Evidence map›Paper›PMID 35165920›Full record

ArticleMovement disorders : official journal of the Movement Disorder Society2022

Neuromelanin-MRI to Quantify and Track Nigral Depigmentation in Parkinson's Disease: A Multicenter Longitudinal Study Using Template-Based Standardized Analysis.

Yue Xing, Abdul Halim Sapuan, Antonio Martín-Bastida, Saadnah Naidu, Christopher Tench, Jonathan Evans, Gillian Sare, Stefan T Schwarz, Sarah Al-Bachari, Laura M Parkes and 9 more

Open access · hybridAbstract readMulticenter Study
In one paragraph

Article in Movement disorders : official journal of the Movement Disorder Society, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
3.2field-weighted citation impact, top 7% of its field
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

18 citing papers in PubMed, 29 citations in OpenAlex.

  1. Article
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  3. Article
  4. Review
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  6. Review
  7. Selective Effects of Substantia Nigra and Locus Coeruleus Degeneration on Cognition in Parkinson's Disease.Movement disorders : official journal of the Movement Disorder Society · 2025
    Article
  8. Article
  9. Article
  10. Neuromelanin-sensitive MRI for mechanistic research and biomarker development in psychiatry.Neuropsychopharmacology : official publication of the American College of Neuropsychopharmacology · 2024
    Review
  11. Review
  12. Article
  13. Review
  14. 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

19 authors at 13 institutions in 2 countries.

Yue XingSchool of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.ORCID 0000-0002-9312-5405
Abdul Halim SapuanSchool of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.
Antonio Martín-BastidaDivision of Neurology, Imperial College London, London, United Kingdom.
Saadnah NaiduSchool of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.
Christopher TenchSchool of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.
Jonathan EvansNeurology, Nottingham University Hospital Trust, Nottingham, United Kingdom.
Gillian SareNeurology, Nottingham University Hospital Trust, Nottingham, United Kingdom.
Stefan T SchwarzSchool of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.
Sarah Al-BachariDivision of Neuroscience and Experimental Psychology, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.
Laura M ParkesDivision of Neuroscience & Experimental Psychology, School of Biological Sciences, Faculty of Biology, Medicine and Health, The University of Manchester, Manchester Academic Health Science Centre, Manchester, United Kingdom.ORCID 0000-0001-6488-507X
Sofia KanavouPopulation Health Sciences, Bristol Medical School, University of Bristol, Bristol, United Kingdom.
Jason RawPennine Acute Hospitals NHS Trust, Oldham, United Kingdom.
Monty SilverdaleDivision of Neurology, Salford Royal NHS Foundation Trust, Manchester Academic Health Science Centre, University of Manchester, Manchester, United Kingdom.ORCID 0000-0002-3295-6897
Nin BajajSchool of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.
Nicola PaveseNewcastle Magnetic Resonance Centre & Positron Emission Tomography Centre and Clinical Ageing Research Unit, Newcastle University, Newcastle upon Tyne, United Kingdom.ORCID 0000-0002-6801-6194
David BurnFaculty of Medical Sciences, The Medical School, Framlington Place, Newcastle University, Newcastle upon Tyne, United Kingdom.
Paola PicciniDivision of Neurology, Imperial College London, London, United Kingdom.
Donald G GrossetInstitute for Neurological Sciences, Queen Elizabeth University Hospital, Glasgow, United Kingdom.
Dorothee P AuerSchool of Medicine, Mental Health & Clinical Neurosciences, Nottingham, United Kingdom.
University of Nottingham · GBNottingham University Hospitals NHS Trust · GBManchester Academic Health Science Centre · GBCardiff and Vale University Health Board · GBClinica Universidad de Navarra · ESImperial College London · GBLancashire Teaching Hospitals NHS Foundation Trust · GBNewcastle University · GBNIHR Newcastle Biomedical Research Centre · GBNottingham General Hospital · GBPennine Acute Hospitals NHS Trust · GBQueen Elizabeth University Hospital · GBUniversity of Bristol · GB

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundClinical diagnosis and monitoring of Parkinson's disease (PD) remain challenging because of the lack of an established biomarker. Neuromelanin-magnetic resonance imaging (NM-MRI) is an emerging biomarker of nigral depigmentation indexing the loss of melanized neurons but has unknown prospective diagnostic and tracking performance in multicenter settings.

objectivesThe aim was to investigate the diagnostic accuracy of NM-MRI in early PD in a multiprotocol setting and to determine and compare serial NM-MRI changes in PD and controls.

methodsIn this longitudinal case-control 3 T MRI study, 148 patients and 97 controls were included from six UK clinical centers, of whom 140 underwent a second scan after 1.5 to 3 years. An automated template-based analysis was applied for subregional substantia nigra NM-MRI contrast and volume assessment. A point estimate of the period of prediagnostic depigmentation was computed.

resultsAll NM metrics performed well to discriminate patients from controls, with receiver operating characteristic showing 85% accuracy for ventral NM contrast and 83% for volume. Generalizability using a priori volume cutoff was good (79% accuracy). Serial MRI demonstrated accelerated NM loss in patients compared to controls. Ventral NM contrast loss was point estimated to start 5 to 6 years before clinical diagnosis. Ventral nigral depigmentation was greater in the most affected side, more severe cases, and nigral NM volume change correlated with change in motor severity.

conclusionsWe demonstrate that NM-MRI provides clinically useful diagnostic information in early PD across protocols, platforms, and sites. It provides methods and estimated depigmentation rates that highlight the potential to detect preclinical PD and track progression for biomarker-enabled clinical trials. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Indexed as

Parkinson DiseaseBiomarkersHumansLongitudinal StudiesMagnetic Resonance ImagingMelaninsProspective StudiesSubstantia NigraBiomarkersMelaninsneuromelaninneuromelanin; magnetic resonance imaging; longitudinal study; depigmentation; substantia nigra

Identifiers

PMID35165920
PMCPMC9303322
OpenAlexW4213166201

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.