Antemortem MRI based STructural Abnormality iNDex (STAND)-scores correlate with postmortem Braak neurofibrillary tangle stage

The clinical diagnosis of Alzheimer's disease (AD) does not exactly match the pathological findings at autopsy in every subject. Therefore, in-vivo imaging measures, such as Magnetic Resonance Imaging (MRI) that reflect underlying pathology, would be clinically useful independent supplementary measures of disease stage. We have developed an algorithm that extracts atrophy information from individual patient's 3D MRI scans and assigns a STructural Abnormality iNDex (STAND)-score to the scan based on the degree of atrophy in comparison to patterns extracted from a large library of clinically well characterized AD and CN (cognitively normal) subject's MRI scans. STAND-scores can be adjusted for demographics to give adjusted-STAND (aSTAND)-scores which are >0 for subjects with brains identified as abnormal by the algorithm. Since histopathological findings are considered to represent the "ground truth", our objective was to assess the sensitivity of aSTAND-scores to pathological AD staging. This was done by comparing antemortem MRI based aSTAND-scores with postmortem grading of disease severity in 101 subjects who had both antemortem MRI and postmortem Braak neurofibrillary tangle (NFT) staging. We found a rank correlation of 0.62 (p<0.0001) between Braak NFT stage and aSTAND-scores. The results show that optimally extracted information from MRI scans such as STAND-scores accurately capture the severity of neuronal pathology and can be used as an independent approximate surrogate marker for in-vivo pathological staging as well as for early identification of AD in individual subjects.

[1]  John Q. Trojanowski,et al.  Consensus Recommendations for the Postmortem Diagnosis of Alzheimer’s Disease , 1997, Neurobiology of Aging.

[2]  J. Morris,et al.  Pathologic correlates of nondemented aging, mild cognitive impairment, and early-stage alzheimer’s disease , 2001, Journal of Molecular Neuroscience.

[3]  Nick C. Fox,et al.  The boundary shift integral: an accurate and robust measure of cerebral volume changes from registered repeat MRI , 1997, IEEE Transactions on Medical Imaging.

[4]  S. M. Sumi,et al.  The Consortium to Establish a Registry for Alzheimer's Disease (CERAD) , 1991, Neurology.

[5]  Masayuki Matsuda,et al.  Four subgroups of Alzheimer's disease based on patterns of atrophy using VBM and a unique pattern for early onset disease , 2006, NeuroImage.

[6]  Clifford R. Jack,et al.  Alzheimer's disease diagnosis in individual subjects using structural MR images: Validation studies , 2008, NeuroImage.

[7]  M. Folstein,et al.  Clinical diagnosis of Alzheimer's disease , 1984, Neurology.

[8]  J Bohl,et al.  Spatial, Temporal and Numeric Analysis of Alzheimer Changes in the Nucleus Coeruleus , 1997, Neurobiology of Aging.

[9]  Karl J. Friston,et al.  Voxel-Based Morphometry—The Methods , 2000, NeuroImage.

[10]  C. Jack,et al.  β‐amyloid burden is not associated with rates of brain atrophy , 2008, Annals of neurology.

[11]  J. Trojanowski,et al.  Editorial on Consensus Recommendations for the Postmortem Diagnosis of Alzheimer Disease from the National Institute on Aging and the Reagan Institute Working Group on Diagnostic Criteria for the Neuropathological Assessment of Alzheimer Disease , 1997, Journal of neuropathology and experimental neurology.

[12]  S. Rose,et al.  Loss of connectivity in Alzheimer's disease: an evaluation of white matter tract integrity with colour coded MR diffusion tensor imaging , 2000, Journal of neurology, neurosurgery, and psychiatry.

[13]  M. Sliwinski,et al.  Pathological markers associated with normal aging and dementia in the elderly , 1993, Annals of neurology.

[14]  J. Baron,et al.  Mapping gray matter loss with voxel-based morphometry in mild cognitive impairment , 2002, Neuroreport.

[15]  M. Mesulam.  Principles of Behavioral and Cognitive Neurology , 2000 .

[16]  Nick C Fox,et al.  Presymptomatic hippocampal atrophy in Alzheimer's disease. A longitudinal MRI study. , 1996, Brain : a journal of neurology.

[17]  W. Markesbery,et al.  Hippocampal volume as an index of Alzheimer neuropathology: Findings from the Nun Study , 2002, Neurology.

[18]  M. Bobinski,et al.  The histological validation of post mortem magnetic resonance imaging-determined hippocampal volume in Alzheimer's disease , 1999, Neuroscience.

[19]  A. Burns.  Clinical diagnosis of Alzheimer's disease , 1991 .

[20]  R. Katzman.,et al.  Clinical, pathological, and neurochemical changes in dementia: A subgroup with preserved mental status and numerous neocortical plaques , 1988, Annals of neurology.

[21]  J. Ashford,et al.  “Preclinical” AD revisited , 2000, Neurology.

[22]  C. Jack,et al.  Rate of medial temporal lobe atrophy in typical aging and Alzheimer's disease , 1998, Neurology.

[23]  F. Schmitt,et al.  Age and gender effects on human brain anatomy: A voxel-based morphometric study in healthy elderly , 2007, Neurobiology of Aging.

[24]  Fabrice Crivello,et al.  Age- and sex-related effects on the neuroanatomy of healthy elderly , 2005, NeuroImage.

[25]  Richard Hollister,et al.  Neuronal loss correlates with but exceeds neurofibrillary tangles in Alzheimer's disease , 1997, Annals of neurology.

[26]  J. Schneider,et al.  Neuropathology of older persons without cognitive impairment from two community-based studies , 2006, Neurology.

[27]  H. Braak,et al.  Relationship between Clinical and Radiological Diagnostic Criteria for Alzheimer’s Disease and the Extent of Neuropathology as Reflected by ‘Stages’: A Prospective Study , 1999, Dementia and Geriatric Cognitive Disorders.

[28]  R. Killiany,et al.  Use of structural magnetic resonance imaging to predict who will get Alzheimer's disease , 2000, Annals of neurology.

[29]  W. Markesbery,et al.  Alzheimer's neurofibrillary pathology and the spectrum of cognitive function: Findings from the Nun Study , 2002, Annals of neurology.

[30]  C. Jack,et al.  Antemortem MRI findings correlate with hippocampal neuropathology in typical aging and dementia , 2002, Neurology.

[31]  Frederik Barkhof,et al.  Unbiased whole-brain analysis of gray matter loss in Alzheimer's disease , 2000, Neuroscience Letters.

[32]  Clifford R. Jack,et al.  Argyrophilic grains: A distinct disease or an additive pathology? , 2008, Neurobiology of Aging.

[33]  M N Rossor,et al.  Measuring atrophy in Alzheimer disease , 2005, Neurology.

[34]  Glenn T. Stebbins,et al.  Hippocampal disconnection due to white matter loss in individuals with amnestic mild cognitive impairment , 2005, Alzheimer's & Dementia.

[35]  C. Jack,et al.  MR‐based hippocampal volumetry in the diagnosis of Alzheimer's disease , 1992, Neurology.

[36]  H. Braak,et al.  Neuropathological stageing of Alzheimer-related changes , 2004, Acta Neuropathologica.

[37]  D. Mash,et al.  Neuropathological and neuropsychological changes in "normal" aging: evidence for preclinical Alzheimer disease in cognitively normal individuals. , 1998, Journal of neuropathology and experimental neurology.

[38]  J. Quinn,et al.  Changes in premorbid brain volume predict Alzheimer’s disease pathology , 2003, Neurology.

[39]  R. Petersen.  Mild cognitive impairment as a diagnostic entity , 2004, Journal of internal medicine.

[40]  C. P. Hughes,et al.  A New Clinical Scale for the Staging of Dementia , 1982, British Journal of Psychiatry.

[41]  G. Frisoni,et al.  Detection of grey matter loss in mild Alzheimer's disease with voxel based morphometry , 2002, Journal of neurology, neurosurgery, and psychiatry.

[42]  C. Jack,et al.  3D maps from multiple MRI illustrate changing atrophy patterns as subjects progress from mild cognitive impairment to Alzheimer's disease. , 2007, Brain : a journal of neurology.

[43]  Keith A. Johnson,et al.  Neuropathology of Cognitively Normal Elderly , 2003, Journal of neuropathology and experimental neurology.

[44]  E. Tangalos,et al.  Mild Cognitive Impairment Clinical Characterization and Outcome , 1999 .

[45]  S. Folstein,et al.  "Mini-mental state". A practical method for grading the cognitive state of patients for the clinician. , 1975, Journal of psychiatric research.

[46]  J. Baron,et al.  In Vivo Mapping of Gray Matter Loss with Voxel-Based Morphometry in Mild Alzheimer's Disease , 2001, NeuroImage.

[47]  Clifford R Jack,et al.  Neuroimaging in Alzheimer disease: an evidence-based review. , 2003, Neuroimaging clinics of North America.

[48]  Howard S. Kirsnher.  Principles of Behavioral and Cognitive Neurology, 2nd Ed. , 2002 .

[49]  T. J. Grabowski,et al.  Neuropathologic Outcome of Mild Cognitive Impairment Following Progression to Clinical Dementia , 2007 .

[50]  M. Albert,et al.  Prevalence of Alzheimer's disease in a community population of older persons. Higher than previously reported. , 1989, JAMA.

[51]  H. Braak,et al.  Morphological criteria for the recognition of Alzheimer's disease and the distribution pattern of cortical changes related to this disorder , 1994, Neurobiology of Aging.

[52]  C. Jack,et al.  Anterior temporal lobes and hippocampal formations: normative volumetric measurements from MR images in young adults. , 1989, Radiology.

[53]  J. Morris,et al.  Profound Loss of Layer II Entorhinal Cortex Neurons Occurs in Very Mild Alzheimer’s Disease , 1996, The Journal of Neuroscience.

[54]  C. Jack,et al.  Medial temporal atrophy on MRI in normal aging and very mild Alzheimer's disease , 1997, Neurology.

[55]  M. Weiner,et al.  Correlates of hippocampal neuron number in Alzheimer's disease and ischemic vascular dementia , 2005, Annals of neurology.

[56]  Lei Wang,et al.  Correlations Between Antemortem Hippocampal Volume and Postmortem Neuropathology in AD Subjects , 2004, Alzheimer disease and associated disorders.