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Research ArticleAdult Brain
Open Access

Neuroanatomic Markers of Posttraumatic Epilepsy Based on MR Imaging and Machine Learning

H. Akrami, R.M. Leahy, A. Irimia, P.E. Kim, C.N. Heck and A.A. Joshi
American Journal of Neuroradiology March 2022, 43 (3) 347-353; DOI: https://doi.org/10.3174/ajnr.A7436
H. Akrami
aFrom the Department of Biomedical Engineering (H.A., A.I.)
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R.M. Leahy
bMing Hsieh Department of Electrical and Computer Engineering (R.M.L., A.A.J.)
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A. Irimia
aFrom the Department of Biomedical Engineering (H.A., A.I.)
cLeonard Davis School of Gerontology (A.I.)
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P.E. Kim
dDepartments of Radiology (P.E.K.)
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C.N. Heck
eNeurology (C.N.H.), University of Southern California, Los Angeles, California
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A.A. Joshi
bMing Hsieh Department of Electrical and Computer Engineering (R.M.L., A.A.J.)
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  • FIG 1.
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    FIG 1.

    The VAE network and an input/output sample pair from the ISLES data set. X denotes the input data; Z denotes its low-dimensional latent representation. The VAE consists of an encoder network that computes an approximate posterior qφ (Z|X), and a decoder network that computes pθ (X|Z). The VAE model takes T1, T2, and FLAIR images from individual subjects (left), compresses them to generate a latent representation (Z), and regenerates 3 images (right). The VAE is trained on a data set that contains few lesions. After training, when presented with a newly lesioned brain, the reconstruction effectively removes the lesion from the image, resulting in a normal (lesion-free) version of the brain.

  • FIG 2.
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    FIG 2.

    Three orthogonal views through the P values thresholded at P = .05 (FDR-corrected) obtained for the F-test for TBM analysis using Jacobian determinants. L indicates left; R, right.

  • FIG 3.
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    FIG 3.

    Reconstruction results obtained by applying the VAE to the ISLES data set. A, Sample slices from input images. B, Slices reconstructed from the VAE. C, Difference between input and reconstructed images. D, Error maps after applying median filtering to reduce the occurrence of spurious voxels. E, Manually delineated lesion masks used as ground truth to evaluate VAE performance.

  • FIG 4.
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    FIG 4.

    Orthogonal views through the P values thresholded at P = .05 (FDR-corrected) obtained for the F-test comparing lesion maps for the PTE and non-PTE groups. L indicates left; R, right.

Tables

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  • Lobe-wise lesion volumes as measured using a 1-class SVM to generate binary lesion maps

    LobePercentages of Lobe Volumes in Subjects with PTE (mean, median [SD])Percentages of Lobe Volumes in Subjects without PTE (mean, median [SD])P Value (F-Test)
    Right temporal5.267, 4.746 [1.496]4.888, 4.803 [0.819].003a
    Left temporal5.267, 4.993 [1.223]4.924, 4.871 [0.7661].02a
    Right occipital4.739, 4.131 [1.749]4.817, 4.724 [1.225].05a
    Left occipital4.472, 4.336 [1.358]4.658, 4.384 [1.001].08
    Right frontal5.223, 4.794 [1.416]5.456, 4.897 [1.868].95
    Left frontal5.513, 5.251 [1.646]5.342, 5.016 [1.399].31
    Right parietal5.113, 4.756 [1.353]5.197, 4.999 [1.337].65
    Left parietal4.943, 4.610 [1.183]5.134, 4.859 [1.320].82
    Right insula5.524, 5.319 [1.259]5.205, 5.147 [1.383].65
    Left insula5.229, 5.082 [1.067]4.797, 4.612 [1.045].82
    Cerebellum5.130, 4.758 [1.269]5.117, 5.046 [0.8524].03a
    • Note:—SVM indicates support vector machine.

    • ↵a Cases of significant differences in the variance of lesion volume between PTE and non-PTE (F-test). the FDR-corrected P values are shown at a significance level of α = .05. We report both mean and median lesion volumes.

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American Journal of Neuroradiology: 43 (3)
American Journal of Neuroradiology
Vol. 43, Issue 3
1 Mar 2022
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H. Akrami, R.M. Leahy, A. Irimia, P.E. Kim, C.N. Heck, A.A. Joshi
Neuroanatomic Markers of Posttraumatic Epilepsy Based on MR Imaging and Machine Learning
American Journal of Neuroradiology Mar 2022, 43 (3) 347-353; DOI: 10.3174/ajnr.A7436

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Neuroanatomic Markers of Posttraumatic Epilepsy Based on MR Imaging and Machine Learning
H. Akrami, R.M. Leahy, A. Irimia, P.E. Kim, C.N. Heck, A.A. Joshi
American Journal of Neuroradiology Mar 2022, 43 (3) 347-353; DOI: 10.3174/ajnr.A7436
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  • Prediction of Post Traumatic Epilepsy Using MR‐Based Imaging Markers
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