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Cho S, Olm CA, Ash S, Shellikeri S, Agmon G, Cousins KAQ, Irwin DJ, Grossman M, Liberman M, Nevler N. Automatic classification of AD pathology in FTD phenotypes using natural speech. Alzheimers Dement 2024. [PMID: 38572850 DOI: 10.1002/alz.13748] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2023] [Revised: 01/23/2024] [Accepted: 01/24/2024] [Indexed: 04/05/2024]
Abstract
INTRODUCTION Screening for Alzheimer's disease neuropathologic change (ADNC) in individuals with atypical presentations is challenging but essential for clinical management. We trained automatic speech-based classifiers to distinguish frontotemporal dementia (FTD) patients with ADNC from those with frontotemporal lobar degeneration (FTLD). METHODS We trained automatic classifiers with 99 speech features from 1 minute speech samples of 179 participants (ADNC = 36, FTLD = 60, healthy controls [HC] = 89). Patients' pathology was assigned based on autopsy or cerebrospinal fluid analytes. Structural network-based magnetic resonance imaging analyses identified anatomical correlates of distinct speech features. RESULTS Our classifier showed 0.88 ± $ \pm $ 0.03 area under the curve (AUC) for ADNC versus FTLD and 0.93 ± $ \pm $ 0.04 AUC for patients versus HC. Noun frequency and pause rate correlated with gray matter volume loss in the limbic and salience networks, respectively. DISCUSSION Brief naturalistic speech samples can be used for screening FTD patients for underlying ADNC in vivo. This work supports the future development of digital assessment tools for FTD. HIGHLIGHTS We trained machine learning classifiers for frontotemporal dementia patients using natural speech. We grouped participants by neuropathological diagnosis (autopsy) or cerebrospinal fluid biomarkers. Classifiers well distinguished underlying pathology (Alzheimer's disease vs. frontotemporal lobar degeneration) in patients. We identified important features through an explainable artificial intelligence approach. This work lays the groundwork for a speech-based neuropathology screening tool.
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Affiliation(s)
- Sunghye Cho
- Linguistic Data Consortium, Department of Linguistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Christopher A Olm
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sharon Ash
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Sanjana Shellikeri
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Galit Agmon
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Katheryn A Q Cousins
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Mark Liberman
- Linguistic Data Consortium, Department of Linguistics, University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - Naomi Nevler
- Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, Pennsylvania, USA
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Phillips JS, Adluru N, Chung MK, Radhakrishnan H, Olm CA, Cook PA, Gee JC, Cousins KAQ, Arezoumandan S, Wolk DA, McMillan CT, Grossman M, Irwin DJ. Greater white matter degeneration and lower structural connectivity in non-amnestic vs. amnestic Alzheimer's disease. Front Neurosci 2024; 18:1353306. [PMID: 38567286 PMCID: PMC10986184 DOI: 10.3389/fnins.2024.1353306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/10/2023] [Accepted: 02/26/2024] [Indexed: 04/04/2024] Open
Abstract
Introduction Multimodal evidence indicates Alzheimer's disease (AD) is characterized by early white matter (WM) changes that precede overt cognitive impairment. WM changes have overwhelmingly been investigated in typical, amnestic mild cognitive impairment and AD; fewer studies have addressed WM change in atypical, non-amnestic syndromes. We hypothesized each non-amnestic AD syndrome would exhibit WM differences from amnestic and other non-amnestic syndromes. Materials and methods Participants included 45 cognitively normal (CN) individuals; 41 amnestic AD patients; and 67 patients with non-amnestic AD syndromes including logopenic-variant primary progressive aphasia (lvPPA, n = 32), posterior cortical atrophy (PCA, n = 17), behavioral variant AD (bvAD, n = 10), and corticobasal syndrome (CBS, n = 8). All had T1-weighted MRI and 30-direction diffusion-weighted imaging (DWI). We performed whole-brain deterministic tractography between 148 cortical and subcortical regions; connection strength was quantified by tractwise mean generalized fractional anisotropy. Regression models assessed effects of group and phenotype as well as associations with grey matter volume. Topological analyses assessed differences in persistent homology (numbers of graph components and cycles). Additionally, we tested associations of topological metrics with global cognition, disease duration, and DWI microstructural metrics. Results Both amnestic and non-amnestic patients exhibited lower WM connection strength than CN participants in corpus callosum, cingulum, and inferior and superior longitudinal fasciculi. Overall, non-amnestic patients had more WM disease than amnestic patients. LvPPA patients had left-lateralized WM degeneration; PCA patients had reductions in connections to bilateral posterior parietal, occipital, and temporal areas. Topological analysis showed the non-amnestic but not the amnestic group had more connected components than controls, indicating persistently lower connectivity. Longer disease duration and cognitive impairment were associated with more connected components and fewer cycles in individuals' brain graphs. Discussion We have previously reported syndromic differences in GM degeneration and tau accumulation between AD syndromes; here we find corresponding differences in WM tracts connecting syndrome-specific epicenters. Determining the reasons for selective WM degeneration in non-amnestic AD is a research priority that will require integration of knowledge from neuroimaging, biomarker, autopsy, and functional genetic studies. Furthermore, longitudinal studies to determine the chronology of WM vs. GM degeneration will be key to assessing evidence for WM-mediated tau spread.
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Affiliation(s)
- Jeffrey S. Phillips
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Nagesh Adluru
- Waisman Center, University of Wisconsin-Madison, Madison, WI, United States
- Department of Radiology, University of Wisconsin-Madison, Madison, WI, United States
| | - Moo K. Chung
- Department of Biostatistics and Medical Informatics, School of Medicine and Public Health, University of Wisconsin-Madison, Madison, WI, United States
| | - Hamsanandini Radhakrishnan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Christopher A. Olm
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Philip A. Cook
- Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - James C. Gee
- Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Katheryn A. Q. Cousins
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Sanaz Arezoumandan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David A. Wolk
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Penn Memory Center, University of Pennsylvania Health System, Philadelphia, PA, United States
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - David J. Irwin
- Penn Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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Nevler N, Cho S, Cousins KAQ, Ash S, Olm CA, Shellikeri S, Agmon G, Gonzalez-Recober C, Xie SX, Barker MS, Manoochehri M, Mcmillan CT, Irwin DJ, Massimo L, Dratch L, Cheran G, Huey ED, Cosentino SA, Van Deerlin VM, Liberman MY, Grossman M. Changes in Digital Speech Measures in Asymptomatic Carriers of Pathogenic Variants Associated With Frontotemporal Degeneration. Neurology 2024; 102:e207926. [PMID: 38165329 DOI: 10.1212/wnl.0000000000207926] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/27/2023] [Accepted: 10/03/2023] [Indexed: 01/03/2024] Open
Abstract
BACKGROUND AND OBJECTIVES Clinical trials developing therapeutics for frontotemporal degeneration (FTD) focus on pathogenic variant carriers at preclinical stages. Objective, quantitative clinical assessment tools are needed to track stability and delayed disease onset. Natural speech can serve as an accessible, cost-effective assessment tool. We aimed to identify early changes in the natural speech of FTD pathogenic variant carriers before they become symptomatic. METHODS In this cohort study, speech samples of picture descriptions were collected longitudinally from healthy participants in observational studies at the University of Pennsylvania and Columbia University between 2007 and 2020. Participants were asymptomatic but at risk for familial FTD. Status as "carrier" or "noncarrier" was based on screening for known pathogenic variants in the participant's family. Thirty previously validated digital speech measures derived from automatic speech processing pipelines were selected a priori based on previous studies in patients with FTD and compared between asymptomatic carriers and noncarriers cross-sectionally and longitudinally. RESULTS A total of 105 participants, all asymptomatic, included 41 carriers: 12 men [30%], mean age 43 ± 13 years; education, 16 ± 2 years; MMSE 29 ± 1; and 64 noncarriers: 27 men [42%]; mean age, 48 ± 14 years; education, 15 ± 3 years; MMSE 29 ± 1. We identified 4 speech measures that differed between carriers and noncarriers at baseline: mean speech segment duration (mean difference -0.28 seconds, 95% CI -0.55 to -0.02, p = 0.04); word frequency (mean difference 0.07, 95% CI 0.008-0.14, p = 0.03); word ambiguity (mean difference 0.02, 95% CI 0.0008-0.05, p = 0.04); and interjection count per 100 words (mean difference 0.33, 95% CI 0.07-0.59, p = 0.01). Three speech measures deteriorated over time in carriers only: particle count per 100 words per month (β = -0.02, 95% CI -0.03 to -0.004, p = 0.009); total narrative production time in seconds per month (β = -0.24, 95% CI -0.37 to -0.12, p < 0.001); and total number of words per month (β = -0.48, 95% CI -0.78 to -0.19, p = 0.002) including in 3 carriers who later converted to symptomatic disease. DISCUSSION Using automatic processing pipelines, we identified early changes in the natural speech of FTD pathogenic variant carriers in the presymptomatic stage. These findings highlight the potential utility of natural speech as a digital clinical outcome assessment tool in FTD, where objective and quantifiable measures for abnormal behavior and language are lacking.
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Affiliation(s)
- Naomi Nevler
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Sunghye Cho
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Katheryn A Q Cousins
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Sharon Ash
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Christopher A Olm
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Sanjana Shellikeri
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Galit Agmon
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Carmen Gonzalez-Recober
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Sharon X Xie
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Megan S Barker
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Masood Manoochehri
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Corey T Mcmillan
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - David J Irwin
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Lauren Massimo
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Laynie Dratch
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Gayathri Cheran
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Edward D Huey
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Stephanie A Cosentino
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Vivianna M Van Deerlin
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Mark Y Liberman
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
| | - Murray Grossman
- From the Frontotemporal Degeneration Center, Department of Neurology, (N.N., K.A.Q.C., S.A., C.A.O., S.S., G.A., C.G.-R., C.T.M., D.J.I., L.M., L.D., M.G.), Linguistic Data Consortium, Department of Linguistics (S.C., M.Y.L.), Penn Image Computing and Science Laboratory, Department of Radiology (C.A.O.), Department of Biostatistics, Epidemiology and Informatics (S.X.X.), and Department of Pathology and Laboratory Medicine (V.M.V.D.), Perelman School of Medicine, University of Pennsylvania, Philadelphia; Taub Institute for Research on Alzheimer's Disease and the Aging Brain (M.S.B.,M.M., G.C., E.D.H., S.A.C.); and Department of Neurology (G.C., E.D.H., S.A.C.) and Gertrude H. Sergievsky Center (S.A.C.), Columbia University Irving Medical Center, New York
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4
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Ohm DT, Rhodes E, Bahena A, Capp N, Lowe M, Sabatini P, Trotman W, Olm CA, Phillips J, Prabhakaran K, Rascovsky K, Massimo L, McMillan C, Gee J, Tisdall MD, Yushkevich PA, Lee EB, Grossman M, Irwin DJ. Neuroanatomical and cellular degeneration associated with a social disorder characterized by new ritualistic belief systems in a TDP-C patient vs. a Pick patient. Front Neurol 2023; 14:1245886. [PMID: 37900607 PMCID: PMC10600461 DOI: 10.3389/fneur.2023.1245886] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2023] [Accepted: 08/15/2023] [Indexed: 10/31/2023] Open
Abstract
Frontotemporal dementia (FTD) is a spectrum of clinically and pathologically heterogenous neurodegenerative dementias. Clinical and anatomical variants of FTD have been described and associated with underlying frontotemporal lobar degeneration (FTLD) pathology, including tauopathies (FTLD-tau) or TDP-43 proteinopathies (FTLD-TDP). FTD patients with predominant degeneration of anterior temporal cortices often develop a language disorder of semantic knowledge loss and/or a social disorder often characterized by compulsive rituals and belief systems corresponding to predominant left or right hemisphere involvement, respectively. The neural substrates of these complex social disorders remain unclear. Here, we present a comparative imaging and postmortem study of two patients, one with FTLD-TDP (subtype C) and one with FTLD-tau (subtype Pick disease), who both developed new rigid belief systems. The FTLD-TDP patient developed a complex set of values centered on positivity and associated with specific physical and behavioral features of pigs, while the FTLD-tau patient developed compulsive, goal-directed behaviors related to general themes of positivity and spirituality. Neuroimaging showed left-predominant temporal atrophy in the FTLD-TDP patient and right-predominant frontotemporal atrophy in the FTLD-tau patient. Consistent with antemortem cortical atrophy, histopathologic examinations revealed severe loss of neurons and myelin predominantly in the anterior temporal lobes of both patients, but the FTLD-tau patient showed more bilateral, dorsolateral involvement featuring greater pathology and loss of projection neurons and deep white matter. These findings highlight that the regions within and connected to anterior temporal lobes may have differential vulnerability to distinct FTLD proteinopathies and serve important roles in human belief systems.
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Affiliation(s)
- Daniel T. Ohm
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Emma Rhodes
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Alejandra Bahena
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Noah Capp
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - MaKayla Lowe
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Philip Sabatini
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Winifred Trotman
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Christopher A. Olm
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Jeffrey Phillips
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Karthik Prabhakaran
- Penn Image Computing and Science Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Katya Rascovsky
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Lauren Massimo
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - Corey McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - James Gee
- Penn Image Computing and Science Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - M. Dylan Tisdall
- Center for Advanced Magnetic Resonance Imaging and Spectroscopy, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Paul A. Yushkevich
- Penn Image Computing and Science Lab, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Edward B. Lee
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - David J. Irwin
- Penn Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
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5
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Chen M, Burke S, Olm CA, Irwin DJ, Massimo L, Lee EB, Trojanowski JQ, Gee JC, Grossman M. Antemortem network analysis of spreading pathology in autopsy-confirmed frontotemporal degeneration. Brain Commun 2023; 5:fcad147. [PMID: 37223129 PMCID: PMC10202556 DOI: 10.1093/braincomms/fcad147] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2022] [Revised: 03/15/2023] [Accepted: 05/10/2023] [Indexed: 05/25/2023] Open
Abstract
Despite well-articulated hypotheses of spreading pathology in animal models of neurodegenerative disease, the basis for spreading neurodegenerative pathology in humans has been difficult to ascertain. In this study, we used graph theoretic analyses of structural networks in antemortem, multimodal MRI from autopsy-confirmed cases to examine spreading pathology in sporadic frontotemporal lobar degeneration. We defined phases of progressive cortical atrophy on T1-weighted MRI using a published algorithm in autopsied frontotemporal lobar degeneration with tau inclusions or with transactional DNA binding protein of ∼43 kDa inclusions. We studied global and local indices of structural networks in each of these phases, focusing on the integrity of grey matter hubs and white matter edges projecting between hubs. We found that global network measures are compromised to an equal degree in patients with frontotemporal lobar degeneration with tau inclusions and frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions compared to healthy controls. While measures of local network integrity were compromised in both frontotemporal lobar degeneration with tau inclusions and frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions, we discovered several important characteristics that distinguished between these groups. Hubs identified in controls were degraded in both patient groups, but degraded hubs were associated with the earliest phase of cortical atrophy (i.e. epicentres) only in frontotemporal lobar degeneration with tau inclusions. Degraded edges were significantly more plentiful in frontotemporal lobar degeneration with tau inclusions than in frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions, suggesting that the spread of tau pathology involves more significant white matter degeneration. Weakened edges were associated with degraded hubs in frontotemporal lobar degeneration with tau inclusions more than in frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions, particularly in the earlier phases of the disease, and phase-to-phase transitions in frontotemporal lobar degeneration with tau inclusions were characterized by weakened edges in earlier phases projecting to diseased hubs in subsequent phases of the disease. When we examined the spread of pathology from a region diseased in an earlier phase to physically adjacent regions in subsequent phases, we found greater evidence of disease spreading to adjacent regions in frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions than in frontotemporal lobar degeneration with tau inclusions. We associated evidence of degraded grey matter hubs and weakened white matter edges with quantitative measures of digitized pathology from direct observations of patients' brain samples. We conclude from these observations that the spread of pathology from diseased regions to distant regions via weakened long-range edges may contribute to spreading disease in frontotemporal dementia-tau, while spread of pathology to physically adjacent regions via local neuronal connectivity may play a more prominent role in spreading disease in frontotemporal lobar degeneration-transactional DNA binding protein of ∼43 kDa inclusions.
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Affiliation(s)
- Min Chen
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Sarah Burke
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Christopher A Olm
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - David J Irwin
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Lauren Massimo
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Center for Neurodegenerative Disease Research, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - James C Gee
- Department of Radiology, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
| | - Murray Grossman
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Bioengineering, Bioengineering Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
- Department of Neurology, Neuroscience Graduate Group, University of Pennsylvania, Philadelphia, PA 19104, USA
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6
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Olm CA, Burke SE, Peterson C, Lee EB, Trojanowski JQ, Massimo L, Irwin DJ, Grossman M, Gee JC. Event-based modeling of T1-weighted MRI is related to pathology in frontotemporal lobar degeneration due to tau and TDP. Neuroimage Clin 2022; 37:103285. [PMID: 36508888 PMCID: PMC9763503 DOI: 10.1016/j.nicl.2022.103285] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/22/2022] [Revised: 12/05/2022] [Accepted: 12/06/2022] [Indexed: 12/12/2022]
Abstract
BACKGROUND In previous studies of patients with frontotemporal lobar degeneration due to tau (FTLD-tau) and FTLD due to TDP (FTLD-TDP), cortical volumes derived from T1-weighted MRI have been used to identify a sequence of volume loss according to arbitrary volumetric criteria. Event-based modeling (EBM) is a probabilistic, generative machine learning model that determines the characteristic sequence of changes, or "events", occurring during disease progression. EBM also estimates an individual patient's disease "stage" by identifying which events have already occurred. In the present study, we use an EBM analysis to derive stages of regional anatomic atrophy in FTLD-tau and FTLD-TDP, and validated these stages against pathologic burden. METHODS Sporadic autopsy-confirmed patients with FTLD-tau (N = 42) and FTLD-TDP (N = 21), and 167 healthy controls with available T1-weighted images were identified. A subset of patients had quantitative digital histopathology of cortex performed at autopsy (FTLD-tau = 30, FTLD-TDP = 17). MRI images were processed, producing regional measures of cortical volumes. K-means clustering was used to find cortical regions with similar amounts of GM volume changes (n = 5 clusters). EBM was used to determine the characteristic sequence of cortical atrophy of identified clusters in autopsy-confirmed FTLD-tau and FTLD-TDP, and estimate each patient's disease stage by cortical volume biomarkers. Linear regressions related pathologic burden to EBM-estimated disease stages. RESULTS EBM for cortical volume biomarkers generated statistically robust characteristic sequences of cortical atrophy in each group of patients. Cortical volume-based EBM-estimated disease stage was associated with pathologic burden in FTLD-tau (R2 = 0.16, p = 0.017) and FTLD-TDP (R2 = 0.51, p = 0.0008). CONCLUSIONS We provide evidence that EBM can identify sequences of pathologically-confirmed cortical atrophy in sporadic FTLD-tau and FTLD-TDP.
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Affiliation(s)
- Christopher A Olm
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States; Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
| | - Sarah E Burke
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
| | - Claire Peterson
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States; Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States.
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Lauren Massimo
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States; Digital Neuropathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
| | - James C Gee
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States.
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7
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Adebimpe A, Bertolero M, Dolui S, Cieslak M, Murtha K, Baller EB, Boeve B, Boxer A, Butler ER, Cook P, Colcombe S, Covitz S, Davatzikos C, Davila DG, Elliott MA, Flounders MW, Franco AR, Gur RE, Gur RC, Jaber B, McMillian C, Milham M, Mutsaerts HJMM, Oathes DJ, Olm CA, Phillips JS, Tackett W, Roalf DR, Rosen H, Tapera TM, Tisdall MD, Zhou D, Esteban O, Poldrack RA, Detre JA, Satterthwaite TD. ASLPrep: a platform for processing of arterial spin labeled MRI and quantification of regional brain perfusion. Nat Methods 2022; 19:683-686. [PMID: 35689029 PMCID: PMC10548890 DOI: 10.1038/s41592-022-01458-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2021] [Accepted: 03/17/2022] [Indexed: 11/08/2022]
Abstract
Arterial spin labeled (ASL) magnetic resonance imaging (MRI) is the primary method for noninvasively measuring regional brain perfusion in humans. We introduce ASLPrep, a suite of software pipelines that ensure the reproducible and generalizable processing of ASL MRI data.
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Affiliation(s)
- Azeez Adebimpe
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Maxwell Bertolero
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Sudipto Dolui
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew Cieslak
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Kristin Murtha
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Erica B Baller
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Bradley Boeve
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Adam Boxer
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Ellyn R Butler
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Phil Cook
- Penn Image Computing and Science Laboratory, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Stan Colcombe
- Child Mind Institute, New York, NY, USA
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Sydney Covitz
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christos Davatzikos
- Center for Biomedical Image Computing and Analytics, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Diego G Davila
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Mark A Elliott
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Matthew W Flounders
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neuromodulation in Depression and Stress, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Alexandre R Franco
- Child Mind Institute, New York, NY, USA
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Raquel E Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Ruben C Gur
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Basma Jaber
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Corey McMillian
- Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Michael Milham
- Child Mind Institute, New York, NY, USA
- Center for Brain Imaging and Neuromodulation, Nathan S. Kline Institute for Psychiatric Research, Orangeburg, NY, USA
| | - Henk J M M Mutsaerts
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Amsterdam Neuroscience, Amsterdam, the Netherlands
| | - Desmond J Oathes
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Center for Neuromodulation in Depression and Stress, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Penn Brain Science, Translation, Innovation, and Modulation Center, Perelmann School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Christopher A Olm
- Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Jeffrey S Phillips
- Frontotemporal Degeneration Center, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Will Tackett
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - David R Roalf
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA
| | - Howard Rosen
- Department of Neurology, University of California, San Francisco, CA, USA
| | - Tinashe M Tapera
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - M Dylan Tisdall
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Dale Zhou
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Oscar Esteban
- Department of Radiology, Lausanne University Hospital and University of Lausanne, Lausanne, Switzerland
- Department of Psychology, Stanford University, Stanford, CA, USA
| | | | - John A Detre
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA
| | - Theodore D Satterthwaite
- Penn Lifespan Informatics and Neuroimaging Center, Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Department of Psychiatry, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA.
- Lifespan Brain Institute, Children's Hospital of Philadelphia, Philadelphia, PA, USA.
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8
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Burke SE, Phillips JS, Olm CA, Peterson CS, Cook PA, Gee JC, Lee EB, Trojanowski JQ, Massimo L, Irwin DJ, Grossman M. Phases of volume loss in patients with known frontotemporal lobar degeneration spectrum pathology. Neurobiol Aging 2022; 113:95-107. [PMID: 35325815 PMCID: PMC9241163 DOI: 10.1016/j.neurobiolaging.2022.02.007] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2021] [Revised: 02/14/2022] [Accepted: 02/16/2022] [Indexed: 10/19/2022]
Abstract
Frontotemporal lobar degeneration (FTLD) includes clinically similar FTLD-tau or FTLD-TDP proteinopathies which lack in vivo markers for accurate antemortem diagnosis. To identify early distinguishing sites of cortical atrophy between groups, we retrospectively analyzed in vivo volumetric MRI from 42 FTLD-Tau and 21 FTLD-TDP patients and validated these findings with postmortem measures of pathological burden. Our frequency-based staging model revealed distinct loci of maximal early cortical atrophy in each group, including dorsolateral and medial frontal regions in FTLD-Tau and ventral frontal and anterior temporal regions in FTLD-TDP. Sørenson-Dice calculations between proteinopathy groups showed little overlap of phases. Conversely, within-group subtypes showed good overlap between 3R- and 4R-tauopathies, and between TDP-43 Types A and C for early regions with subtle divergence between subtypes in subsequent phases of atrophy. Postmortem validation found an association of imaging phases with pathologic burden within FTLD-tau (F(4, 238) = 17.44, p < 0.001) and FTLD-TDP (F(4,245) = 42.32, p < 0.001). These results suggest that relatively early, distinct markers of atrophy may distinguish FTLD proteinopathies during life.
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Affiliation(s)
- Sarah E Burke
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA..
| | - Jeffrey S Phillips
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA
| | - Christopher A Olm
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA.; Department of Radiology, Penn Image Computing & Science Lab (PICSL), Philadelphia, PA, USA
| | - Claire S Peterson
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA.; Digital Pathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Phillip A Cook
- Department of Radiology, Penn Image Computing & Science Lab (PICSL), Philadelphia, PA, USA
| | - James C Gee
- Department of Radiology, Penn Image Computing & Science Lab (PICSL), Philadelphia, PA, USA
| | - Edward B Lee
- Department of Pathology and Laboratory Medicine, Center of Neurodegenerative Disease Research, Philadelphia, PA, USA
| | - John Q Trojanowski
- Department of Pathology and Laboratory Medicine, Center of Neurodegenerative Disease Research, Philadelphia, PA, USA
| | - Lauren Massimo
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA
| | - David J Irwin
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA.; Digital Pathology Laboratory, Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA
| | - Murray Grossman
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA
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Bharne PR, Kinney NG, Da Re F, Spotorno N, Olm CA, Cook P, Irwin DJ, McMillan CT, Grossman M, Phillips JS. Investigating white matter connectomes in amnestic and non‐amnestic Alzheimer's disease clinical variants. Alzheimers Dement 2021. [DOI: 10.1002/alz.054401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/06/2022]
Affiliation(s)
| | | | - Fulvio Da Re
- PhD Program in Neuroscience, University of Milano‐Bicocca Milan Italy
- School of Medicine and Surgery, Milan Center for Neuroscience (NeuroMI), University of Milano‐Bicocca Milan Italy
| | - Nicola Spotorno
- Penn FTD Center, University of Pennsylvania Philadelphia PA USA
| | - Christopher A. Olm
- Penn Image Computing and Science Laboratory, University of Pennsylvania Philadelphia PA USA
| | - Philip Cook
- Penn Image Computing and Science Laboratory, University of Pennsylvania Philadelphia PA USA
| | - David J. Irwin
- Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | | | - Murray Grossman
- Penn FTD Center, University of Pennsylvania Philadelphia PA USA
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10
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Phillips JS, Nitchie FJ, Da Re F, Olm CA, Cook P, McMillan CT, Irwin DJ, Gee JC, Dubroff JG, Grossman M, Nasrallah IM. Reduced longitudinal change in
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F‐flortaucipir PET is associated with clinical phenotype in atypical Alzheimer’s disease. Alzheimers Dement 2021. [DOI: 10.1002/alz.055647] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Jeffrey S Phillips
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Frederick J. Nitchie
- Department of Neurology, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Fulvio Da Re
- School of Medicine and Surgery, Milan Center for Neuroscience (NeuroMI), University of Milano‐Bicocca Milan Italy
| | - Christopher A Olm
- Penn Image Computing and Science Laboratory, University of Pennsylvania Philadelphia PA USA
| | - Philip Cook
- Penn Image Computing and Science Laboratory, University of Pennsylvania Philadelphia PA USA
| | - Corey T McMillan
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - David J. Irwin
- Digital Neuropathology Laboratory, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - James C. Gee
- Penn Image Computing and Science Laboratory (PICSL), Department of Radiology, University of Pennsylvania Philadelphia PA USA
| | - Jacob G. Dubroff
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Murray Grossman
- Penn FTD Center, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
| | - Ilya M. Nasrallah
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania Philadelphia PA USA
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11
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Phillips JS, Nitchie FJ, Da Re F, Olm CA, Cook PA, McMillan CT, Irwin DJ, Gee JC, Dubroff JG, Grossman M, Nasrallah IM. Rates of longitudinal change in 18 F-flortaucipir PET vary by brain region, cognitive impairment, and age in atypical Alzheimer's disease. Alzheimers Dement 2021; 18:1235-1247. [PMID: 34515411 PMCID: PMC9292954 DOI: 10.1002/alz.12456] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/29/2021] [Revised: 06/24/2021] [Accepted: 07/30/2021] [Indexed: 01/12/2023]
Abstract
Introduction Longitudinal positron emission tomography (PET) studies of tau accumulation in Alzheimer's disease (AD) have noted reduced increases or frank decreases in tau signal. We investigated how such reductions related to analytical confounds and disease progression markers in atypical AD. Methods We assessed regional and interindividual variation in longitudinal change on 18F‐flortaucipir PET imaging in 24 amyloid beta (Aβ)+ patients with atypical, early‐onset amnestic or non‐amnestic AD plus 62 Aβ– and 132 Aβ+ Alzheimer's Disease Neuroimaging Initiative (ADNI) participants. Results In atypical AD, 18F‐flortaucipir uptake slowed or declined over time in areas with high baseline signal and older, more impaired individuals. ADNI participants had reduced longitudinal change in early Braak stage regions relative to late‐stage areas. Discussion Results suggested radioligand uptake plateaus or declines in advanced neurodegeneration. Further research should investigate whether results generalize to other radioligands and whether they relate to changes of the radioligand binding site structure or accessibility.
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Affiliation(s)
| | | | - Fulvio Da Re
- University of Milan-Bicocca Faculty of Medicine and Surgery, Universita degli Studi di Milano-Bicocca Dipartimento di Medicina e Chirurgia, Milan, Italy
| | | | - Philip A Cook
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | | | - David J Irwin
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
| | - James C Gee
- University of Pennsylvania, Philadelphia, Pennsylvania, USA
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12
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Kinney NG, Bove J, Phillips JS, Cousins KAQ, Olm CA, Wakeman DG, McMillan CT, Massimo L. Social and leisure activity are associated with attenuated cortical loss in behavioral variant frontotemporal degeneration. Neuroimage Clin 2021; 30:102629. [PMID: 33770546 PMCID: PMC8024767 DOI: 10.1016/j.nicl.2021.102629] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/10/2020] [Revised: 02/16/2021] [Accepted: 03/07/2021] [Indexed: 12/04/2022]
Abstract
Social and leisure activity may contribute to mitigation of cortical loss in bvFTD. This relationship was found in regions important for social cognition. Findings provide new evidence in burgeoning non-AD cognitive reserve literature.
Behavioral variant frontotemporal degeneration (bvFTD) is clinically characterized by progressive decline in social and executive domains. Previous work suggests that early lifestyle factors such as education and occupational attainment may relate to structural integrity and moderate the rate of cognitive decline in bvFTD, but the role of other cognitively stimulating activities is understudied. We sought to investigate the effect of such activities on cortical thickness (CT) in bvFTD. bvFTD patients (n = 31) completed a baseline MRI scan, and informants for the patients completed the Lifetime of Experiences Questionnaire (LEQ), which measures specific activities considered to be undertaken primarily within one particular life phase, such as education (young-life), occupation (mid-life), and social/leisure activity (late-life). At baseline, linear models assessed the effect of LEQ scores from each life phase on regional CT. A subset (n = 19) of patients completed longitudinal MRI, and to evaluate the association of LEQ with longitudinal rates of CT decline, we derived individualized slopes of decline using linear mixed effects models and these were related to LEQ scores from each life phase. At baseline, a higher late-life LEQ score was associated with less atrophy in left superior and inferior anterior temporal regions as well as right middle temporal gyrus. Longitudinally, we observed that higher late-life LEQ scores were associated with an attenuated rate of CT loss in insular cortex. Late-life LEQ score was positively associated with both relatively preserved CT early in bvFTD and a slower rate of cortical loss in regions important for social functioning. These findings suggest that social and leisure activities may contribute to a form of resilience against pathologic effects of disease.
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Affiliation(s)
- Nikolas G Kinney
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, United States
| | - Jessica Bove
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, United States
| | - Jeffrey S Phillips
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, United States
| | - Katheryn A Q Cousins
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, United States
| | - Christopher A Olm
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, United States
| | - Daniel G Wakeman
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, United States
| | - Corey T McMillan
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, United States
| | - Lauren Massimo
- Frontotemporal Degeneration Center, Perelman School of Medicine, Department of Neurology, Philadelphia, PA, United States; School of Nursing, University of Pennsylvania, Philadelphia, PA, United States.
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13
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Healey M, Howard E, Ungrady M, Olm CA, Nevler N, Irwin DJ, Grossman M. More Than Words: Extra-Sylvian Neuroanatomic Networks Support Indirect Speech Act Comprehension and Discourse in Behavioral Variant Frontotemporal Dementia. Front Hum Neurosci 2021; 14:598131. [PMID: 33519400 PMCID: PMC7842266 DOI: 10.3389/fnhum.2020.598131] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/28/2020] [Accepted: 11/24/2020] [Indexed: 11/13/2022] Open
Abstract
Indirect speech acts—responding “I forgot to wear my watch today” to someone who asked for the time—are ubiquitous in daily conversation, but are understudied in current neurobiological models of language. To comprehend an indirect speech act like this one, listeners must not only decode the lexical-semantic content of the utterance, but also make a pragmatic, bridging inference. This inference allows listeners to derive the speaker’s true, intended meaning—in the above dialog, for example, that the speaker cannot provide the time. In the present work, we address this major gap by asking non-aphasic patients with behavioral variant frontotemporal dementia (bvFTD, n = 21) and brain-damaged controls with amnestic mild cognitive impairment (MCI, n = 17) to judge simple question-answer dialogs of the form: “Do you want some cake for dessert?” “I’m on a very strict diet right now,” and relate the results to structural and diffusion MRI. Accuracy and reaction time results demonstrate that subjects with bvFTD, but not MCI, are selectively impaired in indirect relative to direct speech act comprehension, due in part to their social and executive limitations, and performance is related to caregivers’ judgment of communication efficacy. MRI imaging associates the observed impairment in bvFTD to cortical thinning not only in traditional language-associated regions, but also in fronto-parietal regions implicated in social and executive cerebral networks. Finally, diffusion tensor imaging analyses implicate white matter tracts in both dorsal and ventral projection streams, including superior longitudinal fasciculus, frontal aslant, and uncinate fasciculus. These results have strong implications for updated neurobiological models of language, and emphasize a core, language-mediated social disorder in patients with bvFTD.
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Affiliation(s)
- Meghan Healey
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.,Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Erica Howard
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Molly Ungrady
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - Christopher A Olm
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.,Penn Image Computing and Science Laboratory, Department of Radiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Naomi Nevler
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.,Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, United States.,Neuroscience Graduate Group, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, United States
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14
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Spotorno N, Coughlin DG, Olm CA, Wolk D, Vaishnavi SN, Shaw LM, Dahodwala N, Morley JF, Duda JE, Deik AF, Spindler MA, Chen‐Plotkin A, Lee EB, Trojanowski JQ, McMillan CT, Weintraub D, Grossman M, Irwin DJ. Tau pathology associates with in vivo cortical thinning in Lewy body disorders. Ann Clin Transl Neurol 2020; 7:2342-2355. [PMID: 33108692 PMCID: PMC7732256 DOI: 10.1002/acn3.51183] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/24/2020] [Accepted: 08/12/2020] [Indexed: 12/14/2022] Open
Abstract
OBJECTIVES To investigate the impact of Alzheimer's disease (AD) co-pathology on an in vivo structural measure of neurodegeneration in Lewy body disorders (LBD). METHODS We studied 72 LBD patients (Parkinson disease (PD) = 2, PD-MCI = 25, PD with dementia = 10, dementia with Lewy bodies = 35) with either CSF analysis or neuropathological examination and structural MRI during life. The cohort was divided into those harboring significant AD co-pathology, either at autopsy (intermediate/high AD neuropathologic change) or with CSF signature indicating AD co-pathology (t-tau/Aβ1-42 > 0.3) (LBD+AD, N = 19), and those without AD co-pathology (LBD-AD, N = 53). We also included a reference group of 25 patients with CSF biomarker-confirmed amnestic AD. We investigated differences in MRI cortical thickness estimates between groups, and in the 21 autopsied LBD patients (LBD-AD = 14, LBD+AD = 7), directly tested the association between antemortem MRI and post-mortem burdens of tau, Aβ, and alpha-synuclein using digital histopathology in five representative neocortical regions. RESULTS The LBD+AD group was characterized by cortical thinning in anterior/medial and lateral temporal regions (P < 0.05 FWE-corrected) relative to LBD-AD. In LBD+AD, cortical thinning was most pronounced in temporal neocortex, whereas the AD reference group showed atrophy that equally encompassed temporal, parietal and frontal neocortex. In autopsied LBD, we found an inverse correlation with cortical thickness and post-mortem tau pathology, while cortical thickness was not significantly associated with Aβ or alpha-synuclein pathology. INTERPRETATION LBD+AD is characterized by temporal neocortical thinning on MRI, and cortical thinning directly correlated with post-mortem histopathologic burden of tau, suggesting that tau pathology influences the pattern of neurodegeneration in LBD.
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Affiliation(s)
- Nicola Spotorno
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - David G. Coughlin
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
- Department of RadiologyPenn Image Computing and Science LaboratoryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - Christopher A. Olm
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
- Department of NeurosciencesHealth SciencesUC San DiegoSan DiegoCAUSA
| | - David Wolk
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
- Alzheimer's Disease CenterDepartment of Neuropathology Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Sanjeev N. Vaishnavi
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
- Alzheimer's Disease CenterDepartment of Neuropathology Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Leslie M. Shaw
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Nabila Dahodwala
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
| | - James F. Morley
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
- Parkinson's Disease ResearchEducation and Clinical Center (PADRECC)Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPAUSA
| | - John E. Duda
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
- Parkinson's Disease ResearchEducation and Clinical Center (PADRECC)Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPAUSA
| | - Andres F. Deik
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
| | - Meredith A. Spindler
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
| | - Alice Chen‐Plotkin
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
| | - Edward B. Lee
- Alzheimer's Disease CenterDepartment of Neuropathology Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
- Center for Neurodegenerative Disease ResearchPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - John Q. Trojanowski
- Alzheimer's Disease CenterDepartment of Neuropathology Perelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
- Department of Pathology and Laboratory MedicinePerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
- Center for Neurodegenerative Disease ResearchPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Corey T. McMillan
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
| | - Daniel Weintraub
- Department of NeurologyPerelman School of MedicineUniversity of Pennsylvania PhiladelphiaPhiladelphiaPAUSA
- Parkinson's Disease ResearchEducation and Clinical Center (PADRECC)Michael J. Crescenz Veterans Affairs Medical CenterPhiladelphiaPAUSA
- Department of PsychiatryPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
| | - Murray Grossman
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
- Department of RadiologyPenn Image Computing and Science LaboratoryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
| | - David J. Irwin
- Penn Frontotemporal Degeneration CenterDepartment of NeurologyUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
- Department of RadiologyPenn Image Computing and Science LaboratoryUniversity of Pennsylvania Perelman School of MedicinePhiladelphiaPAUSA
- Digital Neuropathology LaboratoryPerelman School of MedicineUniversity of PennsylvaniaPhiladelphiaPAUSA
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15
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Olm CA, McMillan CT, Irwin DJ, Van Deerlin VM, Cook PA, Gee JC, Grossman M. Longitudinal structural gray matter and white matter MRI changes in presymptomatic progranulin mutation carriers. Neuroimage Clin 2018; 19:497-506. [PMID: 29984158 PMCID: PMC6029561 DOI: 10.1016/j.nicl.2018.05.017] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/15/2017] [Revised: 03/29/2018] [Accepted: 05/13/2018] [Indexed: 11/21/2022]
Abstract
Introduction Mutations in the progranulin (GRN) gene are a major source of inherited frontotemporal degeneration (FTD) spectrum disorders associated with TDP-43 proteinopathy. We use structural MRI to identify regions of baseline differences and longitudinal changes in gray matter (GM) and white matter (WM) in presymptomatic GRN mutation carriers (pGRN+) compared to young controls (yCTL). Methods Cognitively intact first-degree relatives of symptomatic GRN+ FTD patients with identified GRN mutations (pGRN+; N = 11, mean age = 41.4) and matched yCTL (N = 11, mean age = 53.6) were identified. They completed a MRI session with T1-weighted imaging to assess GM density (GMD) and diffusion-weighted imaging (DWI) to assess fractional anisotropy (FA). Participants completed a follow-up session with T1 and DWI imaging (pGRN+ mean interval 2.20 years; yCTL mean interval 3.27 years). Annualized changes of GMD and FA were also compared. Results Relative to yCTL, pGRN+ individuals displayed reduced GMD at baseline in bilateral orbitofrontal, insular, and anterior temporal cortices. pGRN+ also showed greater annualized GMD changes than yCTL at follow-up in right orbitofrontal and left occipital cortices. We also observed reduced FA at baseline in bilateral superior longitudinal fasciculus, left corticospinal tract, and frontal corpus callosum in pGRN+ relative to yCTL, and pGRN+ displayed greater annualized longitudinal FA change in right superior longitudinal fasciculus and frontal corpus callosum. Conclusions Longitudinal MRI provides evidence of progressive GM and WM changes in pGRN+ participants relative to yCTL. Structural MRI illustrates the natural history of presymptomatic GRN carriers, and may provide an endpoint during disease-modifying treatment trials for pGRN+ individuals at risk for FTD.
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Key Words
- AD, axial diffusivity
- BA, Brodmann area
- CST, corticospinal tract
- DWI, diffusion-weighted imaging
- FA, fractional anisotropy
- FTD, frontotemporal degeneration
- Frontotemporal lobar degeneration
- GM, gray matter
- GMD, gray matter density
- GRN+, symptomatic progranulin mutation carriers
- GRN, progranulin
- IFO, inferior fronto-occipital fasciculus
- ILF, inferior longitudinal fasciculus
- Longitudinal
- MD, mean diffusivity
- Magnetic resonance imaging
- Neuroimaging
- Presymptomatic
- Progranulin
- RD, radial diffusivity
- ROI, region of interest
- SLF, superior longitudinal fasciculus
- WM, white matter
- eCTL, elderly healthy controls
- pGRN+, presymptomatic progranulin mutation carriers
- yCTL, young healthy controls
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Affiliation(s)
- Christopher A Olm
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States; Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States; Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Vivianna M Van Deerlin
- Center for Neurodegenerative Disease Research, Department of Pathology and Laboratory Medicine, University of Pennsylvania, Philadelphia, PA, United States
| | - Philip A Cook
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - James C Gee
- Penn Image Computing and Science Laboratory, Department of Radiology, University of Pennsylvania, Philadelphia, PA, United States
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA, United States.
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16
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Ferraro PM, Jester C, Olm CA, Placek K, Agosta F, Elman L, McCluskey L, Irwin DJ, Detre JA, Filippi M, Grossman M, McMillan CT. Perfusion alterations converge with patterns of pathological spread in transactive response DNA-binding protein 43 proteinopathies. Neurobiol Aging 2018; 68:85-92. [PMID: 29751289 DOI: 10.1016/j.neurobiolaging.2018.04.008] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2018] [Revised: 03/22/2018] [Accepted: 04/11/2018] [Indexed: 11/18/2022]
Abstract
Amyotrophic lateral sclerosis (ALS) and the behavioral variant of frontotemporal dementia (bvFTD) commonly share the presence of transactive response DNA-binding protein 43 (TDP-43) inclusions. Structural magnetic resonance imaging studies demonstrated evidence for TDP-43 pathology spread, but while structural imaging usually reveals overt neuronal loss, perfusion imaging may detect more subtle neural activity alterations. We evaluated perfusion as an early marker for incipient pathology-associated brain alterations in TDP-43 proteinopathies. Cortical thickness (CT) and perfusion measurements were obtained in ALS (N = 18), pathologically and/or genetically confirmed bvFTD-TDP (N = 12), and healthy controls (N = 33). bvFTD showed reduced frontotemporal CT, hypoperfusion encompassing orbitofrontal and temporal cortices, and hyperperfusion in motor and occipital regions. ALS did not show reduced CT, but exhibited hypoperfusion in motor and temporal regions, and hyperperfusion in frontal and occipital cortices. Frontotemporal hypoperfusion and reduced CT correlated with cognitive and behavioral impairments as investigated using Mini-Mental State Examination and Philadelphia Brief Assessment of Cognition in bvFTD, and hypoperfusion in motor regions correlated with motor disability as measured by the ALS Functional Rating Scale-Revised in ALS. Hypoperfusion marked early pathologically involved regions, while hyperperfusion characterized regions of late pathological involvement. Distinct perfusion patterns may provide early markers of pathology distribution in TDP-43 proteinopathies.
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Affiliation(s)
- Pilar M Ferraro
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA; Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Charles Jester
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA
| | - Christopher A Olm
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA; Department of Radiology, Penn Image Computing and Science Laboratory, Philadelphia, PA, USA
| | - Katerina Placek
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Lauren Elman
- Penn Comprehensive ALS Center, University of Pennsylvania, Philadelphia, PA, USA
| | - Leo McCluskey
- Penn Comprehensive ALS Center, University of Pennsylvania, Philadelphia, PA, USA
| | - David J Irwin
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA
| | - John A Detre
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA; Department of Radiology, Penn Image Computing and Science Laboratory, Philadelphia, PA, USA
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Murray Grossman
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA
| | - Corey T McMillan
- Department of Neurology, Penn Frontotemporal Degeneration Center, Philadelphia, PA, USA.
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17
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Olm CA, Kandel BM, Avants BB, Detre JA, Gee JC, Grossman M, McMillan CT. Arterial spin labeling perfusion predicts longitudinal decline in semantic variant primary progressive aphasia. J Neurol 2016; 263:1927-38. [PMID: 27379517 DOI: 10.1007/s00415-016-8221-1] [Citation(s) in RCA: 16] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2015] [Revised: 04/22/2016] [Accepted: 06/26/2016] [Indexed: 01/04/2023]
Abstract
The objective of the study was to evaluate the prognostic value of regional cerebral blood flow (CBF) measured by arterial spin labeled (ASL) perfusion MRI in patients with semantic variant primary progressive aphasia (svPPA). We acquired pseudo-continuous ASL (pCASL) MRI and whole-brain T1-weighted structural MRI in svPPA patients (N = 13) with cerebrospinal fluid biomarkers consistent with frontotemporal lobar degeneration pathology. Follow-up T1-weighted MRI was available in a subset of patients (N = 8). We performed whole-brain comparisons of partial volume-corrected CBF and cortical thickness between svPPA and controls, and compared baseline and follow-up cortical thickness in regions of significant hypoperfusion and hyperperfusion. Patients with svPPA showed partial volume-corrected hypoperfusion relative to controls in left temporal lobe and insula. svPPA patients also had typical cortical thinning in anterior temporal, insula, and inferior frontal regions at baseline. Volume-corrected hypoperfusion was seen in areas of significant cortical thinning such as the left temporal lobe and insula. Additional regions of hypoperfusion corresponded to areas without cortical thinning. We also observed regions of hyperperfusion, some associated with cortical thinning and others without cortical thinning, including right superior temporal, inferior parietal, and orbitofrontal cortices. Regions of hypoperfusion and hyperperfusion near cortical thinning at baseline had significant longitudinal thinning between baseline and follow-up scans, but perfusion changes in distant areas did not show progressive thinning. Our findings suggest ASL MRI may be sensitive to functional changes not readily apparent in structural MRI, and specific changes in perfusion may be prognostic markers of disease progression in a manner consistent with cell-to-cell spreading pathology.
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Affiliation(s)
- Christopher A Olm
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania Perelman School of Medicine, 3 West Gates, Philadelphia, PA, 19104, USA
| | - Benjamin M Kandel
- Department of Radiology, Penn Image Computing and Science Lab, Philadelphia, PA, 19104, USA
| | - Brian B Avants
- Department of Radiology, Penn Image Computing and Science Lab, Philadelphia, PA, 19104, USA
| | - John A Detre
- Departments of Neurology and Radiology, University of Pennsylvania, Philadelphia, PA, 19104, USA
| | - James C Gee
- Department of Radiology, Penn Image Computing and Science Lab, Philadelphia, PA, 19104, USA
| | - Murray Grossman
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania Perelman School of Medicine, 3 West Gates, Philadelphia, PA, 19104, USA
| | - Corey T McMillan
- Department of Neurology, Penn Frontotemporal Degeneration Center, University of Pennsylvania Perelman School of Medicine, 3 West Gates, Philadelphia, PA, 19104, USA.
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18
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Bisbing TA, Olm CA, McMillan CT, Rascovsky K, Baehr L, Ternes K, Irwin DJ, Clark R, Grossman M. Estimating frontal and parietal involvement in cognitive estimation: a study of focal neurodegenerative diseases. Front Hum Neurosci 2015; 9:317. [PMID: 26089786 PMCID: PMC4454843 DOI: 10.3389/fnhum.2015.00317] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2015] [Accepted: 05/18/2015] [Indexed: 12/14/2022] Open
Abstract
We often estimate an unknown value based on available relevant information, a process known as cognitive estimation. In this study, we assess the cognitive and neuroanatomic basis for quantitative estimation by examining deficits in patients with focal neurodegenerative disease in frontal and parietal cortex. Executive function and number knowledge are key components in cognitive estimation. Prefrontal cortex has been implicated in multilevel reasoning and planning processes, and parietal cortex has been associated with number knowledge required for such estimations. We administered the Biber cognitive estimation test (BCET) to assess cognitive estimation in 22 patients with prefrontal disease due to behavioral variant frontotemporal dementia (bvFTD), to 17 patients with parietal disease due to corticobasal syndrome (CBS) or posterior cortical atrophy (PCA) and 11 patients with mild cognitive impairment (MCI). Both bvFTD and CBS/PCA patients had significantly more difficulty with cognitive estimation than controls. MCI were not impaired on BCET relative to controls. Regression analyses related BCET performance to gray matter atrophy in right lateral prefrontal and orbital frontal cortices in bvFTD, and to atrophy in right inferior parietal cortex, right insula, and fusiform cortices in CBS/PCA. These results are consistent with the hypothesis that a frontal-parietal network plays a crucial role in cognitive estimation.
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Affiliation(s)
- Teagan A Bisbing
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - Christopher A Olm
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - Katya Rascovsky
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - Laura Baehr
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - Kylie Ternes
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - David J Irwin
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
| | - Robin Clark
- Department of Linguistics, University of Pennsylvania, Philadelphia, PA USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, University of Pennsylvania, Philadelphia, PA USA
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Olm CA, McMillan CT, Spotorno N, Clark R, Grossman M. The relative contributions of frontal and parietal cortex for generalized quantifier comprehension. Front Hum Neurosci 2014; 8:610. [PMID: 25147520 PMCID: PMC4124462 DOI: 10.3389/fnhum.2014.00610] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2014] [Accepted: 07/21/2014] [Indexed: 12/13/2022] Open
Abstract
Quantifiers, like “some” or “few,” are frequent in daily language. Linguists posit at least three distinct classes of quantifiers: cardinal quantifiers that rely on numerosity, majority quantifiers that additionally depend on executive resources, and logical quantifiers that rely on perceptual attention. We used BOLD fMRI to investigate the roles of frontal and parietal regions in quantifier comprehension. Participants performed a sentence-picture verification task to determine whether a sentence containing a quantifier accurately describes a picture. A whole-brain analysis identified a network involved in quantifier comprehension: This implicated bilateral inferior parietal, superior parietal and dorsolateral prefrontal cortices, and right inferior frontal cortex. We then performed region-of-interest analyses to assess the relative contribution of each region for each quantifier class. Inferior parietal cortex was equally activated across all quantifier classes, consistent with prior studies implicating the region for quantifier comprehension due in part to its role in the representation of number knowledge. Right superior parietal cortex was up-regulated in comparison to frontal regions for cardinal and logical quantifiers, but parietal and frontal regions were equally activated for majority quantifiers and each frontal region is most highly activated for majority quantifiers. This finding is consistent with the hypothesis that majority quantifiers rely on numerosity mechanisms in parietal cortex and executive mechanisms in frontal cortex. Also, right inferior frontal cortex was up-regulated for logical compared to cardinal quantifiers, which may be related to selection demands associated with logical quantifier comprehension. We conclude that distinct components of a large-scale fronto-parietal network contribute to specific aspects of quantifier comprehension, and that this biologically defined network is consistent with cognitive theories of quantifier meaning.
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Affiliation(s)
- Christopher A Olm
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania Philadelphia, PA, USA
| | - Corey T McMillan
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania Philadelphia, PA, USA
| | - Nicola Spotorno
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania Philadelphia, PA, USA
| | - Robin Clark
- Department of Linguistics, University of Pennsylvania Philadelphia, PA, USA
| | - Murray Grossman
- Penn Frontotemporal Degeneration Center, Department of Neurology, Perelman School of Medicine, University of Pennsylvania Philadelphia, PA, USA
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