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Research ArticleAdult Brain
Open Access

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

D.J. Doss, G.W. Johnson, S. Narasimhan, J.S. Shless, J.W. Jiang, H.F.J. González, D.L. Paulo, A. Lucas, K.A. Davis, C. Chang, V.L. Morgan, C. Constantinidis, B.M. Dawant and D.J. Englot
American Journal of Neuroradiology August 2023, DOI: https://doi.org/10.3174/ajnr.A7950
D.J. Doss
aFrom 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.)
bInstitute 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.)
fVanderbilt 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
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  • ORCID record for D.J. Doss
G.W. Johnson
aFrom 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.)
bInstitute 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.)
fVanderbilt 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
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S. Narasimhan
aFrom 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.)
bInstitute 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.)
fVanderbilt 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
gDepartments of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.)
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J.S. Shless
bInstitute 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.)
gDepartments of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.)
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J.W. Jiang
bInstitute 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.)
gDepartments of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.)
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H.F.J. González
aFrom 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.)
bInstitute 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.)
fVanderbilt 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
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D.L. Paulo
gDepartments of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.)
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A. Lucas
kDepartments of Bioengineering (A.L.)
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K.A. Davis
lNeuroscience (K.A.D.)
mCenter for Neuroengineering and Therapeutics (K.A.D.)
nDepartment of Neurology (K.A.D.), University of Pennsylvania, Philadelphia, Pennsylvania
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C. Chang
aFrom 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.)
bInstitute 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.)
cDepartments of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.)
dComputer Science (C. Chang)
fVanderbilt 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
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V.L. Morgan
aFrom 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.)
bInstitute 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.)
fVanderbilt 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
gDepartments of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.)
hNeurology (V.L.M.)
iRadiological Sciences (V.L.M., D.J.E.)
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  • ORCID record for V.L. Morgan
C. Constantinidis
aFrom 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.)
eNeuroscience (C. Constantinidis), Vanderbilt University, Nashville, Tennessee
jOphthalmology and Visual Sciences (C. Constantinidis), Vanderbilt University Medical Center, Nashville, Tennessee
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B.M. Dawant
bInstitute 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.)
cDepartments of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.)
fVanderbilt 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
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D.J. Englot
aFrom 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.)
bInstitute 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.)
cDepartments of Electrical and Computer Engineering (C. Chang, B.M.D., D.J.E.)
fVanderbilt 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
gDepartments of Neurological Surgery (S.N., J.S.S., J.W.J., D.L.P., V.L.M., D.J.E.)
iRadiological Sciences (V.L.M., D.J.E.)
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Figures

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  • FIG 1.
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    FIG 1.

    Comparison of the probabilistic and manual labels on a similar coronal section of the Montreal Neurological Institute 152 atlas space brain and a subject’s 7T brain. The left NBM is shown in blue, and the right NBM is shown in red.

  • FIG 2.
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    FIG 2.

    Flow chart describing how the 7T NBM segmentation is used for training the network to segment the NBM on 3T MR imaging.

  • FIG 3.
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    FIG 3.

    Example of favorable (A, right), average (A, middle), and poor (A, left) performance. Blue is the correct prediction of NBM, red is the overpredicted NBM (false-positive), and yellow is the ground truth label that was not predicted (false-negative). The Dice coefficient of the favorable example (right) was 0.82, the Dice coefficient of the average example (middle) was 0.63, and the Dice coefficient of the poor example (left) was 0.55. B, The Dice coefficient. C, The mean surface distance. D, The centroid distance of DnSeg versus the probabilistic atlas for both healthy subjects and patients with TLE. The healthy subjects included the nonaugmented held-out test data set (n = 6). The patients with TLE were also not augmented and were held out until final analysis (n = 14). Paired t test: single asterisk indicates P < .05; double asterisks, P < .01; triple asterisks, P < .001.

  • FIG 4.
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    FIG 4.

    Increased accuracy of NBM electrode targeting with DnSeg. The orange electrode was placed in the center of the NBM segmentation generated by the probabilistic atlas. The blue electrode was placed in the center of the segmentation generated by DnSeg. D, Both electrode positions compared with the ground truth segmentation mesh. The ground truth NBM (manually segmented on 7T MR imaging) is shown in red. The outline of the ground truth NBM as well as the lead trajectories can be seen in A, B, and C. The sample DBS planning for this figure was generated using CRAnial Vault Explorer.23

Tables

  • Figures
  • Data set demographicsa

    Healthy subjects, Vanderbilt
     No.11
     Sex3 Female
     Age (yr)38.3 (SD, 10.9)
    Healthy subjects, Amsterdam
     No.10
     Sex8 Female
     Age (yr)25.9 (SD, 5.8)
    Patients with TLE
     No.14
     Age (yr)30.0 (SD, 7.5)
     Sex7 Female
     Disease duration (yr)11.0 (SD, 11.7)
     Number lesional7
    • ↵a Demographics of both the healthy subject data set and the TLE data set. Data are counts or mean (SD).

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Cite this article
D.J. Doss, G.W. Johnson, S. Narasimhan, J.S. Shless, J.W. Jiang, H.F.J. González, D.L. Paulo, A. Lucas, K.A. Davis, C. Chang, V.L. Morgan, C. Constantinidis, B.M. Dawant, D.J. Englot
Deep Learning Segmentation of the Nucleus Basalis of Meynert on 3T MRI
American Journal of Neuroradiology Aug 2023, DOI: 10.3174/ajnr.A7950

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Deep Learning Segmentation of the Nucleus Basalis of Meynert on 3T MRI
D.J. Doss, G.W. Johnson, S. Narasimhan, J.S. Shless, J.W. Jiang, H.F.J. González, D.L. Paulo, A. Lucas, K.A. Davis, C. Chang, V.L. Morgan, C. Constantinidis, B.M. Dawant, D.J. Englot
American Journal of Neuroradiology Aug 2023, DOI: 10.3174/ajnr.A7950
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