Validity Assessment of an Automated Brain Morphometry Tool for Patients with De Novo Memory Symptoms

References

1. 1.↵
   1. Knopman DS,
   2. DeKosky ST,
   3. Cummings JL, et al

   . Practice parameter: diagnosis of dementia (an evidence-based review): Report of the Quality Standards Subcommittee of the American Academy of Neurology. Neurology 2001;56:1143–53 doi:10.1212/WNL.56.9.1143 pmid:11342678

   CrossRefPubMed
2. 2.↵
   1. Desikan RS,
   2. Ségonne F,
   3. Fischl B, et al

   . An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest. Neuroimage 2006;31:968–80 doi:10.1016/j.neuroimage.2006.01.021 pmid:16530430

   CrossRefPubMedWeb of Science
3. 3.↵
   1. Fischl B

   . FreeSurfer. Neuroimage 2012;62:774–81 doi:10.1016/j.neuroimage.2012.01.021 pmid:22248573

   CrossRefPubMedWeb of Science
4. 4.↵
   1. Raji CA,
   2. Ly M,
   3. Benzinger TL

   . Overview of MR imaging volumetric quantification in neurocognitive disorders. Top Magn Reson Imaging 2019;28:311–15 doi:10.1097/RMR.0000000000000224 pmid:31794503

   CrossRefPubMed
5. 5.↵
   1. Owen CJ,
   2. Gordon B,
   3. Brier MR, et al

   . The ILP: a new tool for evaluating preclinical Alzheimer’s disease using volumetric MRI in a single participant. Alzheimers Dement 2015;11:P697 doi:10.1016/j.jalz.2015.06.121 pmid:8232972

   CrossRefPubMed
6. 6.↵
   1. Morris JC

   . The Clinical Dementia Rating (CDR). Neurology 1993;43:2412–14 doi:10.1212/wnl.43.11.2412-a pmid:8232972

   FREE Full Text
7. 7.↵
   1. Folstein MF,
   2. Folstein SE,
   3. McHugh PR

   . “Mini-Mental State”: a practical method for grading the cognitive state of patients for the clinician. J Psychiatr Res 1975;12:189–98 doi:10.1016/0022-3956(75)90026-6 pmid:1202204

   CrossRefPubMedWeb of Science
8. 8.↵
   1. McKhann GM,
   2. Knopman DS,
   3. Chertkow H, et al

   . The diagnosis of dementia due to Alzheimer’s disease: recommendations from the National Institute on Aging-Alzheimer’s Association workgroups on diagnostic guidelines for Alzheimer’s disease. Alzheimers Dement 2011;7:263–69 doi:10.1016/j.jalz.2011.03.005 pmid:21514250

   CrossRefPubMedWeb of Science
9. 9.↵
   1. McKeith IG,
   2. Boeve BF,
   3. Dickson DW, et al

   . Diagnosis and management of dementia with Lewy bodies: Fourth Consensus Report of the DLB Consortium. Neurology 2017;89:88–100 doi:10.1212/WNL.0000000000004058 pmid:28592453

   Abstract/FREE Full Text
10. 10.↵
    1. Rascovsky K,
    2. Hodges JR,
    3. Knopman D, et al

    . Sensitivity of revised diagnostic criteria for the behavioural variant of frontotemporal dementia. Brain 2011;134:2456–77 doi:10.1093/brain/awr179 pmid:21810890

    CrossRefPubMedWeb of Science
11. 11.↵
    1. Skrobot OA,
    2. Black SE,
    3. Chen C, et al

    ; VICCCS group. Progress toward standardized diagnosis of vascular cognitive impairment: guidelines from the Vascular Impairment of Cognition Classification Consensus Study. Alzheimers Dement 2018;14:280–92 doi:10.1016/j.jalz.2017.09.007 pmid:29055812

    CrossRefPubMed
12. 12.↵
    1. Lyness JM,
    2. Noel TK,
    3. Cox C, et al

    . Screening for depression in elderly primary care patients: a comparison of the Center for Epidemiologic Studies-Depression Scale and the Geriatric Depression Scale. Arch Intern Med 1997;157:449–54 pmid:9046897

    CrossRefPubMedWeb of Science
13. 13.↵
    1. Schmitter D,
    2. Roche A,
    3. Maréchal B, et al

    ; Alzheimer's Disease Neuroimaging Initiative. An evaluation of volume-based morphometry for prediction of mild cognitive impairment and Alzheimer’s disease. Neuroimage Clin 2015;7:7–17 doi:10.1016/j.nicl.2014.11.001 pmid:25429357

    CrossRefPubMed
14. 14.↵
    1. Wyman BT,
    2. Harvey DJ,
    3. Crawford K, et al

    ; Alzheimer’s Disease Neuroimaging Initiative. Standardization of analysis sets for reporting results from ADNI MRI data. Alzheimers Dement 2013;9:332–37 doi:10.1016/j.jalz.2012.06.004 pmid:23110865

    CrossRefPubMedWeb of Science
15. 15.↵
    1. Jack CR,
    2. Bernstein MA,
    3. Fox NC, et al

    ; ADNI Study. The Alzheimer’s Disease Neuroimaging Initiative (ADNI): MRI methods. J Magn Reson Imaging 2008;27:685–91 doi:10.1002/jmri.21049 pmid:18302232

    CrossRefPubMedWeb of Science
16. 16.↵
    1. LaMontagne PJ,
    2. Benzinger TLS,
    3. Morris JC, et al

    . OASIS-3: longitudinal neuroimaging, clinical, and cognitive dataset for normal aging and Alzheimer disease. medRxiv https://www.medrxiv.org/content/10.1101/2019.12.13.19014902v1. Accessed January 28, 2023
17. 17.↵
    1. Koenig LN,
    2. Day GS,
    3. Salter A, et al

    . Select Atrophied Regions in Alzheimer disease (SARA): an improved volumetric model for identifying Alzheimer disease dementia. Neuroimage Clin 2020;26:102248 doi:10.1016/j.nicl.2020.102248 pmid:32334404

    CrossRefPubMed
18. 18.↵
    1. Klein A,
    2. Tourville J

    . 101 labeled brain images and a consistent human cortical labeling protocol. Front Neurosci 2012;6:171 doi:10.3389/fnins.2012.00171 pmid:23227001

    CrossRefPubMed
19. 19.↵
    1. Koo TK,
    2. Li MY

    . A guideline of selecting and reporting intraclass correlation coefficients for reliability research. J Chiropr Med 2016;15:155–63 doi:10.1016/j.jcm.2016.02.012 pmid:27330520

    CrossRefPubMed
20. 20.↵
    1. Cohen J

    . Statistical Power Analysis for the Behavioral Sciences, 2nd ed. Routledge; 1998
21. 21.↵
    1. Benjamini Y,
    2. Hochberg Y

    . Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society: Series B (Methodological) 1995;57:289–300 doi:10.1111/j.2517-6161.1995.tb02031.x

    CrossRefPubMed
22. 22.↵
    1. Liu J,
    2. Tang W,
    3. Chen G, et al

    . Correlation and agreement: overview and clarification of competing concepts and measures. Shanghai Arch Psychiatry 2016;28:115–20 doi:10.11919/j.issn.1002-0829.216045 pmid:27605869

    CrossRefPubMed
23. 23.↵
    1. Fischl B,
    2. Sereno MI,
    3. Dale AM

    . Cortical surface-based analysis, II: inflation, flattening, and a surface-based coordinate system. Neuroimage 1999;9:195–207 doi:10.1006/nimg.1998.0396 pmid:9931269

    CrossRefPubMedWeb of Science
24. 24.↵
    1. Dale AM,
    2. Fischl B,
    3. Sereno MI

    . Cortical surface-based analysis, I: segmentation and surface reconstruction. Neuroimage 1999;9:179–94 doi:10.1006/nimg.1998.0395 pmid:9931268

    CrossRefPubMedWeb of Science
25. 25.↵
    1. Su Y,
    2. Flores S,
    3. Hornbeck RC, et al

    . Utilizing the Centiloid scale in cross-sectional and longitudinal PiB PET studies. Neuroimage Clin 2018;19:406–16 doi:10.1016/j.nicl.2018.04.022 pmid:30035025

    CrossRefPubMed
26. 26.↵
    1. Su Y,
    2. Flores S,
    3. Wang G, et al

    . Comparison of Pittsburgh compound B and florbetapir in cross-sectional and longitudinal studies. Alzheimers Dement (Amst) 2019;11:180–90 doi:10.1016/j.dadm.2018.12.008 pmid:30847382

    CrossRefPubMed
27. 27.↵
    1. Janelidze S,
    2. Teunissen CE,
    3. Zetterberg H, et al

    . Head-to-head comparison of 8 plasma amyloid-β 42/40 assays in Alzheimer disease. JAMA Neurol 2021;78:1375–82 doi:10.1001/jamaneurol.2021.3180 pmid:34542571

    CrossRefPubMed
28. 28.↵
    1. Pemberton HG,
    2. Goodkin O,
    3. Prados F, et al

    ; Alzheimer’s Disease Neuroimaging Initiative. Automated quantitative MRI volumetry reports support diagnostic interpretation in dementia: a multi-rater, clinical accuracy study. Eur Radiol 2021;31:5312–23 doi:10.1007/s00330-020-07455-8 pmid:33452627

    CrossRefPubMed
29. 29.↵
    1. Pemberton HG,
    2. Zaki LA,
    3. Goodkin O, et al

    . Technical and clinical validation of commercial automated volumetric MRI tools for dementia diagnosis: a systematic review. Neuroradiology 2021;63:1773–89 doi:10.1007/s00234-021-02746-3 pmid:34476511

    CrossRefPubMed