An open-source tool for longitudinal whole-brain and white matter lesion segmentation

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In this paper we describe and validate a longitudinal method for whole-brain segmentation of longitudinal MRI scans. It builds upon an existing whole-brain segmentation method that can handle multi-contrast data and robustly analyze images with white matter lesions. This method is here extended with subject-specific latent variables that encourage temporal consistency between its segmentation results, enabling it to better track subtle morphological changes in dozens of neuroanatomical structures and white matter lesions. We validate the proposed method on multiple datasets of control subjects and patients suffering from Alzheimer's disease and multiple sclerosis, and compare its results against those obtained with its original cross-sectional formulation and two benchmark longitudinal methods. The results indicate that the method attains a higher test–retest reliability, while being more sensitive to longitudinal disease effect differences between patient groups. An implementation is publicly available as part of the open-source neuroimaging package FreeSurfer.

OriginalsprogEngelsk
Artikelnummer103354
TidsskriftNeuroImage: Clinical
Vol/bind38
Antal sider19
ISSN2213-1582
DOI
StatusUdgivet - 2023

Bibliografisk note

Funding Information:
This project has received funding from the European Union's Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 765148, as well as from the National Institute Of Neurological Disorders and Stroke under project number R01NS112161. Douglas N. Greve has received funding from the National Institute Of Neurological Disorders and Stroke (R01NS105820), the National Institute for Biomedical Imaging and Bioengineering (R01EB023281), and the National Institute on Aging (R01AG057672, R01AG059011, U19AG068753). Henrik Lundell has received funding from the European Research Council (ERC) under the European Union's Horizon 2020 research and innovation programme (grant agreement No 804746). Hartwig R. Siebner holds a 5-year professorship in precision medicine at the Faculty of Health Sciences and Medicine, University of Copenhagen which is sponsored by the Lundbeck Foundation (Grant Nr. R186-2015–2138). Mark Mühlau was also supported by the German Research Foundation (Priority Program SPP2177, Radiomics: Next Generation of Biomedical Imaging) – project number 428223038. Images of MS patients from the Munich dataset were subgroups of the MS cohort study of the Technical University of Munich (TUM-MS) run by the Dept. of Neurology in close collaboration with the Dept. of Diagnostic and Interventional Neuroradiology. A particular thanks to Claus Zimmer, Bernhard, Hemmer, Jan Kirschke, Achim Berthele, Benedikt Wiestler, and Matthias Bussas for their ongoing support. Data used in preparation of this article were obtained from the Alzheimer's Disease Neuroimaging Initiative (ADNI) database (http://adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf.

Funding Information:
This project has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 765148, as well as from the National Institute Of Neurological Disorders and Stroke under project number R01NS112161. Douglas N. Greve has received funding from the National Institute Of Neurological Disorders and Stroke (R01NS105820), the National Institute for Biomedical Imaging and Bioengineering (R01EB023281), and the National Institute on Aging (R01AG057672, R01AG059011, U19AG068753). Henrik Lundell has received funding from the European Research Council (ERC) under the European Union’s Horizon 2020 research and innovation programme (grant agreement No 804746). Hartwig R. Siebner holds a 5-year professorship in precision medicine at the Faculty of Health Sciences and Medicine, University of Copenhagen which is sponsored by the Lundbeck Foundation (Grant Nr. R186-2015–2138). Mark Mühlau was also supported by the German Research Foundation (Priority Program SPP2177, Radiomics: Next Generation of Biomedical Imaging) – project number 428223038. Images of MS patients from the Munich dataset were subgroups of the MS cohort study of the Technical University of Munich (TUM-MS) run by the Dept. of Neurology in close collaboration with the Dept. of Diagnostic and Interventional Neuroradiology. A particular thanks to Claus Zimmer, Bernhard, Hemmer, Jan Kirschke, Achim Berthele, Benedikt Wiestler, and Matthias Bussas for their ongoing support.

Publisher Copyright:
© 2023

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