Deep Learning Segmentation of the Nucleus Basalis of Meynert on 3T MRI.

Humans Basal Nucleus of Meynert Deep Learning Magnetic Resonance Imaging / methods Brain Cognition

Journal

AJNR. American journal of neuroradiology
ISSN: 1936-959X
Titre abrégé: AJNR Am J Neuroradiol
Pays: United States
ID NLM: 8003708

Informations de publication

Date de publication:
09 2023
Historique:
received: 11 11 2022
accepted: 25 06 2023
pmc-release: 01 09 2024
medline: 13 9 2023
pubmed: 11 8 2023
entrez: 10 8 2023
Statut: ppublish

Résumé

The nucleus basalis of Meynert is a key subcortical structure that is important in arousal and cognition and has been explored as a deep brain stimulation target but is difficult to study due to its small size, variability among patients, and lack of contrast on 3T MR imaging. Thus, our goal was to establish and evaluate a deep learning network for automatic, accurate, and patient-specific segmentations with 3T MR imaging. Patient-specific segmentations can be produced manually; however, the nucleus basalis of Meynert is difficult to accurately segment on 3T MR imaging, with 7T being preferred. Thus, paired 3T and 7T MR imaging data sets of 21 healthy subjects were obtained. A test data set of 6 subjects was completely withheld. The nucleus was expertly segmented on 7T, providing accurate labels for the paired 3T MR imaging. An external data set of 14 patients with temporal lobe epilepsy was used to test the model on brains with neurologic disorders. A 3D-Unet convolutional neural network was constructed, and a 5-fold cross-validation was performed. The novel segmentation model demonstrated significantly improved Dice coefficients over the standard probabilistic atlas for both healthy subjects (mean, 0.68 [SD, 0.10] versus 0.45 [SD, 0.11], We developed the first model, to our knowledge, for automatic and accurate patient-specific segmentation of the nucleus basalis of Meynert. This model may enable further study into the nucleus, impacting new treatments such as deep brain stimulation.

Sections du résumé

BACKGROUND AND PURPOSE
The nucleus basalis of Meynert is a key subcortical structure that is important in arousal and cognition and has been explored as a deep brain stimulation target but is difficult to study due to its small size, variability among patients, and lack of contrast on 3T MR imaging. Thus, our goal was to establish and evaluate a deep learning network for automatic, accurate, and patient-specific segmentations with 3T MR imaging.
MATERIALS AND METHODS
Patient-specific segmentations can be produced manually; however, the nucleus basalis of Meynert is difficult to accurately segment on 3T MR imaging, with 7T being preferred. Thus, paired 3T and 7T MR imaging data sets of 21 healthy subjects were obtained. A test data set of 6 subjects was completely withheld. The nucleus was expertly segmented on 7T, providing accurate labels for the paired 3T MR imaging. An external data set of 14 patients with temporal lobe epilepsy was used to test the model on brains with neurologic disorders. A 3D-Unet convolutional neural network was constructed, and a 5-fold cross-validation was performed.
RESULTS
The novel segmentation model demonstrated significantly improved Dice coefficients over the standard probabilistic atlas for both healthy subjects (mean, 0.68 [SD, 0.10] versus 0.45 [SD, 0.11],
CONCLUSIONS
We developed the first model, to our knowledge, for automatic and accurate patient-specific segmentation of the nucleus basalis of Meynert. This model may enable further study into the nucleus, impacting new treatments such as deep brain stimulation.

Identifiants

DOI: 10.3174/ajnr.A7950 PMID: 37562826 PMC: PMC10494939
pubmed: 37562826
pii: ajnr.A7950
doi: 10.3174/ajnr.A7950
pmc: PMC10494939
doi:

Types de publication

Journal Article Research Support, N.I.H., Extramural

Langues

eng

Sous-ensembles de citation

IM

Pagination

1020-1025

Subventions

Organisme : NIBIB NIH HHS
ID : T32 EB001628
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS112252
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS116504
Pays : United States
Organisme : NINDS NIH HHS
ID : F31 NS106735
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM007347
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS108445
Pays : United States
Organisme : NINDS NIH HHS
ID : F31 NS120401
Pays : United States
Organisme : NIBIB NIH HHS
ID : T32 EB021937
Pays : United States
Organisme : NINDS NIH HHS
ID : R01 NS110130
Pays : United States

Informations de copyright

© 2023 by American Journal of Neuroradiology.

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Auteurs

D J Doss (DJ)

From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee derekjdoss@gmail.com.
Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee.
ORCID: 0000-0002-2685-0762

G W Johnson (GW)

From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee.
Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee.
ORCID: 0000-0002-9154-4315

S Narasimhan (S)

From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee.
Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee.
Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee.
ORCID: 0000-0002-2965-2200

J S Shless (JS)

Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee.
ORCID: 0000-0003-0702-4454

J W Jiang (JW)

Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee.

H F J González (HFJ)

From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee.
Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee.
ORCID: 0000-0002-1831-2091

D L Paulo (DL)

Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee.
ORCID: 0000-0002-2292-1164

A Lucas (A)

Department of Bioengineering (A.L.), University of Pennsylvania, Philadelphia, Pennsylvania.
ORCID: 0000-0001-9439-735X

K A Davis (KA)

Department of Neuroscience (K.A.D.), University of Pennsylvania, Philadelphia, Pennsylvania.
Center for Neuroengineering and Therapeutics (K.A.D.), University of Pennsylvania, Philadelphia, Pennsylvania.
Neurology (K.A.D.), University of Pennsylvania, Philadelphia, Pennsylvania.
ORCID: 0000-0002-7020-6480

C Chang (C)

From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee.
Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee.
Department of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Department of Computer Science (C. Chang), Vanderbilt University, Nashville, Tennessee.
ORCID: 0000-0003-1541-9579

V L Morgan (VL)

From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee.
Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee.
Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee.
Department of Neurology (V.L.M.), Vanderbilt University Medical Center, Nashville, Tennessee.
Department of Radiological Sciences (V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee.
ORCID: 0000-0001-8263-2324

C Constantinidis (C)

From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee.
Department of Ophthalmology and Visual Sciences (C. Constantinidis), Vanderbilt University Medical Center, Nashville, Tennessee.
Department of Neuroscience (C. Constantinidis), Vanderbilt University, Nashville, Tennessee.
ORCID: 0000-0001-7441-022X

B M Dawant (BM)

Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee.
Department of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
ORCID: 0000-0002-3804-8400

D J Englot (DJ)

From the Department of Biomedical Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang., V.L.M., C. Constantinidis, D.J.E.), Vanderbilt University, Nashville, Tennessee.
Institute of Imaging Science (D.J.D., G.W.J., S.N., J.S.S., J.W.J., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Vanderbilt Institute for Surgery and Engineering (D.J.D., G.W.J., S.N., H.F.J.G., C. Chang, V.L.M., B.M.D., D.J.E.), Nashville, Tennessee.
Department of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee.
Department of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.), Vanderbilt University, Nashville, Tennessee.
Department of Radiological Sciences (V.L.M., D.J.E.), Vanderbilt University Medical Center, Nashville, Tennessee.
ORCID: 0000-0001-8373-690X

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Classifications MeSH

questionsmedicales.fr › Eucaryotes › Animaux › Chordés › Vertébrés › Mammifères › Eutheria › Primates › Haplorhini › Catarrhini › Hominidae › Humains › Deep Learning Segmentation of the Nucleus...
questionsmedicales.fr › Système nerveux › Système nerveux central › Encéphale › Prosencéphale › Télencéphale › Cerveau › Noyaux gris centraux › Substance innominée › Noyau basal de Meynert › Deep Learning Segmentation of the Nucleus...
questionsmedicales.fr › Sciences de l'information › Méthodologies informatiques › Algorithmes › Intelligence artificielle › Réseaux neuronaux (ordinateur) › Apprentissage profond › Deep Learning Segmentation of the Nucleus...
questionsmedicales.fr › Diagnostic › Techniques et procédures diagnostiques › Imagerie diagnostique › Tomographie › Imagerie par résonance magnétique › Deep Learning Segmentation of the Nucleus...
questionsmedicales.fr › Système nerveux › Système nerveux central › Encéphale › Deep Learning Segmentation of the Nucleus...
questionsmedicales.fr › Phénomènes psychologiques › Processus mentaux › Cognition › Deep Learning Segmentation of the Nucleus...