Evidence map›Paper›PMID 39230009›Full record

ArticleHuman brain mapping2024

Atlas-based assessment of hypomyelination: Quantitative MRI in Pelizaeus-Merzbacher disease.

Caroline Köhler, Paul Kuntke, Prativa Sahoo, Hannes Wahl, Sean C L Deoni, Jutta Gärtner, Steffi Dreha-Kulaczewski, Hagen H Kitzler

Abstract read
In one paragraph

Article in Human brain mapping, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

8 authors.

Caroline KöhlerInstitute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0001-7073-0998
Paul KuntkeInstitute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0003-1838-2230
Prativa SahooDepartment of Pediatrics and Adolescent Medicine, University Medical Center Göttingen, Göttingen, Germany.
Hannes WahlInstitute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.ORCID 0000-0002-4897-1119
Sean C L DeoniAdvanced Baby Imaging Lab, School of Engineering, Brown University, Providence, Rhode Island, USA.ORCID 0000-0002-0633-6328
Jutta GärtnerDepartment of Pediatrics and Adolescent Medicine, University Medical Center Göttingen, Göttingen, Germany.
Steffi Dreha-KulaczewskiDepartment of Pediatrics and Adolescent Medicine, University Medical Center Göttingen, Göttingen, Germany.
Hagen H KitzlerInstitute of Diagnostic and Interventional Neuroradiology, Faculty of Medicine and University Hospital Carl Gustav Carus, Technische Universität Dresden, Dresden, Germany.

Funding

European Leukodystrophie Association Deutschland e.V.
6 · The paper itself

Abstract

Pelizaeus-Merzbacher disease (PMD) is a rare childhood hypomyelinating leukodystrophy. Quantification of the pronounced myelin deficit and delineation of subtle myelination processes are of high clinical interest. Quantitative magnetic resonance imaging (qMRI) techniques can provide in vivo insights into myelination status, its spatial distribution, and dynamics during brain maturation. They may serve as potential biomarkers to assess the efficacy of myelin-modulating therapies. However, registration techniques for image quantification and statistical comparison of affected pediatric brains, especially those of low or deviant image tissue contrast, with healthy controls are not yet established. This study aimed first to develop and compare postprocessing pipelines for atlas-based quantification of qMRI data in pediatric patients with PMD and evaluate their registration accuracy. Second, to apply an optimized pipeline to investigate spatial myelin deficiency using myelin water imaging (MWI) data from patients with PMD and healthy controls. This retrospective single-center study included five patients with PMD (mean age, 6 years ± 3.8) who underwent conventional brain MRI and diffusion tensor imaging (DTI), with MWI data available for a subset of patients. Three methods of registering PMD images to a pediatric template were investigated. These were based on (a) T1-weighted (T1w) images, (b) fractional anisotropy (FA) maps, and (c) a combination of T1w, T2-weighted, and FA images in a multimodal approach. Registration accuracy was determined by visual inspection and calculated using the structural similarity index method (SSIM). SSIM values for the registration approaches were compared using a t test. Myelin water fraction (MWF) was quantified from MWI data as an assessment of relative myelination. Mean MWF was obtained from two PMDs (mean age, 3.1 years ± 0.3) within four major white matter (WM) pathways of a pediatric atlas and compared to seven healthy controls (mean age, 3 years ± 0.2) using a Mann-Whitney U test. Our results show that visual registration accuracy estimation and computed SSIM were highest for FA-based registration, followed by multimodal, and T1w-based registration (SSIM

Indexed as

Atlases as TopicDiffusion Tensor ImagingMyelin SheathPelizaeus-Merzbacher DiseaseBrainChildChild, PreschoolFemaleHumansMagnetic Resonance ImagingMaleRetrospective StudiesWhite Matterhypomyelinating leukodystrophymagnetic resonance imagingmedical image registrationneuroimagingPelizaeus‐Merzbacher diseasewhite matter disorder

Identifiers

PMID39230009
PMCPMC11372820

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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.