Evidence map›Paper›PMID 39451989›Full record

ArticleBrain sciences2024

White Matter Magnetic Resonance Diffusion Measures in Multiple Sclerosis with Overactive Bladder.

Xixi Yang, Martina D Liechti, Baris Kanber, Carole H Sudre, Gloria Castellazzi, Jiaying Zhang, Marios C Yiannakas, Gwen Gonzales, Ferran Prados, Ahmed T Toosy and 2 more

Abstract read
In one paragraph

Article in Brain sciences, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors.

Xixi YangDepartment of Neurology, Xuan Wu Hospital of Capital Medical University, Beijing 100053, China.ORCID 0009-0008-3702-2752
Martina D LiechtiDepartment of Brain Repair and Rehabilitation, Faculty of Brain Sciences, Queen Square Institute of Neurology, University College London, London WC1E 6BT, UK.ORCID 0000-0002-3024-0975
Baris KanberNMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK.ORCID 0000-0003-2443-8800
Carole H SudreCentre for Medical Image Computing (CMIC), Department of Medical Physics and Biomedical Engineering, University College London, London WC1E 6BT, UK.
Gloria CastellazziNMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK.
Jiaying ZhangSchool of Artificial Intelligence, Beijing University of Post and Communications, Beijing 100876, China.
Marios C YiannakasNMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK.
Gwen GonzalesDepartment of Uro-Neurology, The National Hospital for Neurology and Neurosurgery, London WC1N 3BG, UK.
Ferran PradosNMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK.
Ahmed T ToosyNMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK.ORCID 0000-0002-4441-3750
Claudia A M Gandini Wheeler-KingshottNMR Research Unit, Queen Square MS Centre, Department of Neuroinflammation, UCL Institute of Neurology, University College London, London WC1E 6BT, UK.
Jalesh N PanickerDepartment of Brain Repair and Rehabilitation, Faculty of Brain Sciences, Queen Square Institute of Neurology, University College London, London WC1E 6BT, UK.

Funding

EPA EP-W-17-011
6 · The paper itself

Abstract

backgroundLower urinary tract (LUT) symptoms are reported in more than 80% of patients with multiple sclerosis (MS), most commonly an overactive bladder (OAB). The relationship between brain white matter (WM) changes in MS and OAB symptoms is poorly understood.

objectivesWe aim to evaluate (i) microstructural WM differences across MS patients (pwMS) with OAB symptoms, patients without LUT symptoms, and healthy subjects using diffusion tensor imaging (DTI), and (ii) associations between clinical OAB symptom scores and DTI indices.

methodsTwenty-nine female pwMS [mean age (SD) 43.3 years (9.4)], including seventeen with OAB [mean age (SD) 46.1 years (8.6)] and nine without LUT symptoms [mean age (SD) 37.5 years (8.9)], and fourteen healthy controls (HCs) [mean age (SD) 48.5 years (20)] were scanned in a 3T MRI with a DTI protocol. Additionally, clinical scans were performed for WM lesion segmentation. Group differences in fractional anisotropy (FA) were evaluated using tract-based spatial statistics. The Urinary Symptom Profile questionnaire assessed OAB severity.

resultsA statistically significant reduction in FA (

conclusionsThis study identified that lesions affecting different WM tracts in MS can result in OAB symptoms and demonstrated the role of the WM in the neural control of LUT functions. By using DTI, the association between OAB symptom severity and WM changes were identified, adding knowledge to the current LUT working model. As MS is predominantly a WM disease, these findings suggest that regional WM involvement, including of the anterior corona radiata, anterior thalamic radiation, superior longitudinal fasciculus, and superior frontal-occipital fasciculus and a non-dominant prevalence in WM, can result in OAB symptoms. OAB symptoms in MS correlate with anisotropy changes in different white matter tracts as demonstrated by DTI. Structural impairment in WM tracts plays an important role in LUT symptoms in MS.

Indexed as

diffusion tensor imaging (DTI)multiple sclerosis (MS)overactive bladder (OAB) symptomstract-based spatial statistics (TBSS)white matter (WM)

Identifiers

PMID39451989
PMCPMC11506346

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.