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Research ArticleORIGINAL RESEARCH

Super-Resolution in Clinically Available Spinal Cord MRIs Enables Automated Atrophy Analysis

Blake E. Dewey, Samuel W. Remedios, Muraleetharan Sanjayan, Nicole Bou Rjeily, Alexandra Zambriczki Lee, Chelsea Wyche, Safiya Duncan, Jerry L. Prince, Peter. A. Calabresi, Kathryn C. Fitzgerald and Ellen M. Mowry
American Journal of Neuroradiology October 2024, ajnr.A8526; DOI: https://doi.org/10.3174/ajnr.A8526
Blake E. Dewey
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Samuel W. Remedios
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Muraleetharan Sanjayan
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Nicole Bou Rjeily
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Alexandra Zambriczki Lee
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Chelsea Wyche
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Safiya Duncan
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Jerry L. Prince
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Peter. A. Calabresi
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Kathryn C. Fitzgerald
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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Ellen M. Mowry
From the Department of Neurology (B.E.D., M.S., N.B., A.Z.L., C.W., S.D., P.A.C., K.C.F., E.M.M.), Department of Computer Science (S.W.R.) and Department of Electrical and Computer Engineering (J.L.P.) Johns Hopkins University, Baltimore, Maryland, U.S.A
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ABSTRACT

BACKGROUND AND PURPOSE: Measurement of the mean upper cervical cord area (MUCCA) is an important biomarker in the study of neurodegeneration. However, dedicated high-resolution scans of the cervical spinal cord are rare in standard-of-care imaging due to timing and clinical usability. Most clinical cervical spinal cord imaging is sagittally acquired in 2D with thick slices and anisotropic voxels. As a solution, previous work describes high-resolution T1-weighted brain imaging for measuring the upper cord area, but this is still not common in clinical care.

MATERIALS AND METHODS: We propose using a zero-shot super-resolution technique, SMORE, already validated in the brain, to enhance the resolution of 2D-acquired scans for upper cord area calculations. To incorporate super-resolution in spinal cord analysis, we validate SMORE against high-resolution research imaging and in a real-world longitudinal data analysis.

RESULTS: Super-resolved images reconstructed using SMORE showed significantly greater similarity to the ground truth than low-resolution images across all tested resolutions (p<0.001 for all resolutions in PSNR and MSSIM). MUCCA results from super-resolved scans demonstrate excellent correlation with high-resolution scans (r>0.973 for all resolutions) compared to low-resolution scans. Additionally, super-resolved scans are consistent between resolutions (r>0.969), an essential factor in longitudinal analysis. Compared to clinical outcomes such as walking speed or disease severity, MUCCA values from low-resolution scans have significantly lower correlations than those from high-resolution scans. Super-resolved results have no significant difference. In a longitudinal real-world dataset, we show that these super-resolved volumes can be used in conjunction with T1-weighted brain scans to show a significant rate of atrophy (-0.790, p=0.020 vs. -0.438, p=0.301 with low-resolution).

CONCLUSIONS: Super-resolution is a valuable tool for enabling large-scale studies of cord atrophy, as low-resolution images acquired in clinical practice are common and available.

ABBREVIATIONS: MS=multiple sclerosis; MUCCA=mean upper cervical cord; HR=high-resolution; LR=low-resolution; SR=superresolved; CSC=cervical spinal cord; PMJ=pontomedullary junction; MSSIM=mean structural similarity; PSNR=peak signal-to-noise ratio; EDSS=expanded disability status scale.

Footnotes

  • All other authors declare no conflicts of interest related to the content of this article.

  • © 2024 by American Journal of Neuroradiology

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Cite this article
Accepted Manuscript
Blake E. Dewey, Samuel W. Remedios, Muraleetharan Sanjayan, Nicole Bou Rjeily, Alexandra Zambriczki Lee, Chelsea Wyche, Safiya Duncan, Jerry L. Prince, Peter. A. Calabresi, Kathryn C. Fitzgerald, Ellen M. Mowry
Super-Resolution in Clinically Available Spinal Cord MRIs Enables Automated Atrophy Analysis
American Journal of Neuroradiology Oct 2024, ajnr.A8526; DOI: 10.3174/ajnr.A8526

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Accepted Manuscript
Super-Resolution in Clinically Available Spinal Cord MRIs Enables Automated Atrophy Analysis
Blake E. Dewey, Samuel W. Remedios, Muraleetharan Sanjayan, Nicole Bou Rjeily, Alexandra Zambriczki Lee, Chelsea Wyche, Safiya Duncan, Jerry L. Prince, Peter. A. Calabresi, Kathryn C. Fitzgerald, Ellen M. Mowry
American Journal of Neuroradiology Oct 2024, ajnr.A8526; DOI: 10.3174/ajnr.A8526
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