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tensor-based morphometry with stationary velocity field diffeomorphic registration: Application to ADNI

NEUROIMAGE 2010年第3期51卷 956-969页

作者： Bossa, Matias Zacur, Ernesto Olmos, Salvador Univ Zaragoza Aragon Inst Engn Res GTC E-50009 Zaragoza Spain

tensor-based morphometry (TBM) is an analysis technique where anatomical information is characterized by means of the spatial transformations mapping a customized template with the observed images. Therefore, accurate inter-subject non-rigid registration is an essential prerequisite for both template estimation and image warping. Subsequent statistical analysis on the spatial transformations is performed to highlight voxel-wise differences. Most of previous TBM studies did not explore the influence of the registration parameters, such as the parameters defining the deformation and the regularization models. In this work performance evaluation of TBM using stationary velocity field (SVF) diffeomorphic registration was performed in a subset of subjects from Alzheimer's Disease Neuroimaging Initiative (ADNI) study. A wide range of values of the registration parameters that define the transformation smoothness and the balance between image matching and regularization were explored in the evaluation. The proposed methodology provided brain atrophy maps with very detailed anatomical resolution and with a high significance level compared with results recently published on the same data set using a non-linear elastic registration method. (C) 2010 Elsevier Inc. All rights reserved.

关键词： Alzheimer's disease tensor-based morphometry Diffeomorphic registration

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tensor-based morphometry using scalar and directional information of diffusion tensor MRI data (DTBM): Application to hereditary spastic paraplegia

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HUMAN BRAIN MAPPING 2018年第12期39卷 4643-4651页

作者： Sadeghi, Neda Arrigoni, Filippo D'Angelo, Maria Grazia Thomas, Cibu Irfanoglu, M. Okan Hutchinson, Elizabeth B. Nayak, Amritha Modi, Pooja Bassi, Maria Teresa Pierpaoli, Carlo Natl Inst Biomed Imaging & Bioengn Quantitat Med Imaging NIH Bethesda MD 20892 USA IRCCS E Medea Sci Inst Neuroimaging Lab Bosisio Parini Italy IRCCS E Medea Sci Inst Neuromuscular Disorders Unit Bosisio Parini Italy NIMH Sect Learning & Plast Lab Brain & Cognit NIH Bethesda MD 20892 USA Henry M Jackson Fdn Adv Mil Med Inc Bethesda MD USA Eunice Kennedy Shriver Natl Inst Child Hlth & Dev Sect Quantitat Imaging & Tissue Sci NIH Bethesda MD USA IRCCS E Medea Sci Inst Mol Biol Lab Bosisio Parini Italy

tensor-based morphometry (TBM) performed using T1-weighted images (T1WIs) is a well-established method for analyzing local morphological changes occurring in the brain due to normal aging and disease. However, in white matter regions that appear homogeneous on T1WIs, T1W-TBM may be inadequate for detecting changes that affect specific pathways. In these regions, diffusion tensor MRI (DTI) can identify white matter pathways on the basis of their different anisotropy and orientation. In this study, we propose performing TBM using deformation fields constructed using all scalar and directional information provided by the diffusion tensor (DTBM) with the goal of increasing sensitivity in detecting morphological abnormalities of specific white matter pathways. Previously, mostly fractional anisotropy (FA) has been used to drive registration in diffusion MRI-based TBM (FA-TBM). However, FA does not have the directional information that the tensors contain, therefore, the registration based on tensors provides better alignment of brain structures and better localization of volume change. We compare our DTBM method to both T1W-TBM and FA-TBM in investigating differences in brain morphology between patients with complicated hereditary spastic paraplegia of type 11 (SPG11) and a group of healthy controls. Effect size maps of T1W-TBM of SPG11 patients showed diffuse atrophy of white matter. However, DTBM indicated that atrophy was more localized, predominantly affecting several long-range pathways. The results of our study suggest that DTBM could be a powerful tool for detecting morphological changes of specific white matter pathways in normal brain development and aging, as well as in degenerative disorders.

关键词： DTBM deformation-based morphometry diffusion diffusion tensor imaging diffusion tensor MRI hereditary spastic paraplegia spastic paraplegia of type 11 tensor-based morphometry

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Visual rating method and tensor-based morphometry in the diagnosis of mild cognitive impairment and Alzheimer's disease: a comparative magnetic resonance imaging study

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ACTA RADIOLOGICA 2016年第3期57卷 348-355页

作者： Tuokkola, Terhi Koikkalainen, Juha Parkkola, Riitta Karrasch, Mira Lotjonen, Jyrki Rinne, Juha O. Finland Univ Turku Turku PET Ctr Turku Univ Hosp POB 52 FIN-20521 Turku Finland VTT Tech Res Ctr Finland Tampere Finland Univ Turku Dept Radiol SF-20500 Turku Finland Turku Univ Hosp Turku Finland Abo Akad Univ Dept Psychol & Logoped Turku Finland Univ Turku Turku PET Ctr Turku Univ Hosp Finland Div Clin Neurosci SF-20500 Turku Finland

Background Atrophy of the medial temporal lobe (MTL) is the main structural magnetic resonance imaging (MRI) finding in the brain of patients with Alzheimer's disease (AD). However, evaluating the degree of atrophy is still demanding. Purpose The visual rating method (VRM) was compared with multi-template tensor-based morphometry (TBM), in terms of its efficacy in diagnosing of mild cognitive impairment (MCI) and AD. Material and Methods Forty-seven patients with MCI, 80 patients with AD and 84 controls were studied. Results TBM seems to be more sensitive than VRM at the early stage of dementia in the areas of MTL and ventricles. The methods were equally good in distinguishing controls and the MCI group from the AD group. At the frontal areas TBM was better than VRM in all comparisons. Conclusion A user-friendly VRM is still useful for the clinical evaluation of MCI patients, but multi-template TBM is more sensitive for diagnosing the early stages of dementia. However, TBM is currently too demanding to use for daily clinical work.

关键词： Visual rating tensor-based morphometry Alzheimer's disease mild cognitive impairment magnetic resonance imaging (MRI)

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Longitudinal changes in the brain in mild cognitive impairment: a magnetic resonance imaging study using the visual rating method and tensor-based morphometry

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ACTA RADIOLOGICA 2018年第8期59卷 973-979页

作者： Tuokkola, Terhi Koikkalainen, Juha Parkkola, Riitta Karrasch, Mira Lotjonen, Jyrki Rinne, Juha O. Turku Univ Hosp Turku PET Ctr POB 52 Turku 20521 Finland Univ Eastern Finland Fac Hlth Sci Kuopio Finland Univ Hosp Turku Dept Radiol Turku Finland Turku Univ Hosp Turku Finland Abo Akad Univ Dept Psychol Turku Finland Aalto Univ Dept Neurosci & Biomed Engn Helsinki Finland VTT Tech Res Ctr Finland Tampere Finland Turku Univ Hosp Finland Div Clin Neurosci Turku Finland

Background: Brain atrophy is associated with mild cognitive impairment (MCI), and by using volumetric and visual analyzing methods, it is possible to differentiate between individuals with progressive MCI (MCIp) and stable MCI (MCIs). Automated analysis methods detect degenerative changes in the brain earlier and more reliably than visual methods. Purpose: To detect and evaluate structural brain changes between and within the MCIs, MCIp, and control groups during a two-year follow-up period. Material and Methods: Brain magnetic resonance imaging (MRI) scans of 11 participants with MCIs, 18 participants with MCIp, and 84 controls were analyzed by the visual rating method (VRM) and tensor-based morphometry (TBM). Results: At baseline, both VRM and TBM differentiated the whole MCI group (combined MCIs and MCIp) and the MCIp group from the control group, but they did not differentiate the MCIs group from the control group. At follow-up, both methods differentiated the MCIp group from the control group, but minor differences between the MCIs and control groups were only seen by TBM. Neuropsychological tests did not find differences between the MCIs and control groups at follow-up. Neither method revealed relevant signs of brain atrophy progression within or between MCI subgroups during the follow-up time. Conclusion: Both methods are equally good in the evaluation of structural brain changes in MCI if the groups are sufficiently large and the disease progresses to AD. Only TBM disclosed minor atrophic changes in the MCIs group compared to controls at follow-up. The results need to be confirmed with a large patient group and longer follow-up time.

关键词： Visual rating tensor-based morphometry Alzheimer's disease mild cognitive impairment magnetic resonance imaging (MRI) dementia

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Multivariate tensor-based morphometry with a Right-Invariant Riemannian Distance on GL⁺(n)

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JOURNAL OF MATHEMATICAL IMAGING AND VISION 2014年第1-2期50卷 18-31页

作者： Zacur, Ernesto Bossa, Matias Olmos, Salvador Univ Zaragoza I3A GTC Zaragoza 50018 Spain

tensor-based morphometry (TBM) studies encode the anatomical information in spatial deformations which are locally characterized by Jacobian matrices. Current methods perform voxel-wise statistical analysis on some features, such as the Jacobian determinant or the Cauchy-Green deformation tensor, which are not complete descriptors of the local deformation. This article introduces a right-invariant Riemannian distance on the GL(+)(n) group of Jacobian matrices making use of the complete geometrical information of the local deformation. A numerical recipe for the computation of the proposed distance is given. Additionally, experiments are performed on both a synthetic deformation study and a cross-sectional brain MRI study.

关键词： tensor-based morphometry Jacobian matrices Statistics on manifolds Right-invariant Riemannian metric

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Comparing registration methods for mapping brain change using tensor-based morphometry

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MEDICAL IMAGE ANALYSIS 2009年第5期13卷 679-700页

作者： Yanovsky, Igor Leow, Alex D. Lee, Suh Osher, Stanley J. Thompson, Paul M. CALTECH Jet Prop Lab Pasadena CA 91109 USA Univ Calif Los Angeles Dept Math Los Angeles CA 90095 USA Univ Calif Los Angeles Sch Med Lab Neuro Imaging Los Angeles CA 90095 USA

Measures of brain changes can be computed from sequential MRI scans, providing valuable information on disease progression for neuroscientific studies and clinical trials. tensor-based morphometry (TBM) creates maps of these brain changes, visualizing the 3D profile and rates of tissue growth or atrophy. In this paper, we examine the power of different nonrigid registration models to detect changes in TBM, and their stability when no real changes are present. Specifically, we investigate an asymmetric version of a recently proposed Unbiased registration method, using mutual information as the matching criterion. We compare matching functionals (sum of squared differences and mutual information), as well as large-deformation registration schemes (viscous fluid and inverse-consistent linear elastic registration methods versus Symmetric and Asymmetric Unbiased registration) for detecting changes in serial MRI scans of 10 elderly normal subjects and 10 patients with Alzheimer's Disease scanned at 2-week and 1-year intervals. We also analyzed registration results when matching images corrupted with artificial noise. We demonstrated that the unbiased methods, both symmetric and asymmetric, have higher reproducibility. The unbiased methods were also less likely to detect changes in the absence of any real physiological change. Moreover, they measured biological deformations more accurately by penalizing bias in the corresponding statistical maps. (C) 2009 Elsevier B.V. All rights reserved.

关键词： Image registration Unbiased nonlinear registration Information theory Mutual information tensor-based morphometry Computational anatomy

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Brain structural changes following adaptive cognitive training assessed by tensor-based morphometry (TBM)

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NEUROPSYCHOLOGIA 2016年第0期91卷 77-85页

作者： Colom, Roberto Hua, Xue Martinez, Kenia Burgaleta, Miguel Roman, Francisco J. Gunter, Jeffrey L. Carmona, Susanna Jaeggi, Susanne M. Thompson, Paul M. Univ Autonoma Madrid E-28049 Madrid Spain Univ Southern Calif Stevens Inst Neuroimaging & Informat Imaging Genet Ctr Marina Del Rey CA USA Inst Invest Sanitaria Gregorio Maranon Madrid Spain Univ Pompeu Fabra Barcelona Spain Univ Illinois Beckman Inst Adv Sci & Technol Urbana IL USA Mayo Clin Rochester MN USA Univ Calif Irvine Irvine CA 92717 USA

tensor-based morphometry (TBM) allows the automatic mapping of brain changes across time building 3D deformation maps. This technique has been applied for tracking brain degeneration in Alzheimer's and other neurodegenerative diseases with high sensitivity and reliability. Here we applied TBM to quantify changes in brain structure after completing a challenging adaptive cognitive training program based on the n-back task. Twenty-six young women completed twenty-four training sessions across twelve weeks and they showed, on average, large cognitive improvements. High-resolution MRI scans were obtained before and after training. The computed longitudinal deformation maps were analyzed for answering three questions: (a) Are there differential brain structural changes in the training group as compared with a matched control group? (b) Are these changes related to performance differences in the training program? (c) Are standardized changes in a set of psychological factors (fluid and crystallized intelligence, working memory, and attention control) measured before and after training, related to structural changes in the brain? Results showed (a) greater structural changes for the training group in the temporal lobe, (b) a negative correlation between these changes and performance across training sessions (the greater the structural change, the lower the cognitive performance improvements), and (c) negligible effects regarding the psychological factors measured before and after training. (C) 2016 Elsevier Ltd. All rights reserved.

关键词： Working memory training Brain structural changes tensor-based morphometry

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A tensor-based morphometry analysis of regional differences in brain volume in relation to prenatal alcohol exposure

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NEUROIMAGE-CLINICAL 2014年 5卷 152-160页

作者： Meintjes, E. M. Narr, K. L. van der Kouwe, A. J. W. Molteno, C. D. Pirnia, T. Gutman, B. Woods, R. P. Thompson, P. M. Jacobson, J. L. Jacobson, S. W. Univ Cape Town Fac Hlth Sci Dept Human Biol ZA-7925 Cape Town South Africa Univ Cape Town Fac Hlth Sci MRC UCT Med Imaging Res Unit ZA-7925 Cape Town South Africa Univ Calif Los Angeles Dept Neurol Geffen Sch Med Los Angeles CA 90095 USA Massachusetts Gen Hosp Athinoula A Martinos Ctr Biomed Imaging Charlestown MA 02129 USA Harvard Univ Sch Med Dept Radiol Boston MA 02115 USA Univ Cape Town Fac Hlth Sci Dept Psychiat & Mental Hlth ZA-7925 Cape Town South Africa Univ So Calif Imaging Genet Ctr Marina Del Rey CA 90292 USA Wayne State Univ Sch Med Dept Psychiat & Behav Neurosci Detroit MI 48201 USA

Reductions in brain volumes represent a neurobiological signature of fetal alcohol spectrum disorders (FASD). Less clear is how regional brain tissue reductions differ after normalizing for brain size differences linked with FASD and whether these profiles can predict the degree of prenatal exposure to alcohol. To examine associations of regional brain tissue excesses/deficits with degree of prenatal alcohol exposure and diagnosis with and without correction for overall brain volume, tensor-based morphometry (TBM) methods were applied to structural imaging data from a well-characterized, demographically homogeneous sample of children diagnosed with FASD (n = 39, 9.6-11.0 years) and controls (n = 16, 9.5-11.0 years). Degree of prenatal alcohol exposure was significantly associated with regionally pervasive brain tissue reductions in: (1) the thalamus, midbrain, and ventromedial frontal lobe, (2) the superior cerebellum and inferior occipital lobe, (3) the dorsolateral frontal cortex, and (4) the precuneus and superior parietal lobule. When overall brain size was factored out of the analysis on a subject-by-subject basis, no regions showed significant associations with alcohol exposure. FASD diagnosis was associated with a similar deformation pattern, but few of the regions survived FDR correction. In data-driven independent component analyses (ICA) regional brain tissue deformations successfully distinguished individuals based on extent of prenatal alcohol exposure and to a lesser degree, diagnosis. The greater sensitivity of the continuous measure of alcohol exposure compared with the categorical diagnosis across diverse brain regions underscores the dose dependence of these effects. The ICA results illustrate that profiles of brain tissue alterations may be a useful indicator of prenatal alcohol exposure when reliable historical data are not available and facial features are not apparent. (C) 2014 The Authors. Published by Elsevier Inc. This is an open access artic

关键词： tensor-based morphometry Fetal alcohol spectrum disorders Prenatal alcohol exposure Structural MRI Neurodevelopment Morphology Brain structure

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Growth-Associated Protein 43 and tensor-based morphometry Indices in Mild Cognitive Impairment

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NEUROINFORMATICS 2024年第3期22卷 239-250页

作者： Seyedmirzaei, Homa Salmannezhad, Amirhossein Ashayeri, Hamidreza Shushtari, Ali Farazinia, Bita Heidari, Mohammad Mahdi Momayezi, Amirali Shaki Baher, Sara Univ Tehran Med Sci Neurosci Inst Sports Med Res Ctr Tehran Iran Ghazvin Univ Med Sci Student Res Comm Ghazvin Iran Tabriz Univ Med Sci Student Res Comm Tabriz Iran Mazandaran Univ Med Sci Fac Med Sari Iran Islamic Azad Univ Fac Econ & Management Shiraz Branch Shiraz Iran Kashan Univ Med Sci Student Res Comm Fac Med Kashan Iran Iran Univ Sci & Technol Sch Chem Engn Tehran Iran Islamic Azad Univ Fac Med Tehran Branch Tehran Iran

Growth-associated protein 43 (GAP-43) is found in the axonal terminal of neurons in the limbic system, which is affected in people with Alzheimer's disease (AD). We assumed GAP-43 may contribute to AD progression and serve as a biomarker. So, in a two-year follow-up study, we assessed GAP-43 changes and whether they are correlated with tensor-based morphometry (TBM) findings in patients with mild cognitive impairment (MCI). We included MCI and cognitively normal (CN) people with available baseline and follow-up cerebrospinal fluid (CSF) GAP-43 and TBM findings from the ADNI database. We assessed the difference between the two groups and correlations in each group at each time point. CSF GAP-43 and TBM measures were similar in the two study groups in all time points, except for the accelerated anatomical region of interest (ROI) of CN subjects that were significantly greater than those of MCI. The only significant correlations with GAP-43 observed were those inverse correlations with accelerated and non-accelerated anatomical ROI in MCI subjects at baseline. Plus, all TBM metrics decreased significantly in all study groups during the follow-up in contrast to CSF GAP-43 levels. Our study revealed significant associations between CSF GAP-43 levels and TBM indices among people of the AD spectrum.

关键词： Growth-associated protein 43 Alzheimer's disease tensor-based morphometry Mild cognitive impairment Region of interest

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Atrophy progression in semantic dementia with asymmetric temporal involvement: A tensor-based morphometry study

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NEUROBIOLOGY OF AGING 2009年第1期30卷 103-111页

作者： Brambati, S. M. Rankin, K. P. Narvid, J. Seeley, W. W. Dean, D. Rosen, H. J. Miller, B. L. Ashburner, J. Gorno-Tempini, M. L. UCSF Dept Neurol Memory Aging Ctr San Francisco CA USA Univ Vita Salute San Raffaele Milan Italy Funct Imaging Lab Wellcome Dept Imaging Neurosci London England

We performed a longitudinal anatomical study to map the progression of gray matter atrophy in anatomically defined predominantly left (LTLV) and right (RTLV) temporal lobe variants of semantic dementia (SD). TI-weighted MRI scans were obtained at presentation and one-year follow-up from 13 LTLV, 6 RTLV, and 25 control subjects. tensor-based morphometry (TBM) in SPM2 was applied to derive a voxel-wise estimation of-regional tissue loss over time from the deformation held required to warp the follow-up scan to the presentation scan in each subject. When compared to controls, both LTLV and RTLV showed significant progression of gray matter atrophy not only within the temporal lobe most affected at presentation, but also in the controlateral temporal regions (p < 0.05 FWE corrected). In LTLV, significant progression of volume loss also involved the ventromedial frontal and the left anterior insular regions. These results identified the anatomic substartes of the previously reported clinical evolution of LTLV and RTLV into a unique 'merged' clinical syndrome characterized by semantic and behavioral deficits and bilateral temporal atrophy. (C) 2007 Elsevier Inc. All rights reserved.

关键词： tensor-based morphometry Semantic dementia Temporal lobe Progression of gray matter atrophy Longitudinal study

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