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Tranfa M, Lorenzini L, Collij LE, Vállez García D, Ingala S, Pontillo G, Pieperhoff L, Maranzano A, Wolz R, Haller S, Blennow K, Frisoni G, Sudre CH, Chételat G, Ewers M, Payoux P, Waldman A, Martinez‐Lage P, Schwarz AJ, Ritchie CW, Wardlaw JM, Gispert JD, Brunetti A, Mutsaerts HJMM, Wink AM, Barkhof F. Alzheimer's Disease and Small Vessel Disease Differentially Affect White Matter Microstructure. Ann Clin Transl Neurol 2024; 11:1541-1556. [PMID: 38757392 PMCID: PMC11187968 DOI: 10.1002/acn3.52071] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2024] [Accepted: 04/09/2024] [Indexed: 05/18/2024] Open
Abstract
OBJECTIVE Alzheimer's disease (AD) and cerebral small vessel disease (cSVD), the two most common causes of dementia, are characterized by white matter (WM) alterations diverging from the physiological changes occurring in healthy aging. Diffusion tensor imaging (DTI) is a valuable tool to quantify WM integrity non-invasively and identify the determinants of such alterations. Here, we investigated main effects and interactions of AD pathology, APOE-ε4, cSVD, and cardiovascular risk on spatial patterns of WM alterations in non-demented older adults. METHODS Within the prospective European Prevention of Alzheimer's Dementia study, we selected 606 participants (64.9 ± 7.2 years, 376 females) with baseline cerebrospinal fluid samples of amyloid β1-42 and p-Tau181 and MRI scans, including DTI scans. Longitudinal scans (mean follow-up time = 1.3 ± 0.5 years) were obtained in a subset (n = 223). WM integrity was assessed by extracting fractional anisotropy and mean diffusivity in relevant tracts. To identify the determinants of WM disruption, we performed a multimodel inference to identify the best linear mixed-effects model for each tract. RESULTS AD pathology, APOE-ε4, cSVD burden, and cardiovascular risk were all associated with WM integrity within several tracts. While limbic tracts were mainly impacted by AD pathology and APOE-ε4, commissural, associative, and projection tract integrity was more related to cSVD burden and cardiovascular risk. AD pathology and cSVD did not show any significant interaction effect. INTERPRETATION Our results suggest that AD pathology and cSVD exert independent and spatially different effects on WM microstructure, supporting the role of DTI in disease monitoring and suggesting independent targets for preventive medicine approaches.
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Affiliation(s)
- Mario Tranfa
- Department of Advanced Biomedical SciencesUniversity “Federico II”NaplesItaly
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
| | - Luigi Lorenzini
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain ImagingAmsterdamThe Netherlands
| | - Lyduine E. Collij
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain ImagingAmsterdamThe Netherlands
- Clinical Memory Research Unit, Department of Clinical SciencesLund UniversityMalmöSweden
| | - David Vállez García
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain ImagingAmsterdamThe Netherlands
| | - Silvia Ingala
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain ImagingAmsterdamThe Netherlands
- Department of RadiologyCopenhagen University Hospital RigshospitaletCopenhagenDenmark
- Cerebriu A/SCopenhagenDenmark
| | - Giuseppe Pontillo
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
| | - Leonard Pieperhoff
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain ImagingAmsterdamThe Netherlands
| | - Alessio Maranzano
- Department of Neurology and Laboratory of NeuroscienceIRCCS Istituto Auxologico ItalianoMilanItaly
| | | | - Sven Haller
- CIMC ‐ Centre d'Imagerie Médicale de CornavinGenevaSwitzerland
- Department of Surgical Sciences, RadiologyUppsala UniversityUppsalaSweden
- Department of Radiology, Beijing Tiantan HospitalCapital Medical UniversityBeijingChina
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
- Clinical Neurochemistry LaboratorySahlgrenska University HospitalMölndalSweden
| | - Giovanni Frisoni
- Laboratory Alzheimer's Neuroimaging & EpidemiologyIRCCS Istituto Centro San Giovanni di Dio FatebenefratelliBresciaItaly
- University Hospitals and University of GenevaGenevaSwitzerland
| | - Carole H. Sudre
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience and PhysiologyThe Sahlgrenska Academy at the University of GothenburgGothenburgSweden
- Department of Medical Physics and Biomedical Engineering, Centre for Medical Image Computing (CMIC)University College London (UCL)LondonUK
- MRC Unit for Lifelong Health & Ageing at UCLUniversity College LondonLondonUK
- School of Biomedical Engineering and Imaging SciencesKing's College LondonLondonUK
| | - Gael Chételat
- Normandie Univ, Unicaen, Inserm, U1237, PhIND “Physiopathology and Imaging of Neurological Disorders”, institut Blood‐and‐Brain @ Caen‐Normandie, CyceronUniversité de NormandieCaenFrance
| | - Michael Ewers
- German Center for Neurodegenerative Diseases (DZNE)MunichGermany
| | - Pierre Payoux
- Department of Nuclear MedicineToulouse University HospitalToulouseFrance
- ToNIC, Toulouse NeuroImaging CenterUniversity of Toulouse, Inserm, UPSToulouseFrance
| | - Adam Waldman
- Centre for Clinical Brain SciencesThe University of EdinburghEdinburghUK
- Department of MedicineImperial College LondonLondonUK
| | - Pablo Martinez‐Lage
- Centro de Investigación y Terapias Avanzadas, Neurología, CITA‐Alzheimer FoundationSan SebastiánSpain
| | - Adam J. Schwarz
- Takeda Pharmaceuticals, Ltd.CambridgeMassachusettsUSA
- Department of Radiology and Imaging SciencesIndiana University School of MedicineIndianapolisIndianaUSA
| | - Craig W. Ritchie
- Edinburgh Dementia Prevention, Centre for Clinical Brain Sciences, Outpatient Department 2, Western General HospitalUniversity of EdinburghEdinburghUK
- Brain Health ScotlandEdinburghUK
| | - Joanna M. Wardlaw
- Centre for Clinical Brain SciencesThe University of EdinburghEdinburghUK
- UK Dementia Research Institute Centre at the University of EdinburghEdinburghUK
| | - Juan Domingo Gispert
- Barcelonaβeta Brain Research Center (BBRC), Pasqual Maragall FoundationBarcelonaSpain
- CIBER Bioingeniería, Biomateriales y Nanomedicina (CIBER‐BBN)MadridSpain
- IMIM (Hospital del Mar Medical Research Institute)BarcelonaSpain
- Universitat Pompeu FabraBarcelonaSpain
| | - Arturo Brunetti
- Department of Advanced Biomedical SciencesUniversity “Federico II”NaplesItaly
| | - Henk J. M. M. Mutsaerts
- Amsterdam Neuroscience, Brain ImagingAmsterdamThe Netherlands
- Ghent Institute for Functional and Metabolic Imaging (GIfMI)Ghent UniversityGhentBelgium
| | - Alle Meije Wink
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
- Amsterdam Neuroscience, Brain ImagingAmsterdamThe Netherlands
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical CentreVrije UniversiteitAmsterdamThe Netherlands
- Institute of Neurology and Healthcare EngineeringUniversity College LondonLondonUK
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Diao Y, Lanz B, Jelescu IO. Subject classification and cross-time prediction based on functional connectivity and white matter microstructure features in a rat model of Alzheimer's using machine learning. Alzheimers Res Ther 2023; 15:193. [PMID: 37936236 PMCID: PMC10629161 DOI: 10.1186/s13195-023-01328-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2023] [Accepted: 10/09/2023] [Indexed: 11/09/2023]
Abstract
BACKGROUND The pathological process of Alzheimer's disease (AD) typically takes decades from onset to clinical symptoms. Early brain changes in AD include MRI-measurable features such as altered functional connectivity (FC) and white matter degeneration. The ability of these features to discriminate between subjects without a diagnosis, or their prognostic value, is however not established. METHODS The main trigger mechanism of AD is still debated, although impaired brain glucose metabolism is taking an increasingly central role. Here, we used a rat model of sporadic AD, based on impaired brain glucose metabolism induced by an intracerebroventricular injection of streptozotocin (STZ). We characterized alterations in FC and white matter microstructure longitudinally using functional and diffusion MRI. Those MRI-derived measures were used to classify STZ from control rats using machine learning, and the importance of each individual measure was quantified using explainable artificial intelligence methods. RESULTS Overall, combining all the FC and white matter metrics in an ensemble way was the best strategy to discriminate STZ rats, with a consistent accuracy over 0.85. However, the best accuracy early on was achieved using white matter microstructure features, and later on using FC. This suggests that consistent damage in white matter in the STZ group might precede FC. For cross-timepoint prediction, microstructure features also had the highest performance while, in contrast, that of FC was reduced by its dynamic pattern which shifted from early hyperconnectivity to late hypoconnectivity. CONCLUSIONS Our study highlights the MRI-derived measures that best discriminate STZ vs control rats early in the course of the disease, with potential translation to humans.
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Affiliation(s)
- Yujian Diao
- Animal Imaging and Technology Section, CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
- Laboratory for Functional and Metabolic Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Bernard Lanz
- Animal Imaging and Technology Section, CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland
| | - Ileana Ozana Jelescu
- Animal Imaging and Technology Section, CIBM Center for Biomedical Imaging, Ecole Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland.
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Delvenne JF, Scally B, Rose Burke M. Splenium tract projections of the corpus callosum to the parietal cortex classifies Alzheimer's disease and mild cognitive impairment. Neurosci Lett 2023; 810:137331. [PMID: 37302566 PMCID: PMC10862691 DOI: 10.1016/j.neulet.2023.137331] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/16/2023] [Accepted: 06/06/2023] [Indexed: 06/13/2023]
Abstract
The corpus callosum (CC) is the largest bundle of white matter tracts in the brain connecting the left and right cerebral hemispheres. The posterior region of the CC, known as the splenium, seems to be relatively preserved throughout the lifespan and is regularly examined for indications of various pathologies, including Alzheimer's disease (AD) and Mild Cognitive Impairment (MCI). However, the splenium has rarely been investigated in terms of its distinct inter-hemispheric tract bundles that project to bilateral occipital, parietal and temporal areas of the cortex. The aim of the present study was to determine if any of these sub-splenium tract bundles are specifically affected by individuals with AD and MCI compared to normal controls. Diffusion Tensor Imaging was used to directly examine the integrity of these distinct tract bundles and their diffusion metrics were compared between groups of MCI, AD, and control individuals. Results revealed that differences between MCI, AD, and controls were particularly evident at parietal tracts of the CC splenium and were consistent with an interpretation of compromised white matter integrity. Combined parietal tract diffusivity and density information strongly discriminated between AD patients and controls with an accuracy (AUC) of 97.19%. Combined parietal tract diffusivity parameters correctly classified MCI subjects against controls with an accuracy of 74.97%. These findings demonstrated the potential of examining the CC splenium in terms of its distinct inter-hemispheric tract bundles for the diagnosis of AD and MCI.
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Affiliation(s)
| | - Brian Scally
- School of Psychology, University of Leeds, United Kingdom
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Saini F, Dell’Acqua F, Strydom A. Structural Connectivity in Down Syndrome and Alzheimer's Disease. Front Neurosci 2022; 16:908413. [PMID: 35937882 PMCID: PMC9354601 DOI: 10.3389/fnins.2022.908413] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2022] [Accepted: 06/21/2022] [Indexed: 12/02/2022] Open
Abstract
Down syndrome (DS) arises from the triplication of chromosome 21, which leads to an atypical neurodevelopment and the overproduction of the amyloid precursor protein, predisposing to early Alzheimer's disease (AD). Not surprisingly, trisomy 21 is widely considered a model to study predementia stages of AD. After decades, in which neural loss was the main focus, research in AD is now moving toward understanding the neurodegenerative aspects affecting white matter. Motivated by the development of magnetic resonance imaging (MRI)-based diffusion techniques, this shift in focus has led to several exploratory studies on both young and older individuals with DS. In this review, we synthesise the initial efforts made by researchers in characterising in-vivo structural connectivity in DS, together with the AD footprint on top of such pre-existing connectivity related to atypical brain development. The white matter structures found to be affected in DS are the corpus callosum and all the main long-association fibres, namely the inferior fronto-occipital fasciculus, the inferior and superior longitudinal fasciculus, the uncinate fasciculus and the cingulum bundle. Furthermore, the cingulum bundle and the corpus callosum appear to be particularly sensitive to early AD changes in this population. Findings are discussed in terms of their functional significance, alongside methodological considerations and implications for future research.
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Affiliation(s)
- Fedal Saini
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Flavio Dell’Acqua
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Department of Neuroimaging, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
- Department of Forensic and Neurodevelopmental Sciences, Sackler Institute for Translational Neurodevelopment, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
| | - Andre Strydom
- Department of Forensic and Neurodevelopmental Sciences, Institute of Psychiatry, Psychology and Neuroscience, King’s College London, London, United Kingdom
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Keong NC, Lock C, Soon S, Hernowo AT, Czosnyka Z, Czosnyka M, Pickard JD, Narayanan V. Diffusion Tensor Imaging Profiles Can Distinguish Diffusivity and Neural Properties of White Matter Injury in Hydrocephalus vs. Non-hydrocephalus Using a Strategy of a Periodic Table of DTI Elements. Front Neurol 2022; 13:868026. [PMID: 35873785 PMCID: PMC9296826 DOI: 10.3389/fneur.2022.868026] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/02/2022] [Accepted: 04/01/2022] [Indexed: 11/13/2022] Open
Abstract
Background:The aim of this study was to create a simplistic taxonomy to improve transparency and consistency in, and reduce complexity of, interpreting diffusion tensor imaging (DTI) profiles in white matter disruption. Using a novel strategy of a periodic table of DTI elements, we examined if DTI profiles could demonstrate neural properties of disruption sufficient to characterize white matter changes specific for hydrocephalus vs. non-hydrocephalus, and to distinguish between cohorts of neural injury by their differing potential for reversibility.MethodsDTI datasets from three clinical cohorts representing pathological milestones from reversible to irreversible brain injury were compared to those of healthy controls at baseline, over time and with interventions. The final dataset comprised patients vs. controls in the following groupings: mild traumatic brain injury (mTBI), n = 24 vs. 27, normal pressure hydrocephalus (NPH), n = 16 vs. 9 and Alzheimer's disease (AD), n = 27 vs. 47. We generated DTI profiles from fractional anisotropy (FA) and mean, axial and radial diffusivity measures (MD, L1 and L2 and 3 respectively), and constructed an algorithm to map changes consistently to a periodic table of elements, which fully described their diffusivity and neural properties.ResultsMapping tissue signatures to a periodic table of DTI elements rapidly characterized cohorts by their differing patterns of injury. At baseline, patients with mTBI displayed the most preserved tracts. In NPH, the magnitude of changes was dependent on “familial” DTI neuroanatomy, i.e., potential for neural distortion from risk of ventriculomegaly. With time, patients with Alzheimer's disease were significantly different to controls across multiple measures. By contrast, patients with mTBI showed both loss of integrity and pathophysiological processes of neural repair. In NPH, some patterns of injury, such as “stretch/compression” and “compression” were more reversible following intervention than others; these neural profile properties suggested “microstructural resilience” to injury.ConclusionUsing the novel strategy of a periodic table of DTI elements, our study has demonstrated it is possible to distinguish between different cohorts along the spectrum of brain injury by describing neural profile properties of white matter disruption. Further work to contribute datasets of disease toward this proposed taxonomic framework would enhance the translatability of DTI profiles to the clinical-research interface.
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Affiliation(s)
- Nicole C. Keong
- Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
- Duke-NUS Medical School, Singapore, Singapore
- *Correspondence: Nicole C. Keong
| | - Christine Lock
- Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
| | - Shereen Soon
- Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
| | - Aditya Tri Hernowo
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
| | - Zofia Czosnyka
- Neurosurgical Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Marek Czosnyka
- Neurosurgical Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - John D. Pickard
- Neurosurgical Division, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom
| | - Vairavan Narayanan
- Department of Surgery, Faculty of Medicine, University of Malaya, Kuala Lumpur, Malaysia
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Smigielski L, Stämpfli P, Wotruba D, Buechler R, Sommer S, Gerstenberg M, Theodoridou A, Walitza S, Rössler W, Heekeren K. White matter microstructure and the clinical risk for psychosis: A diffusion tensor imaging study of individuals with basic symptoms and at ultra-high risk. Neuroimage Clin 2022; 35:103067. [PMID: 35679786 PMCID: PMC9178487 DOI: 10.1016/j.nicl.2022.103067] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/23/2022] [Revised: 05/19/2022] [Accepted: 05/28/2022] [Indexed: 12/29/2022]
Abstract
This DTI cross-sectional study compared UHR, basic symptom & control groups (n = 112). The splenium of UHR individuals exhibited differences in fractional anisotropy (FA). Basic symptoms alone were not associated with white matter microstructure changes. Large differences in FA & radial diffusivity were found in converters to psychosis. Regional FA was inversely correlated with the general psychopathology domain.
Background Widespread white matter abnormalities are a frequent finding in chronic schizophrenia patients. More inconsistent results have been provided by the sparser literature on at-risk states for psychosis, i.e., emerging subclinical symptoms. However, considering risk as a homogenous construct, an approach of earlier studies, may impede our understanding of neuro-progression into psychosis. Methods An analysis was conducted of 3-Tesla MRI diffusion and symptom data from 112 individuals (mean age, 21.97 ± 4.19) within two at-risk paradigm subtypes, only basic symptoms (n = 43) and ultra-high risk (n = 37), and controls (n = 32). Between-group comparisons (involving three study groups and further split based on the subsequent transition to schizophrenia) of four diffusion-tensor-imaging-derived scalars were performed using voxelwise tract-based spatial statistics, followed by correlational analyses with Structured Interview for Prodromal Syndromes responses. Results Relative to controls, fractional anisotropy was lower in the splenium of the corpus callosum of ultra-high-risk individuals, but only before stringent multiple-testing correction, and negatively correlated with General Symptom severity among at-risk individuals. At-risk participants who transitioned to schizophrenia within 3 years, compared to those that did not transition, had more severe WM differences in fractional anisotropy and radial diffusivity (particularly in the corpus callosum, anterior corona radiata, and motor/sensory tracts), which were even more extensive compared to healthy controls. Conclusions These findings align with the subclinical symptom presentation and more extensive disruptions in converters, suggestive of severity-related demyelination or axonal pathology. Fine-grained but detectable differences among ultra-high-risk subjects (i.e., with brief limited intermittent and/or attenuated psychotic symptoms) point to the splenium as a discrete site of emerging psychopathology, while basic symptoms alone were not associated with altered fractional anisotropy.
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Affiliation(s)
- Lukasz Smigielski
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland.
| | - Philipp Stämpfli
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; MR-Center of the Psychiatric Hospital and the Department of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland
| | - Diana Wotruba
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Roman Buechler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Neuroradiology, University Hospital of Zurich, Zurich, Switzerland
| | - Stefan Sommer
- Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; MR-Center of the Psychiatric Hospital and the Department of Child and Adolescent Psychiatry, University of Zurich, Zurich, Switzerland
| | - Miriam Gerstenberg
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Anastasia Theodoridou
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland
| | - Susanne Walitza
- Department of Child and Adolescent Psychiatry and Psychotherapy, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Neuroscience Center Zurich, University of Zurich and ETH Zurich, Zurich, Switzerland; Zurich Center for Integrative Human Physiology, University of Zurich, Zurich, Switzerland
| | - Wulf Rössler
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry and Psychotherapy, Charité Universitätsmedizin, Campus Charité Mitte, Berlin, Germany; Laboratory of Neuroscience (LIM 27), Institute of Psychiatry, Universidade de São Paulo, São Paulo, Brazil
| | - Karsten Heekeren
- The Zurich Program for Sustainable Development of Mental Health Services (ZInEP), Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric University Hospital Zurich, University of Zurich, Zurich, Switzerland; Department of Psychiatry and Psychotherapy I, LVR-Hospital, Cologne, Germany
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7
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Kok CY, Lock C, Ang TY, Keong NC. Modeling the Properties of White Matter Tracts Using Diffusion Tensor Imaging to Characterize Patterns of Injury in Aging and Neurodegenerative Disease. Front Aging Neurosci 2022; 14:787516. [PMID: 35572145 PMCID: PMC9093601 DOI: 10.3389/fnagi.2022.787516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Accepted: 03/15/2022] [Indexed: 11/13/2022] Open
Abstract
Diffusion tensor imaging (DTI) is a relatively novel magnetic resonance-based imaging methodology that can provide valuable insight into the microstructure of white matter tracts of the brain. In this paper, we evaluated the reliability and reproducibility of deriving a semi-automated pseudo-atlas DTI tractography method vs. standard atlas-based analysis alternatives, for use in clinical cohorts with neurodegeneration and ventriculomegaly. We showed that the semi-automated pseudo-atlas DTI tractography method was reliable and reproducible across different cohorts, generating 97.7% of all tracts. However, DTI metrics obtained from both methods were significantly different across the majority of cohorts and white matter tracts (p < 0.001). Despite this, we showed that both methods produced patterns of white matter injury that are consistent with findings reported in the literature and with DTI profiles generated from these methodologies. Scatter plots comparing DTI metrics obtained from each methodology showed that the pseudo-atlas method produced metrics that implied a more preserved neural structure compared to its counterpart. When comparing DTI metrics against a measure of ventriculomegaly (i.e., Evans’ Index), we showed that the standard atlas-based method was able to detect decreasing white matter integrity with increasing ventriculomegaly, while in contrast, metrics obtained using the pseudo-atlas method were sensitive for stretch or compression in the posterior limb of the internal capsule. Additionally, both methods were able to show an increase in white matter disruption with increasing ventriculomegaly, with the pseudo-atlas method showing less variability and more specificity to changes in white matter tracts near to the ventricles. In this study, we found that there was no true gold-standard for DTI methodologies or atlases. Whilst there was no congruence between absolute values from DTI metrics, differing DTI methodologies were still valid but must be appreciated to be variably sensitive to different changes within white matter injury occurring concurrently. By combining both atlas and pseudo-atlas based methodologies with DTI profiles, it was possible to navigate past such challenges to describe white matter injury changes in the context of confounders, such as neurodegenerative disease and ventricular enlargement, with transparency and consistency.
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Affiliation(s)
- Chun Yen Kok
- Duke-National University of Singapore (NUS) Medical School, Singapore, Singapore
| | - Christine Lock
- Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
| | - Ting Yao Ang
- Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
| | - Nicole C Keong
- Duke-National University of Singapore (NUS) Medical School, Singapore, Singapore
- Department of Neurosurgery, National Neuroscience Institute, Singapore, Singapore
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Fleischman DA, Arfanakis K, Leurgans SE, Zhang S, Poole VN, Han SD, Yu L, Lamar M, Kim N, Bennett DA, Barnes LL. Associations of deformation-based brain morphometry with cognitive level and decline within older Blacks without dementia. Neurobiol Aging 2022; 111:35-43. [PMID: 34963062 PMCID: PMC9070546 DOI: 10.1016/j.neurobiolaging.2021.11.003] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2021] [Revised: 11/04/2021] [Accepted: 11/14/2021] [Indexed: 10/19/2022]
Abstract
Blacks are at higher risk of developing cognitive impairment with age than non-Hispanic Whites, yet most brain morphometry and cognition research is performed with White samples or with mixed samples that control for race or compare across racial groups. A deeper understanding of the within-group variability in associations between brain structure and cognitive decline in Blacks is critically important for designing appropriate outcomes for clinical trials, predicting adverse outcomes, and developing interventions to preserve cognitive function, but no studies have examined these associations longitudinally within Blacks. We performed deformation-based morphometry in 376 older Black participants without dementia and examined associations of deformation-based morphometry with cognitive level and decline for global cognition and five cognitive domains. After correcting for widespread age-associated effects, there remained regions with less tissue and more cerebrospinal fluid associated with level and rate of decline in global cognition, memory, and perceptual speed. Further study is needed to examine the moderators of these associations, identify adverse outcomes predicted by brain morphometry, and deepen knowledge of underlying biological mechanisms.
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Affiliation(s)
- Debra A Fleischman
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA; Department of Neurological Sciences, Rush University Medical Center, Chicago IL, USA; Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago IL, USA.
| | - Konstantinos Arfanakis
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA; Department of Diagnostic Radiology and Nuclear Medicine, Rush University Medical Center, Chicago IL, USA; Department of Biomedical Engineering, Illinois Institute of Technology, Chicago, IL, USA
| | - Sue E Leurgans
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA; Department of Preventive Medicine, Rush University Medical Center, Chicago IL, USA
| | - Shengwei Zhang
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA
| | - Victoria N Poole
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA; Department of Orthopedic Surgery, Rush University Medical Center, Chicago IL, USA
| | - S Duke Han
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA; Departments of Family Medicine and Neurology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Department of Psychology, University of Southern California, Los Angeles, CA, USA; School of Gerontology, University of Southern California, Los Angeles, CA, USA
| | - Lei Yu
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA
| | - Melissa Lamar
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA; Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago IL, USA
| | - Namhee Kim
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA
| | - David A Bennett
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA
| | - Lisa L Barnes
- Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago IL, USA; Department of Neurological Sciences, Rush University Medical Center, Chicago IL, USA; Department of Psychiatry and Behavioral Sciences, Rush University Medical Center, Chicago IL, USA
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9
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Itaguchi Y, Castro-Chavira SA, Waterloo K, Johnsen SH, Rodríguez-Aranda C. Evaluation of Error Production in Animal Fluency and Its Relationship to Frontal Tracts in Normal Aging and Mild Alzheimer's Disease: A Combined LDA and Time-Course Analysis Investigation. Front Aging Neurosci 2022; 13:710938. [PMID: 35095462 PMCID: PMC8790484 DOI: 10.3389/fnagi.2021.710938] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/17/2021] [Accepted: 12/06/2021] [Indexed: 11/13/2022] Open
Abstract
Semantic verbal fluency (VF), assessed by animal category, is a task widely used for early detection of dementia. A feature not regularly assessed is the occurrence of errors such as perseverations and intrusions. So far, no investigation has analyzed the how and when of error occurrence during semantic VF in aging populations, together with their possible neural correlates. The present study aims to address the issue using a combined methodology based on latent Dirichlet allocation (LDA) analysis for word classification together with a time-course analysis identifying exact time of errors' occurrence. LDA is a modeling technique that discloses hidden semantic structures based on a given corpus of documents. We evaluated a sample of 66 participants divided into a healthy young group (n = 24), healthy older adult group (n = 23), and group of patients with mild Alzheimer's disease (AD) (n = 19). We performed DTI analyses to evaluate the white matter integrity of three frontal tracts purportedly underlying error commission: anterior thalamic radiation, frontal aslant tract, and uncinate fasciculus. Contrasts of DTI metrics were performed on the older groups who were further classified into high-error rate and low-error rate subgroups. Results demonstrated a unique deployment of error commission in the patient group characterized by high incidence of intrusions in the first 15 s and higher rate of perseverations toward the end of the trial. Healthy groups predominantly showed very low incidence of perseverations. The DTI analyses revealed that the patients with AD committing high-error rate presented significantly more degenerated frontal tracts in the left hemisphere. Thus, our findings demonstrated that the appearance of intrusions, together with left hemisphere degeneration of frontal tracts, is a pathognomic trait of mild AD. Furthermore, our data suggest that the error commission of patients with AD arises from executive and working memory impairments related partly to deteriorated left frontal tracts.
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Affiliation(s)
| | | | - Knut Waterloo
- Department of Psychology, UiT The Artic University of Norway, Tromsø, Norway
- Department of Neurology, University Hospital North Norway, Tromsø, Norway
| | - Stein Harald Johnsen
- Department of Neurology, University Hospital North Norway, Tromsø, Norway
- Brain and Circulation Research Group, Department of Clinical Medicine, UiT The Artic University of Norway, Tromsø, Norway
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10
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Van der Linden A, Hoehn M. Monitoring Neuronal Network Disturbances of Brain Diseases: A Preclinical MRI Approach in the Rodent Brain. Front Cell Neurosci 2022; 15:815552. [PMID: 35046778 PMCID: PMC8761853 DOI: 10.3389/fncel.2021.815552] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/15/2021] [Accepted: 12/06/2021] [Indexed: 12/20/2022] Open
Abstract
Functional and structural neuronal networks, as recorded by resting-state functional MRI and diffusion MRI-based tractography, gain increasing attention as data driven whole brain imaging methods not limited to the foci of the primary pathology or the known key affected regions but permitting to characterize the entire network response of the brain after disease or injury. Their connectome contents thus provide information on distal brain areas, directly or indirectly affected by and interacting with the primary pathological event or affected regions. From such information, a better understanding of the dynamics of disease progression is expected. Furthermore, observation of the brain's spontaneous or treatment-induced improvement will contribute to unravel the underlying mechanisms of plasticity and recovery across the whole-brain networks. In the present review, we discuss the values of functional and structural network information derived from systematic and controlled experimentation using clinically relevant animal models. We focus on rodent models of the cerebral diseases with high impact on social burdens, namely, neurodegeneration, and stroke.
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Affiliation(s)
- Annemie Van der Linden
- Bio-Imaging Lab, Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium
- μNEURO Research Centre of Excellence, University of Antwerp, Antwerp, Belgium
| | - Mathias Hoehn
- Research Center Jülich, Institute 3 for Neuroscience and Medicine, Jülich, Germany
- *Correspondence: Mathias Hoehn
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11
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Lin CP, Frigerio I, Boon BDC, Zhou Z, Rozemuller AJM, Bouwman FH, Schoonheim MM, van de Berg WDJ, Jonkman LE. OUP accepted manuscript. Brain 2022; 145:2869-2881. [PMID: 35259207 PMCID: PMC9420016 DOI: 10.1093/brain/awac093] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/06/2021] [Revised: 01/23/2022] [Accepted: 02/13/2022] [Indexed: 11/24/2022] Open
Abstract
Cognitive deficits in Alzheimer’s disease, specifically amnestic (memory dominant) deficits, are associated with cholinergic degeneration in the basal forebrain. The cholinergic nucleus within the basal forebrain, the nucleus basalis of Meynert, exhibits local atrophy and reduced cortical tract integrity on MRI, and reveals amyloid-β and phosphorylated-tau pathology at autopsy. To understand the pathophysiology of nucleus basalis of Meynert atrophy and its neocortical projections in Alzheimer’s disease, we used a combined post-mortem in situ MRI and histopathology approach. A total of 19 Alzheimer’s disease (10 amnestic and nine non-amnestic) and nine non-neurological control donors underwent 3 T T1-weighted MRI for anatomical delineation and volume assessment of the nucleus basalis of Meynert, and diffusion-weighted imaging for microstructural assessment of the nucleus and its projections. At subsequent brain autopsy, tissue dissection and immunohistochemistry were performed for amyloid-β, phosphorylated-tau and choline acetyltransferase. Compared to controls, we observed an MRI-derived volume reduction and altered microstructural integrity of the nucleus basalis of Meynert in Alzheimer’s disease donors. Furthermore, decreased cholinergic cell density was associated with reduced integrity of the nucleus and its tracts to the temporal lobe, specifically to the temporal pole of the superior temporal gyrus, and the parahippocampal gyrus. Exploratory post hoc subgroup analyses indicated that cholinergic cell density could be associated with cortical tract alterations in amnestic Alzheimer’s disease donors only. Our study illustrates that in Alzheimer’s disease, cholinergic degeneration in the nucleus basalis of Meynert may contribute to damaged cortical projections, specifically to the temporal lobe, leading to cognitive deterioration.
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Affiliation(s)
- Chen Pei Lin
- Correspondence to: Chen-Pei Lin De Boelelaan 1117 1081 HV, Amsterdam, The Netherlands E-mail:
| | - Irene Frigerio
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Baayla D C Boon
- Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Department of Pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer centrum Amsterdam, Amsterdam, The Netherlands
| | - Zihan Zhou
- Zhejiang University, College of Biomedical Engineering and Instrument Science, Zhejiang, China
| | - Annemieke J M Rozemuller
- Amsterdam UMC, location VUmc, Vrije Universiteit Amsterdam, Department of Pathology, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Femke H Bouwman
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Neurology, Alzheimer centrum Amsterdam, Amsterdam, The Netherlands
| | - Menno M Schoonheim
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Wilma D J van de Berg
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
| | - Laura E Jonkman
- Amsterdam UMC, Location VUmc, Vrije Universiteit Amsterdam, Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam, The Netherlands
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12
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Chabran E, Mondino M, Noblet V, Degiorgis L, Loureiro de Sousa P, Blanc F. Microstructural changes in prodromal dementia with Lewy bodies compared to normal aging: multiparametric quantitative MRI evidences. Eur J Neurosci 2021; 55:611-623. [PMID: 34888964 DOI: 10.1111/ejn.15558] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2021] [Revised: 11/08/2021] [Accepted: 11/20/2021] [Indexed: 11/29/2022]
Abstract
Dementia with Lewy bodies (DLB) patients show few significant macroscopic structural changes, especially at the early stages of the disease, making quantitative MRI especially interesting to explore more subtle changes that are not detectable by conventional volumetric techniques. Microstructural alterations have been reported in DLB at the dementia stage, but no study to date was conducted in prodromal patients. Here, quantitative MRI data were collected from 46 DLB prodromal patients and 20 healthy elderly subjects, who also underwent a detailed clinical examination including the Mayo Clinic Fluctuation Scale. We conducted voxel-wise between-group comparisons in diffusion tensor imaging (DTI) metrics and in R2* mapping, along with a multivariate analysis combining the two modalities. We highlighted multiple grey matter and white matter microstructural changes in DLB patients at the prodromal stage, compared to control subjects. Our multivariate analysis identified three distinct regional patterns of DTI and R2* changes (anterior, anteromedial, posterior) in DLB patients, that could reflect different neuropathological processes across brain regions. We also observed an association between R2* alterations in the thalamus, and the severity of fluctuations, in the DLB group. These preliminary findings are promising and require future investigations to better understand the biological underpinnings of microstructural alterations.
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Affiliation(s)
- Eléna Chabran
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), IMIS team and IRIS plateform, University of Strasbourg and CNRS, Strasbourg, France
| | - Mary Mondino
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), IMIS team and IRIS plateform, University of Strasbourg and CNRS, Strasbourg, France
| | - Vincent Noblet
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), IMIS team and IRIS plateform, University of Strasbourg and CNRS, Strasbourg, France
| | - Laetitia Degiorgis
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), IMIS team and IRIS plateform, University of Strasbourg and CNRS, Strasbourg, France
| | - Paulo Loureiro de Sousa
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), IMIS team and IRIS plateform, University of Strasbourg and CNRS, Strasbourg, France
| | - Frédéric Blanc
- ICube Laboratory UMR 7357 and FMTS (Fédération de Médecine Translationnelle de Strasbourg), IMIS team and IRIS plateform, University of Strasbourg and CNRS, Strasbourg, France.,CM2R (Research and Resources Memory Centre), Geriatric Day Hospital and Neuropsychology Unit, Geriatrics Department, University Hospitals of Strasbourg, Strasbourg, France
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13
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Toniolo S, Serra L, Olivito G, Caltagirone C, Mercuri NB, Marra C, Cercignani M, Bozzali M. Cerebellar White Matter Disruption in Alzheimer's Disease Patients: A Diffusion Tensor Imaging Study. J Alzheimers Dis 2021; 74:615-624. [PMID: 32065792 DOI: 10.3233/jad-191125] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023]
Abstract
The cognitive role of the cerebellum has recently gained much attention, and its pivotal role in Alzheimer's disease (AD) has now been widely recognized. Diffusion tensor imaging (DTI) has been used to evaluate the disruption of the microstructural milieu in AD, and though several white matter (WM) tracts such as corpus callosum, inferior and superior longitudinal fasciculus, cingulum, fornix, and uncinate fasciculus have been evaluated in AD, data on cerebellar WM tracts are currently lacking. We performed a tractography-based DTI reconstruction of the middle cerebellar peduncle (MCP), and the left and right superior cerebellar peduncles separately (SCPL and SCPR) and addressed the differences in fractional anisotropy (FA), axial diffusivity (Dax), radial diffusivity (RD), and mean diffusivity (MD) in the three tracts between 50 patients with AD and 25 healthy subjects. We found that AD patients showed a lower FA and a higher RD compared to healthy subjects in MCP, SCPL, and SCPR. Moreover, higher MD was found in SCPR and SCPL and higher Dax in SCPL. This result is important as it challenges the traditional view that WM bundles in the cerebellum are unaffected in AD and might identify new targets for therapeutic interventions.
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Affiliation(s)
- Sofia Toniolo
- Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Rome, Italy.,Department of Neuroscience, University of Rome 'Tor Vergata', Rome, Italy
| | - Laura Serra
- Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Rome, Italy
| | - Giusy Olivito
- Department of Psychology, Sapienza University of Rome, Rome, Italy.,Ataxia Research Laboratory-Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Carlo Caltagirone
- Department of Neuroscience, University of Rome 'Tor Vergata', Rome, Italy.,Ataxia Research Laboratory-Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | | | - Camillo Marra
- Department of Clinical and Behavioural Neurology, Fondazione Santa Lucia, IRCCS, Rome, Italy
| | | | - Marco Bozzali
- Neuroimaging Laboratory, Fondazione Santa Lucia, IRCCS, Rome, Italy.,Institute of Neurology, Catholic University, Rome, Italy
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14
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Garnier-Crussard A, Bougacha S, Wirth M, Dautricourt S, Sherif S, Landeau B, Gonneaud J, De Flores R, de la Sayette V, Vivien D, Krolak-Salmon P, Chételat G. White matter hyperintensity topography in Alzheimer's disease and links to cognition. Alzheimers Dement 2021; 18:422-433. [PMID: 34322985 PMCID: PMC9292254 DOI: 10.1002/alz.12410] [Citation(s) in RCA: 56] [Impact Index Per Article: 18.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/16/2020] [Revised: 06/09/2021] [Accepted: 06/09/2021] [Indexed: 01/18/2023]
Abstract
Introduction White matter hyperintensities (WMH) are often described in Alzheimer's disease (AD), but their topography and specific relationships with cognition remain unclear. Methods Regional WMH were estimated in 54 cognitively impaired amyloid beta–positive AD (Aβpos‐AD), compared to 40 cognitively unimpaired amyloid beta–negative older controls (Aβneg‐controls) matched for vascular risk factors. The cross‐sectional association between regional WMH volume and cognition was assessed within each group, controlling for cerebral amyloid burden, global cortical atrophy, and hippocampal atrophy. Results WMH volume was larger in Aβpos‐AD compared to Aβneg‐controls in all regions, with the greatest changes in the splenium of the corpus callosum (S‐CC). In Aβpos‐AD patients, larger total and regional WMH volume, especially in the S‐CC, was strongly associated with decreased cognition. Discussion WMH specifically contribute to lower cognition in AD, independently from amyloid deposition and atrophy. This study emphasizes the clinical relevance of WMH in AD, especially posterior WMH, and most notably S‐CC WMH.
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Affiliation(s)
- Antoine Garnier-Crussard
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France.,Clinical and Research Memory Center of Lyon, Lyon Institute For Elderly, Hospices Civils de Lyon, Lyon, France.,University of Lyon, Lyon, France
| | - Salma Bougacha
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Miranka Wirth
- German Center for Neurodegenerative Diseases (DZNE), Dresden, Germany
| | - Sophie Dautricourt
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France.,Department of Neurology, CHU de Caen, Caen, France
| | - Siya Sherif
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Brigitte Landeau
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Julie Gonneaud
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Robin De Flores
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
| | - Vincent de la Sayette
- Department of Neurology, CHU de Caen, Caen, France.,Normandie Univ, UNICAEN, PSL Université, EPHE, INSERM, U1077, CHU de Caen, GIP Cyceron, NIMH, Caen, France
| | - Denis Vivien
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France.,Department of Clinical Research, CHU de Caen, Caen, France
| | - Pierre Krolak-Salmon
- Clinical and Research Memory Center of Lyon, Lyon Institute For Elderly, Hospices Civils de Lyon, Lyon, France.,University of Lyon, Lyon, France.,Neuroscience Research Centre of Lyon, INSERM 1048, CNRS 5292, Lyon, France
| | - Gaël Chételat
- Normandie Univ, UNICAEN, INSERM, U1237, PhIND "Physiopathology and Imaging of Neurological Disorders,", Institut Blood and Brain @ Caen-Normandie, Cyceron, Caen, France
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15
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Bergamino M, Walsh RR, Stokes AM. Free-water diffusion tensor imaging improves the accuracy and sensitivity of white matter analysis in Alzheimer's disease. Sci Rep 2021; 11:6990. [PMID: 33772083 PMCID: PMC7998032 DOI: 10.1038/s41598-021-86505-7] [Citation(s) in RCA: 30] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2020] [Accepted: 03/09/2021] [Indexed: 12/11/2022] Open
Abstract
Magnetic resonance imaging (MRI) based diffusion tensor imaging (DTI) can assess white matter (WM) integrity through several metrics, such as fractional anisotropy (FA), axial/radial diffusivities (AxD/RD), and mode of anisotropy (MA). Standard DTI is susceptible to the effects of extracellular free water (FW), which can be removed using an advanced free-water DTI (FW-DTI) model. The purpose of this study was to compare standard and FW-DTI metrics in the context of Alzheimer’s disease (AD). Data were obtained from the Open Access Series of Imaging Studies (OASIS-3) database and included both healthy controls (HC) and mild-to-moderate AD. With both standard and FW-DTI, decreased FA was found in AD, mainly in the corpus callosum and fornix, consistent with neurodegenerative mechanisms. Widespread higher AxD and RD were observed with standard DTI; however, the FW index, indicative of AD-associated neurodegeneration, was significantly elevated in these regions in AD, highlighting the potential impact of free water contributions on standard DTI in neurodegenerative pathologies. Using FW-DTI, improved consistency was observed in FA, AxD, and RD, and the complementary FW index was higher in the AD group as expected. With both standard and FW-DTI, higher values of MA coupled with higher values of FA in AD were found in the anterior thalamic radiation and cortico-spinal tract, most likely arising from a loss of crossing fibers. In conclusion, FW-DTI better reflects the underlying pathology of AD and improves the accuracy of DTI metrics related to WM integrity in Alzheimer’s disease.
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Affiliation(s)
- Maurizio Bergamino
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, 85013, USA
| | - Ryan R Walsh
- Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, AZ, 85013, USA
| | - Ashley M Stokes
- Division of Neuroimaging Research, Barrow Neurological Institute, Phoenix, AZ, 85013, USA.
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16
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Becerra-Laparra I, Cortez-Conradis D, Garcia-Lazaro HG, Martinez-Lopez M, Roldan-Valadez E. Radial diffusivity is the best global biomarker able to discriminate healthy elders, mild cognitive impairment, and Alzheimer's disease: A diagnostic study of DTI-derived data. Neurol India 2021; 68:427-434. [PMID: 32415019 DOI: 10.4103/0028-3886.284376] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/05/2023]
Abstract
Introduction For the past two decades, diffusion tensor imaging (DTI)-derived metrics allowed the characterization of Alzheimer's disease (AzD). Previous studies reported only a few parameters (most commonly fractional anisotropy, mean diffusivity, and axial and radial diffusivities measured at selected regions). We aimed to assess the diagnostic performance of 11 DTI-derived tensor metrics by using a global approach. Materials and Methods A prospective study performed in 34 subjects: 12 healthy elders, 11 mild cognitive impairment (MCI) patients, and 11 patients with AzD. Postprocessing of DTI magnetic resonance imaging allowed the calculation of 11 tensor metrics. Anisotropies included fractional (FA), and relative (RA). Diffusivities considered simple isotropic diffusion (p), simple anisotropic diffusion (q), mean diffusivity (MD), radial diffusivity (RD), and axial diffusivity (AD). Tensors included the diffusion tensor total magnitude (L); and the linear (Cl), planar (Cp), and spherical tensors (Cs). We performed a multivariate discriminant analysis and diagnostic tests assessment. Results RD was the only variable selected to assemble a predictive model: Wilks' λ = 0.581, χ2 (2) = 14.673, P = 0.001. The model's overall accuracy was 64.5%, with areas under the curve of 0.81, 0.73 and 0.66 to diagnose AzD, MCI, and healthy brains, respectively. Conclusions Global DTI-derived RD alone can discriminate between healthy elders, MCI, and AzD patients. Although this study proves evidence of a potential biomarker, it does not provide clinical guidance yet. Additional studies comparing DTI metrics might determine their usefulness to monitor disease progression, measure outcome in drug trials, and even perform the screening of pre-AzD subjects.
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Affiliation(s)
- Ivonne Becerra-Laparra
- Deputy Director of Academic Affairs and Education and Geriatrics Unit, Medica Sur Clinic and Foundation, Mexico City, Mexico
| | | | | | | | - Ernesto Roldan-Valadez
- Hospital General de Mexico "Dr. Eduardo Liceaga", Mexico City, Mexico; I.M. Sechenov First Moscow State Medical University (Sechenov University), Department of Radiology, Moscow, Russia
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17
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Lama RK, Kwon GR. Diagnosis of Alzheimer's Disease Using Brain Network. Front Neurosci 2021; 15:605115. [PMID: 33613178 PMCID: PMC7894198 DOI: 10.3389/fnins.2021.605115] [Citation(s) in RCA: 7] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2020] [Accepted: 01/06/2021] [Indexed: 12/23/2022] Open
Abstract
Recent studies suggest the brain functional connectivity impairment is the early event occurred in case of Alzheimer’s disease (AD) as well as mild cognitive impairment (MCI). We model the brain as a graph based network to study these impairment. In this paper, we present a new diagnosis approach using graph theory based features from functional magnetic resonance (fMR) images to discriminate AD, MCI, and healthy control (HC) subjects using different classification techniques. These techniques include linear support vector machine (LSVM), and regularized extreme learning machine (RELM). We used pairwise Pearson’s correlation-based functional connectivity to construct the brain network. We compare the classification performance of brain network using Alzheimer’s disease neuroimaging initiative (ADNI) datasets. Node2vec graph embedding approach is employed to convert graph features to feature vectors. Experimental results show that the SVM with LASSO feature selection method generates better classification accuracy compared to other classification technique.
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Affiliation(s)
- Ramesh Kumar Lama
- The Alzheimer's Disease Neuroimaging Initiative, Department of Information and Communication Engineering, Chosun University, Gwangju, South Korea
| | - Goo-Rak Kwon
- The Alzheimer's Disease Neuroimaging Initiative, Department of Information and Communication Engineering, Chosun University, Gwangju, South Korea
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18
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Berkes M, Calvo N, Anderson JAE, Bialystok E. Poorer clinical outcomes for older adult monolinguals when matched to bilinguals on brain health. Brain Struct Funct 2021; 226:415-424. [PMID: 33432426 DOI: 10.1007/s00429-020-02185-5] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/28/2020] [Accepted: 11/24/2020] [Indexed: 12/17/2022]
Abstract
Previous studies have reported bilingualism to be a proxy of cognitive reserve (CR) based on evidence that bilinguals express dementia symptoms ~ 4 years later than monolinguals yet present with greater neuropathology at time of diagnosis when clinical levels are similar. The current study provides new evidence supporting bilingualism's contribution to CR using a novel brain health matching paradigm. Forty cognitively normal bilinguals with diffusion-weighted magnetic resonance images recruited from the community were matched with monolinguals drawn from a pool of 165 individuals in the Alzheimer's Disease Neuroimaging Initiative (ADNI) database. White matter integrity was determined for all participants using fractional anisotropy, axial diffusivity, and radial diffusivity scores. Propensity scores were obtained using white matter measures, sex, age, and education as predictive covariates, and then used in one-to-one matching between language groups, creating a matched sample of 32 participants per group. Matched monolinguals had poorer clinical diagnoses than that predicted by chance from a theoretical null distribution, and poorer cognitive performances than matched bilinguals as measured by scores on the MMSE. The findings provide support for the interpretation that bilingualism acts as a proxy of CR such that monolinguals have poorer clinical and cognitive outcomes than bilinguals for similar levels of white matter integrity even before clinical symptoms appear.
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Affiliation(s)
- Matthias Berkes
- Department of Psychology, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada
| | - Noelia Calvo
- Department of Psychology, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada
| | | | - Ellen Bialystok
- Department of Psychology, York University, 4700 Keele Street, Toronto, ON, M3J 1P3, Canada.
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19
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Spotorno N, Lindberg O, Nilsson C, Landqvist Waldö M, van Westen D, Nilsson K, Vestberg S, Englund E, Zetterberg H, Blennow K, Lätt J, Markus N, Lars-Olof W, Alexander S. Plasma neurofilament light protein correlates with diffusion tensor imaging metrics in frontotemporal dementia. PLoS One 2020; 15:e0236384. [PMID: 33108404 PMCID: PMC7591030 DOI: 10.1371/journal.pone.0236384] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Accepted: 10/12/2020] [Indexed: 12/02/2022] Open
Abstract
Neurofilaments are structural components of neurons and are particularly abundant in highly myelinated axons. The levels of neurofilament light chain (NfL) in both cerebrospinal fluid (CSF) and plasma have been related to degeneration in several neurodegenerative conditions including frontotemporal dementia (FTD) and NfL is currently considered as the most promising diagnostic and prognostic fluid biomarker in FTD. Although the location and function of filaments in the healthy nervous system suggests a link between increased NfL and white matter degeneration, such a claim has not been fully elucidated in vivo, especially in the context of FTD. The present study provides evidence of an association between the plasma levels of NfL and white matter involvement in behavioral variant FTD (bvFTD) by relating plasma concentration of NfL to diffusion tensor imaging (DTI) metrics in a group of 20 bvFTD patients. The results of both voxel-wise and tract specific analysis showed that increased plasma NfL concentration is associated with a reduction in fractional anisotropy (FA) in a widespread set of white matter tracts including the superior longitudinal fasciculus, the fronto-occipital fasciculus the anterior thalamic radiation and the dorsal cingulum bundle. Plasma NfL concentration also correlated with cortical thinning in a portion of the right medial prefrontal cortex and of the right lateral orbitofrontal cortex. These results support the hypothesis that blood NfL levels reflect the global level of neurodegeneration in bvFTD and help to advance our understanding of the association between this blood biomarker for FTD and the disease process.
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Affiliation(s)
- Nicola Spotorno
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States of America
- Department of Clinical Sciences, Clinical Memory Research Unit, Lund University, Malmö, Sweden
| | - Olof Lindberg
- Division of Clinical Geriatrics, Karolinska Institute, Stockholm, Sweden
| | - Christer Nilsson
- Division of Neurology, Department of Clinical Sciences, Lund University, Lund, Sweden
| | - Maria Landqvist Waldö
- Department of clinical Sciences, Clinical Sciences Helsingborg, Lund, Lund University, Lund, Sweden
| | - Danielle van Westen
- Department of Diagnostic Radiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Karin Nilsson
- Department of Clinical Sciences, Clinical Memory Research Unit, Lund University, Malmö, Sweden
| | | | - Elisabet Englund
- Division of Pathology, Department of Clinical Sciences, Lund, Sweden
| | - Henrik Zetterberg
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
- Department of Neurodegenerative Disease, UCL Institute of Neurology, Queen Square, London, United Kingdom
- UK Dementia Research Institute at UCL, London, United Kingdom
| | - Kaj Blennow
- Department of Psychiatry and Neurochemistry, Institute of Neuroscience & Physiology, the Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden
- Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden
| | - Jimmy Lätt
- Center for Medical Imaging and Physiology, Skåne University Hospital, Lund, Sweden
| | - Nilsson Markus
- Department of Diagnostic Radiology, Clinical Sciences, Lund University, Lund, Sweden
| | - Wahlund Lars-Olof
- Division of Clinical Geriatrics, Karolinska Institute, Stockholm, Sweden
| | - Santillo Alexander
- Department of Clinical Sciences, Clinical Memory Research Unit, Lund University, Malmö, Sweden
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20
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Chen H, Sheng X, Qin R, Luo C, Li M, Liu R, Zhang B, Xu Y, Zhao H, Bai F. Aberrant White Matter Microstructure as a Potential Diagnostic Marker in Alzheimer's Disease by Automated Fiber Quantification. Front Neurosci 2020; 14:570123. [PMID: 33071742 PMCID: PMC7541946 DOI: 10.3389/fnins.2020.570123] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2020] [Accepted: 08/19/2020] [Indexed: 12/22/2022] Open
Abstract
Neuroimaging evidence has suggested white matter microstructure are heavily affected in Alzheimer's disease (AD). However, whether white matter dysfunction is localized at the specific regions of fiber tracts and whether they would be a potential biomarker for AD remain unclear. By automated fiber quantification (AFQ), we applied diffusion tensor images from 25 healthy controls (HC), 24 amnestic mild cognitive impairment (aMCI) patients and 18 AD patients to create tract profiles along 16 major white matter fibers. We compared diffusion metrics [Fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (DA), and radial diffusivity (DR)] between groups. To assess the diagnostic value, we applied a random forest (RF) classifier, a type of machine learning method. In the global tract level, we found that aMCI and AD patients showed higher MD, DA, and DR values in some fiber tracts mostly in the left hemisphere compared to HC. In the point-wise level, widespread disruption were distributed on specific locations of different tracts. The point-wise MD measurements presented the best classification performance with respect to differentiating AD from HC. The two most important variables were localized in the prefrontal potion of left uncinate fasciculus and anterior thalamic radiation. In addition, the point-wise DA in the posterior component of the left cingulum cingulate displayed the most robust discriminative ability to identify AD from aMCI. Our findings provide evidence that white matter abnormalities based on the AFQ method could be as a diagnostic biomarker in AD.
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Affiliation(s)
- Haifeng Chen
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Xiaoning Sheng
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Ruomeng Qin
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Caimei Luo
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Mengchun Li
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Renyuan Liu
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Bing Zhang
- Department of Radiology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China
| | - Yun Xu
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Hui Zhao
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
| | - Feng Bai
- Department of Neurology, Drum Tower Hospital, Medical School of Nanjing University, Nanjing, China.,The State Key Laboratory of Pharmaceutical Biotechnology, Institute of Brain Science, Nanjing University, Nanjing, China.,Jiangsu Province Stroke Center for Diagnosis and Therapy, Nanjing, China.,Nanjing Neuropsychiatry Clinic Medical Center, Nanjing, China
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21
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Yang FPG, Bal SS, Lee JF, Chen CC. White Matter Differences in Networks in Elders with Mild Cognitive Impairment and Alzheimer's Disease. Brain Connect 2020; 11:180-188. [PMID: 32731749 DOI: 10.1089/brain.2020.0767] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022] Open
Abstract
Background: Alzheimer's disease (AD) is associated with impairment of large-scale brain networks, disruption in structural connections, and functional disconnection between distant brain regions. Although decreased functional connectivity has been thoroughly investigated and reported by existing functional neuroimaging literature, this study investigated network-based differences due to the structural changes in white matter pathways in AD patients. We hypothesize that diffusion metrics of disrupted tracts that go through cognitive networks related with intrinsic awareness, motor movement, and executive control can be utilized as biomarkers to distinguish prodromal stage from AD stage. Methods: Diffusion MRI data of a total 154 subjects, including patients with clinical AD (n = 47) and patients with mild cognitive impairment (MCI) (n = 107) was used. To study structural changes associated with white matter fiber pathways voxel-averaged diffusion metrics and fiber density metrics were calculated. Results: Study revealed that AD patients exhibit disruptions in intrahemispheric tracts and projection fiber tracts as suggested by diffusion indices. Our whole brain analysis revealed that network differences within default mode network (DMN), sensory motor network, and frontoparietal networks are associated with disruption in inferior fronto-occipital fasciculus (IFOF), corticospinal tract, and superior longitudinal fasciculus. Global function revealed by Mini Mental State Examination correlate with those fiber pathways that form reciprocal connections within networks associated with motor movement and executive control. Conclusion: Diffusion metrics appear to be more sensitive than fiber density metrics in differentiating the structural changes in the white matter. Decreased fractional anisotropy along with increased mean diffusivity and radial diffusivity in forceps minor, corticospinal tract, and IFOF as an imaging biomarker would be ideal to distinguish AD patients from MCI patients. Difference of DMN, sensory motor network, and frontal parietal network in our study reveals that AD patients may suffer from poor motor movement and degraded executive control.
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Affiliation(s)
- Fan Pei Gloria Yang
- Center for Cognition and Mind Sciences, National Tsing Hua University, Hsinchu, Taiwan
| | - Sukhdeep Singh Bal
- Department of Mathematical Sciences Liverpool, University of Liverpool, Merseyside, United Kingdom.,International Intercollegiate PhD Programme, National Tsing Hua University, Hsinchu, Taiwan
| | - Jia-Fu Lee
- Department of Psychiatry, Taipei Tzu Chi Hospital, Taipei, Taiwan
| | - Chia-Chi Chen
- Department of Early Childhood Care and Education, Kang Ning Junior College of Nursing, Taipei, Taiwan
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22
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Zhou Z, Tong Q, Zhang L, Ding Q, Lu H, Jonkman LE, Yao J, He H, Zhu K, Zhong J. Evaluation of the diffusion MRI white matter tract integrity model using myelin histology and Monte-Carlo simulations. Neuroimage 2020; 223:117313. [PMID: 32882384 DOI: 10.1016/j.neuroimage.2020.117313] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2019] [Revised: 08/21/2020] [Accepted: 08/24/2020] [Indexed: 12/13/2022] Open
Abstract
Quantitative evaluation of brain myelination has drawn considerable attention. Conventional diffusion-based magnetic resonance imaging models, including diffusion tensor imaging and diffusion kurtosis imaging (DKI),1 have been used to infer the microstructure and its changes in neurological diseases. White matter tract integrity (WMTI) was proposed as a biophysical model to relate the DKI-derived metrics to the underlying microstructure. Although the model has been validated on ex vivo animal brains, it was not well evaluated with ex vivo human brains. In this study, histological samples (namely corpus callosum) from postmortem human brains have been investigated based on WMTI analyses on a clinical 3T scanner and comparisons with gold standard myelin staining in proteolipid protein and Luxol fast blue. In addition, Monte Carlo simulations were conducted to link changes from ex vivo to in vivo conditions based on the microscale parameters of water diffusivity and permeability. The results show that WMTI metrics, including axonal water fraction AWF, radial extra-axonal diffusivity De⊥, and intra-axonal diffusivity Dawere needed to characterize myelin content alterations. Thus, WMTI model metrics are shown to be promising candidates as sensitive biomarkers of demyelination.
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Affiliation(s)
- Zihan Zhou
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
| | - Qiqi Tong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
| | - Lei Zhang
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China; Department of Pathology, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Qiuping Ding
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
| | - Hui Lu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China
| | - Laura E Jonkman
- Department of Anatomy and Neurosciences, Amsterdam Neuroscience, Amsterdam UMC, location VUmc, the Netherlands
| | - Junye Yao
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China
| | - Hongjian He
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China.
| | - Keqing Zhu
- China Brain Bank and Department of Neurology in Second Affiliated Hospital, Key Laboratory of Medical Neurobiology of Zhejiang Province, and Department of Neurobiology, Zhejiang University School of Medicine, Hangzhou 310058, China; Department of Pathology, Zhejiang University School of Medicine, Hangzhou 310058, China.
| | - Jianhui Zhong
- Center for Brain Imaging Science and Technology, Key Laboratory for Biomedical Engineering of Ministry of Education, College of Biomedical Engineering and Instrumental Science, Zhejiang University, Zhouyiqing Building, Room 314, Yuquan Campus, Hangzhou 310027, China; Department of Imaging Sciences, University of Rochester, United States
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23
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Alzaid H, Ethofer T, Hobert MA, Kardatzki B, Erb M, Maetzler W, Berg D. Distinct Relationship Between Cognitive Flexibility and White Matter Integrity in Individuals at Risk of Parkinson’s Disease. Front Aging Neurosci 2020; 12:250. [PMID: 32903902 PMCID: PMC7439016 DOI: 10.3389/fnagi.2020.00250] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2020] [Accepted: 07/20/2020] [Indexed: 11/13/2022] Open
Affiliation(s)
- Haidar Alzaid
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
- *Correspondence: Haidar Alzaid,
| | - Thomas Ethofer
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
- Department of Psychiatry and Psychotherapy, University of Tübingen, Tübingen, Germany
| | - Markus A. Hobert
- Department of Neurology, Christian-Albrecht University of Kiel, Kiel, Germany
| | - Bernd Kardatzki
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Michael Erb
- Department of Biomedical Magnetic Resonance, University of Tübingen, Tübingen, Germany
| | - Walter Maetzler
- Department of Neurology, Christian-Albrecht University of Kiel, Kiel, Germany
| | - Daniela Berg
- Department of Neurology, Christian-Albrecht University of Kiel, Kiel, Germany
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24
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Cremers LG, Wolters FJ, de Groot M, Ikram MK, van der Lugt A, Niessen WJ, Vernooij MW, Ikram MA. Structural disconnectivity and the risk of dementia in the general population. Neurology 2020; 95:e1528-e1537. [DOI: 10.1212/wnl.0000000000010231] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2019] [Accepted: 03/18/2020] [Indexed: 11/15/2022] Open
Abstract
ObjectiveThe disconnectivity hypothesis postulates that partial loss of connecting white matter fibers between brain regions contributes to the development of dementia. Using diffusion MRI to quantify global and tract-specific white matter microstructural integrity, we tested this hypothesis in a longitudinal population-based study.MethodsGlobal and tract-specific fractional anisotropy (FA) and mean diffusivity (MD) were obtained in 4,415 people without dementia (mean age 63.9 years, 55.0% women) from the prospective population-based Rotterdam Study with brain MRI between 2005 and 2011. We modeled the association of these diffusion measures with risk of dementia (follow-up until 2016) and with changes on repeated cognitive assessment after on average 5.4 years, adjusting for age, sex, education, macrostructural MRI markers, depressive symptoms, cardiovascular risk factors, and APOE genotype.ResultsDuring a median follow-up of 6.8 years, 101 participants had incident dementia, of whom 83 had clinical Alzheimer disease (AD). Lower global values of FA and higher values of MD were associated with an increased risk of dementia (adjusted hazard ratio [95% confidence interval (CI)] per SD increase for MD 1.79 [1.44–2.23] and FA 0.65 [0.52–0.80]). Similarly, lower global values of FA and higher values of MD related to more cognitive decline in people without dementia (difference in global cognition per SD increase in MD [95% CI] was −0.04 [−0.07 to −0.01]). Associations were most profound in the projection, association, and limbic system tracts.ConclusionsStructural disconnectivity is associated with an increased risk of dementia and more pronounced cognitive decline in the general population.
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25
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Caballero MÁA, Song Z, Rubinski A, Duering M, Dichgans M, Park DC, Ewers M. Age‐dependent amyloid deposition is associated with white matter alterations in cognitively normal adults during the adult life span. Alzheimers Dement 2020; 16:651-661. [DOI: 10.1002/alz.12062] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2018] [Revised: 12/10/2019] [Accepted: 01/03/2020] [Indexed: 01/01/2023]
Affiliation(s)
| | - Zhuang Song
- Center for Vital LongevityUniversity of Texas at Dallas Dallas Texas
| | - Anna Rubinski
- Institute for Stroke and Dementia ResearchUniversity HospitalLMU Munich Munich Germany
| | - Marco Duering
- Institute for Stroke and Dementia ResearchUniversity HospitalLMU Munich Munich Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia ResearchUniversity HospitalLMU Munich Munich Germany
- Munich Cluster for Systems Neurology (SyNergy) Munich Germany
| | - Denise C. Park
- Center for Vital LongevityUniversity of Texas at Dallas Dallas Texas
| | - Michael Ewers
- Institute for Stroke and Dementia ResearchUniversity HospitalLMU Munich Munich Germany
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26
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Marzban EN, Eldeib AM, Yassine IA, Kadah YM. Alzheimer's disease diagnosis from diffusion tensor images using convolutional neural networks. PLoS One 2020; 15:e0230409. [PMID: 32208428 PMCID: PMC7092978 DOI: 10.1371/journal.pone.0230409] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/25/2019] [Accepted: 03/01/2020] [Indexed: 12/21/2022] Open
Abstract
Machine learning algorithms are currently being implemented in an escalating manner to classify and/or predict the onset of some neurodegenerative diseases; including Alzheimer's Disease (AD); this could be attributed to the fact of the abundance of data and powerful computers. The objective of this work was to deliver a robust classification system for AD and Mild Cognitive Impairment (MCI) against healthy controls (HC) in a low-cost network in terms of shallow architecture and processing. In this study, the dataset included was downloaded from the Alzheimer's disease neuroimaging initiative (ADNI). The classification methodology implemented was the convolutional neural network (CNN), where the diffusion maps, and gray-matter (GM) volumes were the input images. The number of scans included was 185, 106, and 115 for HC, MCI and AD respectively. Ten-fold cross-validation scheme was adopted and the stacked mean diffusivity (MD) and GM volume produced an AUC of 0.94 and 0.84, an accuracy of 93.5% and 79.6%, a sensitivity of 92.5% and 62.7%, and a specificity of 93.9% and 89% for AD/HC and MCI/HC classification respectively. This work elucidates the impact of incorporating data from different imaging modalities; i.e. structural Magnetic Resonance Imaging (MRI) and Diffusion Tensor Imaging (DTI), where deep learning was employed for the aim of classification. To the best of our knowledge, this is the first study assessing the impact of having more than one scan per subject and propose the proper maneuver to confirm the robustness of the system. The results were competitive among the existing literature, which paves the way for improving medications that could slow down the progress of the AD or prevent it.
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Affiliation(s)
- Eman N. Marzban
- Biomedical Engineering and Systems, Faculty of Engineering, Cairo University, Giza, Egypt
| | - Ayman M. Eldeib
- Biomedical Engineering and Systems, Faculty of Engineering, Cairo University, Giza, Egypt
| | - Inas A. Yassine
- Biomedical Engineering and Systems, Faculty of Engineering, Cairo University, Giza, Egypt
| | - Yasser M. Kadah
- Biomedical Engineering and Systems, Faculty of Engineering, Cairo University, Giza, Egypt
- Biomedical Engineering Program, Electrical and Computer Engineering Department, King Abdulaziz University, Jeddah, Saudi Arabia
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27
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Horgusluoglu-Moloch E, Xiao G, Wang M, Wang Q, Zhou X, Nho K, Saykin AJ, Schadt E, Zhang B. Systems modeling of white matter microstructural abnormalities in Alzheimer's disease. Neuroimage Clin 2020; 26:102203. [PMID: 32062565 PMCID: PMC7025138 DOI: 10.1016/j.nicl.2020.102203] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/10/2019] [Revised: 01/06/2020] [Accepted: 02/03/2020] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Microstructural abnormalities in white matter (WM) are often reported in Alzheimer's disease (AD). However, it is unclear which brain regions have the strongest WM changes in presymptomatic AD and what biological processes underlie WM abnormality during disease progression. METHODS We developed a systems biology framework to integrate matched diffusion tensor imaging (DTI), genetic and transcriptomic data to investigate regional vulnerability to AD and identify genetic risk factors and gene subnetworks underlying WM abnormality in AD. RESULTS We quantified regional WM abnormality and identified most vulnerable brain regions. A SNP rs2203712 in CELF1 was most significantly associated with several DTI-derived features in the hippocampus, the top ranked brain region. An immune response gene subnetwork in the blood was most correlated with DTI features across all the brain regions. DISCUSSION Incorporation of image analysis with gene network analysis enhances our understanding of disease progression and facilitates identification of novel therapeutic strategies for AD.
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Affiliation(s)
- Emrin Horgusluoglu-Moloch
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Gaoyu Xiao
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Minghui Wang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Qian Wang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Xianxiao Zhou
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Kwangsik Nho
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Andrew J Saykin
- Center for Neuroimaging, Department of Radiology and Imaging Sciences, Indiana University School of Medicine, Indianapolis, IN, USA; Indiana Alzheimer Disease Center, Indiana University School of Medicine, Indianapolis, IN, USA
| | - Eric Schadt
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USA
| | - Bin Zhang
- Department of Genetics and Genomic Sciences, Icahn Institute of Genomics and Multiscale Biology, Icahn School of Medicine at Mount Sinai, NY, USA.
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28
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White Matter Network Alterations in Alzheimer’s Disease Patients. APPLIED SCIENCES-BASEL 2020. [DOI: 10.3390/app10030919] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/01/2023]
Abstract
Previous studies have revealed the occurrence of alterations of white matter (WM) and grey matter (GM) microstructures in Alzheimer’s disease (AD) and their prodromal state amnestic mild cognitive impairment (MCI). In general, these alterations can be studied comprehensively by modeling the brain as a complex network, which describes many important topological properties, such as the small-world property, modularity, and efficiency. In this study, we systematically investigated white matter abnormalities using unbiased whole brain network analysis. We compared regional and network related WM features between groups of 19 AD and 25 MCI patients and 22 healthy controls (HC) using tract-based spatial statistics (TBSS), network based statistics (NBS) and graph theoretical analysis. We did not find significant differences in fractional anisotropy (FA) between two groups on TBSS analysis. However, observable alterations were noticed at a network level. Brain network measures such as global efficiency and small world properties were low in AD patients compared to HCs.
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29
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Beard CL, Schmitz JM, Soder HE, Suchting R, Yoon JH, Hasan KM, Narayana PA, Moeller FG, Lane SD. Regional differences in white matter integrity in stimulant use disorders: A meta-analysis of diffusion tensor imaging studies. Drug Alcohol Depend 2019; 201:29-37. [PMID: 31176066 PMCID: PMC6660908 DOI: 10.1016/j.drugalcdep.2019.03.023] [Citation(s) in RCA: 21] [Impact Index Per Article: 4.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 02/14/2019] [Revised: 03/20/2019] [Accepted: 03/25/2019] [Indexed: 12/14/2022]
Abstract
BACKGROUND Converging lines of evidence from diffusion tensor imaging (DTI) studies reveal significant alterations in white matter (WM) microstructure in the prefrontal cortex of chronic stimulant users compared to controls, suggesting compromised axonal microstructure and/or myelin. METHODS A meta-analysis of DTI-based WM integrity was conducted for white matter regions across the corpus callosum and association fibers. Articles were sourced and selected using PRISMA guidelines for systematic review and meta-analysis. Inclusion and exclusion criteria were determined by the authors in order to best capture WM integrity among individuals with primary stimulant use in comparison to healthy control subjects. RESULTS Eleven studies that focused on region-of-interest (ROI)-based analysis of WM integrity were extracted from an initial pool of 113 independent studies. Analysis across ROIs indicated significantly lower fractional anisotropy (FA) values in stimulant use groups compared to controls with a small to moderate overall effect (Hedges' g = -0.37, 95% CI [-0.54, -0.20]). Eigenvalues were also analyzed, revealing a significant effect for radial diffusivity (RD; Hedges' g = 0.24, 95% CI [0.01, 0.47]) but not axial diffusivity (AD; Hedges' g = 0.05, 95% CI [-0.20, 0.29]) or mean diffusivity (MD; Hedges' g = 0.20, 95% CI [-0.01, 0.41]). Subgroup analyses based on specific ROIs, primary substance use, poly-substance use, and imaging technology were also explored. CONCLUSION Results of the present study suggest a consistent effect of compromised WM integrity for individuals with stimulant use disorders. Furthermore, no significant differences were found between cocaine and methamphetamine-based groups.
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Affiliation(s)
- Charlotte L Beard
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, 1941 East Rd., Houston, TX, 77054, USA; Department of Psychology, Palo Alto University, Palo Alto, CA, 94304, USA
| | - Joy M Schmitz
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, 1941 East Rd., Houston, TX, 77054, USA.
| | - Heather E Soder
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, 1941 East Rd., Houston, TX, 77054, USA
| | - Robert Suchting
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, 1941 East Rd., Houston, TX, 77054, USA
| | - Jin H Yoon
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, 1941 East Rd., Houston, TX, 77054, USA
| | - Khader M Hasan
- Department of Diagnostic and Interventional Imaging, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77054, USA
| | - Ponnada A Narayana
- Department of Diagnostic and Interventional Imaging, McGovern Medical School, University of Texas Health Science Center at Houston, Houston, TX, 77054, USA
| | | | - Scott D Lane
- Department of Psychiatry and Behavioral Sciences, McGovern Medical School, University of Texas Health Science Center at Houston, 1941 East Rd., Houston, TX, 77054, USA
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30
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Fu Z, Iraji A, Caprihan A, Adair JC, Sui J, Rosenberg GA, Calhoun VD. In search of multimodal brain alterations in Alzheimer's and Binswanger's disease. NEUROIMAGE-CLINICAL 2019; 26:101937. [PMID: 31351845 PMCID: PMC7229329 DOI: 10.1016/j.nicl.2019.101937] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 01/28/2019] [Revised: 05/16/2019] [Accepted: 07/14/2019] [Indexed: 11/07/2022]
Abstract
Structural and functional brain abnormalities have been widely identified in dementia, but with variable replicability and significant overlap. Alzheimer's disease (AD) and Binswanger's disease (BD) share similar symptoms and common brain changes that can confound diagnosis. In this study, we aimed to investigate correlated structural and functional brain changes in AD and BD by combining resting-state functional magnetic resonance imaging (fMRI) and diffusion MRI. A group independent component analysis was first performed on the fMRI data to extract 49 intrinsic connectivity networks (ICNs). Then we conducted a multi-set canonical correlation analysis on three features, functional network connectivity (FNC) between ICNs, fractional anisotropy (FA) and mean diffusivity (MD). Two inter-correlated components show significant group differences. The first component demonstrates distinct brain changes between AD and BD. AD shows increased cerebellar FNC but decreased thalamic and hippocampal FNC. Such FNC alterations are linked to the decreased corpus callosum FA. AD also has increased MD in the frontal and temporal cortex, but BD shows opposite alterations. The second component demonstrates specific brain changes in BD. Increased FNC is mainly between default mode and sensory regions, while decreased FNC is mainly within the default mode domain and related to auditory regions. The FNC changes are associated with FA changes in posterior/middle cingulum cortex and visual cortex and increased MD in thalamus and hippocampus. Our findings provide evidence of linked functional and structural deficits in dementia and suggest that AD and BD have both common and distinct changes in white matter integrity and functional connectivity. This is the first study to explore multi-modalities changes in different dementia. A multimodal fusion method is applied to identify joint components. Brain abnormalities in different modalities are highly correlated. Alzheimer's and Binswanger's disease share similar brain changes. Alzheimer's and Binswanger's disease also have distinct brain changes.
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Affiliation(s)
- Zening Fu
- The Mind Research Network, Albuquerque, NM, United States.
| | - Armin Iraji
- The Mind Research Network, Albuquerque, NM, United States
| | | | - John C Adair
- Department of Neurology, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
| | - Jing Sui
- The Mind Research Network, Albuquerque, NM, United States; Chinese Academy of Sciences (CAS) Centre for Excellence in Brain Science and Intelligence Technology, University of Chinese Academy of Sciences, China
| | - Gary A Rosenberg
- Department of Neurology, University of New Mexico Health Sciences Center, Albuquerque, NM, United States
| | - Vince D Calhoun
- The Mind Research Network, Albuquerque, NM, United States; Department of Electrical and Computer Engineering, University of New Mexico, Albuquerque, NM, United States
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31
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Araque Caballero MÁ, Suárez-Calvet M, Duering M, Franzmeier N, Benzinger T, Fagan AM, Bateman RJ, Jack CR, Levin J, Dichgans M, Jucker M, Karch C, Masters CL, Morris JC, Weiner M, Rossor M, Fox NC, Lee JH, Salloway S, Danek A, Goate A, Yakushev I, Hassenstab J, Schofield PR, Haass C, Ewers M. White matter diffusion alterations precede symptom onset in autosomal dominant Alzheimer's disease. Brain 2019; 141:3065-3080. [PMID: 30239611 PMCID: PMC6158739 DOI: 10.1093/brain/awy229] [Citation(s) in RCA: 102] [Impact Index Per Article: 20.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/23/2018] [Accepted: 07/20/2018] [Indexed: 12/30/2022] Open
Abstract
White matter alterations are present in the majority of patients with Alzheimer's disease type dementia. However, the spatiotemporal pattern of white matter changes preceding dementia symptoms in Alzheimer's disease remains unclear, largely due to the inherent diagnostic uncertainty in the preclinical phase and increased risk of confounding age-related vascular disease and stroke in late-onset Alzheimer's disease. In early-onset autosomal-dominantly inherited Alzheimer's disease, participants are destined to develop dementia, which provides the opportunity to assess brain changes years before the onset of symptoms, and in the absence of ageing-related vascular disease. Here, we assessed mean diffusivity alterations in the white matter in 64 mutation carriers compared to 45 non-carrier family non-carriers. Using tract-based spatial statistics, we mapped the interaction of mutation status by estimated years from symptom onset on mean diffusivity. For major atlas-derived fibre tracts, we determined the earliest time point at which abnormal mean diffusivity changes in the mutation carriers were detectable. Lastly, we assessed the association between mean diffusivity and cerebrospinal fluid biomarkers of amyloid, tau, phosphorylated-tau, and soluble TREM2, i.e. a marker of microglia activity. Results showed a significant interaction of mutations status by estimated years from symptom onset, i.e. a stronger increase of mean diffusivity, within the posterior parietal and medial frontal white matter in mutation carriers compared with non-carriers. The earliest increase of mean diffusivity was observed in the forceps major, forceps minor and long projecting fibres-many connecting default mode network regions-between 5 to 10 years before estimated symptom onset. Higher mean diffusivity in fibre tracts was associated with lower grey matter volume in the tracts' projection zones. Global mean diffusivity was correlated with lower cerebrospinal fluid levels of amyloid-β1-42 but higher levels of tau, phosphorylated-tau and soluble TREM2. Together, these results suggest that regionally selective white matter degeneration occurs years before the estimated symptom onset. Such white matter alterations are associated with primary Alzheimer's disease pathology and microglia activity in the brain.
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Affiliation(s)
- Miguel Ángel Araque Caballero
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Marc Suárez-Calvet
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany.,Biomedical Center, Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Marco Duering
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Nicolai Franzmeier
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
| | - Tammie Benzinger
- Department of Radiology, Washington University in St Louis, St Louis, MO, USA.,Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Anne M Fagan
- Department of Radiology, Washington University in St Louis, St Louis, MO, USA.,Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | - Randall J Bateman
- Department of Radiology, Washington University in St Louis, St Louis, MO, USA.,Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA
| | | | - Johannes Levin
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany.,Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Martin Dichgans
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Mathias Jucker
- Hertie Institute for Clinical Brain Research, Tübingen, Germany and German Center for Neurodegenerative Diseases (DZNE), Tübingen, Germany
| | - Celeste Karch
- Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA.,Hope Center for Neurological Disorders, Washington University in St. Louis, St. Louis, MO, USA.,Department of Psychiatry, Washington University in St Louis, St Louis, MO, USA
| | - Colin L Masters
- The Florey Institute, The University of Melbourne, Parkville, Victoria, Australia
| | - John C Morris
- Department of Radiology, Washington University in St Louis, St Louis, MO, USA.,Knight Alzheimer's Disease Research Center, Washington University in St. Louis, St. Louis, MO, USA
| | - Michael Weiner
- University of California at San Francisco, San Francisco, CA94143, USA
| | - Martin Rossor
- Dementia Research Centre, University College London, Queen Square, London, UK
| | - Nick C Fox
- Dementia Research Centre, University College London, Queen Square, London, UK
| | - Jae-Hong Lee
- Department of Neurology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Korea
| | - Stephen Salloway
- Department of Neurology, Warren Alpert Medical School of Brown University, Providence, Rhode Island, USA
| | - Adrian Danek
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany.,Department of Neurology, Ludwig-Maximilians-Universität München, Munich, Germany
| | - Alison Goate
- Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York, USA.,Ronald M. Loeb Center for Alzheimer's Disease, Department of Neuroscience, Icahn School of Medicine at Mount Sinai, New York, New York, USA
| | - Igor Yakushev
- Department of Nuclear Medicine, Technical University of Munich, Munich, Germany
| | - Jason Hassenstab
- Department of Neurology, Washington University in St. Louis, St. Louis, MO, USA
| | - Peter R Schofield
- Neuroscience Research Australia, Barker Street Randwick, Sydney, Australia.,School of Medical Sciences, University of New South Wales, Sydney, Australia
| | - Christian Haass
- German Center for Neurodegenerative Diseases (DZNE, Munich), Munich, Germany.,Biomedical Center, Biochemistry, Ludwig-Maximilians-Universität München, Munich, Germany.,Munich Cluster for Systems Neurology (SyNergy), Munich, Germany
| | - Michael Ewers
- Institute for Stroke and Dementia Research, Klinikum der Universität München, Ludwig-Maximilians-Universität LMU, Munich, Germany
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Mishra VR, Sreenivasan KR, Zhuang X, Yang Z, Cordes D, Walsh RR. Influence of analytic techniques on comparing DTI-derived measurements in early stage Parkinson's disease. Heliyon 2019; 5:e01481. [PMID: 31008407 PMCID: PMC6458486 DOI: 10.1016/j.heliyon.2019.e01481] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2018] [Revised: 03/08/2019] [Accepted: 04/02/2019] [Indexed: 11/16/2022] Open
Abstract
Diffusion tensor imaging (DTI) studies in early Parkinson's disease (PD) to understand pathologic changes in white matter (WM) organization are variable in their findings. Evaluation of different analytic techniques frequently employed to understand the DTI-derived change in WM organization in a multisite, well-characterized, early stage PD cohort should aid the identification of the most robust analytic techniques to be used to investigate WM pathology in this disease, an important unmet need in the field. Thus, region of interest (ROI)-based analysis, voxel-based morphometry (VBM) analysis with varying spatial smoothing, and the two most widely used skeletonwise approaches (tract-based spatial statistics, TBSS, and tensor-based registration, DTI-TK) were evaluated in a DTI dataset of early PD and Healthy Controls (HC) from the Parkinson's Progression Markers Initiative (PPMI) cohort. Statistical tests on the DTI-derived metrics were conducted using a nonparametric approach from this cohort of early PD, after rigorously controlling for motion and signal artifacts during DTI scan which are frequent confounds in this disease population. Both TBSS and DTI-TK revealed a significantly negative correlation of fractional anisotropy (FA) with disease duration. However, only DTI-TK revealed radial diffusivity (RD) to be driving this FA correlation with disease duration. HC had a significantly positive correlation of MD with cumulative DaT score in the right middle-frontal cortex after a minimum smoothing level (at least 13mm) was attained. The present study found that scalar DTI-derived measures such as FA, MD, and RD should be used as imaging biomarkers with caution in early PD as the conclusions derived from them are heavily dependent on the choice of the analysis used. This study further demonstrated DTI-TK may be used to understand changes in DTI-derived measures with disease progression as it was found to be more accurate than TBSS. In addition, no singular region was identified that could explain both disease duration and severity in early PD. The results of this study should help standardize the utilization of DTI-derived measures in PD in an effort to improve comparability across studies and time, and to minimize variability in reported results due to variation in techniques.
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Affiliation(s)
- Virendra R. Mishra
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Karthik R. Sreenivasan
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Xiaowei Zhuang
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Zhengshi Yang
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
| | - Dietmar Cordes
- Lou Ruvo Center for Brain Health, Cleveland Clinic Foundation, Las Vegas, Nevada, United States
- Departments of Psychology and Neuroscience, University of Colorado at Boulder, Boulder, Colorado, United States
| | - Ryan R. Walsh
- Muhammad Ali Parkinson Center, Barrow Neurological Institute, Phoenix, Arizona, United States
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33
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Green C, Sydow A, Vogel S, Anglada-Huguet M, Wiedermann D, Mandelkow E, Mandelkow EM, Hoehn M. Functional networks are impaired by elevated tau-protein but reversible in a regulatable Alzheimer's disease mouse model. Mol Neurodegener 2019; 14:13. [PMID: 30917861 PMCID: PMC6438042 DOI: 10.1186/s13024-019-0316-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2018] [Accepted: 03/15/2019] [Indexed: 12/31/2022] Open
Abstract
Background Aggregation of tau proteins is a distinct hallmark of tauopathies and has been a focus of research and clinical trials for Alzheimer’s Disease. Recent reports have pointed towards a toxic effect of soluble or oligomeric tau in the spreading of tau pathology in Alzheimer’s disease. Here we investigated the effects of expressing human tau repeat domain (tauRD) with pro- or anti-aggregant mutations in regulatable transgenic mouse models of Alzheimer’s Disease on the functional neuronal networks and the structural connectivity strength. Methods Pro-aggregant and anti-aggregant mice were studied when their mutant tauRD was switched on for 12 months to reach the stage where pro-aggregant mice show cognitive impairment, whereas anti-aggregant mice remained cognitively normal. Then, mutant tauRD was switched off by doxycycline treatment for 8 weeks so that soluble transgenic tau disappeared and cognition recovered in the pro-aggregant mice, although some aggregates remained. At these two time points, at baseline after 12 months of mutant tau expression and after 8 weeks of doxycycline treatment, resting state fMRI and diffusion MRI were used to determine functional neuronal networks and fiber connectivities. Results of the transgenic mice were compared with wildtype littermates. Results Functional connectivity was strongly reduced in transgenic animals during mutant tauRD expression, in relation to WT mice. Interestingly, transgenic mice with the non-aggregant tau mutant showed identical functional deficits as the pro-aggregant mice, even though in this case there was no cognitive decline by behavioral testing. Upon 8 weeks doxycycline treatment and transgene switch-off, functional connectivity in both transgenic groups presented complete normalization of functional connectivity strength, equivalent to the situation in WT littermates. Structural connectivity was found only marginally sensitive to mutant tau expression (both pro- and anti-aggregant tauRD) and by doxycycline treatment. Conclusions Our in vivo investigations unravel for the first time a strong reduction of functional neuronal networks by the presence of increased soluble rather than fibrillary tau, independent of its intrinsic propensity of aggregation, which is reversible by switching tau off. Our functional MRI study thus is an unexpected in vivo validation of a novel property of tau, while previous results pointed to a role of aggregation propensity for a pathological state by histopathology and cognitive decline. Our results present further evidence for early tauopathy biomarkers or a potential early stage drug target by functional networks analysis. Electronic supplementary material The online version of this article (10.1186/s13024-019-0316-6) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Claudia Green
- In-vivo-NMR Laboratory, Max Planck Institute for Metabolism Research, Gleuelerstrasse 50, D-50931, Cologne, Germany
| | - Astrid Sydow
- Max-Planck-Institute for Metabolism Research, Hamburg Outstation, c/o DESY, Notkestrasse 85, 22607, Hamburg, Germany
| | - Stefanie Vogel
- In-vivo-NMR Laboratory, Max Planck Institute for Metabolism Research, Gleuelerstrasse 50, D-50931, Cologne, Germany
| | - Marta Anglada-Huguet
- Max-Planck-Institute for Metabolism Research, Hamburg Outstation, c/o DESY, Notkestrasse 85, 22607, Hamburg, Germany
| | - Dirk Wiedermann
- In-vivo-NMR Laboratory, Max Planck Institute for Metabolism Research, Gleuelerstrasse 50, D-50931, Cologne, Germany
| | - Eckhard Mandelkow
- German Center for Neurodegenerative Diseases (DZNE), Ludwig-Erhard-Allee 2, 53175, Bonn, Germany.,CAESAR Research Center, Ludwig-Erhard-Allee 2, 53175, Bonn, Germany
| | - Eva-Maria Mandelkow
- German Center for Neurodegenerative Diseases (DZNE), Ludwig-Erhard-Allee 2, 53175, Bonn, Germany.,CAESAR Research Center, Ludwig-Erhard-Allee 2, 53175, Bonn, Germany
| | - Mathias Hoehn
- In-vivo-NMR Laboratory, Max Planck Institute for Metabolism Research, Gleuelerstrasse 50, D-50931, Cologne, Germany. .,Department of Radiology, Leiden University Medical Center, Leiden, The Netherlands. .,Percuros B.V., Enschede, The Netherlands.
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Hwang SJ, Adluru N, Kim WH, Johnson SC, Bendlin BB, Singh V. Associations Between Positron Emission Tomography Amyloid Pathology and Diffusion Tensor Imaging Brain Connectivity in Pre-Clinical Alzheimer's Disease. Brain Connect 2019; 9:162-173. [PMID: 30255713 DOI: 10.1089/brain.2018.0590] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023] Open
Abstract
Characterizing Alzheimer's disease (AD) at pre-clinical stages is crucial for initiating early treatment strategies. It is widely accepted that amyloid accumulation is a primary pathological event in AD. Also, loss of connectivity between brain regions is suspected of contributing to cognitive decline, but studies that test these associations using either local (i.e., individual edges) or global (i.e., modularity) connectivity measures may be limited. In this study, we utilized data acquired from 139 cognitively unimpaired participants. Sixteen gray matter (GM) regions known to be affected by AD were selected for analysis. For each of the 16 regions, the effect of amyloid burden, measured using Pittsburgh Compound B (PiB) positron emission tomography, on each of the 1761 brain network connections derived from diffusion tensor imaging (DTI) connecting 162 GM regions, was investigated. Applying our unique multiresolution statistical analysis called the Wavelet Connectivity Signature (WaCS), this study demonstrates the relationship between amyloid burden and structural brain connectivity as assessed with DTI. Our statistical analysis using WaCS shows that in 15 of 16 GM regions, statistically significant relationships between amyloid burden in those regions and structural connectivity networks were observed. After applying multiple testing correction, 10 unique structural brain connections were found to be significantly associated with amyloid accumulation. For 7 of those 10 network connections, the decrease in their network connection strength indexed by fractional anisotropy was, in turn, associated with lower cognitive function, providing evidence that AD-related structural connectivity loss is a correlate of cognitive decline.
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Affiliation(s)
- Seong Jae Hwang
- 1 Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin.,2 Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin
| | - Nagesh Adluru
- 3 Waisman Laboratory for Brain Imaging and Behavior, University of Wisconsin-Madison, Madison, Wisconsin
| | - Won Hwa Kim
- 4 Department of Computer Science and Engineering, University of Texas at Arlington, Arlington, Texas
| | - Sterling C Johnson
- 2 Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,5 Geriatric Research Education and Clinical Center, William S. Middleton Veteran's Affairs Hospital, Madison, Wisconsin
| | - Barbara B Bendlin
- 2 Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,5 Geriatric Research Education and Clinical Center, William S. Middleton Veteran's Affairs Hospital, Madison, Wisconsin
| | - Vikas Singh
- 1 Department of Computer Sciences, University of Wisconsin-Madison, Madison, Wisconsin.,2 Wisconsin Alzheimer's Disease Research Center, University of Wisconsin School of Medicine and Public Health, Madison, Wisconsin.,6 Department of Biostatistics and Medical Informatics, University of Wisconsin-Madison, Madison, Wisconsin
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Alves C, Jorge L, Canário N, Santiago B, Santana I, Castelhano J, Ambrósio AF, Bernardes R, Castelo-Branco M. Interplay Between Macular Retinal Changes and White Matter Integrity in Early Alzheimer's Disease. J Alzheimers Dis 2019; 70:723-732. [PMID: 31282416 PMCID: PMC6700635 DOI: 10.3233/jad-190152] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 05/15/2019] [Indexed: 11/20/2022]
Abstract
This study aims to investigate the relationship between structural changes in the retina and white matter in the brain, in early Alzheimer's disease (AD). Twenty-three healthy controls (mean age = 63.4±7.5 years) and seventeen AD patients (mean age = 66.5±6.6 years) were recruited for this study. By combining two imaging techniques-optical coherence tomography and diffusion tensor imaging (DTI)-the association between changes in the thickness of individual retinal layers and white matter dysfunction in early AD was assessed. Retinal layers were segmented, and thickness measurements were obtained for each layer. DTI images were analyzed with a quantitative data-driven approach to evaluating whole-brain diffusion metrics, using tract-based spatial statistics. Diffusion metrics, such as fractional anisotropy, are markers for white matter integrity. Multivariate and partial correlation analyses evaluating the association between individual retinal layers thickness and diffusion metrics were performed. We found that axial diffusivity, indexing axonal integrity, was significantly reduced in AD (p = 0.016, Cohen's d = 1.004) while in the retina, only a marginal trend for significance was found for the outer plexiform layer (p = 0.084, Cohen's d = 0.688). Furthermore, a positive association was found in the AD group between fractional anisotropy and the inner nuclear layer thickness (p < 0.05, r = 0.419, corrected for multiple comparisons by controlling family-wise error rate). Our findings suggest that axonal damage in the brain dominates early on in this condition and shows an association with retinal structural integrity already at initial stages of AD. These findings are consistent with an early axonal degeneration mechanism in AD.
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Affiliation(s)
- Carolina Alves
- CIBIT – Coimbra Institute for Biomedical Imaging and Life Sciences, Coimbra, Portugal
- Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Lília Jorge
- CIBIT – Coimbra Institute for Biomedical Imaging and Life Sciences, Coimbra, Portugal
- Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Nádia Canário
- CIBIT – Coimbra Institute for Biomedical Imaging and Life Sciences, Coimbra, Portugal
- Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
| | - Beatriz Santiago
- Department of Neurology, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - Isabel Santana
- Department of Neurology, Centro Hospitalar e Universitário de Coimbra, Coimbra, Portugal
| | - João Castelhano
- CIBIT – Coimbra Institute for Biomedical Imaging and Life Sciences, Coimbra, Portugal
- Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - António Francisco Ambrósio
- CNC.IBILI, University of Coimbra, Coimbra, Portugal
- Coimbra Institute for Clinical and Biomedical Research (iCBR), Faculty of Medicine, University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Rui Bernardes
- CIBIT – Coimbra Institute for Biomedical Imaging and Life Sciences, Coimbra, Portugal
- Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
| | - Miguel Castelo-Branco
- CIBIT – Coimbra Institute for Biomedical Imaging and Life Sciences, Coimbra, Portugal
- Institute for Nuclear Sciences Applied to Health (ICNAS), University of Coimbra, Coimbra, Portugal
- Faculty of Medicine, University of Coimbra, Coimbra, Portugal
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White matter involvement in young non-demented Down's syndrome subjects: a tract-based spatial statistic analysis. Neuroradiology 2018; 60:1335-1341. [PMID: 30264168 DOI: 10.1007/s00234-018-2102-5] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/15/2018] [Accepted: 09/17/2018] [Indexed: 10/28/2022]
Abstract
PURPOSE Cognitive decline in Down syndrome generally shows neurodegenerative aspects similar to what is observed in Alzheimer's disease. Few studies reported information on white matter integrity. The aim of this study was to evaluate white matter alterations in a cohort of young Down subjects, without dementia, by means of DTI technique, compared to a normal control group. METHODS The study group consisted of 17 right-handed subjects with DS and many control subjects. All individuals participating in this study were examined by MR exam including DTI acquisition (32 non-coplanar directions); image processing and analysis were performed using FMRIB Software Library (FSL version 4.1.9, http://www.fmrib.ox.ac.uk/fsl )) software package. Finally, the diffusion tensor was estimated voxel by voxel and the FA map derived from the tensor. A two-sample t test was performed to assess differences between DS and control subjects. RESULTS The FA is decreased in DS subjects, compared to control subjects, in the region of the anterior thalamic radiation, the inferior fronto-occipital fasciculum, the inferior longitudinal fasciculum, and the cortico-spinal tract, bilaterally. CONCLUSIONS The early white matter damage visible in our DS subjects could have great impact in the therapeutic management, in particular in better adapting the timing of therapies to counteract the toxic effect of the deposition of amyloid that leads to oxidative stress.
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37
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De Micco R, Russo A, Tessitore A. Structural MRI in Idiopathic Parkinson's Disease. INTERNATIONAL REVIEW OF NEUROBIOLOGY 2018; 141:405-438. [PMID: 30314605 DOI: 10.1016/bs.irn.2018.08.011] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/03/2023]
Abstract
Among modern neuroimaging modalities, magnetic resonance imaging (MRI) is a widely available, non-invasive, and cost-effective method to detect structural and functional abnormalities related to neurodegenerative disorders. In the last decades, MRI have been widely implemented to support PD diagnosis as well as to provide further insights into motor and non-motor symptoms pathophysiology, complications and treatment-related effects. Different aspects of the brain morphology and function may be derived from a single scan, by applying different analytic approaches. Biomarkers of neurodegeneration as well as tissue microstructural changes may be extracted from structural MRI techniques. In this chapter, we analyze the role of structural imaging to differentiate PD patients from controls and to define neural substrates of motor and non-motor PD symptoms. Evidence collected in the premotor PD phase will be also critically discussed. White matter as well as gray matter integrity imaging studies has been reviewed, aiming to highlight points of strength and limits to their potential application in clinical settings.
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Affiliation(s)
- Rosa De Micco
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "Luigi Vanvitelli", Napoli, Italy; MRI Research Center SUN-FISM, University of Campania "Luigi Vanvitelli", Napoli, Italy
| | - Antonio Russo
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "Luigi Vanvitelli", Napoli, Italy; MRI Research Center SUN-FISM, University of Campania "Luigi Vanvitelli", Napoli, Italy
| | - Alessandro Tessitore
- Department of Medical, Surgical, Neurological, Metabolic and Aging Sciences, University of Campania "Luigi Vanvitelli", Napoli, Italy; MRI Research Center SUN-FISM, University of Campania "Luigi Vanvitelli", Napoli, Italy.
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38
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Perea RD, Rabin JS, Fujiyoshi MG, Neal TE, Smith EE, Van Dijk KRA, Hedden T. Connectome-derived diffusion characteristics of the fornix in Alzheimer's disease. NEUROIMAGE-CLINICAL 2018; 19:331-342. [PMID: 30013916 PMCID: PMC6044183 DOI: 10.1016/j.nicl.2018.04.029] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 12/21/2017] [Revised: 04/03/2018] [Accepted: 04/23/2018] [Indexed: 02/06/2023]
Abstract
The fornix bundle is a major white matter pathway of the hippocampus. While volume of the hippocampus has been a primary imaging biomarker of Alzheimer's disease progression, recent research has suggested that the volume and microstructural characteristics of the fornix bundle connecting the hippocampus could add relevant information for diagnosing and staging Alzheimer's disease. Using a robust fornix bundle isolation technique in native diffusion space, this study investigated whether diffusion measurements of the fornix differed between normal older adults and Alzheimer's disease patients when controlling for volume measurements. Data were collected using high gradient multi-shell diffusion-weighted MRI from a Siemens CONNECTOM scanner in 23 Alzheimer's disease and 23 age- and sex-matched control older adults (age range = 53–92). These data were used to reconstruct a continuous fornix bundle in every participant's native diffusion space, from which tract-derived volumetric and diffusion metrics were extracted and compared between groups. Diffusion metrics included those from a tensor model and from a generalized q-sampling imaging model. Results showed no significant differences in tract-derived fornix volumes but did show altered diffusion metrics within tissue classified as the fornix in the Alzheimer's disease group. Comparisons to a manual tracing method indicated the same pattern of results and high correlations between the methods. These results suggest that in Alzheimer's disease, diffusion characteristics may provide more sensitive measures of fornix degeneration than do volume measures and may be a potential early marker for loss of medial temporal lobe connectivity. An enhanced method for measurement of continuous fornix bundles is described. Diffusion characteristics of the fornix were degraded in Alzheimer's disease. Alzheimer's disease primarily affected the crus and body of the fornix. Diffusion differences were observed controlling for fornix volume differences.
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Affiliation(s)
- Rodrigo D Perea
- Athinoula A. Martinos Center for Biomedical Imaging, Dept. of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Dept. of Radiology, Harvard Medical School, Boston, MA, United States
| | - Jennifer S Rabin
- Dept. of Psychiatry, Massachusetts General Hospital, Boston, MA, United States; Dept. of Psychiatry, Harvard Medical School, Boston, MA, United States
| | - Megan G Fujiyoshi
- Dept. of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
| | - Taylor E Neal
- Dept. of Psychiatry, Massachusetts General Hospital, Boston, MA, United States
| | - Emily E Smith
- Dept. of Psychiatry, Massachusetts General Hospital, Boston, MA, United States; Dept. of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, United States
| | - Koene R A Van Dijk
- Athinoula A. Martinos Center for Biomedical Imaging, Dept. of Radiology, Massachusetts General Hospital, Charlestown, MA, United States
| | - Trey Hedden
- Athinoula A. Martinos Center for Biomedical Imaging, Dept. of Radiology, Massachusetts General Hospital, Charlestown, MA, United States; Dept. of Radiology, Harvard Medical School, Boston, MA, United States.
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39
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Palesi F, De Rinaldis A, Vitali P, Castellazzi G, Casiraghi L, Germani G, Bernini S, Anzalone N, Ramusino MC, Denaro FM, Sinforiani E, Costa A, Magenes G, D'Angelo E, Gandini Wheeler-Kingshott CAM, Micieli G. Specific Patterns of White Matter Alterations Help Distinguishing Alzheimer's and Vascular Dementia. Front Neurosci 2018; 12:274. [PMID: 29922120 PMCID: PMC5996902 DOI: 10.3389/fnins.2018.00274] [Citation(s) in RCA: 41] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/16/2018] [Accepted: 04/09/2018] [Indexed: 12/19/2022] Open
Abstract
Alzheimer disease (AD) and vascular dementia (VaD) together represent the majority of dementia cases. Since their neuropsychological profiles often overlap and white matter lesions are observed in elderly subjects including AD, differentiating between VaD and AD can be difficult. Characterization of these different forms of dementia would benefit by identification of quantitative imaging biomarkers specifically sensitive to AD or VaD. Parameters of microstructural abnormalities derived from diffusion tensor imaging (DTI) have been reported to be helpful in differentiating between dementias, but only few studies have used them to compare AD and VaD with a voxelwise approach. Therefore, in this study a whole brain statistical analysis was performed on DTI data of 93 subjects (31 AD, 27 VaD, and 35 healthy controls—HC) to identify specific white matter patterns of alteration in patients affected by VaD and AD with respect to HC. Parahippocampal tracts were found to be mainly affected in AD, while VaD showed more spread white matter damages associated with thalamic radiations involvement. The genu of the corpus callosum was predominantly affected in VaD, while the splenium was predominantly affected in AD revealing the existence of specific patterns of alteration useful in distinguishing between VaD and AD. Therefore, DTI parameters of these regions could be informative to understand the pathogenesis and support the etiological diagnosis of dementia. Further studies on larger cohorts of subjects, characterized for brain amyloidosis, will allow to confirm and to integrate the present findings and, furthermore, to elucidate the mechanisms of mixed dementia. These steps will be essential to translate these advances to clinical practice.
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Affiliation(s)
- Fulvia Palesi
- Department of Physics, University of Pavia, Pavia, Italy.,Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy
| | - Andrea De Rinaldis
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.,Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Paolo Vitali
- Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation, Pavia, Italy.,Neuroradiology Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Gloria Castellazzi
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.,Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Letizia Casiraghi
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Giancarlo Germani
- Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation, Pavia, Italy.,Neuroradiology Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Sara Bernini
- Alzheimer's Disease Assessment Unit, Laboratory of Neuropsychology, IRCCS Mondino Foundation, Pavia, Italy
| | | | - Matteo Cotta Ramusino
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Alzheimer's Disease Assessment Unit, Laboratory of Neuropsychology, IRCCS Mondino Foundation, Pavia, Italy
| | - Federica M Denaro
- Department of Emergency Neurology, IRCCS Mondino Foundation, Pavia, Italy
| | - Elena Sinforiani
- Alzheimer's Disease Assessment Unit, Laboratory of Neuropsychology, IRCCS Mondino Foundation, Pavia, Italy
| | - Alfredo Costa
- Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Alzheimer's Disease Assessment Unit, Laboratory of Neuropsychology, IRCCS Mondino Foundation, Pavia, Italy
| | - Giovanni Magenes
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, Pavia, Italy
| | - Egidio D'Angelo
- Brain Connectivity Center, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy
| | - Claudia A M Gandini Wheeler-Kingshott
- Brain MRI 3T Mondino Research Center, IRCCS Mondino Foundation, Pavia, Italy.,Department of Brain and Behavioral Sciences, University of Pavia, Pavia, Italy.,Queen Square MS Centre, UCL Institute of Neurology, Faculty of Brain Sciences, University College London, London, United Kingdom
| | - Giuseppe Micieli
- Department of Emergency Neurology, IRCCS Mondino Foundation, Pavia, Italy
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40
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Gerstenecker A, Hoagey DA, Marson DC, Kennedy KM. White Matter Degradation is Associated with Reduced Financial Capacity in Mild Cognitive Impairment and Alzheimer's Disease. J Alzheimers Dis 2018; 60:537-547. [PMID: 28826185 DOI: 10.3233/jad-170341] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Financial capacity (FC) is a cognitively complex activity of daily living that declines in mild cognitive impairment (MCI) and Alzheimer's disease (AD), limiting an individual's ability to manage one's finances and function independently. The neural underpinnings of this decline in function are poorly understood but likely involve age-related and disease-related degradation across structural networks. The purpose of the current study was to determine if altered white matter integrity is associated with declining FC in persons with MCI and AD compared to older controls. Individuals with MCI due to AD (n = 31), mild dementia (n = 39), and cognitively healthy older adults (n = 60) were administered a neuropsychological battery including the FC Instrument, a performance-based measure of FC. All 130 participants also underwent diffusion tensor imaging (DTI) upon which tract-based spatial statistics were performed. Both FC and white matter integrity decreased in accordance with disease severity with little to no effect in healthy elderly, significant effects in MCI, and greater effects in AD. Regional white matter degradation (increased diffusivities and decreased fractional anisotropy) was associated with reduced FC in both MCI and AD groups even after controlling for age, education, and gender. Specifically, in MCI, decreased fractional anisotropy, but not increased diffusivities, was associated with poorer FC in widespread cingulo-parietal-frontal and temporo-occipital areas. In AD, rather than anisotropy, increased mean and axial diffusivities in anterior cingulate, callosum, and frontal areas associated with poorer FC. These findings suggest a severity gradient of white matter degradation across DTI metrics and AD stages that predict declining financial skill and knowledge.
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Affiliation(s)
- Adam Gerstenecker
- Division of Neuropsychology, Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, USA.,Alzheimer's Disease Center, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - David A Hoagey
- The University of Texas at Dallas, School of Behavioral and Brain Sciences, Center for Vital Longevity, Dallas, TX, USA
| | - Daniel C Marson
- Division of Neuropsychology, Department of Neurology, The University of Alabama at Birmingham, Birmingham, AL, USA.,Alzheimer's Disease Center, The University of Alabama at Birmingham, Birmingham, AL, USA
| | - Kristen M Kennedy
- The University of Texas at Dallas, School of Behavioral and Brain Sciences, Center for Vital Longevity, Dallas, TX, USA
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41
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Whittaker HT, Zhu S, Di Curzio DL, Buist R, Li XM, Noy S, Wiseman FK, Thiessen JD, Martin M. T 1, diffusion tensor, and quantitative magnetization transfer imaging of the hippocampus in an Alzheimer's disease mouse model. Magn Reson Imaging 2018; 50:26-37. [PMID: 29545212 DOI: 10.1016/j.mri.2018.03.010] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/09/2018] [Accepted: 03/10/2018] [Indexed: 01/08/2023]
Abstract
Alzheimer's disease (AD) pathology causes microstructural changes in the brain. These changes, if quantified with magnetic resonance imaging (MRI), could be studied for use as an early biomarker for AD. The aim of our study was to determine if T1 relaxation, diffusion tensor imaging (DTI), and quantitative magnetization transfer imaging (qMTI) metrics could reveal changes within the hippocampus and surrounding white matter structures in ex vivo transgenic mouse brains overexpressing human amyloid precursor protein with the Swedish mutation. Delineation of hippocampal cell layers using DTI color maps allows more detailed analysis of T1-weighted imaging, DTI, and qMTI metrics, compared with segmentation of gross anatomy based on relaxation images, and with analysis of DTI or qMTI metrics alone. These alterations are observed in the absence of robust intracellular Aβ accumulation or plaque deposition as revealed by histology. This work demonstrates that multiparametric quantitative MRI methods are useful for characterizing changes within the hippocampal substructures and surrounding white matter tracts of mouse models of AD.
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Affiliation(s)
- Heather T Whittaker
- Biopsychology, University of Winnipeg, Winnipeg, MB R3B 2N2, Canada; Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, United Kingdom.
| | - Shenghua Zhu
- Pharmacology and Therapeutics, University of Manitoba, Winnipeg, MB R3E 0T6, Canada
| | | | - Richard Buist
- Radiology, University of Manitoba, Winnipeg, MB R3E 0T6, Canada
| | - Xin-Min Li
- Psychiatry, University of Alberta, Alberta T6G 2R3, Canada
| | - Suzanna Noy
- Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, United Kingdom
| | - Frances K Wiseman
- Neurodegenerative Disease, University College London Institute of Neurology, London WC1N 3BG, United Kingdom
| | - Jonathan D Thiessen
- Imaging Program, Lawson Health Research Institute, London, ON N6A 4V2, Canada; Medical Biophysics, Western University, London, Ontario, Canada
| | - Melanie Martin
- Pharmacology and Therapeutics, University of Manitoba, Winnipeg, MB R3E 0T6, Canada; Radiology, University of Manitoba, Winnipeg, MB R3E 0T6, Canada; Physics, University of Winnipeg, R3B 2N2, Canada
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42
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White matter degeneration in subjective cognitive decline: a diffusion tensor imaging study. Oncotarget 2018; 7:54405-54414. [PMID: 27384675 PMCID: PMC5342351 DOI: 10.18632/oncotarget.10091] [Citation(s) in RCA: 40] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2015] [Accepted: 05/17/2016] [Indexed: 11/25/2022] Open
Abstract
Subjective cognitive decline (SCD) may be an at-risk stage of Alzheimer's disease (AD) occurring prior to amnestic mild cognitive impairment (aMCI). To examine white matter (WM) defects in SCD, diffusion images from 27 SCD (age=65.3±8.0), 35 aMCI (age=69.2±8.6) and 25 AD patients (age=68.3±9.4) and 37 normal controls (NC) (age=65.1±6.8) were compared using Tract-Based Spatial Statistics (TBSS). WM impairments common to the three patient groups were extracted, and fractional anisotropy (FA) values were averaged in each group. As compared to NC subjects, SCD patients displayed widespread WM alterations represented by decreased FA (p<0.05), increased mean diffusivity (MD; p<0.05), and increased radial diffusivity (RD; p<0.05). In addition, localized WM alterations showed increased axial diffusivity (AxD; p<0.05) similar to what was observed in aMCI and AD patients (p<0.05). In the shared WM impairment tracts, SCD patients had FA values between the NC group and the other two patient groups. In the NC and SCD groups, the AVLT-delayed recall score correlated with higher AxD (r=−0.333, p=0.045), MD (r=−0.351, p=0.03) and RD (r=−0.353, p=0.025). In both the aMCI and AD groups the diffusion parameters were highly correlated with cognitive scores. Our study suggests that SCD patients present with widespread WM changes, which may contribute to the early memory decline they experience.
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Giulietti G, Torso M, Serra L, Spanò B, Marra C, Caltagirone C, Cercignani M, Bozzali M. Whole brain white matter histogram analysis of diffusion tensor imaging data detects microstructural damage in mild cognitive impairment and alzheimer's disease patients. J Magn Reson Imaging 2018; 48:767-779. [PMID: 29356183 DOI: 10.1002/jmri.25947] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/27/2017] [Accepted: 12/21/2017] [Indexed: 01/07/2023] Open
Abstract
BACKGROUND Amnestic mild cognitive impairment (MCI) is a transitional stage between normal aging and Alzheimer's disease (AD). However, the clinical conversion from MCI to AD is unpredictable. Hence, identification of noninvasive biomarkers able to detect early changes induced by dementia is a pressing need. PURPOSE To explore the added value of histogram analysis applied to measures derived from diffusion tensor imaging (DTI) for detecting brain tissue differences between AD, MCI, and healthy subjects (HS). STUDY TYPE Prospective. POPULATION/SUBJECTS A local cohort (57 AD, 28 MCI, 23 HS), and an Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort (41 AD, 58 MCI, 41 HS). FIELD STRENGTH 3T. Dual-echo turbo spin echo (TSE); fluid-attenuated inversion recovery (FLAIR); modified-driven-equilibrium-Fourier-transform (MDEFT); inversion-recovery spoiled gradient recalled (IR-SPGR); diffusion tensor imaging (DTI). ASSESSMENT Normal-appearing white matter (NAWM) masks were obtained using the T1 -weighted volumes for tissue segmentation and T2 -weighted images for removal of hyperintensities/lesions. From DTI images, fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AXD), and radial diffusivity (RD) were obtained. NAWM histograms of FA, MD, AXD, and RD were derived and characterized estimating: peak height, peak location, mean value (MV), and quartiles (C25, C50, C75), which were compared between groups. Receiver operating characteristic (ROC) and area under ROC curves (AUC) were calculated. To confirm our results, the same analysis was repeated on the ADNI dataset. STATISTICAL TESTS One-way analysis of variance (ANOVA), post-hoc Student's t-test, multiclass ROC analysis. RESULTS For the local cohort, C25 of AXD had the maximum capability of group discrimination with AUC of 0.80 for "HS vs. patients" comparison and 0.74 for "AD vs. others" comparison. For the ADNI cohort, MV of AXD revealed the maximum group discrimination capability with AUC of 0.75 for "HS vs. patients" comparison and 0.75 for "AD vs. others" comparison. DATA CONCLUSION AXD of NAWM might be an early marker of microstructural brain tissue changes occurring during the AD course and might be useful for assessing disease progression. LEVEL OF EVIDENCE 1 Technical Efficacy: Stage 2 J. Magn. Reson. Imaging 2017.
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Affiliation(s)
| | - Mario Torso
- Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Laura Serra
- Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Barbara Spanò
- Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Camillo Marra
- Institute of Neurology, Catholic University, Rome, Italy
| | - Carlo Caltagirone
- Department of Systemic Medicine, University of Tor Vergata, Rome, Italy
- Clinical and Behavioral Neurology Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
| | - Mara Cercignani
- Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
- Department of Neuroscience, Clinical Imaging Sciences Centre, Brighton and Sussex Medical School, University of Sussex, Brighton, East Sussex, UK
| | - Marco Bozzali
- Neuroimaging Laboratory, IRCCS Santa Lucia Foundation, Rome, Italy
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Caso F, Agosta F, Ječmenica-Lukić M, Petrović I, Meani A, Kostic VS, Filippi M. Progression of white matter damage in progressive supranuclear palsy with predominant parkinsonism. Parkinsonism Relat Disord 2018; 49:95-99. [PMID: 29336906 DOI: 10.1016/j.parkreldis.2018.01.001] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 10/25/2017] [Revised: 12/14/2017] [Accepted: 01/01/2018] [Indexed: 11/16/2022]
Abstract
INTRODUCTION Progressive supranuclear palsy with predominant parkinsonism (PSP-P) accounts for 14-35% of all PSP cases. A few cross-sectional MRI studies in PSP-P showed a remarkable white matter (WM) damage. Progression of brain structural damage in these patients remains unknown. METHODS Longitudinal clinical, cognitive and diffusion tensor (DT) MRI data were obtained over a mean 1.6 year follow up in 10 PSP-P patients. At study entry, patients were compared with 36 healthy controls. Voxelwise statistical analysis of white matter DT MRI data (mean, axial and radial diffusivity, and fractional anisotropy) was carried out using tract-based spatial statistics. RESULTS During the 1.6 year follow up, PSP-P patients showed significant decline of motor, cognitive and mood disturbances. DT MRI analysis revealed at baseline a widespread pattern of WM alterations. Over time, PSP-P patients exhibited progression of WM damage in supratentorial tracts compared to baseline. No WM changes were detected in cerebellar WM. CONCLUSIONS In PSP-P patients, WM damage significantly progressed over time. Longitudinal DT MRI measures are a potential in vivo marker of disease progression in PSP-P.
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Affiliation(s)
- Francesca Caso
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | | | - Igor Petrović
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Alessandro Meani
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Vladimir S Kostic
- Clinic of Neurology, School of Medicine, University of Belgrade, Belgrade, Serbia
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy; Department of Neurology, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy.
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45
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Ding K, Tarumi T, Zhu DC, Tseng BY, Thomas BP, Turner M, Repshas J, Kerwin DR, Womack KB, Lu H, Cullum CM, Zhang R. Cardiorespiratory Fitness and White Matter Neuronal Fiber Integrity in Mild Cognitive Impairment. J Alzheimers Dis 2018; 61:729-739. [PMID: 29226864 PMCID: PMC6757343 DOI: 10.3233/jad-170415] [Citation(s) in RCA: 20] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022]
Abstract
BACKGROUND Mounting evidence showed the self-reported levels of physical activity are positively associated with white matter (WM) integrity and cognitive performance in normal adults and patients with mild cognitive impairment (MCI). However, the objective measure of cardiorespiratory fitness (CRF) was not used in these studies. OBJECTIVE To determine the associations of CRF measured by maximal oxygen uptake (VO2max) with WM fiber integrity and neurocognitive performance in older adults with MCI. METHODS Eighty-one participants (age = 65±7 years, 43 women), including 26 cognitively normal older adults and 55 amnestic MCI patients, underwent VO2max test to measure CRF, diffusion tensor imaging (DTI) to assess WM fiber integrity, and neurocognitive assessment focused on memory and executive function. DTI data were analyzed by the tract-based spatial statistics and region-of-interest approach. RESULTS Cognitively normal older adults and MCI patients were not different in global WM fiber integrity and VO2max. VO2max was associated positively with DTI metrics of fractional anisotropy in ∼54% WM fiber tracts, and negatively with mean and radial diffusivities in ∼46% and ∼56% of the WM fiber tracts. The associations of VO2max with DTI metrics remained statistically significant after adjustment of age, sex, body mass index, WM lesion burden, and MCI status. The DTI metrics obtained from the area that correlated to VO2max were associated with executive function performance in MCI patients. CONCLUSIONS Higher levels of CRF are associated with better WM fiber integrity, which in turn is correlated with better executive function performance in MCI patients.
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Affiliation(s)
- Kan Ding
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Takashi Tarumi
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital Dallas, Dallas, TX, USA
| | - David C. Zhu
- Departments of Radiology and Psychology, and Cognitive Imaging Research Center, Michigan State University, East Lansing, MI, USA
| | - Benjamin Y. Tseng
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital Dallas, Dallas, TX, USA
| | - Binu P. Thomas
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Marcel Turner
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital Dallas, Dallas, TX, USA
| | - Justin Repshas
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital Dallas, Dallas, TX, USA
| | - Diana R. Kerwin
- Texas Alzheimer’s and Memory Disorders, Texas Health Presbyterian Hospital Dallas, Dallas, TX, USA
| | - Kyle B. Womack
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Hanzhang Lu
- Advanced Imaging Research Center, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - C. Munro Cullum
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Psychiatry, University of Texas Southwestern Medical Center, Dallas, TX, USA
| | - Rong Zhang
- Department of Neurology and Neurotherapeutics, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Department of Internal Medicine, University of Texas Southwestern Medical Center, Dallas, TX, USA
- Institute for Exercise and Environmental Medicine, Texas Health Presbyterian Hospital Dallas, Dallas, TX, USA
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46
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Woodward MR, Dwyer MG, Bergsland N, Hagemeier J, Zivadinov R, Benedict RH, Szigeti K. Olfactory identification deficit predicts white matter tract impairment in Alzheimer's disease. Psychiatry Res Neuroimaging 2017; 266:90-95. [PMID: 28644998 PMCID: PMC5973809 DOI: 10.1016/j.pscychresns.2017.06.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/14/2017] [Revised: 05/08/2017] [Accepted: 06/02/2017] [Indexed: 12/01/2022]
Abstract
Olfactory identification deficit (OID) has been associated with both aging and Alzheimer's disease (AD). In the context of an amnestic disorders, OID predicts conversion to AD. Neuroanatomical correlates could increase specificity and sensitivity and elucidate the mechanistic differences between OID in AD and aging. Cross-sectional analysis of white matter microstructural changes was performed using diffusion tensor imaging (DTI) and tract-based-spatial-statistics in amnestic mild cognitive impairment (aMCI), AD and normal controls (NC) in 66 subjects (26 AD, 15 aMCI, 25 NC). DTI 3-Tesla MRI scans were analyzed and subject level means for fractional anisotropy (FA), mean diffusivity (MD), radial and axial diffusivity (λ1D and λ2,3D) were calculated. Linear regression models were applied using DTI markers as predictor and OID as outcome. OID was associated with increased λ1D in aMCI and increased MD, λ1D and λ2,3D in AD. Voxel-wise analyses revealed widespread differences in all markers in AD. There were significant differences in λ1D in aMCI, particularly in the olfactory tract. OID is correlated with microstructural white matter changes as early as in aMCI. This study may help elucidate the biological basis for olfactory impairment in Alzheimer's disease. Neuroanatomical correlates could help distinguish OID associated with AD and that associated with aging.
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Affiliation(s)
- Matthew R Woodward
- Alzheimer's Disease and Memory Disorder Center, Department of Neurology, University at Buffalo, SUNY, Buffalo, NY, United States
| | - Michael G Dwyer
- Buffalo Neuroimaging Analysis Center, University at Buffalo, SUNY, Buffalo, NY, United States
| | - Niels Bergsland
- Buffalo Neuroimaging Analysis Center, University at Buffalo, SUNY, Buffalo, NY, United States
| | - Jesper Hagemeier
- Buffalo Neuroimaging Analysis Center, University at Buffalo, SUNY, Buffalo, NY, United States
| | - Robert Zivadinov
- Buffalo Neuroimaging Analysis Center, University at Buffalo, SUNY, Buffalo, NY, United States
| | - Ralph Hb Benedict
- Alzheimer's Disease and Memory Disorder Center, Department of Neurology, University at Buffalo, SUNY, Buffalo, NY, United States
| | - Kinga Szigeti
- Alzheimer's Disease and Memory Disorder Center, Department of Neurology, University at Buffalo, SUNY, Buffalo, NY, United States.
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47
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Rasero J, Alonso-Montes C, Diez I, Olabarrieta-Landa L, Remaki L, Escudero I, Mateos B, Bonifazi P, Fernandez M, Arango-Lasprilla JC, Stramaglia S, Cortes JM. Group-Level Progressive Alterations in Brain Connectivity Patterns Revealed by Diffusion-Tensor Brain Networks across Severity Stages in Alzheimer's Disease. Front Aging Neurosci 2017; 9:215. [PMID: 28736521 PMCID: PMC5500648 DOI: 10.3389/fnagi.2017.00215] [Citation(s) in RCA: 22] [Impact Index Per Article: 3.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/13/2017] [Accepted: 06/20/2017] [Indexed: 01/22/2023] Open
Abstract
Alzheimer's disease (AD) is a chronically progressive neurodegenerative disease highly correlated to aging. Whether AD originates by targeting a localized brain area and propagates to the rest of the brain across disease-severity progression is a question with an unknown answer. Here, we aim to provide an answer to this question at the group-level by looking at differences in diffusion-tensor brain networks. In particular, making use of data from Alzheimer's Disease Neuroimaging Initiative (ADNI), four different groups were defined (all of them matched by age, sex and education level): G1 (N1 = 36, healthy control subjects, Control), G2 (N2 = 36, early mild cognitive impairment, EMCI), G3 (N3 = 36, late mild cognitive impairment, LMCI) and G4 (N4 = 36, AD). Diffusion-tensor brain networks were compared across three disease stages: stage I (Control vs. EMCI), stage II (Control vs. LMCI) and stage III (Control vs. AD). The group comparison was performed using the multivariate distance matrix regression analysis, a technique that was born in genomics and was recently proposed to handle brain functional networks, but here applied to diffusion-tensor data. The results were threefold: First, no significant differences were found in stage I. Second, significant differences were found in stage II in the connectivity pattern of a subnetwork strongly associated to memory function (including part of the hippocampus, amygdala, entorhinal cortex, fusiform gyrus, inferior and middle temporal gyrus, parahippocampal gyrus and temporal pole). Third, a widespread disconnection across the entire AD brain was found in stage III, affecting more strongly the same memory subnetwork appearing in stage II, plus the other new subnetworks, including the default mode network, medial visual network, frontoparietal regions and striatum. Our results are consistent with a scenario where progressive alterations of connectivity arise as the disease severity increases and provide the brain areas possibly involved in such a degenerative process. Further studies applying the same strategy to longitudinal data are needed to fully confirm this scenario.
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Affiliation(s)
- Javier Rasero
- Dipartimento Interateneo di Fisica, Istituto Nazionale di Fisica Nucleare, Universita degli Studi di BariBari, Italy
- Biocruces Health Research InstituteBarakaldo, Spain
| | | | - Ibai Diez
- Biocruces Health Research InstituteBarakaldo, Spain
| | | | | | - Iñaki Escudero
- Biocruces Health Research InstituteBarakaldo, Spain
- Radiology Service, Cruces University HospitalBarakaldo, Spain
| | - Beatriz Mateos
- Biocruces Health Research InstituteBarakaldo, Spain
- Radiology Service, Cruces University HospitalBarakaldo, Spain
| | - Paolo Bonifazi
- Biocruces Health Research InstituteBarakaldo, Spain
- IKERBASQUE: The Basque Foundation for ScienceBilbao, Spain
| | - Manuel Fernandez
- Biocruces Health Research InstituteBarakaldo, Spain
- Neurology Service, Cruces University HospitalBarakaldo, Spain
| | | | - Sebastiano Stramaglia
- Dipartimento Interateneo di Fisica, Istituto Nazionale di Fisica Nucleare, Universita degli Studi di BariBari, Italy
- Basque Center for Applied MathematicsBilbao, Spain
| | - Jesus M. Cortes
- Biocruces Health Research InstituteBarakaldo, Spain
- IKERBASQUE: The Basque Foundation for ScienceBilbao, Spain
- Department of Cell Biology and Histology, University of the Basque CountryLeioa, Spain
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48
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Slattery CF, Zhang J, Paterson RW, Foulkes AJM, Carton A, Macpherson K, Mancini L, Thomas DL, Modat M, Toussaint N, Cash DM, Thornton JS, Henley SMD, Crutch SJ, Alexander DC, Ourselin S, Fox NC, Zhang H, Schott JM. ApoE influences regional white-matter axonal density loss in Alzheimer's disease. Neurobiol Aging 2017; 57:8-17. [PMID: 28578156 PMCID: PMC5538347 DOI: 10.1016/j.neurobiolaging.2017.04.021] [Citation(s) in RCA: 69] [Impact Index Per Article: 9.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2016] [Revised: 04/14/2017] [Accepted: 04/22/2017] [Indexed: 01/10/2023]
Abstract
Mechanisms underlying phenotypic heterogeneity in young onset Alzheimer disease (YOAD) are poorly understood. We used diffusion tensor imaging and neurite orientation dispersion and density imaging (NODDI) with tract-based spatial statistics to investigate apolipoprotein (APOE) ε4 modulation of white-matter damage in 37 patients with YOAD (22, 59% APOE ε4 positive) and 23 age-matched controls. Correlation between neurite density index (NDI) and neuropsychological performance was assessed in 4 white-matter regions of interest. White-matter disruption was more widespread in ε4+ individuals but more focal (posterior predominant) in the absence of an ε4 allele. NODDI metrics indicate fractional anisotropy changes are underpinned by combinations of axonal loss and morphological change. Regional NDI in parieto-occipital white matter correlated with visual object and spatial perception battery performance (right and left, both p = 0.02), and performance (nonverbal) intelligence (WASI matrices, right, p = 0.04). NODDI provides tissue-specific microstructural metrics of white-matter tract damage in YOAD, including NDI which correlates with focal cognitive deficits, and APOEε4 status is associated with different patterns of white-matter neurodegeneration.
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Affiliation(s)
- Catherine F Slattery
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK.
| | - Jiaying Zhang
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Ross W Paterson
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | | | - Amelia Carton
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Kirsty Macpherson
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Laura Mancini
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - David L Thomas
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Leonard Wolfson Experimental Neurology Centre, UCL Institute of Neurology, London, UK
| | - Marc Modat
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Nicolas Toussaint
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - David M Cash
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK; Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - John S Thornton
- Neuroradiological Academic Unit, Department of Brain Repair and Rehabilitation, UCL Institute of Neurology, London, UK; Lysholm Department of Neuroradiology, National Hospital for Neurology and Neurosurgery, UCLH NHS Foundation Trust, London, UK
| | - Susie M D Henley
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Sebastian J Crutch
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Daniel C Alexander
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Sebastien Ourselin
- Translational Imaging Group, Centre for Medical Image Computing, Department of Medical Physics and Biomedical Engineering, UCL, London, UK
| | - Nick C Fox
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
| | - Hui Zhang
- Department of Computer Science and Centre for Medical Image Computing, UCL, London, UK
| | - Jonathan M Schott
- Department of Neurodegenerative Disease, Institute of Neurology, UCL, London, UK
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49
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Del Sole A, Malaspina S, Magenta Biasina A. Magnetic resonance imaging and positron emission tomography in the diagnosis of neurodegenerative dementias. FUNCTIONAL NEUROLOGY 2017; 31:205-215. [PMID: 28072381 DOI: 10.11138/fneur/2016.31.4.205] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.9] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Neuroimaging, both with magnetic resonance imaging (MRI) and positron emission tomography (PET), has gained a pivotal role in the diagnosis of primary neurodegenerative diseases. These two techniques are used as biomarkers of both pathology and progression of Alzheimer's disease (AD) and to differentiate AD from other neurodegenerative diseases. MRI is able to identify structural changes including patterns of atrophy characterizing neurodegenerative diseases, and to distinguish these from other causes of cognitive impairment, e.g. infarcts, space-occupying lesions and hydrocephalus. PET is widely used to identify regional patterns of glucose utilization, since distinct patterns of distribution of cerebral glucose metabolism are related to different subtypes of neurodegenerative dementia. The use of PET in mild cognitive impairment, though controversial, is deemed helpful for predicting conversion to dementia and the dementia clinical subtype. Recently, new radiopharmaceuticals for the in vivo imaging of amyloid burden have been licensed and more tracers are being developed for the assessment of tauopathies and inflammatory processes, which may underlie the onset of the amyloid cascade. At present, the cerebral amyloid burden, imaged with PET, may help to exclude the presence of AD as well as forecast its possible onset. Finally PET imaging may be particularly useful in ongoing clinical trials for the development of dementia treatments. In the near future, the use of the above methods, in accordance with specific guidelines, along with the use of effective treatments will likely lead to more timely and successful treatment of neurodegenerative dementias.
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50
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Cai S, Jiang Y, Wang Y, Wu X, Ren J, Lee MS, Lee S, Huang L. Modulation on brain gray matter activity and white matter integrity by APOE ε4 risk gene in cognitively intact elderly: A multimodal neuroimaging study. Behav Brain Res 2017; 322:100-109. [DOI: 10.1016/j.bbr.2017.01.027] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2016] [Revised: 01/11/2017] [Accepted: 01/13/2017] [Indexed: 12/11/2022]
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