Evidence map›Paper›PMID 39091766›Full record

ArticlebioRxiv : the preprint server for biology2024

Fully Automated MRI-based Analysis of the Locus Coeruleus in Aging and Alzheimer's Disease Dementia using ELSI-Net.

Max Dünnwald, Friedrich Krohn, Alessandro Sciarra, Mousumi Sarkar, Anja Schneider, Klaus Fliessbach, Okka Kimmich, Frank Jessen, Ayda Rostamzadeh, Wenzel Glanz and 14 more

Abstract readPreprint
PubMed Full text at PMC Publisher
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

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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. Article
4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

24 authors.

Max DünnwaldDepartment of Neurology, Otto von Guericke University Magdeburg (OvGU), Germany.ORCID 0000-0003-3838-3345
Friedrich KrohnInstitute of Cognitive Neurology and Dementia Research, OvGU, Germany.
Alessandro SciarraDepartment of Neurology, Otto von Guericke University Magdeburg (OvGU), Germany.
Mousumi SarkarInstitute of Cognitive Neurology and Dementia Research, OvGU, Germany.
Anja SchneiderGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
Klaus FliessbachGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
Okka KimmichGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
Frank JessenGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
Ayda RostamzadehDepartment of Psychiatry, University of Cologne, Germany.ORCID 0000-0001-5189-134X
Wenzel GlanzDZNE, Magdeburg, Germany.ORCID 0000-0002-5865-4176
Enise I IncesoyInstitute of Cognitive Neurology and Dementia Research, OvGU, Germany.
Stefan TeipelDZNE, Rostock, Germany.
Ingo KilimannDZNE, Rostock, Germany.
Doreen GoerssDZNE, Rostock, Germany.
Annika SpottkeGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
Johanna BrustkernGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.
Michael T HenekaLuxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
Frederic BrosseronGerman Center for Neurodegenerative Diseases (DZNE), Bonn, Germany.ORCID 0000-0003-3137-7516
Falk LüsebrinkDZNE, Magdeburg, Germany.
Dorothea HämmererDepartment of Psychology, University of Innsbruck, Austria.
Emrah DüzelInstitute of Cognitive Neurology and Dementia Research, OvGU, Germany.
Klaus TönniesFaculty of Computer Science, OvGU, Germany.
Steffen Oeltze-JafraPeter L. Reichertz Institute for Medical Informatics, Hannover Medical School, Germany.
Matthew J BettsInstitute of Cognitive Neurology and Dementia Research, OvGU, Germany.

Funding

Representational dynamics for flexible learning in complex environmentsR01MH126971 · NIMH · BROWN UNIVERSITY · PI Matthew Nassar · 2022 to 2026
$3.0M
NIMH NIH HHS R01 MH126971
6 · The paper itself

Abstract

introductionThe Locus Coeruleus (LC) is linked to the development and pathophysiology of neurodegenerative diseases such as Alzheimer's Disease (AD). Magnetic Resonance Imaging based LC features have shown potential to assess LC integrity in vivo.

methodsWe present a Deep Learning based LC segmentation and feature extraction method: ELSI-Net and apply it to healthy aging and AD dementia datasets. Agreement to expert raters and previously published LC atlases were assessed. We aimed to reproduce previously reported differences in LC integrity in aging and AD dementia and correlate extracted features to cerebrospinal fluid (CSF) biomarkers of AD pathology.

resultsELSI-Net demonstrated high agreement to expert raters and published atlases. Previously reported group differences in LC integrity were detected and correlations to CSF biomarkers were found. DISCUSSION: Although we found excellent performance, further evaluations on more diverse datasets from clinical cohorts are required for a conclusive assessment of ELSI-Nets general applicability.

Indexed as

biomarkerDeep LearningLocus CoeruleusMagnetic Resonance ImagingSegmentation

Identifiers

PMID39091766
PMCPMC11291139

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

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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.