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影像学和临床数据表明,“疑似”进行性延髓麻痹(PLS)患者存在相当大的疾病负担:有2至4年上运动神经元症状的患者。

Imaging and clinical data indicate considerable disease burden in 'probable' PLS: Patients with UMN symptoms for 2-4 years.

作者信息

Finegan Eoin, Siah We Fong, Shing Stacey Li Hi, Chipika Rangariroyashe H, Chang Kai Ming, McKenna Mary Clare, Doherty Mark A, Hengeveld Jennifer C, Vajda Alice, Donaghy Colette, Hutchinson Siobhan, McLaughlin Russel L, Hardiman Orla, Bede Peter

机构信息

Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland.

Electronics and Computer Science, University of Southampton, Southampton, United Kingdom.

出版信息

Data Brief. 2020 Sep 1;32:106247. doi: 10.1016/j.dib.2020.106247. eCollection 2020 Oct.

DOI:10.1016/j.dib.2020.106247
PMID:32944602
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7481824/
Abstract

Primary lateral sclerosis (PLS) is an adult-onset upper motor neuron disease manifesting in progressive spasticity and gradually resulting in considerably motor disability. In the absence of early disease-specific diagnostic indicators, the majority of patients with PLS face a circuitous diagnostic journey. Until the recent publication of consensus diagnostic criteria, 4-year symptom duration was required to establish the diagnosis. The new diagnostic criteria introduced the category of 'probable PLS' for patients with a symptom duration of 2-4 years. "Evolving diagnostic criteria in primary lateral sclerosis: The clinical and radiological basis of "probable PLS" [1]. This dataset provides radiological metrics in a cohort of 'probable PLS' patients, 'definite PLS' patients and age-matched healthy controls. Region-of-interest radiological data include diffusivity metrics in the corticospinal tracts and corpus callosum as well as mean cortical thickness values in the pre- and para-central gyri in each hemisphere. Our data indicate considerable grey matter and relatively limited white matter involvement in 'probable PLS' which supports the rationale for this diagnostic category as a clinically useful entity. The introduction of this diagnostic category will likely facilitate the timely recruitment of PLS patients into research studies and pharmacological trials before widespread neurodegenerative change ensues.

摘要

原发性侧索硬化症(PLS)是一种成人起病的上运动神经元疾病,表现为进行性痉挛,最终逐渐导致严重的运动功能障碍。由于缺乏早期疾病特异性诊断指标,大多数PLS患者面临曲折的诊断过程。在最近的共识诊断标准发布之前,需要4年的症状持续时间才能确诊。新的诊断标准为症状持续时间为2至4年的患者引入了“可能的PLS”类别。“原发性侧索硬化症不断演变的诊断标准:‘可能的PLS’的临床和影像学基础”[1]。该数据集提供了一组“可能的PLS”患者、“确诊的PLS”患者和年龄匹配的健康对照的影像学指标。感兴趣区域的影像学数据包括皮质脊髓束和胼胝体中的扩散指标,以及每个半球中央前回和中央旁回的平均皮质厚度值。我们的数据表明,“可能的PLS”患者存在相当程度的灰质受累和相对有限的白质受累,这支持了将这一诊断类别作为一个临床上有用实体的理论依据。这一诊断类别的引入可能会促进在广泛的神经退行性变发生之前,及时将PLS患者纳入研究和药物试验。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/5785eaabcc45/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/99e530fb6b62/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/8da3c6c93ad5/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/58372427994b/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/5785eaabcc45/gr4.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/99e530fb6b62/gr1.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/8da3c6c93ad5/gr2.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/58372427994b/gr3.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/005a/7481824/5785eaabcc45/gr4.jpg

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本文引用的文献

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J Neurol Sci. 2020 Oct 15;417:117052. doi: 10.1016/j.jns.2020.117052. Epub 2020 Jul 24.
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Primary lateral sclerosis: consensus diagnostic criteria.原发性侧索硬化症:共识诊断标准。
J Neurol Neurosurg Psychiatry. 2020 Apr;91(4):373-377. doi: 10.1136/jnnp-2019-322541. Epub 2020 Feb 6.
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Widespread subcortical grey matter degeneration in primary lateral sclerosis: a multimodal imaging study with genetic profiling.
原发性侧索硬化症中的语言缺陷:皮质萎缩、白质变性及脑区之间的功能脱节。
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Thalamic pathology in frontotemporal dementia: Predilection for specific nuclei, phenotype-specific signatures, clinical correlates, and practical relevance.额颞叶痴呆的丘脑病理学:特定核团的易感性、表型特异性特征、临床相关性及实际意义。
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Clusters of anatomical disease-burden patterns in ALS: a data-driven approach confirms radiological subtypes.ALS 中解剖疾病负担模式的聚类:一种数据驱动的方法证实了影像学亚型。
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