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Callahan BL, Becker S, Ramirez J, Taylor R, Shammi P, Gao F, Black SE. Vascular Burden Moderates the Relationship Between ADHD and Cognition in Older Adults. Am J Geriatr Psychiatry 2024; 32:427-442. [PMID: 37989710 DOI: 10.1016/j.jagp.2023.10.018] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 07/13/2023] [Revised: 10/01/2023] [Accepted: 10/23/2023] [Indexed: 11/23/2023]
Abstract
OBJECTIVES Recent evidence suggests attention-deficit/hyperactivity disorder (ADHD) is a risk factor for cognitive impairment in later life. Here, we investigated cerebrovascular burden, quantified using white matter hyperintensity (WMH) volumes, as a potential mediator of this relationship. DESIGN This was a cross-sectional observational study. SETTING Participants were recruited from a cognitive neurology clinic where they had been referred for cognitive assessment, or from the community. PARTICIPANTS Thirty-nine older adults with clinical ADHD and 50 age- and gender-matched older adults without ADHD. MEASUREMENTS A semiautomated structural MRI pipeline was used to quantify periventricular (pWMH) and deep WMH (dWMH) volumes. Cognition was measured using standardized tests of memory, processing speed, visuo-construction, language, and executive functioning. Mediation models, adjusted for sex, were built to test the hypothesis that ADHD status exerts a deleterious impact on cognitive performance via WMH burden. RESULTS Results did not support a mediated effect of ADHD on cognition. Post hoc inspection of the data rather suggested a moderated effect, which was investigated as an a posteriori hypothesis. These results revealed a significant moderating effect of WMH on the relationship between ADHD memory, speed, and executive functioning, wherein ADHD was negatively associated with cognition at high and medium levels of WMH, but not when WMH volumes were low. CONCLUSIONS ADHD increases older adults' susceptibility to the deleterious cognitive effects of WMH in the brain. Older adults with ADHD may be at risk for cognitive impairment if they have deep WMH volumes above 61 mm3 and periventricular WMH above 260 mm3.
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Affiliation(s)
- Brandy L Callahan
- Department of Psychology (BLC, SB), University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute (BLC, SB), Calgary, Alberta, Canada.
| | - Sara Becker
- Department of Psychology (BLC, SB), University of Calgary, Calgary, Alberta, Canada; Hotchkiss Brain Institute (BLC, SB), Calgary, Alberta, Canada
| | - Joel Ramirez
- Dr. Sandra Black Centre for Brain Resilience & Recovery (JR, RT, FG, SEB), LC Campbell Cognitive Neurology Unit, Sunnybrook Research Institute, Toronto, Ontario, Canada; Hurvitz Brain Sciences Program (JR, RT, PS, FG, SEB), Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Rebecca Taylor
- Dr. Sandra Black Centre for Brain Resilience & Recovery (JR, RT, FG, SEB), LC Campbell Cognitive Neurology Unit, Sunnybrook Research Institute, Toronto, Ontario, Canada; Hurvitz Brain Sciences Program (JR, RT, PS, FG, SEB), Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Prathiba Shammi
- Hurvitz Brain Sciences Program (JR, RT, PS, FG, SEB), Sunnybrook Research Institute, Toronto, Ontario, Canada; Neuropsychology & Cognitive Health Program (PS), Baycrest Health Sciences Centre, Toronto, Ontario, Canada
| | - Fuqiang Gao
- Dr. Sandra Black Centre for Brain Resilience & Recovery (JR, RT, FG, SEB), LC Campbell Cognitive Neurology Unit, Sunnybrook Research Institute, Toronto, Ontario, Canada; Hurvitz Brain Sciences Program (JR, RT, PS, FG, SEB), Sunnybrook Research Institute, Toronto, Ontario, Canada
| | - Sandra E Black
- Dr. Sandra Black Centre for Brain Resilience & Recovery (JR, RT, FG, SEB), LC Campbell Cognitive Neurology Unit, Sunnybrook Research Institute, Toronto, Ontario, Canada; Hurvitz Brain Sciences Program (JR, RT, PS, FG, SEB), Sunnybrook Research Institute, Toronto, Ontario, Canada; Department of Medicine (Neurology) (SEB), University of Toronto, Toronto, Ontario, Canada
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Sakurai R, Pieruccini‐Faria F, Cornish B, Fraser J, Binns MA, Beaton D, Dilliott AA, Kwan D, Ramirez J, Tan B, Scott CJM, Sunderland KM, Tartaglia C, Finger E, Zinman L, Freedman M, McLaughlin PM, Swartz RH, Symons S, Lang AE, Bartha R, Black SE, Masellis M, Hegele RA, McIlroy W, Montero‐Odasso M. Link among apolipoprotein E E4, gait, and cognition in neurodegenerative diseases: ONDRI study. Alzheimers Dement 2024; 20:2968-2979. [PMID: 38470007 PMCID: PMC11032526 DOI: 10.1002/alz.13740] [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: 06/16/2023] [Revised: 12/08/2023] [Accepted: 12/14/2023] [Indexed: 03/13/2024]
Abstract
INTRODUCTION Apolipoprotein E E4 allele (APOE E4) and slow gait are independently associated with cognitive impairment and dementia. However, it is unknown whether their coexistence is associated with poorer cognitive performance and its underlying mechanism in neurodegenerative diseases. METHODS Gait speed, APOE E4, cognition, and neuroimaging were assessed in 480 older adults with neurodegeneration. Participants were grouped by APOE E4 presence and slow gait. Mediation analyses were conducted to determine if brain structures could explain the link between these factors and cognitive performance. RESULTS APOE E4 carriers with slow gait had the lowest global cognitive performance and smaller gray matter volumes compared to non-APOE E4 carriers with normal gait. Coexistence of APOE E4 and slow gait best predicted global and domain-specific poorer cognitive performances, mediated by smaller gray matter volume. DISCUSSION Gait slowness in APOE E4 carriers with neurodegenerative diseases may indicate extensive gray matter changes associated with poor cognition. HIGHLIGHTS APOE E4 and slow gait are risk factors for cognitive decline in neurodegenerative diseases. Slow gait and smaller gray matter volumes are associated, independently of APOE E4. Worse cognition in APOE E4 carriers with slow gait is explained by smaller GM volume. Gait slowness in APOE E4 carriers indicates poorer cognition-related brain changes.
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Affiliation(s)
- Ryota Sakurai
- Research Team for Social Participation and Healthy AgingTokyo Metropolitan Institute for Geriatrics and GerontologyItabashi‐kuTokyoJapan
- Gait & Brain Lab, St. Joseph' Health Care London, Lawson Health Research, Western University, Division of Geriatric MedicineLondonOntarioCanada
| | - Frederico Pieruccini‐Faria
- Gait & Brain Lab, St. Joseph' Health Care London, Lawson Health Research, Western University, Division of Geriatric MedicineLondonOntarioCanada
- Department of MedicineDivision of Geriatric MedicineParkwood HospitalWestern University, Parkwood InstituteLondonOntarioCanada
| | - Benjamin Cornish
- Neuroscience, Mobility and Balance Lab, Department of Kinesiology and Health SciencesUniversity of WaterlooWaterlooOntarioCanada
| | - Julia Fraser
- Neuroscience, Mobility and Balance Lab, Department of Kinesiology and Health SciencesUniversity of WaterlooWaterlooOntarioCanada
| | - Malcolm A. Binns
- Rotman Research Institute, Baycrest Health SciencesTorontoOntarioCanada
| | - Derek Beaton
- Data Science and Advanced Analytics, St. Michael's Hospital, Unity Health TorontoTorontoOntarioCanada
| | - Allison Ann Dilliott
- Department of Neurology and NeurosurgeryMontreal Neurological Institute, McGill UniversityMontréalQuebecCanada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's UniversityKingstonOntarioCanada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology)Sunnybrook Research Institute, Sunnybrook HSC, University of TorontoTorontoOntarioCanada
| | - Brian Tan
- Rotman Research Institute, Baycrest Health SciencesTorontoOntarioCanada
| | | | | | - Carmela Tartaglia
- Krembil Brain InstituteUniversity Health Network Memory Clinic, Toronto Western HospitalTorontoOntarioCanada
- Tanz Centre for Research in Neurodegenerative Diseases, University of TorontoTorontoOntarioCanada
| | - Elizabeth Finger
- Department of Clinical Neurological SciencesSchulich School of Medicine and Dentistry, Western UniversityLondonOntarioCanada
| | - Lorne Zinman
- Sunnybrook Research Institute, Sunnybrook Health Sciences CentreTorontoOntarioCanada
- Department of Medicine (Neurology)University of TorontoTorontoOntarioCanada
| | - Morris Freedman
- Rotman Research Institute, Baycrest Health SciencesTorontoOntarioCanada
- Department of Medicine (Neurology)University of TorontoTorontoOntarioCanada
- Division of NeurologyBaycrest Health SciencesTorontoOntarioCanada
| | - Paula M. McLaughlin
- Halifax Clinical Psychology Residency ProgramNova Scotia Health AuthorityHalifaxNova ScotiaCanada
| | - Richard H. Swartz
- Sunnybrook Research Institute, Sunnybrook Health Sciences CentreTorontoOntarioCanada
- Department of Medicine (Neurology)University of TorontoTorontoOntarioCanada
| | - Sean Symons
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology)Sunnybrook Research Institute, Sunnybrook HSC, University of TorontoTorontoOntarioCanada
| | - Anthony E. Lang
- Division of NeurologyDepartment of MedicineEdmond J Safra Program in Parkinson's Disease and Morton and Gloria Shulman Movement Disorders ClinicToronto Western HospitalUniversity of TorontoTorontoOntarioCanada
| | - Robert Bartha
- Department of Medical BiophysicsSchulich School of Medicine and Dentistry, Robarts Research Institute, Western UniversityLondonOntarioCanada
| | - Sandra E. Black
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology)Sunnybrook Research Institute, Sunnybrook HSC, University of TorontoTorontoOntarioCanada
| | - Mario Masellis
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Program, Department of Medicine (Neurology)Sunnybrook Research Institute, Sunnybrook HSC, University of TorontoTorontoOntarioCanada
| | - Robert A. Hegele
- Schulich School of Medicine and Dentistry, Western UniversityLondonOntarioCanada
- Robarts Research Institute, Western UniversityLondonOntarioCanada
| | - William McIlroy
- Neuroscience, Mobility and Balance Laboratory, Department of Kinesiology and Health SciencesUniversity of WaterlooWaterlooOntarioCanada
| | - ONDRI Investigators
- Research Team for Social Participation and Healthy AgingTokyo Metropolitan Institute for Geriatrics and GerontologyItabashi‐kuTokyoJapan
| | - Manuel Montero‐Odasso
- Gait & Brain Lab, St. Joseph' Health Care London, Lawson Health Research, Western University, Division of Geriatric MedicineLondonOntarioCanada
- Gait and Brain Lab, Division of Geriatric Medicineand Lawson Health Research InstituteParkwood Institute, Western UniversityLondonOntarioCanada
- Division of Geriatric MedicineDepartment of MedicineSchulich School of Medicine and Dentistry, Western University, Parkwood InstituteLondonOntarioCanada
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Ozzoude M, Varriano B, Beaton D, Ramirez J, Adamo S, Holmes MF, Scott CJM, Gao F, Sunderland KM, McLaughlin P, Goubran M, Kwan D, Roberts A, Bartha R, Symons S, Tan B, Swartz RH, Abrahao A, Saposnik G, Masellis M, Lang AE, Marras C, Zinman L, Shoesmith C, Borrie M, Fischer CE, Frank A, Freedman M, Montero-Odasso M, Kumar S, Pasternak S, Strother SC, Pollock BG, Rajji TK, Seitz D, Tang-Wai DF, Turnbull J, Dowlatshahi D, Hassan A, Casaubon L, Mandzia J, Sahlas D, Breen DP, Grimes D, Jog M, Steeves TDL, Arnott SR, Black SE, Finger E, Rabin J, Tartaglia MC. White matter hyperintensities and smaller cortical thickness are associated with neuropsychiatric symptoms in neurodegenerative and cerebrovascular diseases. Alzheimers Res Ther 2023; 15:114. [PMID: 37340319 PMCID: PMC10280981 DOI: 10.1186/s13195-023-01257-y] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Accepted: 06/01/2023] [Indexed: 06/22/2023]
Abstract
BACKGROUND Neuropsychiatric symptoms (NPS) are a core feature of most neurodegenerative and cerebrovascular diseases. White matter hyperintensities and brain atrophy have been implicated in NPS. We aimed to investigate the relative contribution of white matter hyperintensities and cortical thickness to NPS in participants across neurodegenerative and cerebrovascular diseases. METHODS Five hundred thirteen participants with one of these conditions, i.e. Alzheimer's Disease/Mild Cognitive Impairment, Amyotrophic Lateral Sclerosis, Frontotemporal Dementia, Parkinson's Disease, or Cerebrovascular Disease, were included in the study. NPS were assessed using the Neuropsychiatric Inventory - Questionnaire and grouped into hyperactivity, psychotic, affective, and apathy subsyndromes. White matter hyperintensities were quantified using a semi-automatic segmentation technique and FreeSurfer cortical thickness was used to measure regional grey matter loss. RESULTS Although NPS were frequent across the five disease groups, participants with frontotemporal dementia had the highest frequency of hyperactivity, apathy, and affective subsyndromes compared to other groups, whilst psychotic subsyndrome was high in both frontotemporal dementia and Parkinson's disease. Results from univariate and multivariate results showed that various predictors were associated with neuropsychiatric subsyndromes, especially cortical thickness in the inferior frontal, cingulate, and insula regions, sex(female), global cognition, and basal ganglia-thalamus white matter hyperintensities. CONCLUSIONS In participants with neurodegenerative and cerebrovascular diseases, our results suggest that smaller cortical thickness and white matter hyperintensity burden in several cortical-subcortical structures may contribute to the development of NPS. Further studies investigating the mechanisms that determine the progression of NPS in various neurodegenerative and cerebrovascular diseases are needed.
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Affiliation(s)
- Miracle Ozzoude
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 2S8, Canada
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Psychology, Faculty of Health, York University, Toronto, ON, Canada
| | - Brenda Varriano
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 2S8, Canada
- Central Michigan University College of Medicine, Mount Pleasant, MI, USA
| | - Derek Beaton
- Data Science & Advanced Analytic, St. Michael's Hospital, Toronto, ON, Canada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Sabrina Adamo
- Graduate Department of Psychological Clinical Science, University of Toronto Scarborough, Scarborough, ON, Canada
| | - Melissa F Holmes
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher J M Scott
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Fuqiang Gao
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | | | - Maged Goubran
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
- Queen's University, Kingston, ON, Canada
| | - Angela Roberts
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA
- School of Communication Sciences and Disorders, Faculty of Health Sciences, Western University, London, ON, Canada
| | - Robert Bartha
- Robarts Research Institute, Western University, London, ON, Canada
| | - Sean Symons
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Richard H Swartz
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Agessandro Abrahao
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Gustavo Saposnik
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Mario Masellis
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Anthony E Lang
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Edmond J Safra Program for Parkinson Disease, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Connie Marras
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Edmond J Safra Program for Parkinson Disease, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Lorne Zinman
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Christen Shoesmith
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Michael Borrie
- Robarts Research Institute, Western University, London, ON, Canada
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Corinne E Fischer
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada
| | - Andrew Frank
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada
- Bruyère Research Institute, Ottawa, ON, Canada
| | - Morris Freedman
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Division of Neurology, Baycrest Health Sciences, Toronto, ON, Canada
| | - Manuel Montero-Odasso
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Lawsone Health Research Institute, London, ON, Canada
- Gait and Brain Lab, Parkwood Institute, London, ON, Canada
| | - Sanjeev Kumar
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Stephen Pasternak
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Stephen C Strother
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Bruce G Pollock
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tarek K Rajji
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada
- Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada
| | - Dallas Seitz
- Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - David F Tang-Wai
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Memory Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - John Turnbull
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
- Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Dar Dowlatshahi
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, ON, Canada
| | - Leanne Casaubon
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
| | - Jennifer Mandzia
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- St. Joseph's Healthcare Centre, London, ON, Canada
| | - Demetrios Sahlas
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
- Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK
- Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK
- Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - David Grimes
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute, Ottawa, ON, Canada
| | - Mandar Jog
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
- London Health Sciences Centre, London, ON, Canada
| | - Thomas D L Steeves
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Stephen R Arnott
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Sandra E Black
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Jennifer Rabin
- Dr. Sandra Black Centre for Brain Resilience and Recovery, Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 2S8, Canada.
- Department of Medicine, Division of Neurology, University of Toronto, Toronto, ON, Canada.
- Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada.
- Memory Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.
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Otoki Y, Yu D, Shen Q, Sahlas DJ, Ramirez J, Gao F, Masellis M, Swartz RH, Chan PC, Pettersen JA, Kato S, Nakagawa K, Black SE, Swardfager W, Taha AY. Quantitative Lipidomic Analysis of Serum Phospholipids Reveals Dissociable Markers of Alzheimer's Disease and Subcortical Cerebrovascular Disease. J Alzheimers Dis 2023; 93:665-682. [PMID: 37092220 DOI: 10.3233/jad-220795] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
BACKGROUND Circulating phospholipid species have been shown to predict Alzheimer's disease (AD) prognosis but the link between phospholipid disturbances and subcortical small vessel cerebrovascular disease (CeVD) common in AD patients is not known. OBJECTIVE This study used quantitative lipidomics to measure serum diacyl, alkenyl (ether), alkyl, and lyso phospholipid species in individuals with extensive CeVD (n = 29), AD with minimal CeVD (n = 16), and AD with extensive CeVD (n = 14), and compared them to age-matched controls (n = 27). Memory was assessed using the California Verbal Learning Test. 3.0T MRI was used to assess hippocampal volume, atrophy, and white matter hyperintensity (WMH) volumes as manifestations of CeVD. RESULTS AD was associated with significantly higher concentrations of choline plasmalogen 18:0_18:1 and alkyl-phosphocholine 18:1. CeVD was associated with significantly lower lysophospholipids containing 16:0. Phospholipids containing arachidonic acid (AA) were associated with poorer memory in controls, whereas docosahexaenoic acid (DHA)-containing phospholipids were associated with better memory in individuals with AD+CeVD. In controls, DHA-containing phospholipids were associated with more atrophy and phospholipids containing linoleic acid and AA were associated with less atrophy. Lysophospholipids containing 16:0, 18:0, and 18:1 were correlated with less atrophy in controls, and of these, alkyl-phosphocholine 18:1 was correlated with smaller WMH volumes. Conversely, 16:0_18:1 choline plasmalogen was correlated with greater WMH volumes in controls. CONCLUSION This study demonstrates discernable differences in circulating phospholipids in individuals with AD and CeVD, as well as new associations between phospholipid species with memory and brain structure that were specific to contexts of commonly comorbid vascular and neurodegenerative pathologies.
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Affiliation(s)
- Yurika Otoki
- Department of Food Science and Technology, College of Agriculture and Environmental Sciences, University of California, Davis, CA, USA
- Laboratory of Food Function Analysis, Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi, Japan
| | - Di Yu
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, Canada
- Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, Canada
- LC Campbell Cognitive Neurology Unit, Sunnybrook Research Institute, Toronto, Canada
| | - Qing Shen
- Department of Food Science and Technology, College of Agriculture and Environmental Sciences, University of California, Davis, CA, USA
| | - Demetrios J Sahlas
- Department of Medicine (Neurology Division), McMaster University, Hamilton, Canada
| | - Joel Ramirez
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
| | - Fuqiang Gao
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
- Department of Medicine (Neurology Division) and the Northern Medical Program, University of British Columbia, Vancouver, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
| | - Pak Cheung Chan
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, Canada
- Department of Laboratory Medicine and Molecular Diagnostics, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Jacqueline A Pettersen
- Department of Medicine (Neurology Division) and the Northern Medical Program, University of British Columbia, Vancouver, Canada
| | - Shunji Kato
- Laboratory of Food Function Analysis, Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi, Japan
| | - Kiyotaka Nakagawa
- Laboratory of Food Function Analysis, Graduate School of Agricultural Science, Tohoku University, Sendai, Miyagi, Japan
| | - Sandra E Black
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
- Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, Canada
- LC Campbell Cognitive Neurology Unit, Sunnybrook Research Institute, Toronto, Canada
- Department of Medicine (Neurology Division), University of Toronto, Toronto, Canada
| | - Walter Swardfager
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, Toronto, Canada
- Department of Pharmacology & Toxicology, University of Toronto, Toronto, Canada
- Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, Toronto, Canada
- LC Campbell Cognitive Neurology Unit, Sunnybrook Research Institute, Toronto, Canada
- University Health Network Toronto Rehabilitation Institute, Toronto, Canada
| | - Ameer Y Taha
- Department of Food Science and Technology, College of Agriculture and Environmental Sciences, University of California, Davis, CA, USA
- West Coast Metabolomics Center, Genome Center, University of California - Davis, Davis, CA, USA
- Center for Neuroscience, University of California - Davis, Davis, CA, USA
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Ferris JK, Lo BP, Khlif MS, Brodtmann A, Boyd LA, Liew SL. Optimizing automated white matter hyperintensity segmentation in individuals with stroke. FRONTIERS IN NEUROIMAGING 2023; 2:1099301. [PMID: 37554631 PMCID: PMC10406248 DOI: 10.3389/fnimg.2023.1099301] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 11/15/2022] [Accepted: 02/15/2023] [Indexed: 08/10/2023]
Abstract
White matter hyperintensities (WMHs) are a risk factor for stroke. Consequently, many individuals who suffer a stroke have comorbid WMHs. The impact of WMHs on stroke recovery is an active area of research. Automated WMH segmentation methods are often employed as they require minimal user input and reduce risk of rater bias; however, these automated methods have not been specifically validated for use in individuals with stroke. Here, we present methodological validation of automated WMH segmentation methods in individuals with stroke. We first optimized parameters for FSL's publicly available WMH segmentation software BIANCA in two independent (multi-site) datasets. Our optimized BIANCA protocol achieved good performance within each independent dataset, when the BIANCA model was trained and tested in the same dataset or trained on mixed-sample data. BIANCA segmentation failed when generalizing a trained model to a new testing dataset. We therefore contrasted BIANCA's performance with SAMSEG, an unsupervised WMH segmentation tool available through FreeSurfer. SAMSEG does not require prior WMH masks for model training and was more robust to handling multi-site data. However, SAMSEG performance was slightly lower than BIANCA when data from a single site were tested. This manuscript will serve as a guide for the development and utilization of WMH analysis pipelines for individuals with stroke.
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Affiliation(s)
- Jennifer K. Ferris
- Graduate Program in Rehabilitation Sciences, University of British Columbia, Vancouver, BC, Canada
- Gerontology Research Centre, Simon Fraser University, Vancouver, BC, Canada
| | - Bethany P. Lo
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
| | - Mohamed Salah Khlif
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, VIC, Australia
| | - Amy Brodtmann
- Cognitive Health Initiative, Central Clinical School, Monash University, Melbourne, VIC, Australia
- Department of Medicine, Royal Melbourne Hospital, Melbourne, VIC, Australia
| | - Lara A. Boyd
- Graduate Program in Rehabilitation Sciences, University of British Columbia, Vancouver, BC, Canada
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia, Vancouver, BC, Canada
| | - Sook-Lei Liew
- Chan Division of Occupational Science and Occupational Therapy, University of Southern California, Los Angeles, CA, United States
- Department of Neurology, Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA, United States
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6
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Geng J, Gao F, Ramirez J, Honjo K, Holmes MF, Adamo S, Ozzoude M, Szilagyi GM, Scott CJM, Stebbins GT, Nyenhuis DL, Goubran M, Black SE. Secondary thalamic atrophy related to brain infarction may contribute to post-stroke cognitive impairment. J Stroke Cerebrovasc Dis 2023; 32:106895. [PMID: 36495644 DOI: 10.1016/j.jstrokecerebrovasdis.2022.106895] [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: 07/27/2022] [Revised: 10/24/2022] [Accepted: 11/10/2022] [Indexed: 12/13/2022] Open
Abstract
BACKGROUND AND PURPOSE The thalamus is a key brain hub that is globally connected to many cortical regions. Previous work highlights thalamic contributions to multiple cognitive functions, but few studies have measured thalamic volume changes or cognitive correlates. This study investigates associations between thalamic volumes and post-stroke cognitive function. METHODS Participants with non-thalamic brain infarcts (3-42 months) underwent MRI and cognitive testing. Focal infarcts and thalami were traced manually. In cases with bilateral infarcts, the side of the primary infarct volume defined the hemisphere involved. Brain parcellation and volumetrics were extracted using a standardized and previously validated neuroimaging pipeline. Age and gender-matched healthy controls provided normal comparative thalamic volumes. Thalamic atrophy was considered when the volume exceeded 2 standard deviations greater than the controls. RESULTS Thalamic volumes ipsilateral to the infarct in stroke patients (n=55) were smaller than left (4.4 ± 1.4 vs. 5.4 ± 0.5 cc, p < 0.001) and right (4.4 ± 1.4 vs. 5.5 ± 0.6 cc, p < 0.001) thalamic volumes in the controls. After controlling for head-size and global brain atrophy, infarct volume independently correlated with ipsilateral thalamic volume (β= -0.069, p=0.024). Left thalamic atrophy correlated significantly with poorer cognitive performance (β = 4.177, p = 0.008), after controlling for demographics and infarct volumes. CONCLUSIONS Our results suggest that the remote effect of infarction on ipsilateral thalamic volume is associated with global post-stroke cognitive impairment.
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Affiliation(s)
- Jieli Geng
- Department of Neurology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Fuqiang Gao
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada; Heart and Stroke Foundation Canadian Partnership for Stroke Recovery (Sunnybrook site), Toronto, Ontario, Canada
| | - Kie Honjo
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada; Heart and Stroke Foundation Canadian Partnership for Stroke Recovery (Sunnybrook site), Toronto, Ontario, Canada
| | - Melissa F Holmes
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
| | - Sabrina Adamo
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
| | - Miracle Ozzoude
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
| | - Gregory M Szilagyi
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
| | - Christopher J M Scott
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada
| | - Glen T Stebbins
- Department of Neurological Sciences, Rush University Medical Center, Chicago, IL, USA
| | - David L Nyenhuis
- Hauenstein Neuroscience Center, Saint Mary's Health Care, Grand Rapids, MI, USA; LCC International University
| | - Maged Goubran
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada; Heart and Stroke Foundation Canadian Partnership for Stroke Recovery (Sunnybrook site), Toronto, Ontario, Canada; Department of Medical Biophysics, University of Toronto, Ontario, Canada
| | - Sandra E Black
- LC Campbell Cognitive Neurology, Dr. Sandra Black Centre for Brain Resilience & Recovery, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Ontario, Canada; Heart and Stroke Foundation Canadian Partnership for Stroke Recovery (Sunnybrook site), Toronto, Ontario, Canada; Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Ontario, Canada.
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7
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Haddad SMH, Scott CJM, Ozzoude M, Berezuk C, Holmes M, Adamo S, Ramirez J, Arnott SR, Nanayakkara ND, Binns M, Beaton D, Lou W, Sunderland K, Sujanthan S, Lawrence J, Kwan D, Tan B, Casaubon L, Mandzia J, Sahlas D, Saposnik G, Hassan A, Levine B, McLaughlin P, Orange JB, Roberts A, Troyer A, Black SE, Dowlatshahi D, Strother SC, Swartz RH, Symons S, Montero-Odasso M, ONDRI Investigators, Bartha R. Comparison of Diffusion Tensor Imaging Metrics in Normal-Appearing White Matter to Cerebrovascular Lesions and Correlation with Cerebrovascular Disease Risk Factors and Severity. Int J Biomed Imaging 2022; 2022:5860364. [PMID: 36313789 PMCID: PMC9616672 DOI: 10.1155/2022/5860364] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2021] [Revised: 04/21/2022] [Accepted: 06/01/2022] [Indexed: 11/13/2023] Open
Abstract
Alterations in tissue microstructure in normal-appearing white matter (NAWM), specifically measured by diffusion tensor imaging (DTI) fractional anisotropy (FA), have been associated with cognitive outcomes following stroke. The purpose of this study was to comprehensively compare conventional DTI measures of tissue microstructure in NAWM to diverse vascular brain lesions in people with cerebrovascular disease (CVD) and to examine associations between FA in NAWM and cerebrovascular risk factors. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were measured in cerebral tissues and cerebrovascular anomalies from 152 people with CVD participating in the Ontario Neurodegenerative Disease Research Initiative (ONDRI). Ten cerebral tissue types were segmented including NAWM, and vascular lesions including stroke, periventricular and deep white matter hyperintensities, periventricular and deep lacunar infarcts, and perivascular spaces (PVS) using T1-weighted, proton density-weighted, T2-weighted, and fluid attenuated inversion recovery MRI scans. Mean DTI metrics were measured in each tissue region using a previously developed DTI processing pipeline and compared between tissues using multivariate analysis of covariance. Associations between FA in NAWM and several CVD risk factors were also examined. DTI metrics in vascular lesions differed significantly from healthy tissue. Specifically, all tissue types had significantly different MD values, while FA was also found to be different in most tissue types. FA in NAWM was inversely related to hypertension and modified Rankin scale (mRS). This study demonstrated the differences between conventional DTI metrics, FA, MD, AD, and RD, in cerebral vascular lesions and healthy tissue types. Therefore, incorporating DTI to characterize the integrity of the tissue microstructure could help to define the extent and severity of various brain vascular anomalies. The association between FA within NAWM and clinical evaluation of hypertension and disability provides further evidence that white matter microstructural integrity is impacted by cerebrovascular function.
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Affiliation(s)
- Seyyed M. H. Haddad
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Canada
| | - Christopher J. M. Scott
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | - Miracle Ozzoude
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | | | - Melissa Holmes
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | - Sabrina Adamo
- Clinical Neurosciences, University of Toronto, Toronto, Canada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
| | - Stephen R. Arnott
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Nuwan D. Nanayakkara
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Canada
| | - Malcolm Binns
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Derek Beaton
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Wendy Lou
- Dalla Lana School of Public Health, University of Toronto, Toronto, Canada
| | - Kelly Sunderland
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | | | - Jane Lawrence
- Thunder Bay Regional Health Research Institute, Thunder Bay, Canada
| | | | - Brian Tan
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Leanne Casaubon
- Department of Medicine, University of Toronto, Toronto, Canada
| | - Jennifer Mandzia
- Department of Medicine, Division of Neurology, University of Western Ontario, London, Canada
| | - Demetrios Sahlas
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, Canada
| | | | - Ayman Hassan
- Thunder Bay Regional Research Institute, Thunder Bay, Canada
| | - Brian Levine
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | | | - J. B. Orange
- School of Communication Sciences and Disorders, Western University, London, Canada
| | - Angela Roberts
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorder, Northwestern University, Evanston, USA
| | - Angela Troyer
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
| | - Sandra E. Black
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, Ontario, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, Canada
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Sunnybrook Health Sciences Centre, University of Toronto, Stroke Research Program, Toronto, Canada
| | | | - Stephen C. Strother
- Rotman Research Institute, Baycrest Health Sciences, Toronto, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Canada
| | - Richard H. Swartz
- Sunnybrook Health Sciences Centre, University of Toronto, Stroke Research Program, Toronto, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Manuel Montero-Odasso
- Department of Medicine, Division of Geriatric Medicine, Parkwood Hospital, St. Joseph's Health Care London, London, Canada
| | - ONDRI Investigators
- Ontario Neurodegenerative Disease Initiative, Ontario Brain Institute, Toronto, Canada
| | - Robert Bartha
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Canada
- Department of Medical Biophysics, University of Western Ontario, London, Canada
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8
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Han J, Kim MN, Lee HW, Jeong SY, Lee SW, Yoon U, Kang K. Distinct volumetric features of cerebrospinal fluid distribution in idiopathic normal-pressure hydrocephalus and Alzheimer's disease. Fluids Barriers CNS 2022; 19:66. [PMID: 36045420 PMCID: PMC9434899 DOI: 10.1186/s12987-022-00362-8] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/04/2022] [Accepted: 07/13/2022] [Indexed: 12/04/2022] Open
Abstract
Objective The aims of the study were to measure the cerebrospinal fluid (CSF) volumes in the lateral ventricle, high-convexity subarachnoid space, and Sylvian fissure region in patients with idiopathic normal-pressure hydrocephalus (INPH) and Alzheimer’s disease (AD), and to evaluate differences in these volumes between INPH and AD groups and healthy controls. Methods Forty-nine INPH patients, 59 AD patients, and 26 healthy controls were imaged with automated three-dimensional volumetric MRI. Results INPH patients had larger lateral ventricles and CSF spaces of the Sylvian fissure region and smaller high-convexity subarachnoid spaces than other groups, and AD patients had larger lateral ventricles and CSF spaces of the Sylvian fissure region than the control group. The INPH group showed a negative correlation between lateral ventricle and high-convexity subarachnoid space volumes, while the AD group showed a positive correlation between lateral ventricle volume and volume for CSF spaces of the Sylvian fissure region. The ratio of lateral ventricle to high-convexity subarachnoid space volumes yielded an area under the curve of 0.990, differentiating INPH from AD. Conclusions Associations between CSF volumes suggest that there might be different mechanisms between INPH and AD to explain their respective lateral ventricular dilations. The ratio of lateral ventricle to high-convexity subarachnoid space volumes distinguishes INPH from AD with good diagnostic sensitivity and specificity. We propose to refer to this ratio as the VOSS (ventricle over subarachnoid space) index.
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Affiliation(s)
- Jaehwan Han
- Department of Biomedical Engineering, School of Medicine, Kyungpook National University, Daegu, South Korea
| | - Myoung Nam Kim
- Department of Biomedical Engineering, School of Medicine, Kyungpook National University, Daegu, South Korea
| | - Ho-Won Lee
- Department of Neurology, School of Medicine, Kyungpook National University, 680 Gukchaebosang-ro, Jung-gu, Daegu, 41944, South Korea.,Brain Science and Engineering Institute, Kyungpook National University, Daegu, South Korea
| | - Shin Young Jeong
- Department of Nuclear Medicine, School of Medicine, Kyungpook National University, Daegu, South Korea
| | - Sang-Woo Lee
- Department of Nuclear Medicine, School of Medicine, Kyungpook National University, Daegu, South Korea
| | - Uicheul Yoon
- Department of Biomedical Engineering, Daegu Catholic University, 13-13 Hayang- ro, Hayang-eup, Gyeongsan, Gyeongbuk, 38430, South Korea.
| | - Kyunghun Kang
- Department of Neurology, School of Medicine, Kyungpook National University, 680 Gukchaebosang-ro, Jung-gu, Daegu, 41944, South Korea.
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9
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Ferris J, Greeley B, Yeganeh NM, Rinat S, Ramirez J, Black S, Boyd L. Exploring biomarkers of processing speed and executive function: The role of the anterior thalamic radiations. Neuroimage Clin 2022; 36:103174. [PMID: 36067614 PMCID: PMC9460835 DOI: 10.1016/j.nicl.2022.103174] [Citation(s) in RCA: 10] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2022] [Revised: 08/08/2022] [Accepted: 08/27/2022] [Indexed: 12/14/2022]
Abstract
INTRODUCTION Processing speed and executive function are often impaired after stroke and in typical aging. However, there are no reliable neurological markers of these cognitive impairments. The trail making test (TMT) is a common index of processing speed and executive function. Here, we tested candidate MRI markers of TMT performance in a cohort of older adults and individuals with chronic stroke. METHODS In 61 older adults and 32 individuals with chronic stroke, we indexed white matter structure with region-specific lesion load (of white matter hyperintensities (WMHs) and stroke lesions) and diffusion tensor imaging (DTI) from four regions related to TMT performance: the anterior thalamic radiations (ATR), superior longitudinal fasciculus (SLF), forceps minor, and cholinergic pathways. Regression modelling was used to identify the marker(s) that explained the most variance in TMT performance. RESULTS DTI metrics of the ATR related to processing speed in both the older adult (TMT A: β = -3.431, p < 0.001) and chronic stroke (TMT A: β = 11.282, p < 0.001) groups. In the chronic stroke group executive function was best predicted by a combination of ATR and forceps minor DTI metrics (TMT B: adjustedR2 = 0.438, p < 0.001); no significant predictors of executive function (TMT B) emerged in the older adult group. No imaging metrics related to set shifting (TMT B-A). Regional DTI metrics predicted TMT performance above and beyond whole-brain stroke and WMH volumes and removing whole-brain lesion volumes improved model fits. CONCLUSIONS In this comprehensive assessment of candidate imaging markers, we demonstrate an association between ATR microstructure and processing speed and executive function performance. Regional DTI metrics provided better predictors of cognitive performance than whole-brain lesion volumes or regional lesion load, emphasizing the importance of lesion location in understanding cognition. We propose ATR DTI metrics as novel candidate imaging biomarker of post-stroke cognitive impairment.
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Affiliation(s)
- Jennifer Ferris
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada,Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada
| | - Brian Greeley
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada
| | - Negin Motamed Yeganeh
- Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada
| | - Shie Rinat
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada,Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery, Toronto, Canada,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Sandra Black
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery, Toronto, Canada,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Canada
| | - Lara Boyd
- Department of Physical Therapy, University of British Columbia, Vancouver, Canada,Graduate Programs in Rehabilitation Sciences, University of British Columbia, Vancouver, Canada,Djavad Mowafaghian Centre for Brain Health, University of British Columbia, Vancouver, Canada,Corresponding author at: University of British Columbia, 212-2177 Wesbrook Mall, Vancouver, British Columbia V6T 2B5, Canada.
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10
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Nanayakkara ND, Arnott SR, Scott CJM, Solovey I, Liang S, Fonov VS, Gee T, Broberg DN, Haddad SMH, Ramirez J, Berezuk C, Holmes M, Adamo S, Ozzoude M, Theyers A, Sujanthan S, Zamyadi M, Casaubon L, Dowlatshahi D, Mandzia J, Sahlas D, Saposnik G, Hassan A, Swartz RH, Strother SC, Szilagyi GM, Black SE, Symons S, Investigators ONDRI, Bartha R. Increased brain volumetric measurement precision from multi-site 3D T1-weighted 3 T magnetic resonance imaging by correcting geometric distortions. Magn Reson Imaging 2022; 92:150-160. [PMID: 35753643 DOI: 10.1016/j.mri.2022.06.005] [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: 06/27/2021] [Revised: 04/29/2022] [Accepted: 06/19/2022] [Indexed: 11/16/2022]
Abstract
PURPOSE Magnetic resonance imaging (MRI) scanner-specific geometric distortions may contribute to scanner induced variability and decrease volumetric measurement precision for multi-site studies. The purpose of this study was to determine whether geometric distortion correction increases the precision of brain volumetric measurements in a multi-site multi-scanner study. METHODS Geometric distortion variation was quantified over a one-year period at 10 sites using the distortion fields estimated from monthly 3D T1-weighted MRI geometrical phantom scans. The variability of volume and distance measurements were quantified using synthetic volumes and a standard quantitative MRI (qMRI) phantom. The effects of geometric distortion corrections on MRI derived volumetric measurements of the human brain were assessed in two subjects scanned on each of the 10 MRI scanners and in 150 subjects with cerebrovascaular disease (CVD) acquired across imaging sites. RESULTS Geometric distortions were found to vary substantially between different MRI scanners but were relatively stable on each scanner over a one-year interval. Geometric distortions varied spatially, increasing in severity with distance from the magnet isocenter. In measurements made with the qMRI phantom, the geometric distortion correction decreased the standard deviation of volumetric assessments by 35% and distance measurements by 42%. The average coefficient of variance decreased by 16% in gray matter and white matter volume estimates in the two subjects scanned on the 10 MRI scanners. CONCLUSION Geometric distortion correction using an up-to-date correction field is recommended to increase precision in volumetric measurements made from MRI images.
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Affiliation(s)
- Nuwan D Nanayakkara
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Christopher J M Scott
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Igor Solovey
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Shuai Liang
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
| | - Vladimir S Fonov
- Montreal Neurological Institute, McGill University, Montreal, Quebec, Canada
| | - Tom Gee
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
| | - Dana N Broberg
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Seyyed M H Haddad
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Joel Ramirez
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Courtney Berezuk
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Melissa Holmes
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Sabrina Adamo
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Miracle Ozzoude
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Athena Theyers
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
| | | | - Mojdeh Zamyadi
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
| | - Leanne Casaubon
- Department of Medicine, University of Toronto, Toronto, ON, Canada
| | | | - Jennifer Mandzia
- Department of Medicine, Division of Neurology, Western University, London, ON, Canada
| | - Demetrios Sahlas
- Department of Medicine, Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada
| | | | - Ayman Hassan
- Thunder Bay Regional Research Institute, Thunder Bay, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Stephen C Strother
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada; Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Gregory M Szilagyi
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Sean Symons
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | | | - Robert Bartha
- Robarts Research Institute, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada; Departments of Medical Biophysics, Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.
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11
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Ferris JK, Greeley B, Vavasour IM, Kraeutner SN, Rinat S, Ramirez J, Black SE, Boyd LA. In vivo myelin imaging and tissue microstructure in white matter hyperintensities and perilesional white matter. Brain Commun 2022; 4:fcac142. [PMID: 35694147 PMCID: PMC9178967 DOI: 10.1093/braincomms/fcac142] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2022] [Revised: 03/28/2022] [Accepted: 05/26/2022] [Indexed: 11/12/2022] Open
Abstract
White matter hyperintensities negatively impact white matter structure and relate to cognitive decline in aging. Diffusion tensor imaging detects changes to white matter microstructure, both within the white matter hyperintensity and extending into surrounding (perilesional) normal-appearing white matter. However, diffusion tensor imaging markers are not specific to tissue components, complicating the interpretation of previous microstructural findings. Myelin water imaging is a novel imaging technique that provides specific markers of myelin content (myelin water fraction) and interstitial fluid (geometric mean T2). Here we combined diffusion tensor imaging and myelin water imaging to examine tissue characteristics in white matter hyperintensities and perilesional white matter in 80 individuals (47 older adults and 33 individuals with chronic stroke). To measure perilesional normal-appearing white matter, white matter hyperintensity masks were dilated in 2 mm segments up to 10 mm in distance from the white matter hyperintensity. Fractional anisotropy, mean diffusivity, myelin water fraction, and geometric mean T2 were extracted from white matter hyperintensities and perilesional white matter. We observed a spatial gradient of higher mean diffusivity and geometric mean T2, and lower fractional anisotropy, in the white matter hyperintensity and perilesional white matter. In the chronic stroke group, myelin water fraction was reduced in the white matter hyperintensity but did not show a spatial gradient in perilesional white matter. Across the entire sample, white matter metrics within the white matter hyperintensity related to whole-brain white matter hyperintensity volume; with increasing white matter hyperintensity volume there was increased mean diffusivity and geometric mean T2, and decreased myelin water fraction in the white matter hyperintensity. Normal-appearing white matter adjacent to white matter hyperintensities exhibits characteristics of a transitional stage between healthy white matter and white matter hyperintensities. This effect was observed in markers sensitive to interstitial fluid, but not in myelin water fraction, the specific marker of myelin concentration. Within the white matter hyperintensity, interstitial fluid was higher and myelin concentration was lower in individuals with more severe cerebrovascular disease. Our data suggests white matter hyperintensities have penumbra-like effects in perilesional white matter that specifically reflect increased interstitial fluid, with no changes to myelin concentration. In contrast, within the white matter hyperintensity there are varying levels of demyelination, which vary based on the severity of cerebrovascular disease. Diffusion tensor imaging and myelin imaging may be useful clinical markers to predict white matter hyperintensity formation, and to stage neuronal damage within white matter hyperintensities.
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Affiliation(s)
- Jennifer K. Ferris
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
| | - Brian Greeley
- University of British Columbia Department of Physical Therapy, , Vancouver, Canada
| | - Irene M. Vavasour
- The University of British Columbia Department of Radiology, , Vancouver, Canada
- University of British Columbia UBC MRI Research Centre, Faculty of Medicine, , Vancouver, Canada
| | - Sarah N. Kraeutner
- University of British Columbia Department of Psychology, , Okanagan, Kelowna, Canada
| | - Shie Rinat
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
| | - Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery , Toronto, Canada
- Sunnybrook Research Institute, University of Toronto Hurvitz Brain Sciences Research Program, , Toronto, Canada
| | - Sandra E. Black
- LC Campbell Cognitive Neurology Research Unit, Dr Sandra Black Centre for Brain Resilience and Recovery , Toronto, Canada
- Sunnybrook Research Institute, University of Toronto Hurvitz Brain Sciences Research Program, , Toronto, Canada
| | - Lara A. Boyd
- University of British Columbia Graduate Programs in Rehabilitation Sciences, , Vancouver, Canada
- University of British Columbia Department of Physical Therapy, , Vancouver, Canada
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12
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Callahan BL, Ramakrishnan N, Shammi P, Bierstone D, Taylor R, Ozzoude M, Goubran M, Stuss DT, Black SE. Cognitive and Neuroimaging Profiles of Older Adults With Attention Deficit/Hyperactivity Disorder Presenting to a Memory Clinic. J Atten Disord 2022; 26:1118-1129. [PMID: 34784815 PMCID: PMC9066671 DOI: 10.1177/10870547211060546] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
OBJECTIVE Some features of attention-deficit/hyperactivity disorder (ADHD) may resemble those of mild cognitive impairment (MCI) in older adults, contributing to diagnostic uncertainty in individuals seeking assessment in memory clinics. We systematically compared cognition and brain structure in ADHD and MCI to clarify the extent of overlap and identify potential features unique to each. METHOD Older adults from a Cognitive Neurology clinic (40 ADHD, 29 MCI, 37 controls) underwent neuropsychological assessment. A subsample (n = 80) underwent structural neuroimaging. RESULTS Memory was impaired in both patient groups, but reflected a storage deficit in MCI (supported by relatively smaller hippocampi) and an encoding deficit in ADHD (supported by frontal lobe thinning). Both groups displayed normal executive functioning. Semantic retrieval was uniquely impaired in MCI. CONCLUSION Although ADHD has been proposed as a dementia risk factor or prodrome, we propose it is rather a pathophysiologically-unique phenotypic mimic acting via overlap in memory and executive performance.
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Affiliation(s)
- Brandy L. Callahan
- University of Calgary, Calgary, AB, Canada
- Hotchkiss Brain Institute, Calgary, AB, Canada
- Brandy Callahan, RPsych. Department of Psychology, Hotchkiss Brain Institute, University of Calgary, 2500 University Drive NW, Calgary, AB T2N 1N4, Canada.
| | | | | | - Daniel Bierstone
- University of Toronto, Toronto, ON, Canada
- Children’s Hospital of Eastern Ontario, Ottawa, ON, Canada
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13
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Ozzoude M, Varriano B, Beaton D, Ramirez J, Holmes MF, Scott CJM, Gao F, Sunderland KM, McLaughlin P, Rabin J, Goubran M, Kwan D, Roberts A, Bartha R, Symons S, Tan B, Swartz RH, Abrahao A, Saposnik G, Masellis M, Lang AE, Marras C, Zinman L, Shoesmith C, Borrie M, Fischer CE, Frank A, Freedman M, Montero-Odasso M, Kumar S, Pasternak S, Strother SC, Pollock BG, Rajji TK, Seitz D, Tang-Wai DF, Turnbull J, Dowlatshahi D, Hassan A, Casaubon L, Mandzia J, Sahlas D, Breen DP, Grimes D, Jog M, Steeves TDL, Arnott SR, Black SE, Finger E, Tartaglia MC. Investigating the contribution of white matter hyperintensities and cortical thickness to empathy in neurodegenerative and cerebrovascular diseases. GeroScience 2022; 44:1575-1598. [PMID: 35294697 DOI: 10.1007/s11357-022-00539-x] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 02/22/2022] [Indexed: 11/24/2022] Open
Abstract
Change in empathy is an increasingly recognised symptom of neurodegenerative diseases and contributes to caregiver burden and patient distress. Empathy impairment has been associated with brain atrophy but its relationship to white matter hyperintensities (WMH) is unknown. We aimed to investigate the relationships amongst WMH, brain atrophy, and empathy deficits in neurodegenerative and cerebrovascular diseases. Five hundred thirteen participants with Alzheimer's disease/mild cognitive impairment, amyotrophic lateral sclerosis, frontotemporal dementia (FTD), Parkinson's disease, or cerebrovascular disease (CVD) were included. Empathy was assessed using the Interpersonal Reactivity Index. WMH were measured using a semi-automatic segmentation and FreeSurfer was used to measure cortical thickness. A heterogeneous pattern of cortical thinning was found between groups, with FTD showing thinning in frontotemporal regions and CVD in left superior parietal, left insula, and left postcentral. Results from both univariate and multivariate analyses revealed that several variables were associated with empathy, particularly cortical thickness in the fronto-insulo-temporal and cingulate regions, sex (female), global cognition, and right parietal and occipital WMH. Our results suggest that cortical atrophy and WMH may be associated with empathy deficits in neurodegenerative and cerebrovascular diseases. Future work should consider investigating the longitudinal effects of WMH and atrophy on empathy deficits in neurodegenerative and cerebrovascular diseases.
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Affiliation(s)
- Miracle Ozzoude
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 0S8, Canada.,L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Brenda Varriano
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 0S8, Canada
| | - Derek Beaton
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Melissa F Holmes
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Christopher J M Scott
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Fuqiang Gao
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | | | - Paula McLaughlin
- Nova Scotia Health and Dalhousie University, Halifax, NS, Canada
| | - Jennifer Rabin
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Donna Kwan
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada.,Queen's University, Kingston, ON, Canada
| | - Angela Roberts
- Roxelyn and Richard Pepper Department of Communication Sciences and Disorders, Northwestern University, Evanston, IL, USA.,School of Communication Sciences and Disorders, Faculty of Health Sciences, Western University, London, ON, Canada
| | - Robert Bartha
- Robarts Research Institute, Western University, London, ON, Canada
| | - Sean Symons
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Brian Tan
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Agessandro Abrahao
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Harquail Centre for Neuromodulation, Hurvitz Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Gustavo Saposnik
- Li Ka Shing Knowledge Institute, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Mario Masellis
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Anthony E Lang
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Edmond J Safra Program for Parkinson Disease, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Connie Marras
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Edmond J Safra Program for Parkinson Disease, Movement Disorder Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - Lorne Zinman
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Christen Shoesmith
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Michael Borrie
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,St. Joseph's Healthcare Centre, London, ON, Canada
| | - Corinne E Fischer
- Keenan Research Centre for Biomedical Science, St. Michael's Hospital, Toronto, ON, Canada
| | - Andrew Frank
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, ON, Canada.,Bruyère Research Institute, Ottawa, ON, Canada
| | - Morris Freedman
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Baycrest Health Sciences, Toronto, ON, Canada
| | - Manuel Montero-Odasso
- Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,Lawson Health Research Institute, London, ON, Canada.,Gait and Brain Lab, Parkwood Institute, London, ON, Canada
| | - Sanjeev Kumar
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Stephen Pasternak
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada
| | - Stephen C Strother
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Bruce G Pollock
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada
| | - Tarek K Rajji
- Department of Psychiatry, University of Toronto, Toronto, ON, Canada.,Adult Neurodevelopment and Geriatric Psychiatry, Centre for Addiction and Mental Health, Toronto, ON, Canada.,Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada
| | - Dallas Seitz
- Cumming School of Medicine, University of Calgary, Calgary, AB, Canada
| | - David F Tang-Wai
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada.,Memory Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada
| | - John Turnbull
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.,Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - Dar Dowlatshahi
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Ayman Hassan
- Thunder Bay Regional Health Research Institute, Thunder Bay, ON, Canada
| | - Leanne Casaubon
- Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada
| | - Jennifer Mandzia
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | - Demetrios Sahlas
- Faculty of Health Sciences, McMaster University, Hamilton, ON, Canada.,Department of Medicine, McMaster University, Hamilton, ON, Canada
| | - David P Breen
- Centre for Clinical Brain Sciences, University of Edinburgh, Edinburgh, UK.,Anne Rowling Regenerative Neurology Clinic, University of Edinburgh, Edinburgh, UK.,Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, Edinburgh, UK
| | - David Grimes
- Department of Medicine (Neurology), University of Ottawa Brain and Mind Research Institute and Ottawa Hospital Research Institute, Ottawa, ON, Canada
| | - Mandar Jog
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Schulich School of Medicine and Dentistry, Western University, London, ON, Canada.,London Health Sciences Centre, London, ON, Canada
| | - Thomas D L Steeves
- Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Stephen R Arnott
- Rotman Research Institute of Baycrest Centre, Toronto, ON, Canada
| | - Sandra E Black
- L.C. Campbell Cognitive Neurology Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada.,Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Toronto Dementia Research Alliance, University of Toronto, Toronto, ON, Canada.,Division of Neurology, Department of Medicine, St. Michael's Hospital, University of Toronto, Toronto, ON, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, Western University, London, ON, Canada.,Schulich School of Medicine and Dentistry, Western University, London, ON, Canada
| | | | - Maria Carmela Tartaglia
- Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, Krembil Discovery Tower, 60 Leonard Avenue, 6th floor 6KD-407, Toronto, ON, M5T 0S8, Canada. .,Division of Neurology, Department of Medicine, University of Toronto, Toronto, ON, Canada. .,Memory Clinic, Toronto Western Hospital, University Health Network, Toronto, ON, Canada.
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14
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Sapkota S, McFall GP, Masellis M, Dixon RA, Black SE. Differential Cognitive Decline in Alzheimer's Disease Is Predicted by Changes in Ventricular Size but Moderated by Apolipoprotein E and Pulse Pressure. J Alzheimers Dis 2021; 85:545-560. [PMID: 34864669 DOI: 10.3233/jad-215068] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Differential cognitive trajectories in Alzheimer's disease (AD) may be predicted by biomarkers from multiple domains. OBJECTIVE In a longitudinal sample of AD and AD-related dementias patients (n = 312), we tested whether 1) change in brain morphometry (ventricular enlargement) predicts differential cognitive trajectories, 2) further risk is contributed by genetic (Apolipoprotein E [APOE] ɛ4+) and vascular (pulse pressure [PP]) factors separately, and 3) the genetic + vascular risk moderates this pattern. METHODS We applied a dynamic computational approach (parallel process models) to test both concurrent and change-related associations between predictor (ventricular size) and cognition (executive function [EF]/attention). We then tested these associations as stratified by APOE (ɛ4-/ɛ4+), PP (low/high), and APOE+ PP (low/intermediate/high) risk. RESULTS First, concurrently, higher ventricular size predicted lower EF/attention performance and, longitudinally, increasing ventricular size predicted steeper EF/attention decline. Second, concurrently, higher ventricular size predicted lower EF/attention performance selectively in APOEɛ4+ carriers, and longitudinally, increasing ventricular size predicted steeper EF/attention decline selectively in the low PP group. Third, ventricular size and EF/attention associations were absent in the high APOE+ PP risk group both concurrently and longitudinally. CONCLUSION As AD progresses, a threshold effect may be present in which ventricular enlargement in the context of exacerbated APOE+ PP risk does not produce further cognitive decline.
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Affiliation(s)
- Shraddha Sapkota
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - G Peggy McFall
- Department of Psychology (Science), University of Alberta, Edmonton, AB, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada
| | - Roger A Dixon
- Department of Psychology (Science), University of Alberta, Edmonton, AB, Canada.,Neuroscience and Mental Health Institute, University of Alberta, Edmonton, AB, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.,Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada
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15
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Sapkota S, Ramirez J, Yhap V, Masellis M, Black SE. Brain atrophy trajectories predict differential functional performance in Alzheimer's disease: Moderations with apolipoprotein E and sex. ALZHEIMER'S & DEMENTIA (AMSTERDAM, NETHERLANDS) 2021; 13:e12244. [PMID: 34692981 PMCID: PMC8515221 DOI: 10.1002/dad2.12244] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/23/2021] [Accepted: 08/09/2021] [Indexed: 12/30/2022]
Abstract
INTRODUCTION We examine whether distinct brain atrophy patterns (using brain parenchymal fraction [BPF]) differentially predict functional performance and decline in Alzheimer's disease (AD), and are independently moderated by (1) a key AD genetic risk marker (apolipoprotein E [APOE]), (2) sex, and (3) high-risk group (women APOE ɛ4 carriers). METHODS We used a 2-year longitudinal sample of AD patients (baseline N = 170; mean age = 71.3 [9.1] years) from the Sunnybrook Dementia Study. We applied latent class analysis, latent growth modeling, and path analysis. We aimed to replicate our findings (N = 184) in the Alzheimer's Disease Neuroimaging Initiative. RESULTS We observed that high brain atrophy class predicted lower functional performance and steeper decline. This association was moderated by APOE, sex, and high-risk group. Baseline findings as moderated by APOE and high-risk group were replicated. DISCUSSION Women APOE ɛ4 carriers may selectively be at a greater risk of functional impairment with higher brain atrophy.
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Affiliation(s)
- Shraddha Sapkota
- Hurvitz Brain Sciences Research ProgramSunnybrook Research InstituteSunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Joel Ramirez
- Hurvitz Brain Sciences Research ProgramSunnybrook Research InstituteSunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Vanessa Yhap
- Hurvitz Brain Sciences Research ProgramSunnybrook Research InstituteSunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Mario Masellis
- Hurvitz Brain Sciences Research ProgramSunnybrook Research InstituteSunnybrook Health Sciences CentreTorontoOntarioCanada
- Department of Medicine (Neurology)University of TorontoTorontoOntarioCanada
| | - Sandra E. Black
- Hurvitz Brain Sciences Research ProgramSunnybrook Research InstituteSunnybrook Health Sciences CentreTorontoOntarioCanada
- Department of Medicine (Neurology)University of TorontoTorontoOntarioCanada
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16
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Ramirez J, Holmes MF, Scott CJM, Ozzoude M, Adamo S, Szilagyi GM, Goubran M, Gao F, Arnott SR, Lawrence-Dewar JM, Beaton D, Strother SC, Munoz DP, Masellis M, Swartz RH, Bartha R, Symons S, Black SE. Ontario Neurodegenerative Disease Research Initiative (ONDRI): Structural MRI Methods and Outcome Measures. Front Neurol 2020; 11:847. [PMID: 32849254 PMCID: PMC7431907 DOI: 10.3389/fneur.2020.00847] [Citation(s) in RCA: 23] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2020] [Accepted: 07/07/2020] [Indexed: 01/18/2023] Open
Abstract
The Ontario Neurodegenerative Research Initiative (ONDRI) is a 3 years multi-site prospective cohort study that has acquired comprehensive multiple assessment platform data, including 3T structural MRI, from neurodegenerative patients with Alzheimer's disease, mild cognitive impairment, Parkinson's disease, amyotrophic lateral sclerosis, frontotemporal dementia, and cerebrovascular disease. This heterogeneous cross-section of patients with complex neurodegenerative and neurovascular pathologies pose significant challenges for standard neuroimaging tools. To effectively quantify regional measures of normal and pathological brain tissue volumes, the ONDRI neuroimaging platform implemented a semi-automated MRI processing pipeline that was able to address many of the challenges resulting from this heterogeneity. The purpose of this paper is to serve as a reference and conceptual overview of the comprehensive neuroimaging pipeline used to generate regional brain tissue volumes and neurovascular marker data that will be made publicly available online.
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Affiliation(s)
- Joel Ramirez
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Melissa F Holmes
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Christopher J M Scott
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Miracle Ozzoude
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Sabrina Adamo
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Gregory M Szilagyi
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Maged Goubran
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Fuqiang Gao
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | | | | | - Derek Beaton
- Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | - Stephen C Strother
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada.,Rotman Research Institute, Baycrest, Toronto, ON, Canada
| | - Douglas P Munoz
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON, Canada
| | - Richard H Swartz
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON, Canada
| | - Robert Bartha
- Department of Medical Biophysics, Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Sean Symons
- Department of Medical Imaging, University of Toronto, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Program, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada.,Department of Medicine (Neurology), Sunnybrook Health Sciences Centre and University of Toronto, Toronto, ON, Canada
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17
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Classification of general and personal semantic details in the Autobiographical Interview. Neuropsychologia 2020; 144:107501. [PMID: 32445644 DOI: 10.1016/j.neuropsychologia.2020.107501] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/30/2020] [Revised: 05/02/2020] [Accepted: 05/19/2020] [Indexed: 12/20/2022]
Abstract
The Autobiographical Interview (AI) separates internal (episodic) and external (non-episodic) details from transcribed protocols using an exhaustive and reliable scoring system. While the details comprising the internal composite are centered on elements of episodic memory, external details are more heterogeneous as they are meant to capture a variety of non-episodic utterances: general semantics, different types of personal semantics details, metacognitive statements, repetitions, and details about off topic events. Elevated external details are consistently observed in aging and in neurodegenerative diseases. In the present study, we augmented the AI scoring system to differentiate subtypes of external details to test whether the elevation of these details in aging and in frontotemporal lobar degeneration (including mixed frontotemporal/semantic dementia [FTD/SD] and progressive non-fluent aphasia [PNFA]) would be specific to general and personal semantics or would concern all subtypes. Specifically, we separated general semantic details from personal semantic details (including autobiographical facts, self-knowledge, and repeated events). With aging, external detail elevation was observed for general and personal semantic details but not for other types of external details. In frontotemporal lobar degeneration, patients with FTD/SD (but not PNFA) generated an excess of personal semantic details but not general semantic details. The increase in personal but not general semantic details in FTD/SD is consistent with prevalent impairment of general semantic memory in SD, and with the personalization of concepts in this condition. Under standard AI instructions, external details were intended to capture off-topic utterances and were not intended as a direct measure of semantic abilities. Future investigations concerned with semantic processing in aging and in dementia could modify standard instructions of the AI to directly probe semantic content.
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18
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Haddad SMH, Scott CJM, Ozzoude M, Holmes MF, Arnott SR, Nanayakkara ND, Ramirez J, Black SE, Dowlatshahi D, Strother SC, Swartz RH, Symons S, Montero-Odasso M, Bartha R. Comparison of quality control methods for automated diffusion tensor imaging analysis pipelines. PLoS One 2019; 14:e0226715. [PMID: 31860686 PMCID: PMC6924651 DOI: 10.1371/journal.pone.0226715] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/09/2019] [Accepted: 12/02/2019] [Indexed: 12/29/2022] Open
Abstract
The processing of brain diffusion tensor imaging (DTI) data for large cohort studies requires fully automatic pipelines to perform quality control (QC) and artifact/outlier removal procedures on the raw DTI data prior to calculation of diffusion parameters. In this study, three automatic DTI processing pipelines, each complying with the general ENIGMA framework, were designed by uniquely combining multiple image processing software tools. Different QC procedures based on the RESTORE algorithm, the DTIPrep protocol, and a combination of both methods were compared using simulated ground truth and artifact containing DTI datasets modeling eddy current induced distortions, various levels of motion artifacts, and thermal noise. Variability was also examined in 20 DTI datasets acquired in subjects with vascular cognitive impairment (VCI) from the multi-site Ontario Neurodegenerative Disease Research Initiative (ONDRI). The mean fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were calculated in global brain grey matter (GM) and white matter (WM) regions. For the simulated DTI datasets, the measure used to evaluate the performance of the pipelines was the normalized difference between the mean DTI metrics measured in GM and WM regions and the corresponding ground truth DTI value. The performance of the proposed pipelines was very similar, particularly in FA measurements. However, the pipeline based on the RESTORE algorithm was the most accurate when analyzing the artifact containing DTI datasets. The pipeline that combined the DTIPrep protocol and the RESTORE algorithm produced the lowest standard deviation in FA measurements in normal appearing WM across subjects. We concluded that this pipeline was the most robust and is preferred for automated analysis of multisite brain DTI data.
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Affiliation(s)
- Seyyed M. H. Haddad
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Christopher J. M. Scott
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Miracle Ozzoude
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Melissa F. Holmes
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Stephen R. Arnott
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada
| | - Nuwan D. Nanayakkara
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
| | - Joel Ramirez
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
| | - Sandra E. Black
- L.C. Campbell Cognitive Neurology Research Unit, Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, University of Toronto, Toronto, Ontario, Canada
- Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, and University of Toronto, Toronto, Ontario, Canada
| | | | - Stephen C. Strother
- Rotman Research Institute, Baycrest Centre, Toronto, Ontario, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Richard H. Swartz
- Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, and University of Toronto, Toronto, Ontario, Canada
- Sunnybrook Health Sciences Centre, University of Toronto, Stroke Research Program, Toronto, Ontario, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada
| | - Manuel Montero-Odasso
- Department of Medicine, Division of Geriatric Medicine, Parkwood Hospital, University of Western Ontario, London, Ontario, Canada
| | | | - Robert Bartha
- Centre for Functional and Metabolic Mapping, Robarts Research Institute, University of Western Ontario, London, Ontario, Canada
- Department of Medical Biophysics, University of Western Ontario, London, Ontario, Canada
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19
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Riekert M, Kreppel M, Schier R, Zöller JE, Rempel V, Schick VC. Postoperative complications after bimaxillary orthognathic surgery: A retrospective study with focus on postoperative ventilation strategies and posterior airway space (PAS). J Craniomaxillofac Surg 2019; 47:1848-1854. [PMID: 31810851 DOI: 10.1016/j.jcms.2019.11.007] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/22/2019] [Revised: 08/29/2019] [Accepted: 11/18/2019] [Indexed: 02/08/2023] Open
Abstract
PURPOSE The aim of this study was to evaluate the impact of extubation time on postoperative complications in patients undergoing bimaxillary orthognathic surgery. We therefore retrospectively compared the effect of early extubating (EE) in the operating room versus delayed extubating (LE) on the intensive care unit (ICU) regarding postoperative complications and length of ICU/hospital stay (LOICUS/LOHS). Furthermore, we analyzed the influence of the PAS change on postoperative complications. METHODS The clinical data of 117 patients were retrospective analyzed regarding postoperative complications using Clavian-Dindo Classification. Volumetric calculations of the pre- and postoperative PAS were conducted using ITK-SNAP software. The Fisher's exact test was performed to evaluate the significance of differences between categorical variables. Continuous variables were analyzed using the Mann-Whitney U-Test or the Kruskal-Wallis one-way analysis of variance. Regression analysis was used estimating predictors for postoperative complications. RESULTS EE led to significant shortening of LOICUS (p < 0.001) and LOHS (p = 0.023). In total, we recorded 38 complications (minor n = 30; major n = 8) within the hospital stay. Complication rates were without significant differences with respect to the postoperative ventilation strategy. Large changes in PAS volume led to an increase in the major complication rates (p = 0.031). Increase or decrease of PAS was independent from postoperative complication rates (p = 1.000). Higher body mass index (p = 0.04) and a higher ASA PS score (p = 0.016) were associated with increased major complication rates. CONCLUSION Early extubation after surgery is a safe procedure and is associated with a reduced LOICUS and LOHS. Complications seem to occur more frequently in marked changes of the PAS and should be considered in perioperative risk stratification.
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Affiliation(s)
- Maximilian Riekert
- Department of Oral and Craniomaxillofacial and Plastic Surgery, (Head: Prof. Dr. Dr. Joachim E. Zöller), University Hospital of Cologne, Germany.
| | - Matthias Kreppel
- Department of Oral and Craniomaxillofacial and Plastic Surgery, (Head: Prof. Dr. Dr. Joachim E. Zöller), University Hospital of Cologne, Germany
| | - Robert Schier
- Department of Anaesthesiology and Intensive Care Medicine, (Head: Prof. Dr. Bernd W. Böttiger), University Hospital of Cologne, Germany
| | - Joachim E Zöller
- Department of Oral and Craniomaxillofacial and Plastic Surgery, (Head: Prof. Dr. Dr. Joachim E. Zöller), University Hospital of Cologne, Germany
| | - Vadim Rempel
- Department of Oral and Craniomaxillofacial and Plastic Surgery, (Head: Prof. Dr. Dr. Joachim E. Zöller), University Hospital of Cologne, Germany
| | - Volker C Schick
- Department of Anaesthesiology and Intensive Care Medicine, (Head: Prof. Dr. Bernd W. Böttiger), University Hospital of Cologne, Germany
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20
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Dey AK, Stamenova V, Bacopulos A, Jeyakumar N, Turner GR, Black SE, Levine B. Cognitive heterogeneity among community-dwelling older adults with cerebral small vessel disease. Neurobiol Aging 2019; 77:183-193. [DOI: 10.1016/j.neurobiolaging.2018.12.011] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2018] [Revised: 12/16/2018] [Accepted: 12/26/2018] [Indexed: 10/27/2022]
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21
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Frontal Anatomical Correlates of Cognitive and Speech Motor Deficits in Amyotrophic Lateral Sclerosis. Behav Neurol 2019; 2019:9518309. [PMID: 31001362 PMCID: PMC6436339 DOI: 10.1155/2019/9518309] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2018] [Revised: 10/25/2018] [Accepted: 12/11/2018] [Indexed: 01/15/2023] Open
Abstract
The goal of this study was to identify neurostructural frontal lobe correlates of cognitive and speaking rate changes in amyotrophic lateral sclerosis (ALS). 17 patients diagnosed with ALS and 12 matched controls underwent clinical, bulbar, and neuropsychological assessment and structural neuroimaging. Neuropsychological testing was performed via a novel computerized frontal battery (ALS-CFB), based on a validated theoretical model of frontal lobe functions, and focused on testing energization, executive function, emotion processing, theory of mind, and behavioral inhibition via antisaccades. The measure of speaking rate represented bulbar motor changes. Neuroanatomical assessment was performed using volumetric analyses focused on frontal lobe regions, postcentral gyrus, and occipital lobes as controls. Partial least square regressions (PLS) were used to predict behavioral (cognitive and speech rate) outcomes using volumetric measures. The data supported the overall hypothesis that distinct behavioral changes in cognition and speaking rate in ALS were related to specific regional neurostructural brain changes. These changes did not support a notion of a general dysexecutive syndrome in ALS. The observed specificity of behavior-brain changes can begin to provide a framework for subtyping of ALS. The data also support a more integrative framework for clinical assessment of frontal lobe functioning in ALS, which requires both behavioral testing and neuroimaging.
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22
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Atwi S, Shao H, Crane DE, da Costa L, Aviv RI, Mikulis DJ, Black SE, MacIntosh BJ. BOLD-based cerebrovascular reactivity vascular transfer function isolates amplitude and timing responses to better characterize cerebral small vessel disease. NMR IN BIOMEDICINE 2019; 32:e4064. [PMID: 30693582 DOI: 10.1002/nbm.4064] [Citation(s) in RCA: 21] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2018] [Revised: 12/03/2018] [Accepted: 12/18/2018] [Indexed: 06/09/2023]
Abstract
Cerebrovascular reactivity (CVR) is a dynamic measure of the cerebral blood vessel response to vasoactive stimulus. Conventional CVR measures amplitude changes in the blood-oxygenation-level-dependent (BOLD) signal per unit change in end-tidal CO2 (PET CO2 ), effectively discarding potential timing information. This study proposes a deconvolution procedure to characterize CVR responses based on a vascular transfer function (VTF) that separates amplitude and timing CVR effects. We implemented the CVR-VTF to primarily evaluate normal-appearing white matter (WM) responses in those with a range of small vessel disease. Comparisons between simulations of PET CO2 input models revealed that boxcar and ramp hypercapnia paradigms had the lowest relative deconvolution error. We used a T2 * BOLD-MRI sequence on a 3 T MRI scanner, with a boxcar delivery model of CO2 , to test the CVR-VTF approach in 18 healthy adults and three white matter hyperintensity (WMH) groups: 20 adults with moderate WMH, 12 adults with severe WMH, and 10 adults with genetic WMH (CADASIL). A subset of participants performed a second CVR session at a one-year follow-up. Conventional CVR, area under the curve of VTF (VTF-AUC), and VTF time-to-peak (VTF-TTP) were assessed in WM and grey matter (GM) at baseline and one-year follow-up. WMH groups had lower WM VTF-AUC compared with the healthy group (p < 0.0001), whereas GM CVR did not differ between groups (p > 0.1). WM VTF-TTP of the healthy group was less than that in the moderate WMH group (p = 0.016). Baseline VTF-AUC was lower than follow-up VTF-AUC in WM (p = 0.013) and GM (p = 0.026). The intraclass correlation for VTF-AUC in WM was 0.39 and coefficient of repeatability was 0.08 [%BOLD/mm Hg]. This study assessed CVR timing and amplitude information without applying model assumptions to the CVR response; this approach may be useful in the development of robust clinical biomarkers of CSVD.
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Affiliation(s)
- Sarah Atwi
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
| | - Han Shao
- Division of Engineering Science, Faculty of Applied Science and Engineering, University of Toronto, Toronto, ON, Canada
| | - David E Crane
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
| | - Leodante da Costa
- Division of Neurosurgery, Department of Surgery, Sunnybrook Hospital, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Richard I Aviv
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - David J Mikulis
- Division of Neuroradiology, Joint Department of Medical Imaging, University Health Network, Toronto, Canada
- Department of Medical Imaging, University of Toronto, Toronto, Canada
| | - Sandra E Black
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
- Rehabilitation Sciences Institute, University of Toronto, Toronto, ON, Canada
- Rotman Research Institute, Baycrest Centre, Toronto, ON, Canada
- Department of Medicine (Neurology), University of Toronto, Toronto, ON, Canada
| | - Bradley J MacIntosh
- Heart and Stroke Foundation Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute, University of Toronto, Toronto, ON, Canada
- Department of Medical Biophysics, University of Toronto, Toronto, ON, Canada
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
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Ganzetti M, Liu Q, Mantini D. A Spatial Registration Toolbox for Structural MR Imaging of the Aging Brain. Neuroinformatics 2019; 16:167-179. [PMID: 29352390 DOI: 10.1007/s12021-018-9355-3] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
During aging the brain undergoes a series of structural changes, in size, shape as well as tissue composition. In particular, cortical atrophy and ventricular enlargement are often present in the brain of elderly individuals. This poses serious challenges in the spatial registration of structural MR images. In this study, we addressed this open issue by proposing an enhanced framework for MR registration and segmentation. Our solution was compared with other approaches based on the tools available in SPM12, a widely used software package. Performance of the different methods was assessed on 229 T1-weighted images collected in healthy individuals, with age ranging between 55 and 90 years old. Our method showed a consistent improvement as compared to other solutions, especially for subjects with enlarged lateral ventricles. It also provided a superior inter-subject alignment in cortical regions, with the most marked improvement in the frontal lobe. We conclude that our method is a valid alternative to standard approaches based on SPM12, and is particularly suitable for the processing of structural MR images of brains with cortical atrophy and ventricular enlargement. The method is integrated in our software toolbox MRTool, which is freely available to the scientific community.
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Affiliation(s)
- Marco Ganzetti
- Laboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium.
| | - Quanying Liu
- Laboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland
| | - Dante Mantini
- Laboratory of Movement Control and Neuroplasticity, KU Leuven, Leuven, Belgium.,Neural Control of Movement Lab, ETH Zurich, Zurich, Switzerland.,Department of Experimental Psychology, Oxford University, Oxford, UK
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Abstract
PURPOSE/BACKGROUND Loss of gray matter after stroke has been associated with cognitive impairment. This pilot study aimed to investigate the therapeutic potential of lithium, a putative neurotrophic agent, in the stroke recovery process within a year of stroke occurrence. METHODS Twelve stroke patients (mean ± SD age, 71.1 ± 11.9 years) were recruited to the study, and eligible participants were prescribed open-label lithium for 60 days. Magnetic resonance imaging was used to assess global gray matter at baseline and end of treatment; global cognition was assessed using the standardized Mini-Mental State Examination and Montreal Cognitive Assessment, and verbal memory was evaluated using the Hopkins Verbal Learning Test-Revised. FINDINGS/RESULTS There was no difference in global gray matter volume between baseline and follow-up (t = 1.977, P = 0.074). There was a significant interaction between higher lithium dose and increased global gray matter volume (F = 14.25, P = 0.004) and a correlation between higher lithium dose and improved verbal memory (r = 0.576, P = 0.05). IMPLICATIONS/CONCLUSIONS Lithium pharmacotherapy may be associated with gray matter volume change and verbal memory improvement in stroke patients, providing a rationale for future trials assessing therapeutic potential of lithium in a poststroke population.
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25
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Ito KL, Kumar A, Zavaliangos-Petropulu A, Cramer SC, Liew SL. Pipeline for Analyzing Lesions After Stroke (PALS). Front Neuroinform 2018; 12:63. [PMID: 30319385 PMCID: PMC6165891 DOI: 10.3389/fninf.2018.00063] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/04/2018] [Accepted: 09/05/2018] [Indexed: 02/04/2023] Open
Abstract
Lesion analyses are critical for drawing insights about stroke injury and recovery, and their importance is underscored by growing efforts to collect and combine stroke neuroimaging data across research sites. However, while there are numerous processing pipelines for neuroimaging data in general, few can be smoothly applied to stroke data due to complications analyzing the lesioned region. As researchers often use their own tools or manual methods for stroke MRI analysis, this could lead to greater errors and difficulty replicating findings over time and across sites. Rigorous analysis protocols and quality control pipelines are thus urgently needed for stroke neuroimaging. To this end, we created the Pipeline for Analyzing Lesions after Stroke (PALS; DOI: https://doi.org/10.5281/zenodo.1266980), a scalable and user-friendly toolbox to facilitate and ensure quality in stroke research specifically using T1-weighted MRIs. The PALS toolbox offers four modules integrated into a single pipeline, including (1) reorientation to radiological convention, (2) lesion correction for healthy white matter voxels, (3) lesion load calculation, and (4) visual quality control. In the present paper, we discuss each module and provide validation and example cases of our toolbox using multi-site data. Importantly, we also show that lesion correction with PALS significantly improves similarity between manual lesion segmentations by different tracers (z = 3.43, p = 0.0018). PALS can be found online at https://github.com/npnl/PALS. Future work will expand the PALS capabilities to include multimodal stroke imaging. We hope PALS will be a useful tool for the stroke neuroimaging community and foster new clinical insights.
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Affiliation(s)
- Kaori L Ito
- Neural Plasticity and Neurorehabilitation Laboratory, University of Southern California, Los Angeles, CA, United States
| | - Amit Kumar
- Neural Plasticity and Neurorehabilitation Laboratory, University of Southern California, Los Angeles, CA, United States
| | - Artemis Zavaliangos-Petropulu
- Neural Plasticity and Neurorehabilitation Laboratory, University of Southern California, Los Angeles, CA, United States.,Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
| | - Steven C Cramer
- Department of Neurology, University of California, Irvine, Irvine, CA, United States
| | - Sook-Lei Liew
- Neural Plasticity and Neurorehabilitation Laboratory, University of Southern California, Los Angeles, CA, United States.,Imaging Genetics Center, Mark and Mary Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Marina del Rey, CA, United States
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26
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Sapkota S, Ramirez J, Stuss DT, Masellis M, Black SE. Clinical dementia severity associated with ventricular size is differentially moderated by cognitive reserve in men and women. ALZHEIMERS RESEARCH & THERAPY 2018; 10:89. [PMID: 30185213 PMCID: PMC6123907 DOI: 10.1186/s13195-018-0419-2] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 04/09/2018] [Accepted: 08/07/2018] [Indexed: 01/08/2023]
Abstract
Background Interindividual differences in cognitive reserve (CR) are associated with complex and dynamic clinical phenotypes observed in cognitive impairment and dementia. We tested whether (1) CR early in life (E-CR; measured by education and IQ), (2) CR later in life (L-CR; measured by occupation), and (3) CR panel (CR-P) with the additive effects of E-CR and L-CR, act as moderating factors between baseline ventricular size and clinical dementia severity at baseline and across 2 years. We further examined whether this moderation is differentially represented by sex. Methods We examined a longitudinal model using patients (N = 723; mean age = 70.8 ± 9.4 years; age range = 38–90 years; females = 374) from the Sunnybrook Dementia Study. The patients represented Alzheimer’s disease (n = 439), mild cognitive impairment (n = 77), vascular cognitive impairment (n = 52), Lewy body disease (n = 30), and frontotemporal dementia (n = 125). Statistical analyses included (1) latent growth modeling to determine how clinical dementia severity changes over 2 years (measured by performance on the Dementia Rating Scale), (2) confirmatory factor analysis to establish a baseline E-CR factor, and (3) path analysis to predict dementia severity. Baseline age (continuous) and Apolipoprotein E status (ɛ4−/ɛ4+) were included as covariates. Results The association between higher baseline ventricular size and dementia severity was moderated by (1) E-CR and L-CR and (2) CR-P. This association was differentially represented in men and women. Specifically, men in only the low CR-P had higher baseline clinical dementia severity with larger baseline ventricular size. However, women in the low CR-P showed the (1) highest baseline dementia severity and (2) fastest 2-year decline with larger baseline ventricular size. Conclusions Clinical dementia severity associated with ventricular size may be (1) selectively moderated by complex and additive CR networks and (2) differentially represented by sex. Trials registration ClinicalTrials.gov, NCT01800214. Registered on 27 February 2013. Electronic supplementary material The online version of this article (10.1186/s13195-018-0419-2) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Shraddha Sapkota
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, M6-192, Toronto, ON, M4N 3M5, Canada.
| | - Joel Ramirez
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, M6-192, Toronto, ON, M4N 3M5, Canada
| | - Donald T Stuss
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, M6-192, Toronto, ON, M4N 3M5, Canada.,Departments of Medicine, University of Toronto, 190 Elizabeth Street, R. Fraser Elliot Building, 3-805, Toronto, ON, M5G 2C4, Canada.,Department of Psychology, University of Toronto, 100 St. George Street, 4th Floor, Sidney Smith Hall, Toronto, ON, M5S 3G3, Canada.,Rotman Research Institute of Baycrest Centre, 3560 Bathurst Street, Toronto, ON, M6H 4A6, Canada
| | - Mario Masellis
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, M6-192, Toronto, ON, M4N 3M5, Canada.,Department of Medicine (Neurology), University of Toronto, 190 Elizabeth Street, R. Fraser Elliot Building, 3-805, Toronto, ON, M5G 2C4, Canada
| | - Sandra E Black
- Hurvitz Brain Sciences Research Program, Sunnybrook Research Institute, Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, M6-192, Toronto, ON, M4N 3M5, Canada.,Department of Medicine (Neurology), University of Toronto, 190 Elizabeth Street, R. Fraser Elliot Building, 3-805, Toronto, ON, M5G 2C4, Canada
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27
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Montero-Odasso M, Pieruccini-Faria F, Bartha R, Black SE, Finger E, Freedman M, Greenberg B, Grimes DA, Hegele RA, Hudson C, Kleinstiver PW, Lang AE, Masellis M, McLaughlin PM, Munoz DP, Strother S, Swartz RH, Symons S, Tartaglia MC, Zinman L, Strong MJ, McIlroy W. Motor Phenotype in Neurodegenerative Disorders: Gait and Balance Platform Study Design Protocol for the Ontario Neurodegenerative Research Initiative (ONDRI). J Alzheimers Dis 2018; 59:707-721. [PMID: 28671116 PMCID: PMC5523841 DOI: 10.3233/jad-170149] [Citation(s) in RCA: 49] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
Background: The association of cognitive and motor impairments in Alzheimer’s disease and other neurodegenerative diseases is thought to be related to damage in the common brain networks shared by cognitive and cortical motor control processes. These common brain networks play a pivotal role in selecting movements and postural synergies that meet an individual’s needs. Pathology in this “highest level” of motor control produces abnormalities of gait and posture referred to as highest-level gait disorders. Impairments in cognition and mobility, including falls, are present in almost all neurodegenerative diseases, suggesting common mechanisms that still need to be unraveled. Objective: To identify motor-cognitive profiles across neurodegenerative diseases in a large cohort of patients. Methods: Cohort study that includes up to 500 participants, followed every year for three years, across five neurodegenerative disease groups: Alzheimer’s disease/mild cognitive impairment, frontotemporal degeneration, vascular cognitive impairment, amyotrophic lateral sclerosis, and Parkinson’s disease. Gait and balance will be assessed using accelerometers and electronic walkways, evaluated at different levels of cognitive and sensory complexity, using the dual-task paradigm. Results: Comparison of cognitive and motor performances across neurodegenerative groups will allow the identification of motor-cognitive phenotypes through the standardized evaluation of gait and balance characteristics. Conclusions: As part of the Ontario Neurodegenerative Research Initiative (ONDRI), the gait and balance platform aims to identify motor-cognitive profiles across neurodegenerative diseases. Gait assessment, particularly while dual-tasking, will help dissect the cognitive and motor contribution in mobility and cognitive decline, progression to dementia syndromes, and future adverse outcomes including falls and mortality.
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Affiliation(s)
- Manuel Montero-Odasso
- Department of Medicine, Division of Geriatric Medicine, Parkwood Hospital, University of Western Ontario, London, ON, Canada.,Department of Epidemiology and Biostatistics, University of Western Ontario, London, ON, Canada.,Lawson Health Research Institute, London, ON, Canada
| | - Frederico Pieruccini-Faria
- Department of Medicine, Division of Geriatric Medicine, Parkwood Hospital, University of Western Ontario, London, ON, Canada.,Lawson Health Research Institute, London, ON, Canada
| | - Robert Bartha
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Sandra E Black
- Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, ON, Canada.,Canadian Partnership for Stroke Recovery Sunnybrook Site, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada
| | - Elizabeth Finger
- Department of Clinical Neurological Sciences, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Morris Freedman
- Department of Medicine (Neurology), Baycrest Health Sciences and University of Toronto, Toronto, ON, Canada; Rotman Research Institute, Baycrest Centre for Geriatric Care, Toronto, ON, Canada
| | - Barry Greenberg
- Toronto Dementia Research Alliance, University Health Network, Toronto, ON, Canada
| | - David A Grimes
- Department of Medicine, The Ottawa Hospital, Faculty of Medicine, University of Ottawa, Ottawa, ON, Canada
| | - Robert A Hegele
- Department of Biochemistry, Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada.,Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Robarts Research Institute, University of Western Ontario, London, ON, Canada
| | - Christopher Hudson
- School of Optometry and Vision Science, University of Waterloo, Waterloo, ON, Canada
| | - Peter W Kleinstiver
- Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Anthony E Lang
- Morton and Gloria Shulman Movement Disorders Clinic and the Edmond J. Safra Program in Parkinson's Disease, Toronto Western Hospital and the Department of Medicine, University of Toronto, ON, Canada
| | - Mario Masellis
- Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, ON, Canada
| | - Paula M McLaughlin
- Schulich School of Medicine and Dentistry, University of Western Ontario, London, ON, Canada
| | - Douglas P Munoz
- Centre for Neuroscience Studies, Queen's University, Kingston, ON, Canada
| | - Stephen Strother
- Department of Medical Biophysics, Rotman Research Institute, Baycrest, University of Toronto, ON, Canada
| | - Richard H Swartz
- Sunnybrook Health Sciences Centre, University of Toronto, Stroke Research Program, Toronto, ON, Canada
| | - Sean Symons
- Department of Medical Imaging, Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | - Maria Carmela Tartaglia
- Department of Medicine and Division of Neurology, University of Toronto, Tanz Centre for Research in Neurodegenerative Diseases, University of Toronto, ON, Canada
| | - Lorne Zinman
- Department of Medicine, Division of Neurology, Sunnybrook Health Sciences Centre, University of Toronto, ON, Canada
| | - Michael J Strong
- Department of Medical Biophysics, Schulich School of Medicine and Dentistry, Robarts Research Institute, University of Western Ontario, London, ON, Canada.,Department of Medicine (Neurology), Baycrest Health Sciences and University of Toronto, Toronto, ON, Canada; Rotman Research Institute, Baycrest Centre for Geriatric Care, Toronto, ON, Canada
| | | | - William McIlroy
- Canadian Partnership for Stroke Recovery Sunnybrook Site, Sunnybrook Health Sciences Centre, University of Toronto, Toronto, ON, Canada.,Morton and Gloria Shulman Movement Disorders Clinic and the Edmond J. Safra Program in Parkinson's Disease, Toronto Western Hospital and the Department of Medicine, University of Toronto, ON, Canada.,Department of Kinesiology, University of Waterloo, Waterloo, ON, Canada
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28
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Reduced substantia innominata volume mediates contributions of microvascular and macrovascular disease to cognitive deficits in Alzheimer's disease. Neurobiol Aging 2018; 66:23-31. [PMID: 29505952 DOI: 10.1016/j.neurobiolaging.2018.01.025] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/23/2017] [Revised: 01/29/2018] [Accepted: 01/31/2018] [Indexed: 01/06/2023]
Abstract
The relationships between cholinergic system damage and cerebrovascular disease are not entirely understood. Here, we investigate associations between atrophy of the substantia innominata (SI; the origin of cortical cholinergic projections) and measures of large and small vessel disease; specifically, elongation of the juxtaposed internal carotid artery termination and Cholinergic Pathways Hyperintensity scores (CHIPS). The study (n = 105) consisted of patients with Alzheimer's disease (AD) and/or subcortical ischemic vasculopathy, and elderly controls. AD and subcortical ischemic vasculopathy groups showed greater impingement of the carotid termination on the SI and smaller SI volumes. Both carotid termination elongation and CHIPS were associated independently with smaller SI volumes in those with and without AD. Atrophy of the SI mediated effects of carotid termination elongation on language and memory functions and the effect of CHIPS on attention/working memory. In conclusion, SI atrophy was related to cerebrovascular disease of the large and small vessels and to cognitive deficits in people with and without AD.
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29
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Santiago C, Herrmann N, Swardfager W, Saleem M, Oh PI, Black SE, Bradley J, Lanctôt KL. Subcortical hyperintensities in the cholinergic system are associated with improvements in executive function in older adults with coronary artery disease undergoing cardiac rehabilitation. Int J Geriatr Psychiatry 2018; 33:279-287. [PMID: 28474775 PMCID: PMC5811800 DOI: 10.1002/gps.4729] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/01/2016] [Accepted: 03/24/2017] [Indexed: 11/24/2022]
Abstract
OBJECTIVE Coronary artery disease (CAD) is frequently accompanied by white matter hyperintensities and executive dysfunction. Because acetylcholine is important in executive function, these symptoms may be exacerbated by subcortical hyperintensities (SH) located in cholinergic (CH) tracts. This study investigated the effects of SH on cognitive changes in CAD patients undergoing a 48-week cardiac rehabilitation program. METHODS Fifty patients (age 66.5 ± 7.1 years, 84% male) underwent the National Institute of Neurological Disorders and Stroke - Canadian Stroke Network neurocognitive battery at baseline and 48 weeks. Patients underwent a 48-week cardiac program and completed neuroimaging at baseline. Subcortical hyperintensities in CH tracts were measured using Lesion Explorer. Repeated measures general linear models were used to examine interactions between SH and longitudinal cognitive outcomes, controlling for age, education, and max VO2 change as a measure of fitness. RESULTS In patients with SH in CH tracts, there was a significant interaction with the Trail Making Test (TMT) part A and part B over time. Patients without SH improved on average 16.6 and 15.0% on the TMT-A and TMT-B, respectively. Patients with SH on average showed no improvements in either TMT-A or TMT-B over time. There were no significant differences in other cognitive measures. CONCLUSION These results suggest that CAD patients with SH in CH tracts improve less than those without SH in CH tracts, over 48 weeks of cardiac rehabilitation. Thus, SH in CH tracts may contribute to longitudinal cognitive decline following a cardiac event and may represent a vascular risk factor of cognitive decline. © 2017 The Authors. International Journal of Geriatric Psychiatry Published by John Wiley & Sons Ltd.
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Affiliation(s)
- Calvin Santiago
- Neuropsychopharmacology Research GroupSunnybrook Research InstituteTorontoOntarioCanada,Toronto Rehabilitation InstituteTorontoOntarioCanada
| | - Nathan Herrmann
- Neuropsychopharmacology Research GroupSunnybrook Research InstituteTorontoOntarioCanada,Department of PsychiatryUniversity of TorontoTorontoOntarioCanada,Canadian Partnership for Stroke RecoverySunnybrook Research InstituteTorontoOntarioCanada
| | - Walter Swardfager
- Canadian Partnership for Stroke RecoverySunnybrook Research InstituteTorontoOntarioCanada,Department of Pharmacology and ToxicologyUniversity of TorontoTorontoOntarioCanada
| | - Mahwesh Saleem
- Neuropsychopharmacology Research GroupSunnybrook Research InstituteTorontoOntarioCanada,Department of Pharmacology and ToxicologyUniversity of TorontoTorontoOntarioCanada
| | - Paul I. Oh
- Toronto Rehabilitation InstituteTorontoOntarioCanada
| | - Sandra E. Black
- Canadian Partnership for Stroke RecoverySunnybrook Research InstituteTorontoOntarioCanada,Department of Medicine (Neurology)Sunnybrook Health Sciences Centre and University of TorontoTorontoOntarioCanada,Brain Sciences Research ProgramSunnybrook Research Institute, Sunnybrook Health Sciences CentreTorontoOntarioCanada
| | - Janelle Bradley
- Neuropsychopharmacology Research GroupSunnybrook Research InstituteTorontoOntarioCanada
| | - Krista L. Lanctôt
- Neuropsychopharmacology Research GroupSunnybrook Research InstituteTorontoOntarioCanada,Toronto Rehabilitation InstituteTorontoOntarioCanada,Department of PsychiatryUniversity of TorontoTorontoOntarioCanada,Canadian Partnership for Stroke RecoverySunnybrook Research InstituteTorontoOntarioCanada,Department of Pharmacology and ToxicologyUniversity of TorontoTorontoOntarioCanada,Brain Sciences Research ProgramSunnybrook Research Institute, Sunnybrook Health Sciences CentreTorontoOntarioCanada
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Freedman M, Binns M, Gao F, Holmes M, Roseborough A, Strother S, Vallesi A, Jeffers S, Alain C, Whitehouse P, Ryan JD, Chen R, Cusimano MD, Black SE. Mind-Matter Interactions and the Frontal Lobes of the Brain: A Novel Neurobiological Model of Psi Inhibition. Explore (NY) 2017; 14:76-85. [PMID: 29169779 DOI: 10.1016/j.explore.2017.08.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/16/2017] [Revised: 07/11/2017] [Accepted: 08/01/2017] [Indexed: 10/18/2022]
Abstract
CONTEXT Despite a large literature on psi, which encompasses a range of experiences including putative telepathy (mind-mind connections), clairvoyance (perceiving distant objects or events), precognition (perceiving future events), and mind-matter interactions, there has been insufficient focus on the brain in relation to this controversial phenomenon. In contrast, our research is based on a novel neurobiological model suggesting that frontal brain systems act as a filter to inhibit psi and that the inhibitory mechanisms may relate to self-awareness. OBJECTIVE To identify frontal brain regions that may inhibit psi. DESIGN We used mind-matter interactions to study psi in two participants with frontal lobe damage. The experimental task was to influence numerical output of a Random Event Generator translated into movement of an arrow on a computer screen to the right or left. Brain MRI was analyzed to determine frontal volume loss. RESULTS The primary area of lesion overlap between the participants was in the left medial middle frontal region, an area related to self-awareness, and involved Brodmann areas 9, 10, and 32. Both participants showed a significant effect in moving the arrow to the right, i.e., contralateral to the side of primary lesion overlap. Effect sizes were much larger compared to normal participants. CONCLUSIONS The medial frontal lobes may act as a biological filter to inhibit psi through mechanisms related to self-awareness. Neurobiological studies with a focus on the brain may open new avenues of research on psi and may significantly advance the state of this poorly understood field.
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Affiliation(s)
- Morris Freedman
- Department of Medicine (Neurology) and Sam and Ida Ross Memory Clinic, Baycrest Health Sciences, Toronto, Ontario, Canada; Department of Medicine (Neurology), Mt. Sinai Hospital and University of Toronto, Toronto, Ontario, Canada; Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst Street, Toronto, Ontario M6A 2E1, Canada.
| | - Malcolm Binns
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst Street, Toronto, Ontario M6A 2E1, Canada; Dalla Lana School of Public Health, University of Toronto, Toronto, Ontario, Canada
| | - Fuqiang Gao
- LC Campbell Cognitive Neurology Research Unit and Hurvitz Brain Science Research Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada
| | - Melissa Holmes
- LC Campbell Cognitive Neurology Research Unit and Hurvitz Brain Science Research Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada
| | - Austyn Roseborough
- LC Campbell Cognitive Neurology Research Unit and Hurvitz Brain Science Research Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada
| | - Stephen Strother
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst Street, Toronto, Ontario M6A 2E1, Canada; Department of Medical Biophysics, University of Toronto, Toronto, Ontario, Canada
| | - Antonino Vallesi
- Department of Neuroscience, University of Padova, Via Giustiniani 5, 35128 Padova, Italy; Fondazione Ospedale San Camillo, IRCCS, Lido-Venice, Italy
| | - Stanley Jeffers
- Department of Physics and Astronomy, York University, 4700 Keele Street, Toronto, Ontario M3J 1P3, Canada
| | - Claude Alain
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst Street, Toronto, Ontario M6A 2E1, Canada; Department of Psychology, University of Toronto, Toronto, Canada
| | - Peter Whitehouse
- Department of Neurology, Case Western Reserve University, 2895 Carlton Road, Shaker Heights, Ohio 44122; Department of Medicine (Neurology), University of Toronto, Toronto, Canada
| | - Jennifer D Ryan
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst Street, Toronto, Ontario M6A 2E1, Canada; Department of Psychology, University of Toronto, Toronto, Canada; Department of Psychiatry, University of Toronto, Toronto, Canada
| | - Robert Chen
- Department of Medicine (Neurology), University of Toronto, Toronto, Canada; Krembil Research Institute, University Health Network and Toronto Western Hospital, 399 Bathurst Street, Toronto, Ontario M5T 2S8, Canada
| | - Michael D Cusimano
- Division of Neurosurgery, University of Toronto, Toronto, Canada; St. Michael's Hospital, 30 Bond Street, Toronto, Ontario M5B 1W8, Canada
| | - Sandra E Black
- Rotman Research Institute, Baycrest Health Sciences, 3560 Bathurst Street, Toronto, Ontario M6A 2E1, Canada; LC Campbell Cognitive Neurology Research Unit and Hurvitz Brain Science Research Program, Sunnybrook Research Institute, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada; Department of Medicine (Neurology), University of Toronto, Toronto, Canada; Sunnybrook Health Sciences Centre, 2075 Bayview Avenue, Toronto, Ontario M4N 3M5, Canada
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31
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Shirzadi Z, Stefanovic B, Chappell MA, Ramirez J, Schwindt G, Masellis M, Black SE, MacIntosh BJ. Enhancement of automated blood flow estimates (ENABLE) from arterial spin-labeled MRI. J Magn Reson Imaging 2017; 47:647-655. [DOI: 10.1002/jmri.25807] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2017] [Accepted: 06/20/2017] [Indexed: 11/06/2022] Open
Affiliation(s)
- Zahra Shirzadi
- Department of Medical Biophysics; University of Toronto; Toronto ON Canada
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
| | - Bojana Stefanovic
- Department of Medical Biophysics; University of Toronto; Toronto ON Canada
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
| | - Michael A. Chappell
- Institute of Biomedical Engineering, Department of Engineering Science; University of Oxford; Oxford UK
- Oxford Centre for Functional MRI of the Brain, Nuffield Department of Clinical Neurosciences; University of Oxford; Oxford UK
| | - Joel Ramirez
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
| | - Graeme Schwindt
- Hurvitz Brain Sciences, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Department of Family and Community Medicine; University of Toronto; Toronto ON Canada
| | - Mario Masellis
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre; University of Toronto; Toronto ON Canada
| | - Sandra E. Black
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre; University of Toronto; Toronto ON Canada
| | - Bradley J. MacIntosh
- Department of Medical Biophysics; University of Toronto; Toronto ON Canada
- Heart and Stroke Foundation, Canadian Partnership for Stroke Recovery, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
- Hurvitz Brain Sciences, Sunnybrook Research Institute; University of Toronto; Toronto ON Canada
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The effect of focal cortical frontal and posterior lesions on recollection and familiarity in recognition memory. Cortex 2017; 91:316-326. [PMID: 28499557 DOI: 10.1016/j.cortex.2017.04.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2016] [Revised: 02/02/2017] [Accepted: 04/05/2017] [Indexed: 11/21/2022]
Abstract
Recognition memory can be subdivided into two processes: recollection (a contextually rich memory) and familiarity (a sense that an item is old). The brain network supporting recognition encompasses frontal, parietal and medial temporal regions. Which specific regions within the frontal lobe are critical for recollection vs. familiarity, however, are unknown; past studies of focal lesion patients have yielded conflicting results. We examined patients with focal lesions confined to medial polar (MP), right dorsal frontal (RDF), right frontotemporal (RFT), left dorsal frontal (LDF), temporal, and parietal regions and matched controls. A series of words and their humorous definitions were presented either auditorily or visually to all participants. Recall, recognition, and source memory were tested at 30 min and 24 h delay, along with "remember/know" judgments for recognized items. The MP, RDF, temporal and parietal groups were impaired on subjectively reported recollection; their intact recognition performance was supported by familiarity. None of the groups were impaired on cued recall, recognition familiarity or source memory. These findings suggest that the MP and RDF regions, along with parietal and temporal regions, are necessary for subjectively-reported recollection, while the LDF and right frontal ventral regions, as those affected in the RTF group, are not.
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Abstract
AbstractBecause individuals develop dementia as a manifestation of neurodegenerative or neurovascular disorder, there is a need to develop reliable approaches to their identification. We are undertaking an observational study (Ontario Neurodegenerative Disease Research Initiative [ONDRI]) that includes genomics, neuroimaging, and assessments of cognition as well as language, speech, gait, retinal imaging, and eye tracking. Disorders studied include Alzheimer’s disease, amyotrophic lateral sclerosis, frontotemporal dementia, Parkinson’s disease, and vascular cognitive impairment. Data from ONDRI will be collected into the Brain-CODE database to facilitate correlative analysis. ONDRI will provide a repertoire of endophenotyped individuals that will be a unique, publicly available resource.
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Graham NL, Leonard C, Tang-Wai DF, Black S, Chow TW, Scott CJM, McNeely AA, Masellis M, Rochon E. Lack of Frank Agrammatism in the Nonfluent Agrammatic Variant of Primary Progressive Aphasia. Dement Geriatr Cogn Dis Extra 2016; 6:407-423. [PMID: 27790240 PMCID: PMC5075721 DOI: 10.1159/000448944] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/02/2023] Open
Abstract
Background/Aims Frank agrammatism, defined as the omission and/or substitution of grammatical morphemes with associated grammatical errors, is variably reported in patients with nonfluent variant primary progressive aphasia (nfPPA). This study addressed whether frank agrammatism is typical in agrammatic nfPPA patients when this feature is not required for diagnosis. Method We assessed grammatical production in 9 patients who satisfied current diagnostic criteria. Although the focus was agrammatism, motor speech skills were also evaluated to determine whether dysfluency arose primarily from apraxia of speech (AOS), instead of, or in addition to, agrammatism. Volumetric MRI analyses provided impartial imaging-supported diagnosis. Results The majority of cases exhibited neither frank agrammatism nor AOS. Conclusion There are nfPPA patients with imaging-supported diagnosis and preserved motor speech skills who do not exhibit frank agrammatism, and this may persist beyond the earliest stages of the illness. Because absence of frank agrammatism is a subsidiary diagnostic feature in the logopenic variant of PPA, this result has implications for differentiation of the nonfluent and logopenic variants, and indicates that PPA patients with nonfluent speech in the absence of frank agrammatism or AOS do not necessarily have the logopenic variant.
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Affiliation(s)
- Naida L Graham
- Department of Speech-Language Pathology, Faculty of Medicine, University of Toronto, Ont., Canada; Toronto Rehabilitation Institute, Toronto, Ont, Canada
| | - Carol Leonard
- Department of Audiology and Speech-Language Pathology, University of Ottawa, Ottawa, Ont, Canada
| | - David F Tang-Wai
- University Health Network Memory Clinic, Toronto Western Hospital, Ont., Canada; Department of Medicine (Neurology), University of Toronto, Ont., Canada
| | - Sandra Black
- Department of Medicine (Neurology), University of Toronto, Ont., Canada; L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Ont., Canada; Rotman Research Institute, University of Toronto, Toronto, Ont., Canada
| | - Tiffany W Chow
- Department of Medicine (Neurology), University of Toronto, Ont., Canada; Rotman Research Institute, University of Toronto, Toronto, Ont., Canada; Department of Psychiatry (Geriatric Psychiatry), University of Toronto, Toronto, Ont., Canada
| | - Chris J M Scott
- L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Ont., Canada
| | - Alicia A McNeely
- L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Ont., Canada
| | - Mario Masellis
- L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Ont., Canada
| | - Elizabeth Rochon
- Department of Speech-Language Pathology, Faculty of Medicine, University of Toronto, Ont., Canada; Toronto Rehabilitation Institute, Toronto, Ont, Canada
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Automatic Detection of White Matter Hyperintensities in Healthy Aging and Pathology Using Magnetic Resonance Imaging: A Review. Neuroinformatics 2016; 13:261-76. [PMID: 25649877 PMCID: PMC4468799 DOI: 10.1007/s12021-015-9260-y] [Citation(s) in RCA: 96] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
Abstract
White matter hyperintensities (WMH) are commonly seen in the brain of healthy elderly subjects and patients with several neurological and vascular disorders. A truly reliable and fully automated method for quantitative assessment of WMH on magnetic resonance imaging (MRI) has not yet been identified. In this paper, we review and compare the large number of automated approaches proposed for segmentation of WMH in the elderly and in patients with vascular risk factors. We conclude that, in order to avoid artifacts and exclude the several sources of bias that may influence the analysis, an optimal method should comprise a careful preprocessing of the images, be based on multimodal, complementary data, take into account spatial information about the lesions and correct for false positives. All these features should not exclude computational leanness and adaptability to available data.
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Auriat AM, Neva JL, Peters S, Ferris JK, Boyd LA. A Review of Transcranial Magnetic Stimulation and Multimodal Neuroimaging to Characterize Post-Stroke Neuroplasticity. Front Neurol 2015; 6:226. [PMID: 26579069 PMCID: PMC4625082 DOI: 10.3389/fneur.2015.00226] [Citation(s) in RCA: 82] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2015] [Accepted: 10/12/2015] [Indexed: 01/09/2023] Open
Abstract
Following stroke, the brain undergoes various stages of recovery where the central nervous system can reorganize neural circuitry (neuroplasticity) both spontaneously and with the aid of behavioral rehabilitation and non-invasive brain stimulation. Multiple neuroimaging techniques can characterize common structural and functional stroke-related deficits, and importantly, help predict recovery of function. Diffusion tensor imaging (DTI) typically reveals increased overall diffusivity throughout the brain following stroke, and is capable of indexing the extent of white matter damage. Magnetic resonance spectroscopy (MRS) provides an index of metabolic changes in surviving neural tissue after stroke, serving as a marker of brain function. The neural correlates of altered brain activity after stroke have been demonstrated by abnormal activation of sensorimotor cortices during task performance, and at rest, using functional magnetic resonance imaging (fMRI). Electroencephalography (EEG) has been used to characterize motor dysfunction in terms of increased cortical amplitude in the sensorimotor regions when performing upper limb movement, indicating abnormally increased cognitive effort and planning in individuals with stroke. Transcranial magnetic stimulation (TMS) work reveals changes in ipsilesional and contralesional cortical excitability in the sensorimotor cortices. The severity of motor deficits indexed using TMS has been linked to the magnitude of activity imbalance between the sensorimotor cortices. In this paper, we will provide a narrative review of data from studies utilizing DTI, MRS, fMRI, EEG, and brain stimulation techniques focusing on TMS and its combination with uni- and multimodal neuroimaging methods to assess recovery after stroke. Approaches that delineate the best measures with which to predict or positively alter outcomes will be highlighted.
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Affiliation(s)
- Angela M Auriat
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia , Vancouver, BC , Canada
| | - Jason L Neva
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia , Vancouver, BC , Canada
| | - Sue Peters
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia , Vancouver, BC , Canada
| | - Jennifer K Ferris
- Graduate Program in Neuroscience, Faculty of Medicine, University of British Columbia , Vancouver, BC , Canada
| | - Lara A Boyd
- Department of Physical Therapy, Faculty of Medicine, University of British Columbia , Vancouver, BC , Canada ; Graduate Program in Neuroscience, Faculty of Medicine, University of British Columbia , Vancouver, BC , Canada
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Ramirez J, McNeely AA, Scott CJ, Stuss DT, Black SE. Subcortical hyperintensity volumetrics in Alzheimer's disease and normal elderly in the Sunnybrook Dementia Study: correlations with atrophy, executive function, mental processing speed, and verbal memory. ALZHEIMERS RESEARCH & THERAPY 2014; 6:49. [PMID: 25478020 PMCID: PMC4255416 DOI: 10.1186/alzrt279] [Citation(s) in RCA: 39] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/16/2013] [Accepted: 07/15/2014] [Indexed: 01/18/2023]
Abstract
INTRODUCTION Subcortical hyperintensities (SHs) are radiological entities commonly observed on magnetic resonance imaging (MRI) of patients with Alzheimer's disease (AD) and normal elderly controls. Although the presence of SH is believed to indicate some form of subcortical vasculopathy, pathological heterogeneity, methodological differences, and the contribution of brain atrophy associated with AD pathology have yielded inconsistent results in the literature. METHODS Using the Lesion Explorer (LE) MRI processing pipeline for SH quantification and brain atrophy, this study examined SH volumes of interest and cognitive function in a sample of patients with AD (n = 265) and normal elderly controls (n = 100) from the Sunnybrook Dementia Study. RESULTS Compared with healthy controls, patients with AD were found to have less gray matter, less white matter, and more sulcal and ventricular cerebrospinal fluid (all significant, P <0.0001). Additionally, patients with AD had greater volumes of whole-brain SH (P <0.01), periventricular SH (pvSH) (P <0.01), deep white SH (dwSH) (P <0.05), and lacunar lesions (P <0.0001). In patients with AD, regression analyses revealed a significant association between global atrophy and pvSH (P = 0.02) and ventricular atrophy with whole-brain SH (P <0.0001). Regional volumes of interest revealed significant correlations with medial middle frontal SH volume and executive function (P <0.001) in normal controls but not in patients with AD, global pvSH volume and mental processing speed (P <0.01) in patients with AD, and left temporal SH volume and memory (P <0.01) in patients with AD. CONCLUSIONS These brain-behavior relationships and correlations with brain atrophy suggest that subtle, yet measurable, signs of small vessel disease may have potential clinical relevance as targets for treatment in Alzheimer's dementia.
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Affiliation(s)
- Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit, 2075 Bayview Avenue, Room A4 21, Toronto, ON M4N 3M5, Canada ; Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Toronto, ON, Canada ; Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Alicia A McNeely
- LC Campbell Cognitive Neurology Research Unit, 2075 Bayview Avenue, Room A4 21, Toronto, ON M4N 3M5, Canada ; Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Toronto, ON, Canada ; Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Christopher Jm Scott
- LC Campbell Cognitive Neurology Research Unit, 2075 Bayview Avenue, Room A4 21, Toronto, ON M4N 3M5, Canada ; Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Toronto, ON, Canada ; Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada
| | - Donald T Stuss
- Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, ON, Canada ; Rotman Research Institute, Baycrest, Toronto, ON, Canada ; Ontario Brain Institute, Toronto, ON, Canada
| | - Sandra E Black
- LC Campbell Cognitive Neurology Research Unit, 2075 Bayview Avenue, Room A4 21, Toronto, ON M4N 3M5, Canada ; Heart & Stroke Foundation Canadian Partnership for Stroke Recovery, Toronto, ON, Canada ; Sunnybrook Health Sciences Centre, Brain Sciences Research Program, Sunnybrook Research Institute, Toronto, ON, Canada ; Faculty of Medicine, Institute of Medical Science, University of Toronto, Toronto, ON, Canada ; Rotman Research Institute, Baycrest, Toronto, ON, Canada
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Object alternation: a novel probe of medial frontal function in frontotemporal dementia. Alzheimer Dis Assoc Disord 2014; 27:316-23. [PMID: 23604006 DOI: 10.1097/wad.0b013e318293b546] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
We studied behavioral variant frontotemporal dementia (bvFTD) using object alternation (OA) as a novel probe of cognition. This task was adopted from animal models and is sensitive to ventrolateral-orbitofrontal and medial frontal function in humans. OA was administered to bvFTD patients, normal controls, and a dementia control group with Alzheimer disease (AD). Two other frontal lobe measures adopted from animal models were administered: delayed response (DR) and delayed alternation (DA). Brain volumes were measured using the semiautomatic brain region extraction method. Compared with the normal controls, bvFTD patients were significantly impaired on OA and DR. For OA and DR, sensitivities and specificities were 100% and 51.5% (cutoff=22.5 errors) and 9.5% and 98% (cutoff=1.5 errors), respectively. Negative predictive value (NPV) for OA was 100% at all prevalence rates. Comparing AD with bvFTD, there were no significant differences on OA, DR, or DA. Nevertheless, positive predictive value (PPV) and NPV were good at all prevalence rates for OA (cutoff=36.5 errors) and DA (cutoff=6 errors); PPV was good for DR (cutoff=9 errors). Error scores above cutoffs favored diagnosis of AD. Performance on OA was significantly related to medial frontal gray matter atrophy. OA, together with DR and DA, may facilitate assessment of bvFTD as a novel probe of medial frontal function.
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Craik FIM, Barense MD, Rathbone CJ, Grusec JE, Stuss DT, Gao F, Scott CJM, Black SE. VL: a further case of erroneous recollection. Neuropsychologia 2014; 56:367-80. [PMID: 24560915 DOI: 10.1016/j.neuropsychologia.2014.02.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/13/2013] [Revised: 02/06/2014] [Accepted: 02/08/2014] [Indexed: 11/19/2022]
Abstract
We report a single-case study of a female patient (VL) who exhibited frequent episodes of erroneous recollections triggered by everyday events. Based on neuropsychological testing, VL was classified as suffering from mild to moderate dementia (MMSE=18) and was given a diagnosis of probable Alzheimer׳s disease. Her memory functions were uniformly impaired but her verbal abilities were generally well preserved. A structural MRI scan showed extensive areas of gray matter atrophy particularly in frontal and medial-temporal (MTL) areas. Results of experimental recognition tests showed that VL had very high false alarm rates on tests using pictures, faces and auditory stimuli, but lower false alarm rates on verbal tests. We provide a speculative account of her erroneous recollections in terms of her MTL and frontal pathology. In outline, we suggest that owing to binding failures in MTL regions, VL׳s recognition processes were forced to rely on earlier than normal stages of analysis. Environmental features on a given recognition trial may have combined with fragments persisting from previous trials resulting in erroneous feelings of familiarity and of recollection that were not discounted or edited out, due to her impaired frontal processes.
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Affiliation(s)
- Fergus I M Craik
- Rotman Research Institute, Toronto, ON, Canada M6A 2E1; University of Toronto, ON, Canada.
| | - Morgan D Barense
- Rotman Research Institute, Toronto, ON, Canada M6A 2E1; University of Toronto, ON, Canada
| | - Clare J Rathbone
- Rotman Research Institute, Toronto, ON, Canada M6A 2E1; Oxford Brookes University, Oxford, UK
| | | | - Donald T Stuss
- Rotman Research Institute, Toronto, ON, Canada M6A 2E1; University of Toronto, ON, Canada
| | - Fuqiang Gao
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada
| | | | - Sandra E Black
- Rotman Research Institute, Toronto, ON, Canada M6A 2E1; University of Toronto, ON, Canada; Sunnybrook Health Sciences Centre, Toronto, ON, Canada
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Eilaghi A, Kassner A, Sitartchouk I, Francis PL, Jakubovic R, Feinstein A, Aviv RI. Normal-appearing white matter permeability distinguishes poor cognitive performance in processing speed and working memory. AJNR Am J Neuroradiol 2013; 34:2119-24. [PMID: 23721894 DOI: 10.3174/ajnr.a3539] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
BACKGROUND AND PURPOSE Secondary-progressive MS is characterized by reduced acute inflammation and contrast enhancement but with increased axonal degeneration and cognitive/clinical disability that worsens with advanced disease. Relative recirculation, extracted from DSC is a surrogate measure of BBB integrity. We hypothesized that normal-appearing white matter relative recirculation is reduced in cognitively impaired compared with nonimpaired secondary-progressive MS, reflecting more advanced disease. MATERIALS AND METHODS Cognitive performance was classified as impaired or nonimpaired by use of Minimal Assessment of Cognitive Function In MS test components. Demographic data, brain parenchymal fraction, WM lesion fraction, and weighted mean normal-appearing white matter relative recirculation were compared in cognitively dichotomized groups. Univariate and multivariate logistic regressions were used to study the association between cognitive test results and normal-appearing white matter relative recirculation. RESULTS The mean (SD) age of 36 patients with secondary-progressive MS studied was 55.9 ± 9.3 years; 13 of 36 (36%) patients were male. A highly significant difference between normal-appearing white matter relative recirculation and WM lesion relative recirculation was present for all patients (P < .001). Normal-appearing white matter relative recirculation in impaired patients was significantly lower than in nonimpaired subjects for the Symbol Digit Modalities Test (P = .007), Controlled Word Association Test (P = .008), and Paced Auditory Serial Addition Test (P = .024). The Expanded Disability Status Scale demonstrated an inverse correlation with normal-appearing white matter relative recirculation (r = -0.319, P = .075). After adjustment for confounders, significant normal-appearing white matter relative recirculation reduction persisted for the Symbol Digit Modalities Test (P = .023) and the Paced Auditory Serial Addition Test (P = .047) but not for the Controlled Word Association Test (P = .13) in impaired patients. CONCLUSIONS Significant normal-appearing white matter relative recirculation reduction exists in cognitively impaired patients with secondary-progressive MS, localizing to the domains of processing speed and working memory.
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Levine B, Kovacevic N, Nica EI, Schwartz ML, Gao F, Black SE. Quantified MRI and cognition in TBI with diffuse and focal damage ☆. NEUROIMAGE-CLINICAL 2013; 2:534-541. [PMID: 24049744 PMCID: PMC3773881 DOI: 10.1016/j.nicl.2013.03.015] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
In patients with chronic-phase traumatic brain injury (TBI), structural MRI is readily attainable and provides rich anatomical information, yet the relationship between whole-brain structural MRI measures and neurocognitive outcome is relatively unexplored and can be complicated by the presence of combined focal and diffuse injury. In this study, sixty-three patients spanning the full range of TBI severity received high-resolution structural MRI concurrent with neuropsychological testing. Multivariate statistical analysis assessed covariance patterns between volumes of grey matter, white matter, and sulcal/subdural and ventricular CSF across 38 brain regions and neuropsychological test performance. Patients with diffuse and diffuse + focal injury were analyzed both separately and together. Tests of speeded attention, working memory, and verbal learning and memory robustly covaried with a distributed pattern of volume loss over temporal, ventromedial prefrontal, right parietal regions, and cingulate regions. This pattern was modulated by the presence of large focal lesions, but held even when analyses were restricted to those with diffuse injury. Effects were most consistently observed within grey matter. Relative to regional brain volumetric data, clinically defined injury severity (depth of coma at time of injury) showed only weak relation to neuropsychological outcome. The results showed that neuropsychological test performance in patients with TBI is related to a distributed pattern of volume loss in regions mediating mnemonic and attentional processing. This relationship holds for patients with and without focal lesions, indicating that diffuse injury alone is sufficient to cause significant neuropsychological disability in relation to regional volume loss. Quantified structural brain imaging data provides a highly sensitive index of brain integrity that is related to cognitive functioning in chronic phase TBI.
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Affiliation(s)
- Brian Levine
- Rotman Research Institute, Baycrest, Toronto, Canada
- Department of Psychology, University of Toronto, Canada
- Department of Medicine (Neurology), University of Toronto, Canada
- Corresponding author at: The Rotman Research Institute at Baycrest, 3560 Bathurst St., Toronto, ON, M6A 2E1, Canada. Tel.: + 1 416 785 2500x3593; fax: + 1 416 785 2862.
| | | | | | | | - Fuqiang Gao
- L.C. Campbell Cognitive Neurology Research Unit and Heart and Stroke Foundation Center for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, Canada
| | - Sandra E. Black
- Rotman Research Institute, Baycrest, Toronto, Canada
- Department of Medicine (Neurology), University of Toronto, Canada
- Department of Surgery (Neurosurgery), University of Toronto, Canada
- Department of Medicine (Neurology), Sunnybrook Health Sciences Centre, Toronto, Canada
- L.C. Campbell Cognitive Neurology Research Unit and Heart and Stroke Foundation Center for Stroke Recovery, Sunnybrook Health Sciences Centre, Toronto, Canada
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Riley C, Azevedo C, Bailey M, Pelletier D. Clinical applications of imaging disease burden in multiple sclerosis: MRI and advanced imaging techniques. Expert Rev Neurother 2012; 12:323-33. [PMID: 22364331 DOI: 10.1586/ern.11.196] [Citation(s) in RCA: 10] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/25/2022]
Abstract
This review will address the critical role of radiographic techniques in monitoring multiple sclerosis disease course and response to therapeutic interventions using conventional imaging. We propose an algorithm of obtaining a contrast-enhanced brain MRI 6 months after starting a disease-modifying therapy, and considering a gadolinium-enhancing lesion on that scan to indicate suboptimal response to therapy. New or enlarging T2 lesions should be followed on scans at 6-month intervals to assess for change, and the presence of one or more enhancing lesions on a 6- or 12-month scan, or two or more new or enlarging T2 lesions on a 12-month scan should prompt consideration of therapy change. New techniques such as PET imaging, magnetic resonance spectroscopy, magnetic resonance relaxometry, iron-sensitive imaging and perfusion MRI will also be overviewed, with their potential roles in monitoring disease course and activity.
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Affiliation(s)
- Claire Riley
- Yale University School of Medicine, Yale Multiple Sclerosis Center, 40 Temple St LL, New Haven, CT 06510, USA.
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Ramirez J, Scott CJM, Black SE. A short-term scan-rescan reliability test measuring brain tissue and subcortical hyperintensity volumetrics obtained using the lesion explorer structural MRI processing pipeline. Brain Topogr 2012; 26:35-8. [PMID: 22562092 DOI: 10.1007/s10548-012-0228-z] [Citation(s) in RCA: 20] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/08/2012] [Accepted: 04/20/2012] [Indexed: 11/28/2022]
Abstract
Lesion Explorer (LE) is a reliable and comprehensive MRI-derived tissue segmentation and brain region parcellation processing pipeline for obtaining intracranial tissue and subcortical hyperintensity (SH) volumetrics. The processing pipeline segments: gray (GM) and white matter (WM); sulcal (sCSF) and ventricular cerebrospinal fluid (vCSF); periventricular (pvSH) and deep white subcortical hyperintensities (dwSH); and cystic fluid filled lacunar-like infarcts (Lacunar); into 26 regions of interest. A short-term scan-rescan reliability test was performed on 20 healthy volunteers: 10 older (mean = 77.7 years, SD = 11.1) and 10 younger (mean = 29.4 years, SD = 7.1). Each participant was scanned twice with an average interscan interval of 15.4 days (range: 29 min-50 days). Results suggest low technique-related error as indicated by excellent intraclass correlation coefficient (ICC) results, with ICCs above 0.90 (p < 0.05) for GM, WM, and CSF, in all 26 regions of interest (13 per hemisphere). Ventricular and lesion sub-type (pvSH, dwSH, and Lacunar) volumes also showed high scan-rescan reliability (dwSH = 0.9998, pvSH = 0.9998, Lacunar = 0.9859, p < 0.01). As indicated by the results of this short-term scan-rescan study, the LE structural MRI processing pipeline can be applied for longitudinal volumetric analyses with confidence.
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Affiliation(s)
- Joel Ramirez
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
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Chow, Gao, Links, Ween, Tang-Wai, Ramirez, Scott, Freedman, Stuss, Black. Visual rating versus volumetry to detect frontotemporal dementia. Dement Geriatr Cogn Disord 2011; 31:371-8. [PMID: 21625137 PMCID: PMC3202946 DOI: 10.1159/000328415] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Accepted: 04/08/2011] [Indexed: 11/19/2022] Open
Abstract
BACKGROUND/AIMS Automated, volumetrically defined atrophy in the left anterior cingulate (LAC) and anterior temporal regions (LAT) on MRI can be used to distinguish most patients with frontotemporal dementia (FTD) from controls. FTD and Alzheimer's disease (AD) can differ in the degree of anterior temporal atrophy. We explored whether clinicians can visually detect this atrophy pattern and whether they can use it to classify the 2 groups of dementia patients with the same accuracy. METHODS Four neurologists rated atrophy in the LAC and LAT regions on MRI slices from 21 FTD, 21 controls, and 14 AD participants. Inter-rater reliability and diagnostic accuracy were assessed. RESULTS All 4 raters agreed on the presence of clinically significant atrophy, and their atrophy scoring correlated with the volumes, but without translation into high inter-rater diagnostic agreement. CONCLUSIONS Volumetric analyses are difficult to translate into routine clinical practice.
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Affiliation(s)
- Chow
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, Ont., Canada,Department of Psychiatry (Division of Geriatric Psychiatry), University of Toronto, Toronto, Ont., Canada,Division of Neurology, Baycrest, Toronto, Ont., Canada,Rotman Research Institute, Baycrest, Toronto, Ont., Canada,*Tiffany Chow, MD, Baycrest Rotman Research Institute, 3560 Bathurst Street, 8th Floor Posluns Building, Toronto, ON M6A 2E1 (Canada), Tel. +1 416 785 2500, ext. 3459, E-Mail
| | - Gao
- L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Ont., Canada
| | - Links
- Rotman Research Institute, Baycrest, Toronto, Ont., Canada
| | - Ween
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, Ont., Canada,Division of Neurology, Baycrest, Toronto, Ont., Canada,Kunin-Lunenfeld Applied Research Unit, Baycrest, Toronto, Ont., Canada
| | - Tang-Wai
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, Ont., Canada,Toronto Western Hospital Division of Neurology, University Health Network Memory Clinic, Toronto, Ont., Canada
| | - Ramirez
- L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Ont., Canada
| | - Scott
- L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Ont., Canada
| | - Freedman
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, Ont., Canada,Institute of Medical Sciences, University of Toronto, Toronto, Ont., Canada,Division of Neurology, Baycrest, Toronto, Ont., Canada,Rotman Research Institute, Baycrest, Toronto, Ont., Canada,Toronto Western Hospital Division of Neurology, University Health Network Memory Clinic, Toronto, Ont., Canada,Division of Neurology, Mt. Sinai Hospital, Toronto, Ont., Canada
| | - Stuss
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, Ont., Canada,Department of Psychology, University of Toronto, Toronto, Ont., Canada,Institute of Medical Sciences, University of Toronto, Toronto, Ont., Canada,Division of Neurology, Baycrest, Toronto, Ont., Canada,Rotman Research Institute, Baycrest, Toronto, Ont., Canada
| | - Black
- Department of Medicine (Division of Neurology), University of Toronto, Toronto, Ont., Canada,Institute of Medical Sciences, University of Toronto, Toronto, Ont., Canada,Division of Neurology, Baycrest, Toronto, Ont., Canada,Rotman Research Institute, Baycrest, Toronto, Ont., Canada,L.C. Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Ont., Canada
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Ghaffar O, Lobaugh NJ, Szilagyi GM, Reis M, O'Connor P, Feinstein A. Imaging genetics in multiple sclerosis: a volumetric and diffusion tensor MRI study of APOE ε4. Neuroimage 2011; 58:724-31. [PMID: 21723395 DOI: 10.1016/j.neuroimage.2011.06.024] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2011] [Revised: 06/07/2011] [Accepted: 06/09/2011] [Indexed: 11/30/2022] Open
Abstract
Evidence linking the ε4 allele of APOE to more severe brain MRI abnormalities in multiple sclerosis (MS) has been conflicting and limited to studies of lesion load and whole brain atrophy. The purpose of the present study was to determine whether the ε4 allele of APOE is associated with more extensive brain pathology in MS using structural and diffusion tensor MRI. Using a case-control design, 43 MS patients with the ε4 allele and 47 ε4 negative MS patients underwent structural and diffusion tensor imaging (DTI) at 3T. Hypo- and hyperintense lesion volumes, whole brain and medial temporal volumes, and DTI parameters (fractional anisotropy (FA) and mean diffusivity (MD)) in normal-appearing brain tissue and lesions were compared between the groups. ε4+ and ε4- MS patients were well-matched on demographic characteristics, disease variables, and proportions receiving disease-modifying therapy. ε4+ and ε4- patients did not differ on any MRI or DTI measure. This study refutes a role for the ε4 allele in MRI abnormalities in MS, particularly those linking ε4 to greater T1 hypointense lesion volume and brain atrophy. Previous work on this putative gene-MRI relationship is extended by comparing DTI measures within lesions and normal-appearing brain tissue. A lack of differences in medial temporal regions, areas that have been linked to ε4-associated changes in health and disease, further supports the conclusion that that ε4 is not associated with more subtle MRI markers of brain pathology in MS.
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Affiliation(s)
- Omar Ghaffar
- Brain Sciences Program, Sunnybrook Health Sciences Centre, Toronto, ON, Canada.
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Gibson E, Gao F, Black SE, Lobaugh NJ. Automatic segmentation of white matter hyperintensities in the elderly using FLAIR images at 3T. J Magn Reson Imaging 2010; 31:1311-22. [PMID: 20512882 PMCID: PMC2905619 DOI: 10.1002/jmri.22004] [Citation(s) in RCA: 87] [Impact Index Per Article: 5.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
Purpose To determine the precision and accuracy of an automated method for segmenting white matter hyperintensities (WMH) on fast fluid-attenuated inversion-recovery (FLAIR) images in elderly brains at 3T. Materials and Methods FLAIR images from 18 individuals (60–82 years, 9 females) with WMH burdens ranging from 1–80 cm3 were used. The protocol included the removal of clearly hyperintense voxels; two-class fuzzy C-means clustering (FCM); and thresholding to segment probable WMH. Two false-positive minimization (FPM) methods using white matter templates were tested. Precision was assessed by adding synthetic hyperintense voxels to brain slices. Accuracy was validated by comparing automatic and manual segmentations. Whole-brain, voxel-wise metrics of similarity, under- and overestimation were used to evaluate both precision and accuracy. Results Precision was high, as the lowest accuracy in the synthetic datasets was 93%. Both FPM strategies successfully improved overall accuracy. Whole-brain accuracy for the FCM segmentation alone ranged from 45%–81%, which improved to 75%–85% using the FPM strategies. Conclusion The method was accurate across the range of WMH burden typically seen in the elderly. Accuracy levels achieved or exceeded those of other approaches using multispectral and/or more sophisticated pattern recognition methods. J. Magn. Reson. Imaging 2010;31:1311–1322. © 2010 Wiley-Liss, Inc.
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Affiliation(s)
- Erin Gibson
- Cognitive Neurology, Sunnybrook Health Sciences Centre, Toronto, Ontario M4N 3M5, Canada
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Ramirez J, Gibson E, Quddus A, Lobaugh NJ, Feinstein A, Levine B, Scott CJM, Levy-Cooperman N, Gao FQ, Black SE. Lesion Explorer: a comprehensive segmentation and parcellation package to obtain regional volumetrics for subcortical hyperintensities and intracranial tissue. Neuroimage 2010; 54:963-73. [PMID: 20849961 DOI: 10.1016/j.neuroimage.2010.09.013] [Citation(s) in RCA: 96] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/17/2010] [Revised: 09/01/2010] [Accepted: 09/03/2010] [Indexed: 12/16/2022] Open
Abstract
Subcortical hyperintensities (SH) are a commonly observed phenomenon on MRI of the aging brain (Kertesz et al., 1988). Conflicting behavioral, cognitive and pathological associations reported in the literature underline the need to develop an intracranial volumetric analysis technique to elucidate pathophysiological origins of SH in Alzheimer's disease (AD), vascular cognitive impairment (VCI) and normal aging (De Leeuw et al., 2001; Mayer and Kier, 1991; Pantoni and Garcia, 1997; Sachdev et al., 2008). The challenge is to develop processing tools that effectively and reliably quantify subcortical small vessel disease in the context of brain tissue compartments. Segmentation and brain region parcellation should account for SH subtypes which are often classified as: periventricular (pvSH) and deep white (dwSH), incidental white matter disease or lacunar infarcts and Virchow-Robin spaces. Lesion Explorer (LE) was developed as the final component of a comprehensive volumetric segmentation and parcellation image processing stream built upon previously published methods (Dade et al., 2004; Kovacevic et al., 2002). Inter-rater and inter-method reliability was accomplished both globally and regionally. Volumetric analysis showed high inter-rater reliability both globally (ICC=.99) and regionally (ICC=.98). Pixel-wise spatial congruence was also high (SI=.97). Whole brain pvSH volumes yielded high inter-rater reliability (ICC=.99). Volumetric analysis against an alternative kNN segmentation revealed high inter-method reliability (ICC=.97). Comparison with visual rating scales showed high significant correlations (ARWMC: r=.86; CHIPS: r=.87). The pipeline yields a comprehensive and reliable individualized volumetric profile for subcortical vasculopathy that includes regionalized (26 brain regions) measures for: GM, WM, sCSF, vCSF, lacunar and non-lacunar pvSH and dwSH.
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Affiliation(s)
- J Ramirez
- LC Campbell Cognitive Neurology Research Unit, Sunnybrook Health Sciences Centre, Toronto, Ontario, Canada.
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Antulov R, Carone DA, Bruce J, Yella V, Dwyer MG, Tjoa CW, Benedict RHB, Zivadinov R. Regionally Distinct White Matter Lesions Do Not Contribute to Regional Gray Matter Atrophy in Patients with Multiple Sclerosis. J Neuroimaging 2010; 21:210-8. [DOI: 10.1111/j.1552-6569.2010.00482.x] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022] Open
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Blaizot X, Mansilla F, Insausti AM, Constans JM, Salinas-Alamán A, Pró-Sistiaga P, Mohedano-Moriano A, Insausti R. The human parahippocampal region: I. Temporal pole cytoarchitectonic and MRI correlation. Cereb Cortex 2010; 20:2198-212. [PMID: 20064939 PMCID: PMC2923216 DOI: 10.1093/cercor/bhp289] [Citation(s) in RCA: 81] [Impact Index Per Article: 5.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/18/2023] Open
Abstract
The temporal pole (TP) is the rostralmost portion of the human temporal lobe. Characteristically, it is only present in human and nonhuman primates. TP has been implicated in different cognitive functions such as emotion, attention, behavior, and memory, based on functional studies performed in healthy controls and patients with neurodegenerative diseases through its anatomical connections (amygdala, pulvinar, orbitofrontal cortex). TP was originally described as a single uniform area by Brodmann area 38, and von Economo (area TG of von Economo and Koskinas), and little information on its cytoarchitectonics is known in humans. We hypothesize that 1) TP is not a homogenous area and we aim first at fixating the precise extent and limits of temporopolar cortex (TPC) with adjacent fields and 2) its structure can be correlated with structural magnetic resonance images. We describe here the macroscopic characteristics and cytoarchitecture as two subfields, a medial and a lateral area, that constitute TPC also noticeable in 2D and 3D reconstructions. Our findings suggest that the human TP is a heterogeneous region formed exclusively by TPC for about 7 mm of the temporal tip, and that becomes progressively restricted to the medial and ventral sides of the TP. This cortical area presents topographical and structural features in common with nonhuman primates, which suggests an evolutionary development in human species.
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Affiliation(s)
- X Blaizot
- Department of Health Sciences, School of Medicine, University of Castilla-La Mancha, 02006 Albacete, Spain
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Feinstein A, O'Connor P, Akbar N, Moradzadeh L, Scott CJM, Lobaugh NJ. Diffusion tensor imaging abnormalities in depressed multiple sclerosis patients. Mult Scler 2009; 16:189-96. [PMID: 20007425 DOI: 10.1177/1352458509355461] [Citation(s) in RCA: 69] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/01/2023]
Abstract
Depression is common in patients with multiple sclerosis, but to date no studies have explored diffusion tensor imaging indices associated with mood change. This study aimed to determine cerebral correlates of depression in multiple sclerosis patients using diffusion tensor imaging. Sixty-two subjects with multiple sclerosis were assessed for depression with the Beck Depression Inventory (BDI-II). All subjects underwent magnetic resonance imaging. Whole brain and regional volumes were calculated for lesions (hyper/hypointense) and normal-appearing white and grey matter. Fractional anisotropy and mean diffusivity were calculated for each brain region. Magnetic resonance imaging comparisons were undertaken between depressed (Beck Depression Inventory > or = 19) and non-depressed subjects. Depressed subjects (n = 30) had a higher hypointense lesion volume in the right medial inferior frontal region, a smaller normal-appearing white matter volume in the left superior frontal region, and lower fractional anisotropy and higher mean diffusivity in the left anterior temporal normal-appearing white matter and normal-appearing grey matter regions, respectively. Depressed subjects also had higher mean diffusivity in right inferior frontal hyperintense lesions. Magnetic resonance imaging variables contributed to 43% of the depression variance. We conclude that the presence of more marked diffusion tensor imaging abnormalities in the normal-appearing white matter and normal-appearing grey matter of depressed subjects highlights the importance of more subtle measures of structural brain change in the pathogenesis of depression.
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Affiliation(s)
- A Feinstein
- Department of Psychiatry, University of Toronto, Toronto, Canada.
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