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Research ArticleAdult Brain
Open Access

Cortical and Subcortical Brain Atrophy Assessment Using Simple Measures on NCCT Compared with MRI in Acute Stroke

Tanaporn Jaroenngarmsamer, Faysal Benali, Joachim Fladt, Nishita Singh, Fouzi Bala, Michael Tymianski, Michael D. Hill, Mayank Goyal, Aravind Ganesh and On behalf of the ESCAPE-NA1 Investigators
American Journal of Neuroradiology October 2023, 44 (10) 1144-1149; DOI: https://doi.org/10.3174/ajnr.A7981

References

  1. 1.↵
    1. Rabinstein AA,
    2. Albers GW,
    3. Brinjikji W, et al
    . Factors that may contribute to poor outcome despite good reperfusion after acute endovascular stroke therapy. Int J Stroke 2019;14:23–31 doi:10.1177/1747493018799979 pmid:30188259
    CrossRefPubMed
  2. 2.↵
    1. Pedraza MI,
    2. de Lera M,
    3. Bos D, et al
    . Brain atrophy and the risk of futile endovascular reperfusion in acute ischemic stroke. Stroke 2020;51:1514–21 doi:10.1161/STROKEAHA.119.028511 pmid:32188368
    CrossRefPubMed
  3. 3.↵
    1. Luijten SP,
    2. Compagne KC,
    3. van Es AC, et al
    . Brain atrophy and endovascular treatment effect in acute ischemic stroke: a secondary analysis of the MR CLEAN trial. Int J Stroke 2021 Oct 28. [Epub ahead of print] doi:10.1177/17474930211054964 pmid:34711105
    CrossRefPubMed
  4. 4.↵
    1. Lauksio I,
    2. Lindström I,
    3. Khan N, et al
    . Brain atrophy predicts mortality after mechanical thrombectomy of proximal anterior circulation occlusion. J Neurointerv Surg 2021;13:415–20 doi:10.1136/neurintsurg-2020-016168 pmid:32620574
    CrossRefPubMed
  5. 5.↵
    1. Lamballais S,
    2. Zijlmans JL,
    3. Vernooij MW, et al
    . The risk of dementia in relation to cognitive and brain reserve. J Alzheimers Dis 2020;77:607–18 doi:10.3233/JAD-200264 pmid:32741820
    CrossRefPubMed
  6. 6.↵
    1. Fuchs TA,
    2. Benedict RH,
    3. Bartnik A, et al
    . Preserved network functional connectivity underlies cognitive reserve in multiple sclerosis. Hum Brain Mapp 2019;40:5231–41 doi:10.1002/hbm.24768 pmid:31444887
    CrossRefPubMed
  7. 7.↵
    1. Yoon HJ,
    2. Kim SG,
    3. Kim SH, et al
    ; For the Alzheimer’s Disease Neuroimaing Initiative. Associations between brain reserve proxies and clinical progression in Alzheimer’s disease dementia. Int J Environ Res Public Health 2021;18:12159 doi:10.3390/ijerph182212159
    CrossRefPubMed
  8. 8.↵
    1. Benali F,
    2. Singh N,
    3. Fladt J, et al
    . Brain frailty mediates the relationship between age and 90-day functional outcome after endovascular therapy: analysis of the Escape-NA1 trial. Stroke 2023;54(Suppl1):AWMP57 doi:10.1161/str.54.suppl_1.WMP57
    CrossRef
  9. 9.↵
    1. Husseini NE,
    2. Katzan IL,
    3. Rost NS, et al
    ; American Heart Association Stroke Council; Council on Cardiovascular and Stroke Nursing; Council on Cardiovascular Radiology and Intervention; Council on Hypertension; and Council on Lifestyle and Cardiometabolic Health. Cognitive impairment after ischemic and hemorrhagic stroke: a scientific statement from the American Heart Association/American Stroke Association. Stroke 2023;54:e272–91 doi:10.1161/STR.0000000000000430 pmid:37125534
    CrossRefPubMed
  10. 10.↵
    1. Bigler ED
    . The clinical significance of cerebral atrophy in traumatic brain injury. Arch Clin Neuropsychol 1987;2:293–304 pmid:14589621
    CrossRefPubMed
  11. 11.↵
    1. Caspers J,
    2. Heeger A,
    3. Turowski B, et al
    . Automated age- and sex-specific volumetric estimation of regional brain atrophy: workflow and feasibility. Eur Radiol 2021;31:1043–48 doi:10.1007/s00330-020-07196-8 pmid:32852588
    CrossRefPubMed
  12. 12.↵
    1. Kaipainen AL,
    2. Pitkänen J,
    3. Haapalinna F, et al
    . A novel CT-based automated analysis method provides comparable results with MRI in measuring brain atrophy and white matter lesions. Neuroradiology 2021;63:2035–46 doi:10.1007/s00234-021-02761-4 pmid:34389887
    CrossRefPubMed
  13. 13.↵
    1. Pasquier F,
    2. Leys D,
    3. Weerts JG, et al
    . Inter- and intraobserver reproducibility of cerebral atrophy assessment on MRI scans with hemispheric infarcts. Eur Neurol 1996;36:268–72 doi:10.1159/000117270 pmid:8864706
    CrossRefPubMed
  14. 14.↵
    1. Koedam EL,
    2. Lehmann M,
    3. van der Flier WM, et al
    . Visual assessment of posterior atrophy development of an MRI rating scale. Eur Radiol 2011;21:2618–25 doi:10.1007/s00330-011-2205-4 pmid:21805370
    CrossRefPubMed
  15. 15.↵
    1. Torisson G,
    2. van Westen D,
    3. Stavenow L, et al
    . Medial temporal lobe atrophy is underreported and may have important clinical correlates in medical inpatients. BMC Geriatr 2015;15:65 doi:10.1186/s12877-015-0066-4 pmid:26076825
    CrossRefPubMed
  16. 16.↵
    1. van Zagten M,
    2. Kessels F,
    3. Boiten J, et al
    . Interobserver agreement in the assessment of cerebral atrophy on CT using bicaudate and Sylvian-fissure ratios. Neuroradiology 1999;41:261–64 doi:10.1007/s002340050743 pmid:10344510
    CrossRefPubMed
  17. 17.↵
    1. Kipps CM,
    2. Davies RR,
    3. Mitchell J, et al
    . Clinical significance of lobar atrophy in frontotemporal dementia: application of an MRI visual rating scale. Dement Geriatr Cogn Disord 2007;23:334–42 doi:10.1159/000100973 pmid:17374952
    CrossRefPubMed
  18. 18.↵
    1. Boldor N,
    2. Vaknin S,
    3. Myers V, et al
    . Reforming the MRI system: the Israeli National Program to shorten waiting times and increase efficiency. Isr J Health Policy Res 2021;10:57 doi:10.1186/s13584-021-00493-7 pmid:34663450
    CrossRefPubMed
  19. 19.↵
    1. Frija G,
    2. Blažić I,
    3. Frush DP, et al
    . How to improve access to medical imaging in low- and middle-income countries? EClinicalMedicine 2021;38:101034 doi:10.1016/j.eclinm.2021.101034 pmid:34337368
    CrossRefPubMed
  20. 20.↵
    1. Wattjes MP,
    2. Henneman WJ,
    3. van der Flier WM, et al
    . Diagnostic imaging of patients in a memory clinic: comparison of MR imaging and 64-detector row CT. Radiology 2009;253:174–83 doi:10.1148/radiol.2531082262 pmid:19635835
    CrossRefPubMed
  21. 21.↵
    1. Ferguson KJ,
    2. Cvoro V,
    3. MacLullich AM, et al
    . Visual rating scales of white matter hyperintensities and atrophy: comparison of computed tomography and magnetic resonance imaging. J Stroke Cerebrovasc Dis 2018;27:1815–21 doi:10.1016/j.jstrokecerebrovasdis.2018.02.028 pmid:29576397
    CrossRefPubMed
  22. 22.↵
    1. Lee SH,
    2. Oh CW,
    3. Han JH, et al
    . The effect of brain atrophy on outcome after a large cerebral infarction. J Neurol Neurosurg Psychiatry 2010;81:1316–21 doi:10.1136/jnnp.2009.197335 pmid:20650914
    CrossRefPubMed
  23. 23.↵
    1. Butzkueven H,
    2. Kolbe SC,
    3. Jolley DJ, et al
    . Validation of linear cerebral atrophy markers in multiple sclerosis. J Clin Neurosci 2008;15:130–37 doi:10.1016/j.jocn.2007.02.089 pmid:18068987
    CrossRefPubMed
  24. 24.↵
    1. Hill MD,
    2. Goyal M,
    3. Menon BK, et al
    ; ESCAPE-NA1 Investigators. Efficacy and Safety of Nerinetide for the Ttreatment of Acute Ischaemic Stroke (ESCAPE-NA1): a multicentre, double-blind, randomised controlled trial. Lancet 2020;395:878–87 doi:10.1016/S0140-6736(20)30258-0 pmid:32087818
    CrossRefPubMed
  25. 25.↵
    1. Schmaranzer F,
    2. Kallini JR,
    3. Miller PE, et al
    . The effect of modality and landmark selection on MRI and CT femoral torsion angles. Radiology 2020;296:381–90 doi:10.1148/radiol.2020192723 pmid:32515680
    CrossRefPubMed
  26. 26.↵
    1. Liao JJ
    . Sample size calculation for an agreement study. Pharm Stat 2010;9:125–32 doi:10.1002/pst.382 pmid:19507134
    CrossRefPubMed
  27. 27.↵
    1. Zec S,
    2. Soriani N,
    3. Comoretto R, et al
    . High agreement and high prevalence: the paradox of Cohen’s Kappa. Open Nurs J 2017;11:211–18 doi:10.2174/1874434601711010211 pmid:29238424
    CrossRefPubMed
  28. 28.↵
    1. Gwet KL
    . Computing inter-rater reliability and its variance in the presence of high agreement. Br J Math Stat Psychol 2008;61:29–48 doi:10.1348/000711006X126600 pmid:18482474
    CrossRefPubMed
  29. 29.↵
    1. Gwet KL
    . Testing the difference of correlated agreement coefficients for statistical significance. Educ Psychol Meas 2016;76:609–37 doi:10.1177/0013164415596420 pmid:29795880
    CrossRefPubMed
  30. 30.↵
    1. Wongpakaran N,
    2. Wongpakaran T,
    3. Wedding D, et al
    . A comparison of Cohen’s kappa and Gwet’s AC1 when calculating inter-rater reliability coefficients: a study conducted with personality disorder samples. BMC Med Res Methodol 2013;13:61 doi:10.1186/1471-2288-13-61 pmid:23627889
    CrossRefPubMed
  31. 31.↵
    1. Landis JR,
    2. Koch GG
    . The measurement of observer agreement for categorical data. Biometrics 1977;33:159–74
    CrossRefPubMedWeb of Science
  32. 32.↵
    1. Schober P,
    2. Boer C,
    3. Schwarte LA
    . Correlation coefficients: appropriate use and interpretation. Anesth Analg 2018;126:1763–68 doi:10.1213/ANE.0000000000002864 pmid:29481436
    CrossRefPubMed
  33. 33.↵
    1. Giavarina D
    . Understanding Bland Altman analysis. Biochem Med (Zagreb) 2015;25:141–51 doi:10.11613/BM.2015.015 pmid:26110027
    CrossRefPubMed
  34. 34.↵
    1. Bland JM,
    2. Altman DG
    . Statistical methods for assessing agreement between two methods of clinical measurement. Lancet 1986;1:307–10 pmid:2868172
    PubMedWeb of Science
  35. 35.↵
    1. Park J,
    2. Goh DH,
    3. Sung JK, et al
    . Timely assessment of infarct volume and brain atrophy in acute hemispheric infarction for early surgical decompression: strict cutoff criteria with high specificity. Acta Neurochir (Wien) 2012;154:79–85 doi:10.1007/s00701-011-1178-z pmid:21979162
    CrossRefPubMed
  36. 36.↵
    1. Benali F,
    2. Fladt J,
    3. Jaroenngarmsamer T, et al
    . Association of white matter disease with functional recovery and 90‐day outcome after EVT: beyond chronological age. Stroke Vasc Interv Neurol 2023;3:e000734 doi:10.1161/SVIN.122.000734
    CrossRef
  37. 37.↵
    1. Bretzner M,
    2. Bonkhoff AK,
    3. Schirmer MD, et al
    ; MRI-GENIE and GISCOME Investigators and the International Stroke Genetics Consortium. Radiomics-derived brain age predicts functional outcome after acute ischemic stroke. Neurology 2023;100:e822–33 doi:10.1212/WNL.0000000000201596 pmid:36443016
    CrossRefPubMed
  38. 38.↵
    1. Benali F,
    2. Fladt J,
    3. Jaroenngarmsamer T, et al
    . Association of brain atrophy with functional outcome and recovery trajectories after thrombectomy: Post-hoc analysis of the ESCAPE-NA1 Trial. Neurology 2023;17 doi:10.1212/WNL.0000000000207700 pmid:37591777
    CrossRefPubMed
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NCCT vs. MRI for Brain Atrophy in Acute Stroke
Tanaporn Jaroenngarmsamer, Faysal Benali, Joachim Fladt, Nishita Singh, Fouzi Bala, Michael Tymianski, Michael D. Hill, Mayank Goyal, Aravind Ganesh, On behalf of the ESCAPE-NA1 Investigators
American Journal of Neuroradiology Oct 2023, 44 (10) 1144-1149; DOI: 10.3174/ajnr.A7981
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