A Comprehensive Visual Rating Scale for Predicting Progression from Mild Cognitive Impairment to Dementia in Patients with Alzheimer's Pathology or Suspected Non-Alzheimer's Pathology
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Background and Purpose: To identify biomarkers for prediction of the progression to dementia in mild cognitive impairment (MCI) patients, evaluation of brain structure changes has been validated by a comprehensive visual grading scale (CVRS) through magnetic resonance imaging (MRI). In this study, we specifically elucidated for the cognitive change of MCI patients classified based on AT(N) pathological status classification during the follow-up period of 3 years through the CVRS. Methods: The 301 patients with initial MCI visited at least once for follow-up period. The data used in this study were obtained from the Alzheimer's disease (AD) Neuroimaging Initiative study. Brain atrophy was assessed by CVRS using MRI. AT(N) profiles were classified by cerebrospinal fluid abnormality. Based on the AT(N) assessment, all individuals in this study were divided into 3 groups (normal state biomarker, suspected non-Alzheimer's pathology [SNAP], or Alzheimer's continuum). The cox regression was used to analyze the hazard ratios of CVRS for progression to dementia. Results: Sixty-three progressed and 238 remained stable to dementia and the CVRS (mean±standard deviation) had significant difference between progressive MCI and stable MCI (p<0.001). Univariate and multivariate cox regression results (p<0.001) showed the independence of initial CVRS as a predictor for the progression to dementia. Moreover, comparing the classified AT(N) pathology group, SNAP and AD, effectiveness of CVRS as a predictor was verified only in Alzheimer's continuum. Conclusions: The initial CVRS score as a predictor of dementia progression was independently validated at the stage of Alzheimer's progression among AT(N) pathologically differentiated MCI.
Abstract
Background and Purpose: To identify biomarkers for prediction of the progression to dementia in mild cognitive impairment (MCI) patients, evaluation of brain structure changes has been validated by a comprehensive visual grading scale (CVRS) through magnetic resonance imaging (MRI). In this study, we specifically elucidated for the cognitive change of MCI patients classified based on AT(N) pathological status classification during the follow-up period of 3 years through the CVRS. Methods: The 301 patients with initial MCI visited at least once for follow-up period. The data used in this study were obtained from the Alzheimer's disease (AD) Neuroimaging Initiative study. Brain atrophy was assessed by CVRS using MRI. AT(N) profiles were classified by cerebrospinal fluid abnormality. Based on the AT(N) assessment, all individuals in this study were divided into 3 groups (normal state biomarker, suspected non-Alzheimer's pathology [SNAP], or Alzheimer's continuum). The cox regression was used to analyze the hazard ratios of CVRS for progression to dementia. Results: Sixty-three progressed and 238 remained stable to dementia and the CVRS (mean±standard deviation) had significant difference between progressive MCI and stable MCI (p<0.001). Univariate and multivariate cox regression results (p<0.001) showed the independence of initial CVRS as a predictor for the progression to dementia. Moreover, comparing the classified AT(N) pathology group, SNAP and AD, effectiveness of CVRS as a predictor was verified only in Alzheimer's continuum. Conclusions: The initial CVRS score as a predictor of dementia progression was independently validated at the stage of Alzheimer's progression among AT(N) pathologically differentiated MCI.
참고문헌 (37)
- Meles SK, "The Alzheimer's disease metabolic brain pattern in mild cognitive impairment", J Cereb Blood Flow Metab, 37, pp.3643~3648 (2017)
- Huijbers W, "Amyloid-β deposition in mild cognitive impairment is associated with increased hippocampal activity, atrophy and clinical progression", Brain, 138, pp.1023~1035 (2015)
- Selkoe DJ, "The amyloid hypothesis of Alzheimer's disease at 25 years", EMBO Mol Med, 8, pp.595~608 (2016)
- Winblad B, "Mild cognitive impairment--beyond controversies, towards a consensus : report of the International Working Group on Mild Cognitive Impairment", J Intern Med, 256, pp.240~246 (2004)
- Beach TG, "Accuracy of the clinical diagnosis of Alzheimer disease at National Institute on Aging Alzheimer Disease Centers, 2005–2010", J Neuropathol Exp Neurol, 71, pp.266~273 (2012)
- Gamberger D, "Identification of clusters of rapid and slow decliners among subjects at risk for Alzheimer's disease", Sci Rep, 7, pp.6763~ (2017)
- Hinrichs C, "Predictive markers for AD in a multi-modality framework : an analysis of MCI progression in the ADNI population", Neuroimage, 55, pp.574~589 (2011)
- Jack CR Jr, "NIA-AA research framework : toward a biological definition of Alzheimer's disease", Alzheimers Dement, 14, pp.535~562 (2018)
- Olsson B, "CSF and blood biomarkers for the diagnosis of Alzheimer's disease : a systematic review and meta-analysis", Lancet Neurol, 15, pp.673~684 (2016)
- Murray ME, "Neuropathologically defined subtypes of Alzheimer's disease with distinct clinical characteristics : a retrospective study", Lancet Neurol, 10, pp.785~796 (2011)
- Jang JW, "A ‘comprehensive visual rating scale’for predicting progression to dementia in patients with mild cognitive impairment", PLoS One, 13, pp.e0201852~ (2018)
- McKhann GM, "The diagnosis of dementia due to Alzheimer's disease : recommendations from the National Institute on AgingAlzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease", Alzheimers Dement, 7, pp.263~269 (2011)
- Sperling RA, "Toward defining the preclinical stages of Alzheimer's disease : recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease", Alzheimers Dement, 7, pp.280~292 (2011)
- Jack CR Jr, "Introduction to the recommendations from the National Institute on Aging-Alzheimer's Association workgroups on diagnostic guidelines for Alzheimer's disease", Alzheimers Dement, 7, pp.257~262 (2011)
- Jang JW, "A comprehensive visual rating scale of brain magnetic resonance imaging : application in elderly subjects with Alzheimer's disease, mild cognitive impairment, and normal cognition", J Alzheimers Dis, 44, pp.1023~1034 (2015)
- Wechsler D, "WMS-R : Wechsler Memory Scale--Revised Manual" (1987), Psychological Corp
- Shaw LM, "Cerebrospinal fluid biomarker signature in Alzheimer's disease neuroimaging initiative subjects", Ann Neurol, 65, pp.403~413 (2009)
- McKhann G, "Clinical diagnosis of Alzheimer's disease : report of the NINCDS-ADRDA work group under the auspices of Department of Health and Human Services task force on Alzheimer's disease", Neurology, 34, pp.939~944 (1984)
- Jack CR Jr, "A", T, Neurology, pp.2016, 87[DOI]
- Jack CR Jr, "The Alzheimer's Disease Neuroimaging Initiative(ADNI) : MRI methods", J Magn Reson Imaging, 27, pp.685~691 (2008)
- Fox J, "Generalized collinearity diagnostics", J Am Stat Assoc, 87, pp.178~183 (1992)
- Therneau T, "A Package for Survival Analysis in R" (2020), R Foundation
- Wickham H, "ggplot2 : Elegant Graphics for Data Analysis" (2009), Springer
- Roberts RO, "Higher risk of progression to dementia in mild cognitive impairment cases who revert to normal", Neurology, 82, pp.317~325 (2014)
- Jack CR Jr, "Brain beta-amyloid measures and magnetic resonance imaging atrophy both predict time-to-progression from mild cognitive impairment to Alzheimer's disease", Brain, 133, pp.3336~3348 (2010)
- Pankratz VS, "Predicting the risk of mild cognitive impairment in the Mayo Clinic Study of Aging", Neurology, 84, pp.1433~1442 (2015)
- Shen Q, "Volumetric and visual rating of magnetic resonance imaging scans in the diagnosis of amnestic mild cognitive impairment and Alzheimer's disease", Alzheimers Dement, 7, pp.e101~e108 (2011)
- Frisoni GB, "Visual rating and volumetry of the medial temporal lobe on magnetic resonance imaging in dementia", J Neurol Neurosurg Psychiatry, 69, pp.572~ (2000)
- Bresciani L, "Visual assessment of medial temporal atrophy on MR films in Alzheimer's disease : comparison with volumetry", Aging Clin Exp Res, 17, pp.8~13 (2005)
- Ekman U, "The A", T, Sci Rep, pp.2018, 8[DOI]
- Maia LF, "Changes in amyloid-β and tau in the cerebrospinal fluid of transgenic mice overexpressing amyloid precursor protein", Sci Transl Med, 5, pp.194re2~ (2013)
- Wallin A, "The Gothenburg MCI study : design and distribution of Alzheimer's disease and subcortical vascular disease diagnoses from baseline to 6-year follow-up", J Cereb Blood Flow Metab, 36, pp.114~131 (2016)
- Barnes J, "Vascular and Alzheimer's disease markers independently predict brain atrophy rate in Alzheimer's Disease Neuroimaging Initiative controls", Neurobiol Aging, 34, pp.1996~2002 (2013)
- Fiford CM, "White matter hyperintensities are associated with disproportionate progressive hippocampal atrophy", Hippocampus, 27, pp.249~262 (2017)
- Ferreira D, "Distinct subtypes of Alzheimer's disease based on patterns of brain atrophy : longitudinal trajectories and clinical applications", Sci Rep, 7, pp.46263~ (2017)
- Jokinen H, "Incident lacunes influence cognitive decline : the LADIS study", Neurology, 76, pp.1872~1878 (2011)
- Ikram MA, "The Rotterdam Scan Study : design update 2016 and main findings", Eur J Epidemiol, 30, pp.1299~1315 (2015)
