Combining MRI and MRS to distinguish between Alzheimer's disease and healthy controls.

Alzheimer's disease (AD) is the most common neurodegenerative disorder among the elderly, and early detection is of great importance if new therapies are to be effectively administered. We have used multivariate data analysis (orthogonal partial least squares to latent structures (OPLS) analysis) to investigate whether the discrimination between AD and elderly healthy control subjects can be improved by adding magnetic resonance spectroscopy (MRS) measures to magnetic resonance imaging (MRI). In this study, 30 AD patients and 36 control subjects were included (mean (SD) age=77(5) and 77(5) years, MMSE=23(4) and 29(1) respectively). High resolution T1-weighted axial magnetic resonance images were obtained from each subject. Automated regional volume segmentation and cortical thickness measures were determined for the images. 1H MRS was acquired from the hippocampus and LCModel was used for metabolite quantification. Altogether, this yielded 54 different volumetric, cortical thickness and metabolite ratio variables which were used for multivariate analysis. All analyses were performed using seven-fold-cross-validation. Combining MRI and MRS measures resulted in a sensitivity of 97% and a specificity of 94% compared to using MRI or MRS measures alone (sensitivity: 93%, 76%, specificity: 86%, 83% respectively). Adding the MRS measures to the MRI measures more than doubled the positive likelihood ratio from 7 to 17. Adding MRS measures to a multivariate analysis of MRI measures resulted in significantly better classification than using MRI measures alone. The OPLS method shows strong potential for discriminating between Alzheimer's disease and controls.

[1]  Anthony Randal McIntosh,et al.  Partial least squares analysis of neuroimaging data: applications and advances , 2004, NeuroImage.

[2]  M. Albert,et al.  Temporal lobe regions on magnetic resonance imaging identify patients with early Alzheimer's disease. , 1993, Archives of neurology.

[3]  Alan C. Evans,et al.  Automatic "pipeline" analysis of 3-D MRI data for clinical trials: application to multiple sclerosis , 2002, IEEE Transactions on Medical Imaging.

[4]  D. Auer,et al.  Hippocampal metabolic abnormalities in mild cognitive impairment and Alzheimer's disease , 2005, Neuroscience Letters.

[5]  Eric Westman,et al.  In vivo 1H-magnetic resonance spectroscopy can detect metabolic changes in APP/PS1 mice after donepezil treatment , 2009, BMC Neuroscience.

[6]  A. Dale,et al.  Improved Localizadon of Cortical Activity by Combining EEG and MEG with MRI Cortical Surface Reconstruction: A Linear Approach , 1993, Journal of Cognitive Neuroscience.

[7]  Anders M. Dale,et al.  Sequence-independent segmentation of magnetic resonance images , 2004, NeuroImage.

[8]  W. Jagust,et al.  Quantitative NMR measurements of hippocampal atrophy in Alzheimer's disease , 1988, Magnetic resonance in medicine.

[9]  Nick C Fox,et al.  Automatic classification of MR scans in Alzheimer's disease. , 2008, Brain : a journal of neurology.

[10]  N. Schuff,et al.  Selective reduction of N-acetylaspartate in medial temporal and parietal lobes in AD , 2002, Neurology.

[11]  R. Bartha,et al.  High field 1H MRS of the hippocampus after donepezil treatment in Alzheimer disease , 2008, Progress in Neuro-Psychopharmacology and Biological Psychiatry.

[12]  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.

[13]  Anders M. Dale,et al.  Automated manifold surgery: constructing geometrically accurate and topologically correct models of the human cerebral cortex , 2001, IEEE Transactions on Medical Imaging.

[14]  M. Rantalainen,et al.  Statistically integrated metabonomic-proteomic studies on a human prostate cancer xenograft model in mice. , 2006, Journal of proteome research.

[15]  U. Edlund,et al.  Visualization of GC/TOF-MS-based metabolomics data for identification of biochemically interesting compounds using OPLS class models. , 2008, Analytical chemistry.

[16]  Anders M. Dale,et al.  Cortical Surface-Based Analysis I. Segmentation and Surface Reconstruction , 1999, NeuroImage.

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

[18]  H. Soininen,et al.  Hippocampal volumes in Alzheimer's disease, Parkinson's disease with and without dementia, and in vascular dementia , 1996, Neurology.

[19]  et al.,et al.  Spatial patterns of brain atrophy in MCI patients, identified via high-dimensional pattern classification, predict subsequent cognitive decline , 2008, NeuroImage.

[20]  Ulf Norinder,et al.  Age related changes in brain metabolites observed by 1H MRS in APP/PS1 mice , 2008, Neurobiology of Aging.

[21]  Anders M. Dale,et al.  An automated labeling system for subdividing the human cerebral cortex on MRI scans into gyral based regions of interest , 2006, NeuroImage.

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

[23]  C. Jack,et al.  Risk of dementia in MCI , 2009, Neurology.

[24]  E Moore,et al.  Serial precision of metabolite peak area ratios and water referenced metabolite peak areas in proton MR spectroscopy of the human brain. , 1998, Magnetic resonance imaging.

[25]  Nikos Makris,et al.  Automatically parcellating the human cerebral cortex. , 2004, Cerebral cortex.

[26]  K. Kantarci.  1H magnetic resonance spectroscopy in dementia. , 2007, The British journal of radiology.

[27]  A. Dale,et al.  High‐resolution intersubject averaging and a coordinate system for the cortical surface , 1999, Human brain mapping.

[28]  H. Soininen,et al.  MRI of the Hippocampus in Alzheimer’s Disease: Sensitivity, Specificity, and Analysis of the Incorrectly Classified Subjects , 1998, Neurobiology of Aging.

[29]  Alan C. Evans,et al.  Automated cortical thickness measurements from MRI can accurately separate Alzheimer's patients from normal elderly controls , 2008, Neurobiology of Aging.

[30]  M. Sokół,et al.  Pattern recognition methods in (1)H MRS monitoring in vivo of normal appearing cerebellar tissue after treatment of posterior fossa tumors. , 2010, Acta neurochirurgica. Supplement.

[31]  M N Rossor,et al.  MRS shows abnormalities before symptoms in familial Alzheimer disease , 2006, Neurology.

[32]  Sterling C. Johnson,et al.  Magnetic Resonance Imaging Characterization of Brain Structure and Function in Mild Cognitive Impairment: A Review , 2008, Journal of the American Geriatrics Society.

[33]  Christian Böhm,et al.  Automated detection of brain atrophy patterns based on MRI for the prediction of Alzheimer's disease , 2010, NeuroImage.

[34]  S. Provencher.  Automatic quantitation of localized in vivo 1H spectra with LCModel , 2001, NMR in biomedicine.

[35]  Johann Gasteiger,et al.  Comparison of Different Classification Methods Applied to a Mode of Toxic Action Data Set , 2004 .

[36]  A. Simmons,et al.  Effects of estrogen replacement therapy on human brain aging: An in vivo 1H MRS study , 2001, Neurology.

[37]  S. Wold,et al.  Orthogonal projections to latent structures (O‐PLS) , 2002 .

[38]  Alan C. Evans,et al.  A nonparametric method for automatic correction of intensity nonuniformity in MRI data , 1998, IEEE Transactions on Medical Imaging.

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

[40]  Fritz Albregtsen,et al.  Many are called, but few are chosen. Feature selection and error estimation in high dimensional spaces , 2004, Comput. Methods Programs Biomed..

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

[42]  S. Black,et al.  Beyond the hippocampus , 2001, Neurology.

[43]  J. O'Brien,et al.  A Comprehensive Review of Proton Magnetic Resonance Spectroscopy Studies in Dementia and Parkinson’s Disease , 2002, Dementia and Geriatric Cognitive Disorders.

[44]  S. Lovestone,et al.  Proteome-based plasma biomarkers for Alzheimer's disease. , 2006, Brain : a journal of neurology.

[45]  Elena I. Nica,et al.  The Toronto traumatic brain injury study , 2008, Neurology.

[46]  S. Provencher.  Estimation of metabolite concentrations from localized in vivo proton NMR spectra , 1993, Magnetic resonance in medicine.

[47]  Nick C Fox,et al.  Accuracy of dementia diagnosis—a direct comparison between radiologists and a computerized method , 2008, Brain : a journal of neurology.

[48]  A M Dale,et al.  Measuring the thickness of the human cerebral cortex from magnetic resonance images. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[49]  Daniel Eriksson,et al.  Data integration in plant biology: the O2PLS method for combined modeling of transcript and metabolite data. , 2007, The Plant journal : for cell and molecular biology.

[50]  H. Soininen,et al.  Comparative MR analysis of the entorhinal cortex and hippocampus in diagnosing Alzheimer disease. , 1999, AJNR. American journal of neuroradiology.

[51]  J T O'Brien,et al.  Role of imaging techniques in the diagnosis of dementia. , 2007, The British journal of radiology.

[52]  Usefulness of MRI measures of entorhinal cortex versus hippocampus in AD. , 2000 .

[53]  M. Law,et al.  Magnetic resonance spectroscopy of the brain: review of metabolites and clinical applications. , 2009, Clinical radiology.

[54]  Eric Westman,et al.  Carbamazepine treatment recovered low N-acetylaspartate+N-acetylaspartylglutamate (tNAA) levels in the megencephaly mouse BALB/cByJ-Kv1.1 mceph/mceph , 2007, Neurobiology of Disease.

[55]  Bruce Fischl,et al.  Geometrically Accurate Topology-Correction of Cortical Surfaces Using Nonseparating Loops , 2007, IEEE Transactions on Medical Imaging.

[56]  A. Dale,et al.  Alzheimer disease: quantitative structural neuroimaging for detection and prediction of clinical and structural changes in mild cognitive impairment. , 2009, Radiology.

[57]  A. M. Dale,et al.  A hybrid approach to the skull stripping problem in MRI , 2004, NeuroImage.

[58]  M. Albert,et al.  MRI measures of entorhinal cortex vs hippocampus in preclinical AD , 2002, Neurology.

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

[60]  Nick C Fox,et al.  Longitudinal imaging in dementia. , 2007, The British journal of radiology.

[61]  Alan C. Evans,et al.  A fully automatic and robust brain MRI tissue classification method , 2003, Medical Image Anal..

[62]  S Lehéricy,et al.  Amygdalohippocampal MR volume measurements in the early stages of Alzheimer disease. , 1994, AJNR. American journal of neuroradiology.

[63]  F. Jessen,et al.  A Comparative Study of the Different N-Acetylaspartate Measures of the Medial Temporal Lobe in Alzheimer’s Disease , 2005, Dementia and Geriatric Cognitive Disorders.

[64]  G J Barker,et al.  Simulation of MRI cluster plots and application to neurological segmentation. , 1996, Magnetic resonance imaging.