimbria revealed by ex vivo diffusion MRI.通过离体扩散磁共振成像揭示的人类海马体和海马伞的中尺度连接性
Neuroimage. 2025 Apr 15;310:121125. doi: 10.1016/j.neuroimage.2025.121125. Epub 2025 Mar 16.
10
Developing an anatomically valid segmentation protocol for anterior regions of the medial temporal lobe for neurodegenerative diseases.为神经退行性疾病开发一种用于内侧颞叶前部区域的解剖学上有效的分割方案。
bioRxiv. 2025 Feb 13:2025.02.11.637506. doi: 10.1101/2025.02.11.637506.

本文引用的文献

1
Multi-Template Mesiotemporal Lobe Segmentation: Effects of Surface and Volume Feature Modeling.多模板中颞叶分割:表面和体积特征建模的影响
Front Neuroinform. 2018 Jul 12;12:39. doi: 10.3389/fninf.2018.00039. eCollection 2018.
2
Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer's Disease at 3T and 7T: What Atlas Composition Works Best?在 3T 和 7T 下阿尔茨海默病的海马和海马外亚区的自动多图谱分割:哪种图谱组合效果最好?
J Alzheimers Dis. 2018;63(1):217-225. doi: 10.3233/JAD-170932.
3
Optimization and validation of automated hippocampal subfield segmentation across the lifespan.优化并验证全生命周期内的自动海马亚区分割。
Hum Brain Mapp. 2018 Feb;39(2):916-931. doi: 10.1002/hbm.23891. Epub 2017 Nov 23.
4
Earliest accumulation of β-amyloid occurs within the default-mode network and concurrently affects brain connectivity.β-淀粉样蛋白最早在默认模式网络中积累,并同时影响大脑的连接。
Nat Commun. 2017 Oct 31;8(1):1214. doi: 10.1038/s41467-017-01150-x.
5
AV-1451 PET imaging of tau pathology in preclinical Alzheimer disease: Defining a summary measure.AV-1451 正电子发射断层扫描(PET)对阿尔茨海默病临床前tau 病理学的成像:定义一个综合指标。
Neuroimage. 2017 Nov 1;161:171-178. doi: 10.1016/j.neuroimage.2017.07.050. Epub 2017 Jul 26.
6
Accounting for the Confound of Meninges in Segmenting Entorhinal and Perirhinal Cortices in T1-Weighted MRI.在T1加权磁共振成像中分割内嗅皮质和嗅周皮质时对脑膜混杂因素的考量
Med Image Comput Comput Assist Interv. 2016 Oct;9901:564-571. doi: 10.1007/978-3-319-46723-8_65. Epub 2016 Oct 2.
7
A protocol for manual segmentation of medial temporal lobe subregions in 7 Tesla MRI.一种在7特斯拉磁共振成像中手动分割内侧颞叶亚区域的方案。
Neuroimage Clin. 2017 May 26;15:466-482. doi: 10.1016/j.nicl.2017.05.022. eCollection 2017.
8
Human anterolateral entorhinal cortex volumes are associated with cognitive decline in aging prior to clinical diagnosis.人类前外侧内嗅皮质体积与临床诊断前衰老过程中的认知衰退相关。
Neurobiol Aging. 2017 Sep;57:195-205. doi: 10.1016/j.neurobiolaging.2017.04.025. Epub 2017 May 8.
9
Medial temporal lobe subregional morphometry using high resolution MRI in Alzheimer's disease.使用高分辨率磁共振成像对阿尔茨海默病进行内侧颞叶亚区域形态测量
Neurobiol Aging. 2017 Jan;49:204-213. doi: 10.1016/j.neurobiolaging.2016.09.011. Epub 2016 Sep 30.
10
Multi-template analysis of human perirhinal cortex in brain MRI: Explicitly accounting for anatomical variability.脑磁共振成像中人类嗅周皮质的多模板分析:明确考虑解剖变异性。
Neuroimage. 2017 Jan 1;144(Pt A):183-202. doi: 10.1016/j.neuroimage.2016.09.070. Epub 2016 Oct 1.