• 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

儿科人群中MRI白质信号异常的特征

Characterization of MRI White Matter Signal Abnormalities in the Pediatric Population.

作者信息

Wenger Katharina J, Koldijk Caroline E, Hattingen Elke, Porto Luciana, Kurre Wiebke

机构信息

Institute of Neuroradiology, University Hospital Frankfurt, Goethe University, 60528 Frankfurt am Main, Germany.

Gynacology Department, Buerger Hospital, 60318 Frankfurt am Main, Germany.

出版信息

Children (Basel). 2023 Jan 24;10(2):206. doi: 10.3390/children10020206.

DOI:10.3390/children10020206
PMID:36832335
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9955075/
Abstract

(1) Background and Purpose: The aim of this study was to retrospectively characterize WMSAs in an unselected patient cohort at a large pediatric neuroimaging facility, in order to learn more about the spectrum of the underlying disorders encountered in everyday clinical practice. (2) Materials and Methods: Radiology reports of 5166 consecutive patients with standard brain MRI (2006-2018) were searched for predefined keywords describing WMSAs. A neuroradiology specialist enrolled patients with WMSAs following a structured approach. Imaging characteristics, etiology (autoimmune disorders, non-genetic hypoxic and ischemic insults, traumatic white matter injuries, no final diagnosis due to insufficient clinical information, "non-specific" WMSAs, infectious white matter damage, leukodystrophies, toxic white matter injuries, inborn errors of metabolism, and white matter damage caused by tumor infiltration/cancer-like disease), and age/gender distribution were evaluated. (3) Results: Overall, WMSAs were found in 3.4% of pediatric patients scanned at our and referring hospitals within the ten-year study period. The majority were found in the supratentorial region only (87%) and were non-enhancing (78% of CE-MRI). WMSAs caused by autoimmune disorders formed the largest group (23%), followed by "non-specific" WMSAs (18%), as well as non-genetic hypoxic and ischemic insults (17%). The majority were therefore acquired as opposed to inherited. Etiology-based classification of WMSAs was affected by age but not by gender. In 17% of the study population, a definite diagnosis could not be established due to insufficient clinical information (mostly external radiology consults). (4) Conclusions: An "integrated diagnosis" that combines baseline demographics, including patient age as an important factor, clinical characteristics, and additional diagnostic workup with imaging patterns can be made in the majority of cases.

摘要

(1) 背景与目的:本研究旨在对一家大型儿科神经影像机构中未经挑选的患者队列中的白质微结构异常(WMSAs)进行回顾性特征分析,以便更多地了解日常临床实践中所遇到的潜在疾病谱。(2) 材料与方法:在5166例连续接受标准脑部磁共振成像(2006 - 2018年)的患者的放射学报告中搜索描述WMSAs的预定义关键词。一位神经放射学专家按照结构化方法纳入患有WMSAs的患者。评估影像特征、病因(自身免疫性疾病、非遗传性缺氧和缺血性损伤、创伤性白质损伤、因临床信息不足未得出最终诊断、“非特异性”WMSAs、感染性白质损伤、脑白质营养不良、中毒性白质损伤、先天性代谢缺陷以及肿瘤浸润/类癌疾病导致的白质损伤)以及年龄/性别分布。(3) 结果:总体而言,在为期十年的研究期间,在我们医院及转诊医院接受扫描的儿科患者中,3.4%发现有WMSAs。大多数仅见于幕上区域(87%)且无强化表现(对比增强磁共振成像的78%)。由自身免疫性疾病导致的WMSAs构成最大组(23%),其次是“非特异性”WMSAs(18%)以及非遗传性缺氧和缺血性损伤(17%)。因此,大多数是后天获得而非遗传所致。基于病因的WMSAs分类受年龄影响,但不受性别影响。在17%的研究人群中,由于临床信息不足(大多为外部放射学会诊)无法确立明确诊断。(4) 结论:在大多数情况下,可以做出一种“综合诊断”,将包括患者年龄这一重要因素在内的基线人口统计学特征、临床特征以及带有影像模式的额外诊断检查相结合。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/e79e48a52a8c/children-10-00206-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/6013ca6028c4/children-10-00206-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/79cce7ce1025/children-10-00206-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/bffa499237e3/children-10-00206-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/38765d853896/children-10-00206-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/636c134a3ce4/children-10-00206-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/95aab1c822eb/children-10-00206-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/a181042e4df8/children-10-00206-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/0becef6ca86c/children-10-00206-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/05ffb84cb6a3/children-10-00206-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/e79e48a52a8c/children-10-00206-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/6013ca6028c4/children-10-00206-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/79cce7ce1025/children-10-00206-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/bffa499237e3/children-10-00206-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/38765d853896/children-10-00206-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/636c134a3ce4/children-10-00206-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/95aab1c822eb/children-10-00206-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/a181042e4df8/children-10-00206-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/0becef6ca86c/children-10-00206-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/05ffb84cb6a3/children-10-00206-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/d6ec/9955075/e79e48a52a8c/children-10-00206-g010.jpg

相似文献

1
Characterization of MRI White Matter Signal Abnormalities in the Pediatric Population.儿科人群中MRI白质信号异常的特征
Children (Basel). 2023 Jan 24;10(2):206. doi: 10.3390/children10020206.
2
Magnetic resonance imaging in the diagnosis of white matter signal abnormalities.磁共振成像在白质信号异常诊断中的应用
Neuroradiol J. 2018 Aug;31(4):362-371. doi: 10.1177/1971400918764016. Epub 2018 Mar 8.
3
Optical measures of cerebral arterial stiffness are associated with white matter signal abnormalities and cognitive performance in normal aging.光学测量大脑动脉僵硬度与正常衰老过程中的白质信号异常和认知表现相关。
Neurobiol Aging. 2019 Dec;84:200-207. doi: 10.1016/j.neurobiolaging.2019.08.004. Epub 2019 Aug 10.
4
Neuropathology of Mild Traumatic Brain Injury: Correlation to Neurocognitive and Neurobehavioral Findings轻度创伤性脑损伤的神经病理学:与神经认知和神经行为结果的相关性
5
White matter signal abnormalities in former National Football League players.前美国国家橄榄球联盟球员的白质信号异常。
Alzheimers Dement (Amst). 2017 Nov 6;10:56-65. doi: 10.1016/j.dadm.2017.10.003. eCollection 2018.
6
Shades of white: diffusion properties of T1- and FLAIR-defined white matter signal abnormalities differ in stages from cognitively normal to dementia.色调的变化:从认知正常到痴呆,T1 和 FLAIR 定义的脑白质信号异常在不同阶段的扩散性质不同。
Neurobiol Aging. 2018 Aug;68:48-58. doi: 10.1016/j.neurobiolaging.2018.03.029. Epub 2018 Apr 5.
7
Imaging manifestations of the leukodystrophies, inherited disorders of white matter.脑白质营养不良的影像学表现,即白质的遗传性疾病。
Radiol Clin North Am. 2014 Mar;52(2):279-319. doi: 10.1016/j.rcl.2013.11.008.
8
Brain MRI findings in paediatric genetic disorders associated with white matter abnormalities.与白质异常相关的儿科遗传疾病的脑部磁共振成像表现
Dev Med Child Neurol. 2025 Feb;67(2):186-194. doi: 10.1111/dmcn.16036. Epub 2024 Jul 30.
9
Novel imaging technologies for genetic diagnoses in the inborn errors of metabolism.用于先天性代谢缺陷基因诊断的新型成像技术。
J Transl Genet Genom. 2020;4:429-445. doi: 10.20517/jtgg.2020.09. Epub 2020 Nov 13.
10
Genetic disorders affecting white matter in the pediatric age.影响儿童期白质的遗传性疾病。
Am J Med Genet B Neuropsychiatr Genet. 2004 Aug 15;129B(1):85-93. doi: 10.1002/ajmg.b.30029.

本文引用的文献

1
Magnetic resonance imaging of disorders with white matter changes in children and adolescents: a pictorial essay.儿童和青少年伴脑白质改变的疾病的磁共振成像:影像学专题论文集。
Pediatr Radiol. 2023 May;53(6):1188-1206. doi: 10.1007/s00247-022-05580-8. Epub 2023 Jan 10.
2
Diagnostic performance of deep learning-based automatic white matter hyperintensity segmentation for classification of the Fazekas scale and differentiation of subcortical vascular dementia.基于深度学习的自动脑白质高信号分割对 Fazekas 量表分类和皮质下血管性痴呆鉴别诊断的性能评估。
PLoS One. 2022 Sep 15;17(9):e0274562. doi: 10.1371/journal.pone.0274562. eCollection 2022.
3
A deep learning algorithm for white matter hyperintensity lesion detection and segmentation.
一种用于检测和分割脑白质高信号病灶的深度学习算法。
Neuroradiology. 2022 Apr;64(4):727-734. doi: 10.1007/s00234-021-02820-w. Epub 2021 Oct 2.
4
Leukodystrophies in Children: Diagnosis, Care, and Treatment.儿童脑白质营养不良:诊断、护理和治疗。
Pediatrics. 2021 Sep;148(3). doi: 10.1542/peds.2021-053126.
5
Automatic Segmentation of Diffuse White Matter Abnormality on T2-weighted Brain MR Images Using Deep Learning in Very Preterm Infants.使用深度学习对极早产儿T2加权脑磁共振图像上的弥漫性白质异常进行自动分割
Radiol Artif Intell. 2021 Feb 3;3(3):e200166. doi: 10.1148/ryai.2021200166. eCollection 2021 May.
6
White Matter Lesions in Migraine.偏头痛的脑白质病变。
Am J Pathol. 2021 Nov;191(11):1955-1962. doi: 10.1016/j.ajpath.2021.02.007. Epub 2021 Feb 24.
7
Associated factors of white matter hyperintensity volume: a machine-learning approach.与脑白质高信号体积相关的因素:一种机器学习方法。
Sci Rep. 2021 Jan 27;11(1):2325. doi: 10.1038/s41598-021-81883-4.
8
White Matter Lesions in Adults - a Differential Diagnostic Approach.成人脑白质病变——一种鉴别诊断方法。
Rofo. 2020 Dec;192(12):1154-1173. doi: 10.1055/a-1207-1006. Epub 2020 Jul 20.
9
Incidental Brain MRI Findings in Children: A Systematic Review and Meta-Analysis.偶然发现的儿童脑 MRI 结果:系统评价和荟萃分析。
AJNR Am J Neuroradiol. 2019 Nov;40(11):1818-1823. doi: 10.3174/ajnr.A6281. Epub 2019 Oct 17.
10
Assessment of lesions on magnetic resonance imaging in multiple sclerosis: practical guidelines.多发性硬化症磁共振成像病变评估:实用指南。
Brain. 2019 Jul 1;142(7):1858-1875. doi: 10.1093/brain/awz144.