Journal Article

DZNE-2025-00612

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Fully automated MRI-based analysis of the locus coeruleus in aging and Alzheimer's disease dementia using ELSI-Net.

Dünnwald, M.Extern* ; Krohn, F.Extern* ; Sciarra, A. ; Sarkar, M.Extern* ; Schneider, A.DZNE* ; Fliessbach, K.DZNE* ; Kimmich, O.DZNE* ; Jessen, F.DZNE* ; Rostamzadeh, A. ; Glanz, W.DZNE* ; Incesoy, E. I.DZNE* ; Teipel, S.DZNE* ; Kilimann, I.DZNE* ; Goerss, D.DZNE* ; Spottke, A.DZNE* ; Brustkern, J.DZNE* ; Heneka, M. T. ; Brosseron, F.DZNE* ; Lüsebrink, F.DZNE* ; Hämmerer, D.DZNE* ; Düzel, E.DZNE* ; Tönnies, K. ; Oeltze-Jafra, S.Extern* ; Betts, M. J. (First author)DZNE*

2025
Wiley Hoboken, NJ

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Please use a persistent id in citations: doi:10.1002/dad2.70118

Abstract: The 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.We present a deep learning-based LC segmentation and feature extraction method called Ensemble-based Locus Coeruleus Segmentation Network (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.ELSI-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.Although we found excellent performance, further evaluations on more diverse datasets from clinical cohorts are required for a conclusive assessment of ELSI-Net's general applicability.We provide a thorough evaluation of a fully automatic locus coeruleus (LC) segmentation method termed Ensemble-based Locus Coeruleus Segmentation Network (ELSI-Net) in aging and Alzheimer's disease (AD) dementia.ELSI-Net outperforms previous work and shows high agreement with manual ratings and previously published LC atlases.ELSI-Net replicates previously shown LC group differences in aging and AD.ELSI-Net's LC mask volume correlates with cerebrospinal fluid biomarkers of AD pathology.

Keyword(s): biomarker ; deep learning ; locus coeruleus ; magnetic resonance imaging ; segmentation

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Contributing Institute(s):

1. Clinical Neurophysiology and Memory (AG Düzel)
2. Translational Dementia Research (Bonn) (AG Schneider)
3. Patient Studies (Bonn) (Patient Studies (Bonn))
4. Clinical Research Coordination (Clinical Research (Bonn))
5. Clinical Research Platform (CRP) (AG Spottke)
6. Clinical Alzheimer’s Disease Research (AG Jessen)
7. Clinical Dementia Research (Rostock /Greifswald) (AG Teipel)
8. Neuroinflammation, Biomarker (AG Heneka)

Research Program(s):

1. 353 - Clinical and Health Care Research (POF4-353) (POF4-353)

Appears in the scientific report 2025

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Database coverage:
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