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

MRI Neuroimaging Primary lateral sclerosis Upper motor neuron

Journal

Data in brief
ISSN: 2352-3409
Titre abrégé: Data Brief
Pays: Netherlands
ID NLM: 101654995

Informations de publication

Date de publication:
Oct 2020
Historique:
received: 04 08 2020
revised: 12 08 2020
accepted: 25 08 2020
entrez: 18 9 2020
pubmed: 19 9 2020
medline: 19 9 2020
Statut: epublish

Résumé

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.

Identifiants

pubmed: 32944602
doi: 10.1016/j.dib.2020.106247
pii: S2352-3409(20)31141-0
pii: 106247
pmc: PMC7481824
doi:

Types de publication

Journal Article

Langues

eng

Pagination

106247

Informations de copyright

© 2020 The Author(s). Published by Elsevier Inc.

Déclaration de conflit d'intérêts

None.

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Auteurs

Eoin Finegan (E)

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

We Fong Siah (WF)

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

Stacey Li Hi Shing (SLH)

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

Rangariroyashe H Chipika (RH)

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

Kai Ming Chang (KM)

Computational Neuroimaging Group, Biomedical Sciences Institute, Trinity College Dublin, Ireland.
Electronics and Computer Science, University of Southampton, Southampton, United Kingdom.

Mary Clare McKenna (MC)

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

Mark A Doherty (MA)

Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Ireland.

Jennifer C Hengeveld (JC)

Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Ireland.

Alice Vajda (A)

Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Ireland.

Colette Donaghy (C)

Department of Neurology, Western Health & Social Care Trust, Belfast, United Kingdom.

Siobhan Hutchinson (S)

Department of Neurology, St James's Hospital, Dublin, Ireland.

Russel L McLaughlin (RL)

Complex Trait Genomics Laboratory, Smurfit Institute of Genetics, Trinity College Dublin, Ireland.

Orla Hardiman (O)

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

Peter Bede (P)

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

Classifications MeSH