MRI-Based Methods for Spinal Cord Atrophy Evaluation: A Comparison of Cervical Cord Cross-Sectional Area, Cervical Cord Volume, and Full Spinal Cord Volume in Patients with Aquaporin-4 Antibody Seropositive Neuromyelitis Optica Spectrum Disorders

References

1. 1.↵
   2. Filippi M,
   3. Rocca MA,
   4. Ciccarelli O, et al

   ; MAGNIMS Study Group. MRI criteria for the diagnosis of multiple sclerosis: MAGNIMS consensus guidelines. Lancet Neurol 2016;15:292–303 doi:10.1016/S1474-4422(15)00393-2 pmid:26822746

   CrossRefPubMed
2. 2.↵
   2. Pittock SJ,
   3. Lennon VA,
   4. Krecke K, et al

   . Brain abnormalities in neuromyelitis optica. Arch Neurol 2006;63:390–96 doi:10.1001/archneur.63.3.390 pmid:16533966

   CrossRefPubMedWeb of Science
3. 3.↵
   2. Kim HJ,
   3. Paul F,
   4. Lana-Peixoto MA, et al

   ; Guthy-Jackson Charitable Foundation NMO International Clinical Consortium & Biorepository. MRI characteristics of neuromyelitis optica spectrum disorder: an international update. Neurology 2015;84:1165–73 doi:10.1212/WNL.0000000000001367 pmid:25695963

   Abstract/FREE Full Text
4. 4.↵
   2. Asgari N,
   3. Flanagan EP,
   4. Fujihara K, et al

   . Disruption of the leptomeningeal blood barrier in neuromyelitis optica spectrum disorder. Neurol Neuroimmunol Neuroinflamm 2017;4:e343 doi:10.1212/NXI.0000000000000343 pmid:28451627

   Abstract/FREE Full Text
5. 5.↵
   2. Schmidt F,
   3. Zimmermann H,
   4. Mikolajczak J, et al

   . Severe structural and functional visual system damage leads to profound loss of vision-related quality of life in patients with neuromyelitis optica spectrum disorders. Mult Scler Relat Disord 2017;11:45–50 doi:10.1016/j.msard.2016.11.008 pmid:28104256

   CrossRefPubMed
6. 6.↵
   2. Oertel FC,
   3. Kuchling J,
   4. Zimmermann H, et al

   . Microstructural visual system changes in AQP4-antibody-seropositive NMOSD. Neurol Neuroimmunol Neuroinflamm 2017;4:e334 doi:10.1212/NXI.0000000000000334 pmid:28255575

   CrossRefPubMed
7. 7.↵
   2. Wingerchuk DM,
   3. Banwell B,
   4. Bennett JL, et al

   ; International Panel for NMO Diagnosis. International consensus diagnostic criteria for neuromyelitis optica spectrum disorders. Neurology 2015;85:177–89 doi:10.1212/WNL.0000000000001729 pmid:26092914

   CrossRefPubMed
8. 8.↵
   2. Pekcevik Y,
   3. Mitchell CH,
   4. Mealy MA, et al

   . Differentiating neuromyelitis optica from other causes of longitudinally extensive transverse myelitis on spinal magnetic resonance imaging. Mult Scler 2016;22:302–11 doi:10.1177/1352458515591069 pmid:26209588

   CrossRefPubMed
9. 9.↵
   2. Akaishi T,
   3. Nakashima I,
   4. Sato DK, et al

   . Neuromyelitis optica spectrum disorders. Neuroimaging Clin N Am 2017;27:251–65 doi:10.1016/j.nic.2016.12.010 pmid:28391784

   CrossRefPubMed
10. 10.↵
    2. Wang Y,
    3. Wu A,
    4. Chen X, et al

    . Comparison of clinical characteristics between neuromyelitis optica spectrum disorders with and without spinal cord atrophy. BMC Neurol 2014;14:246 doi:10.1186/s12883-014-0246-4 pmid:25526927

    CrossRefPubMed
11. 11.↵
    2. Stevenson VL,
    3. Leary SM,
    4. Losseff NA, et al

    . Spinal cord atrophy and disability in MS: a longitudinal study. Neurology 1998;51:234–38 doi:10.1212/WNL.51.1.234 pmid:9674808

    Abstract/FREE Full Text
12. 12.↵
    2. Losseff NA,
    3. Webb SL,
    4. O'Riordan JI, et al

    . Spinal cord atrophy and disability in multiple sclerosis: a new reproducible and sensitive MRI method with potential to monitor disease progression. Brain 1996;119(Pt 3):701–08 doi:10.1093/brain/119.3.701 pmid:8673483

    CrossRefPubMedWeb of Science
13. 13.↵
    2. Daams M,
    3. Weiler F,
    4. Steenwijk MD, et al

    . Mean upper cervical cord area (MUCCA) measurement in long-standing multiple sclerosis: relation to brain findings and clinical disability. Mult Scler 2014;20:1860–65 doi:10.1177/1352458514533399 pmid:24812042

    CrossRefPubMed
14. 14.↵
    2. Liu Z,
    3. Yaldizli Ö,
    4. Pardini M, et al

    . Cervical cord area measurement using volumetric brain magnetic resonance imaging in multiple sclerosis. Mult Scler Relat Disord 2015;4:52–57 doi:10.1016/j.msard.2014.11.004 pmid:25787053

    CrossRefPubMed
15. 15.↵
    2. Liu Y,
    3. Lukas C,
    4. Steenwijk MD, et al

    . Multicenter validation of mean upper cervical cord area measurements from head 3D T1-weighted MR imaging in patients with multiple sclerosis. AJNR Am J Neuroradiol 2016;37:749–54 doi:10.3174/ajnr.A4635 pmid:26659338

    Abstract/FREE Full Text
16. 16.↵
    2. Jarius S,
    3. Ruprecht K,
    4. Kleiter I, et al

    ; in cooperation with the Neuromyelitis Optica Study Group (NEMOS). MOG-IgG in NMO and related disorders: a multicenter study of 50 patients, part 2—epidemiology, clinical presentation, radiological and laboratory features, treatment responses, and long-term outcome. J Neuroinflammation 2016;13:280 doi:10.1186/s12974-016-0718-0 pmid:27793206

    CrossRefPubMed
17. 17.↵
    2. Sato DK,
    3. Callegaro D,
    4. Lana-Peixoto MA, et al

    . Distinction between MOG antibody-positive and AQP4 antibody-positive NMO spectrum disorders. Neurology 2014;82:474–81 doi:10.1212/WNL.0000000000000101 pmid:24415568

    Abstract/FREE Full Text
18. 18.↵
    2. Zekeridou A,
    3. Lennon VA

    . Aquaporin-4 autoimmunity. Neurol Neuroimmunol Neuroinflamm 2015;2:e110 doi:10.1212/NXI.0000000000000110 pmid:26185772

    Abstract/FREE Full Text
19. 19.↵
    2. Horsfield MA,
    3. Sala S,
    4. Neema M, et al

    . Rapid semi-automatic segmentation of the spinal cord from magnetic resonance images: application in multiple sclerosis. Neuroimage 2010;50:446–55 doi:10.1016/j.neuroimage.2009.12.121 pmid:20060481

    CrossRefPubMedWeb of Science
20. 20.↵
    2. Kim G,
    3. Khalid F,
    4. Oommen VV, et al

    . T1- vs. T2-based MRI measures of spinal cord volume in healthy subjects and patients with multiple sclerosis. BMC Neurol 2015;15:124 doi:10.1186/s12883-015-0387-0 pmid:26227960

    CrossRefPubMed
21. 21.↵
    2. Castellano A,
    3. Papinutto N,
    4. Cadioli M, et al

    . Quantitative MRI of the spinal cord and brain in adrenomyeloneuropathy: in vivo assessment of structural changes. Brain 2016;139(Pt 6):1735–46 doi:10.1093/brain/aww068 pmid:27068048

    CrossRefPubMed
22. 22.↵
    2. Cawley N,
    3. Tur C,
    4. Prados F, et al

    . Spinal cord atrophy as a primary outcome measure in phase II trials of progressive multiple sclerosis. Mult Scler 2017 May 1. [Epub ahead of print] doi:10.1177/1352458517709954 pmid:28516804

    CrossRefPubMed
23. 23.↵
    2. Hajian-Tilaki K

    . Receiver operating characteristic (ROC) curve analysis for medical diagnostic test evaluation. Caspian J Intern Med 2013;4:627–35 pmid:24009950

    PubMed
24. 24.↵
    R Core Team. R version 3.4.1. 2014. http://www.R-project.org/.
25. 25.↵
    2. Wickham H

    . Tidyverse: Easily Install and Load the “Tidyverse.” November 14, 2017. https://CRAN.R-project.org/package=tidyverse. Accessed April 27, 2018
26. 26.↵
    2. Kassambara A

    . ggpubr: “ggplot2” Based Publication Ready Plots. November 14, 2017. https://cran.r-project.org/web/packages/ggpubr/index.html. Accessed April 27, 2018
27. 27.↵
    2. Robin X,
    3. Turck N,
    4. Hainard A, et al

    . pROC: an open-source package for R and S+ to analyze and compare receiver operating characteristic curves. BMC Bioinformatics 2011;12:77 doi:10.1186/1471-2105-12-77 pmid:21414208

    CrossRefPubMed
28. 28.↵
    2. Ontaneda D,
    3. Cohen JA,
    4. Amato MP

    . Clinical outcome measures for progressive MS trials. Mult Scler 2017;23:1627–35 doi:10.1177/1352458517729465 pmid:29041863

    CrossRefPubMed
29. 29.↵
    2. Liu Y,
    3. Wang J,
    4. Daams M, et al

    . Differential patterns of spinal cord and brain atrophy in NMO and MS. Neurology 2015;84:1465–72 doi:10.1212/WNL.0000000000001441 pmid:25762714

    Abstract/FREE Full Text
30. 30.↵
    2. Ventura RE,
    3. Kister I,
    4. Chung S, et al

    . Cervical spinal cord atrophy in NMOSD without a history of myelitis or MRI-visible lesions. Neurol Neuroimmunol Neuroinflamm 2016;3:e224 doi:10.1212/NXI.0000000000000224 pmid:27144215

    CrossRefPubMed
31. 31.↵
    2. Skates SJ

    . A statistical challenge: developing tests for biomarker utility specific to the intended use. J Natl Cancer Inst 2014;106:dju076 doi:10.1093/jnci/dju076 pmid:24681600

    CrossRefPubMed
32. 32.↵
    2. Chen W,
    3. Samuelson FW,
    4. Gallas BD, et al

    . On the assessment of the added value of new predictive biomarkers. BMC Med Res Methodol 2013;13:98 doi:10.1186/1471-2288-13-98 pmid:23895587

    CrossRefPubMed
33. 33.↵
    2. Wang Y,
    3. Wang Y,
    4. Tan S, et al

    . Spinal cord atrophy in neuromyelitis optica spectrum disorders. Mult Scler Relat Disord 2016;8:9–10 doi:10.1016/j.msard.2016.04.007 pmid:27456868

    CrossRefPubMed
34. 34.↵
    2. Liu Y,
    3. Duan Y,
    4. Huang J, et al

    . Different patterns of longitudinal brain and spinal cord changes and their associations with disability progression in NMO and MS. Eur Radiol 2018;28:96–103 doi:10.1007/s00330-017-4921-x pmid:28667482

    CrossRefPubMed
35. 35.↵
    2. Cree BA,
    3. Bennett JL,
    4. Sheehan M, et al

    . Placebo-controlled study in neuromyelitis optica: ethical and design considerations. Mult Scler 2016;22:862–72 doi:10.1177/1352458515620934 pmid:26666258

    CrossRefPubMed
36. 36.↵
    2. Healy BC,
    3. Arora A,
    4. Hayden DL, et al

    . Approaches to normalization of spinal cord volume: application to multiple sclerosis. J Neuroimaging 2012;22:e12–19 doi:10.1111/j.1552-6569.2011.00629.x pmid:21854479

    CrossRefPubMedWeb of Science
37. 37.↵
    2. Oh J,
    3. Seigo M,
    4. Saidha S, et al

    . Spinal cord normalization in multiple sclerosis. J Neuroimaging 2014;24:577–84 doi:10.1111/jon.12097 pmid:24593281

    CrossRefPubMed
38. 38.↵
    2. Kearney H,
    3. Yiannakas MC,
    4. Abdel-Aziz K, et al

    . Improved MRI quantification of spinal cord atrophy in multiple sclerosis. J Magn Reson Imaging 2014;39:617–23 doi:10.1002/jmri.24194 pmid:23633384

    CrossRefPubMed
39. 39.↵
    2. Papinutto N,
    3. Schlaeger R,
    4. Panara V, et al

    . Age, gender and normalization covariates for spinal cord gray matter and total cross-sectional areas at cervical and thoracic levels: a 2D phase sensitive inversion recovery imaging study. PLoS One 2015;10:e0118576 doi:10.1371/journal.pone.0118576 pmid:25781178

    CrossRefPubMed
40. 40.↵
    2. Zamvil SS,
    3. Slavin AJ

    . Does MOG Ig-positive AQP4-seronegative opticospinal inflammatory disease justify a diagnosis of NMO spectrum disorder? Neurol Neuroimmunol Neuroinflamm 2015;2:e62 doi:10.1212/NXI.0000000000000062 pmid:25635259

    CrossRefPubMed
41. 41.↵
    2. Jarius S,
    3. Ruprecht K,
    4. Kleiter I, et al

    ; in cooperation with the Neuromyelitis Optica Study Group (NEMOS). MOG-IgG in NMO and related disorders: a multicenter study of 50 patients, Part 1: frequency, syndrome specificity, influence of disease activity, long-term course, association with AQP4-IgG, and origin. J Neuroinflammation 2016;13:279 doi:10.1186/s12974-016-0717-1 pmid:27788675

    CrossRefPubMed
42. 42.↵
    2. Ozturk A,
    3. Aygun N,
    4. Smith SA, et al

    . Axial 3D gradient-echo imaging for improved multiple sclerosis lesion detection in the cervical spinal cord at 3T. Neuroradiology 2013;55:431–39 doi:10.1007/s00234-012-1118-5 pmid:23208410

    CrossRefPubMed
43. 43.↵
    2. Finke C,
    3. Heine J,
    4. Pache F, et al

    . Normal volumes and microstructural integrity of deep gray matter structures in AQP4+ NMOSD. Neurol Neuroimmunol Neuroinflamm 2016;3:e229 doi:10.1212/NXI.0000000000000229 pmid:27144219

    Abstract/FREE Full Text
44. 44.↵
    2. Pache F,
    3. Zimmermann H,
    4. Finke C, et al

    . Brain parenchymal damage in neuromyelitis optica spectrum disorder: a multimodal MRI study. Eur Radiol 2016;26:4413–22 doi:10.1007/s00330-016-4282-x pmid:27012555

    CrossRefPubMed
45. 45.↵
    2. Dupont SM,
    3. De Leener B,
    4. Taso M, et al

    . Fully-integrated framework for the segmentation and registration of the spinal cord white and gray matter. Neuroimage 2017;150:358–72 doi:10.1016/j.neuroimage.2016.09.02672 pmid:27663988

    CrossRefPubMed