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Arbizu J, Morbelli S, Minoshima S, Barthel H, Kuo P, Van Weehaeghe D, Horner N, Colletti PM, Guedj E. SNMMI Procedure Standard/EANM Practice Guideline for Brain [ 18F]FDG PET Imaging, Version 2.0. J Nucl Med 2024:jnumed.124.268754. [PMID: 39419552 DOI: 10.2967/jnumed.124.268754] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2024] [Accepted: 09/05/2024] [Indexed: 10/19/2024] Open
Abstract
PREAMBLEThe Society of Nuclear Medicine and Molecular Imaging (SNMMI) is an international scientific and professional organization founded in 1954 to promote the science, technology, and practical application of nuclear medicine. The European Association of Nuclear Medicine (EANM) is a professional nonprofit medical association that facilitates communication worldwide between individuals pursuing clinical and research excellence in nuclear medicine. The EANM was founded in 1985. The EANM was founded in 1985. SNMMI and EANM members are physicians, technologists, and scientists specializing in the research and practice of nuclear medicine.The SNMMI and EANM will periodically define new guidelines for nuclear medicine practice to help advance the science of nuclear medicine and to improve the quality of service to patients throughout the world. Existing practice guidelines will be reviewed for revision or renewal, as appropriate, on their fifth anniversary or sooner, if indicated.Each practice guideline, representing a policy statement by the SNMMI/EANM, has undergone a thorough consensus process in which it has been subjected to extensive review. The SNMMI and EANM recognize that the safe and effective use of diagnostic nuclear medicine imaging requires specific training, skills, and techniques, as described in each document. Reproduction or modification of the published practice guideline by those entities not providing these services is not authorized.These guidelines are an educational tool designed to assist practitioners in providing appropriate care for patients. They are not inflexible rules or requirements of practice and are not intended, nor should they be used, to establish a legal standard of care. For these reasons and those set forth below, both the SNMMI and the EANM caution against the use of these guidelines in litigation in which the clinical decisions of a practitioner are called into question.The ultimate judgment regarding the propriety of any specific procedure or course of action must be made by the physician or medical physicist in light of all the circumstances presented. Thus, there is no implication that an approach differing from the guidelines, standing alone, is below the standard of care. To the contrary, a conscientious practitioner may responsibly adopt a course of action different from that set forth in the guidelines when, in the reasonable judgment of the practitioner, such course of action is indicated by the condition of the patient, limitations of available resources, or advances in knowledge or technology subsequent to publication of the guidelines.The practice of medicine includes both the art and the science of the prevention, diagnosis, alleviation, and treatment of disease. The variety and complexity of human conditions make it impossible to always reach the most appropriate diagnosis or to predict with certainty a particular response to treatment.Therefore, it should be recognized that adherence to these guidelines will not ensure an accurate diagnosis or a successful outcome. All that should be expected is that the practitioner will follow a reasonable course of action based on current knowledge, available resources, and the needs of the patient to deliver effective and safe medical care. The sole purpose of these guidelines is to assist practitioners in achieving this objective.
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Affiliation(s)
- Javier Arbizu
- Department of Nuclear Medicine, Clinica Universidad de Navarra, University of Navarra, Pamplona, Spain;
| | - Silvia Morbelli
- Nuclear Medicine Unit, Citta'della Scenza e della Salute di Torino, Turin, Italy
- Department of Medical Sciences, University of Turin, Turin, Italy
| | - Satoshi Minoshima
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah
| | - Henryk Barthel
- Department of Nuclear Medicine, Leipzig University Medical Centre, Leipzig, Germany
| | | | | | - Neil Horner
- Atlantic Health System, Morristown, New Jersey, and Icahn School of Medicine at Mount Sinai, New York, New York
| | - Patrick M Colletti
- Department of Radiology and Nuclear Medicine, University of Southern California, Los Angeles, California; and
| | - Eric Guedj
- APHM, CNRS, Centrale Marseille, Institut Fresnel, Timone Hospital, CERIMED, Nuclear Medicine Department, Aix Marseille University, Marseille, France
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Fan L, Su C, Li Y, Guo J, Huang Z, Zhang W, Liu T, Wang J. The alterations of repetitive transcranial magnetic stimulation on the energy landscape of resting-state networks differ across the human cortex. Hum Brain Mapp 2024; 45:e70029. [PMID: 39465912 PMCID: PMC11514123 DOI: 10.1002/hbm.70029] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/31/2023] [Revised: 08/25/2024] [Accepted: 09/04/2024] [Indexed: 10/29/2024] Open
Abstract
Repetitive transcranial magnetic stimulation (rTMS) is a promising intervention tool for the noninvasive modulation of brain activity and behavior in neuroscience research and clinical settings. However, the resting-state dynamic evolution of large-scale functional brain networks following rTMS has rarely been investigated. Here, using resting-state fMRI images collected from 23 healthy individuals before (baseline) and after 1 Hz rTMS of the left frontal (FRO) and occipital (OCC) lobes, we examined the different effects of rTMS on brain dynamics across the human cortex. By fitting a pairwise maximum entropy model (pMEM), we constructed an energy landscape for the baseline and poststimulus conditions by fitting a pMEM. We defined dominant brain states (local minima) in the energy landscape with synergistic activation and deactivation patterns of large-scale functional networks. We calculated state dynamics including appearance probability, transitions and duration. The results showed that 1 Hz rTMS induced increased and decreased state probability, transitions and duration when delivered to the FRO and OCC targets, respectively. Most importantly, the shortest path and minimum cost between dominant brain states were altered after stimulation. The absolute sum of the costs from the source states to the destinations was lower after OCC stimulation than after FRO stimulation. In conclusion, our study characterized the dynamic trajectory of state transitions in the energy landscape and suggested that local rTMS can induce significant dynamic perturbation involving stimulated and distant functional networks, which aligns with the modern view of the dynamic and complex brain. Our results suggest low-dimensional mapping of rTMS-induced brain adaption, which will contribute to a broader and more effective application of rTMS in clinical settings.
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Affiliation(s)
- Liming Fan
- The Key Laboratory of Biomedical Information Engineering of Ministry of EducationInstitute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anShaanxiP. R. China
- National Engineering Research Center of Health Care and Medical DevicesGuangzhouGuangdongP. R. China
| | - Chunwang Su
- The Key Laboratory of Biomedical Information Engineering of Ministry of EducationInstitute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anShaanxiP. R. China
- National Engineering Research Center of Health Care and Medical DevicesGuangzhouGuangdongP. R. China
| | - Youjun Li
- The Key Laboratory of Biomedical Information Engineering of Ministry of EducationInstitute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anShaanxiP. R. China
- National Engineering Research Center of Health Care and Medical DevicesGuangzhouGuangdongP. R. China
| | - Jinjia Guo
- The Key Laboratory of Biomedical Information Engineering of Ministry of EducationInstitute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anShaanxiP. R. China
- National Engineering Research Center of Health Care and Medical DevicesGuangzhouGuangdongP. R. China
| | - Zi‐Gang Huang
- The Key Laboratory of Biomedical Information Engineering of Ministry of EducationInstitute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anShaanxiP. R. China
- National Engineering Research Center of Health Care and Medical DevicesGuangzhouGuangdongP. R. China
| | - Wenlong Zhang
- The Key Laboratory of Biomedical Information Engineering of Ministry of EducationInstitute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anShaanxiP. R. China
- National Engineering Research Center of Health Care and Medical DevicesGuangzhouGuangdongP. R. China
| | - Tian Liu
- The Key Laboratory of Biomedical Information Engineering of Ministry of EducationInstitute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anShaanxiP. R. China
- National Engineering Research Center of Health Care and Medical DevicesGuangzhouGuangdongP. R. China
| | - Jue Wang
- The Key Laboratory of Biomedical Information Engineering of Ministry of EducationInstitute of Health and Rehabilitation Science, School of Life Science and Technology, Xi'an Jiaotong UniversityXi'anShaanxiP. R. China
- National Engineering Research Center of Health Care and Medical DevicesGuangzhouGuangdongP. R. China
- The Key Laboratory of Neuro‐informatics & Rehabilitation Engineering of Ministry of Civil AffairsXi'anShaanxiP. R. China
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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] [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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Sintini I, Corriveau-Lecavalier N, Jones DT, Machulda MM, Gunter JL, Schwarz CG, Botha H, Carlos AF, Kamykowski MG, Singh NA, Petersen RC, Jack CR, Lowe VJ, Graff-Radford J, Josephs KA, Whitwell JL. Longitudinal default mode sub-networks in the language and visual variants of Alzheimer's disease. Brain Commun 2024; 6:fcae005. [PMID: 38444909 PMCID: PMC10914456 DOI: 10.1093/braincomms/fcae005] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2023] [Revised: 11/13/2023] [Accepted: 01/05/2024] [Indexed: 03/07/2024] Open
Abstract
Disruption of the default mode network is a hallmark of Alzheimer's disease, which has not been extensively examined in atypical phenotypes. We investigated cross-sectional and 1-year longitudinal changes in default mode network sub-systems in the visual and language variants of Alzheimer's disease, in relation to age and tau. Sixty-one amyloid-positive Alzheimer's disease participants diagnosed with posterior cortical atrophy (n = 33) or logopenic progressive aphasia (n = 28) underwent structural MRI, resting-state functional MRI and [18F]flortaucipir PET. One-hundred and twenty-two amyloid-negative cognitively unimpaired individuals and 60 amyloid-positive individuals diagnosed with amnestic Alzheimer's disease were included as controls and as a comparison group, respectively, and had structural and resting-state functional MRI. Forty-one atypical Alzheimer's disease participants, 26 amnestic Alzheimer's disease participants and 40 cognitively unimpaired individuals had one follow-up functional MRI ∼1-2 years after the baseline scan. Default mode network connectivity was calculated using the dual regression method for posterior, ventral, anterior ventral and anterior dorsal sub-systems derived from independent component analysis. A global measure of default mode network connectivity, the network failure quotient, was also calculated. Linear mixed-effects models and voxel-based analyses were computed for each connectivity measure. Both atypical and amnestic Alzheimer's disease participants had lower cross-sectional posterior and ventral and higher anterior dorsal connectivity and network failure quotient relative to cognitively unimpaired individuals. Age had opposite effects on connectivity in Alzheimer's disease participants and cognitively unimpaired individuals. While connectivity declined with age in cognitively unimpaired individuals, younger Alzheimer's disease participants had lower connectivity than the older ones, particularly in the ventral default mode network. Greater baseline tau-PET uptake was associated with lower ventral and anterior ventral default mode network connectivity in atypical Alzheimer's disease. Connectivity in the ventral default mode network declined over time in atypical Alzheimer's disease, particularly in older participants, with lower tau burden. Voxel-based analyses validated the findings of higher anterior dorsal default mode network connectivity, lower posterior and ventral default mode network connectivity and decline in ventral default mode network connectivity over time in atypical Alzheimer's disease. Visuospatial symptoms were associated with default mode network connectivity disruption. In summary, default mode connectivity disruption was similar between atypical and amnestic Alzheimer's disease variants, and discriminated Alzheimer's disease from cognitively unimpaired individuals, with decreased posterior and increased anterior connectivity and with disruption more pronounced in younger participants. The ventral default mode network declined over time in atypical Alzheimer's disease, suggesting a shift in default mode network connectivity likely related to tau pathology.
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Affiliation(s)
- Irene Sintini
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - David T Jones
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Mary M Machulda
- Department of Psychiatry and Psychology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | - Arenn F Carlos
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
| | | | | | | | - Clifford R Jack
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN 55905, USA
| | | | - Keith A Josephs
- Department of Neurology, Mayo Clinic, Rochester, MN 55905, USA
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Bick A, McKyton A, Glick-Shames H, Rein N, Levin N. Abnormal network connections to early visual cortex in posterior cortical atrophy. J Neurol Sci 2023; 454:120826. [PMID: 37832379 DOI: 10.1016/j.jns.2023.120826] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2023] [Revised: 10/02/2023] [Accepted: 10/04/2023] [Indexed: 10/15/2023]
Abstract
INTRODUCTION Posterior Cortical Atrophy (PCA), a visual variant of Alzheimer's disease, initially manifests with higher-order visual disorders and parieto/temporo-occipital atrophy. Recent studies have shown remote functional impairment in both distant brain networks and along the calcarine sulcus (V1). Functional alteration in the calcarine differs along its length, reflecting center to periphery visual space differences. Herein, we aim to connect between these two sets of findings by looking at the retinotopic patterns of functional connectivity between large-scale brain networks and V1, comparing patients with normally sighted subjects. METHODS Resting state functional magnetic resonance imaging (fMRI) and T1 anatomical scans were obtained from 11 PCA patients and 17 age-matched healthy volunteers. Default mode network (DMN) and fronto parietal network (FPN) were defined and differences between the networks in patients and healthy controls were evaluated at the whole brain level, specifically their connectivity to V1. RESULTS Connectivity patterns within the DMN and the FPN were similar between the groups, although differences were found in regions within and beyond the networks. Focusing on V1, in the control group we identified the expected pattern of a distributed connectivity along eccentricity, with foveal regions showing stronger connectivity to the FPN and peripheral regions showing stronger connectivity to the DMN. However, in PCA patients we could not identify a clear difference in connectivity along the eccentricities. CONCLUSION Lost specialization of function along the calcarine in PCA patients may have further implications on large-scale networks or vice versa. This impairment, distant from the core pathology, might explain patients' visual disabilities.
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Affiliation(s)
- Atira Bick
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Ayelet McKyton
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Haya Glick-Shames
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Netaniel Rein
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel
| | - Netta Levin
- fMRI unit, Neurology department, Hadassah Medical Center and Faculty of Medicine, Hebrew University of Jerusalem, Israel.
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Katsumi Y, Putcha D, Eckbo R, Wong B, Quimby M, McGinnis S, Touroutoglou A, Dickerson BC. Anterior dorsal attention network tau drives visual attention deficits in posterior cortical atrophy. Brain 2023; 146:295-306. [PMID: 36237170 PMCID: PMC10060714 DOI: 10.1093/brain/awac245] [Citation(s) in RCA: 18] [Impact Index Per Article: 9.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 05/16/2022] [Accepted: 06/21/2022] [Indexed: 01/11/2023] Open
Abstract
Posterior cortical atrophy (PCA), usually an atypical clinical syndrome of Alzheimer's disease, has well-characterized patterns of cortical atrophy and tau deposition that are distinct from typical amnestic presentations of Alzheimer's disease. However, the mechanisms underlying the cortical spread of tau in PCA remain unclear. Here, in a sample of 17 biomarker-confirmed (A+/T+/N+) individuals with PCA, we sought to identify functional networks with heightened vulnerability to tau pathology by examining the cortical distribution of elevated tau as measured by 18F-flortaucipir (FTP) PET. We then assessed the relationship between network-specific FTP uptake and visuospatial cognitive task performance. As predicted, we found consistent and prominent localization of tau pathology in the dorsal attention network and visual network of the cerebral cortex. Elevated FTP uptake within the dorsal attention network (particularly the ratio of FTP uptake between the anterior and posterior nodes) was associated with poorer visuospatial attention in PCA; associations were also identified in other functional networks, although to a weaker degree. Furthermore, using functional MRI data collected from each patient at wakeful rest, we found that a greater anterior-to-posterior ratio in FTP uptake was associated with stronger intrinsic functional connectivity between anterior and posterior nodes of the dorsal attention network. Taken together, we conclude that our cross-sectional marker of anterior-to-posterior FTP ratio could indicate tau propagation from posterior to anterior dorsal attention network nodes, and that this anterior progression occurs in relation to intrinsic functional connectivity within this network critical for visuospatial attention. Our findings help to clarify the spatiotemporal pattern of tau propagation in relation to visuospatial cognitive decline and highlight the key role of the dorsal attention network in the disease progression of PCA.
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Affiliation(s)
- Yuta Katsumi
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Deepti Putcha
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Ryan Eckbo
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bonnie Wong
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Megan Quimby
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Scott McGinnis
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Alexandra Touroutoglou
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
| | - Bradford C Dickerson
- Frontotemporal Disorders Unit, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Neurology, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Department of Psychiatry, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Alzheimer’s Disease Research Center, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital and Harvard Medical School, Boston, MA 02114, USA
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Filippi M, Spinelli EG, Cividini C, Ghirelli A, Basaia S, Agosta F. The human functional connectome in neurodegenerative diseases: relationship to pathology and clinical progression. Expert Rev Neurother 2023; 23:59-73. [PMID: 36710600 DOI: 10.1080/14737175.2023.2174016] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/31/2023]
Abstract
INTRODUCTION Neurodegenerative diseases can be considered as 'disconnection syndromes,' in which a communication breakdown prompts cognitive or motor dysfunction. Mathematical models applied to functional resting-state MRI allow for the organization of the brain into nodes and edges, which interact to form the functional brain connectome. AREAS COVERED The authors discuss the recent applications of functional connectomics to neurodegenerative diseases, from preclinical diagnosis, to follow up along with the progressive changes in network organization, to the prediction of the progressive spread of neurodegeneration, to stratification of patients into prognostic groups, and to record responses to treatment. The authors searched PubMed using the terms 'neurodegenerative diseases' AND 'fMRI' AND 'functional connectome' OR 'functional connectivity' AND 'connectomics' OR 'graph metrics' OR 'graph analysis.' The time range covered the past 20 years. EXPERT OPINION Considering the great pathological and phenotypical heterogeneity of neurodegenerative diseases, identifying a common framework to diagnose, monitor and elaborate prognostic models is challenging. Graph analysis can describe the complexity of brain architectural rearrangements supporting the network-based hypothesis as unifying pathogenetic mechanism. Although a multidisciplinary team is needed to overcome the limit of methodologic complexity in clinical application, advanced methodologies are valuable tools to better characterize functional disconnection in neurodegeneration.
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Affiliation(s)
- Massimo Filippi
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Vita-Salute San Raffaele University, Milan, Italy.,Neurophysiology Service, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Edoardo Gioele Spinelli
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Camilla Cividini
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Alma Ghirelli
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Basaia
- Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Federica Agosta
- Neurology Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neuroimaging Research Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Neurorehabilitation Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
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Migliaccio R, Cacciamani F. The temporal lobe in typical and atypical Alzheimer disease. HANDBOOK OF CLINICAL NEUROLOGY 2022; 187:449-466. [PMID: 35964987 DOI: 10.1016/b978-0-12-823493-8.00004-3] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
Alzheimer disease (AD) is defined neuropathologically by abnormal extra-cellular β-amyloid plaques combined with intraneuronal tau aggregation. Patients sharing the same neuropathological features but presenting different clinical manifestations and evolutions have led to the notion of AD spectrum. This spectrum encompasses typical and atypical forms of AD. For all of them, specific parts of the temporal lobes, as well as their structural and functional connections with other brain regions, are affected. In typical amnestic late-onset Alzheimer's disease (>65 years old; LOAD), tau pathology gradually spreads to the brain from the medial temporal lobe (MTL). MTL is an inhomogeneous structure consisting of several subregions densely connected to each other and to other cortical and subcortical brain regions. These regions play a crucial role in the storage of information in episodic memory. In less common early-onset AD (<65 years old; EOAD), a large proportion of patients presents atypical clinical manifestations, in which memory impairment is not inaugural and predominant. Instead, these patients have predominant and/or isolated deficits in language, visuospatial, motor, or executive/behavioral functions. In atypical variants, brain damage is mainly centered on the posterior regions, with relative sparing of the MTL. However, the temporal lobe also appears to be variably and specifically damaged in some subtypes of EOAD. For example, the left superior temporal gyrus is the core of brain damage in the language variant, as well as the ventral regions of the temporal lobe play an important role in the clinic of the visual variant.
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Affiliation(s)
- Raffaella Migliaccio
- Paris Brain Institute, INSERM U1127, Hôpital de la Pitié-Salpêtrière, Paris, France; Department of Neurology, Institut de la mémoire et de la maladie d'Alzheimer, Hôpital de la Pitié-Salpêtrière, Paris, France.
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Guedj E, Varrone A, Boellaard R, Albert NL, Barthel H, van Berckel B, Brendel M, Cecchin D, Ekmekcioglu O, Garibotto V, Lammertsma AA, Law I, Peñuelas I, Semah F, Traub-Weidinger T, van de Giessen E, Van Weehaeghe D, Morbelli S. EANM procedure guidelines for brain PET imaging using [ 18F]FDG, version 3. Eur J Nucl Med Mol Imaging 2021; 49:632-651. [PMID: 34882261 PMCID: PMC8803744 DOI: 10.1007/s00259-021-05603-w] [Citation(s) in RCA: 133] [Impact Index Per Article: 33.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2021] [Accepted: 10/21/2021] [Indexed: 12/13/2022]
Abstract
The present procedural guidelines summarize the current views of the EANM Neuro-Imaging Committee (NIC). The purpose of these guidelines is to assist nuclear medicine practitioners in making recommendations, performing, interpreting, and reporting results of [18F]FDG-PET imaging of the brain. The aim is to help achieve a high-quality standard of [18F]FDG brain imaging and to further increase the diagnostic impact of this technique in neurological, neurosurgical, and psychiatric practice. The present document replaces a former version of the guidelines that have been published in 2009. These new guidelines include an update in the light of advances in PET technology such as the introduction of digital PET and hybrid PET/MR systems, advances in individual PET semiquantitative analysis, and current broadening clinical indications (e.g., for encephalitis and brain lymphoma). Further insight has also become available about hyperglycemia effects in patients who undergo brain [18F]FDG-PET. Accordingly, the patient preparation procedure has been updated. Finally, most typical brain patterns of metabolic changes are summarized for neurodegenerative diseases. The present guidelines are specifically intended to present information related to the European practice. The information provided should be taken in the context of local conditions and regulations.
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Affiliation(s)
- Eric Guedj
- APHM, CNRS, Centrale Marseille, Institut Fresnel, Timone Hospital, CERIMED, Nuclear Medicine Department, Aix Marseille Univ, Marseille, France. .,Service Central de Biophysique et Médecine Nucléaire, Hôpital de la Timone, 264 rue Saint Pierre, 13005, Marseille, France.
| | - Andrea Varrone
- Department of Clinical Neuroscience, Centre for Psychiatry Research, Karolinska Institutet and Stockholm Healthcare Services, Stockholm, Sweden
| | - Ronald Boellaard
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Nathalie L Albert
- Department of Nuclear Medicine, Ludwig Maximilians-University of Munich, Munich, Germany
| | - Henryk Barthel
- Department of Nuclear Medicine, Leipzig University, Leipzig, Germany
| | - Bart van Berckel
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands
| | - Matthias Brendel
- Department of Nuclear Medicine, Ludwig Maximilians-University of Munich, Munich, Germany.,German Centre of Neurodegenerative Diseases (DZNE), Site Munich, Bonn, Germany
| | - Diego Cecchin
- Nuclear Medicine Unit, Department of Medicine - DIMED, University of Padua, Padua, Italy
| | - Ozgul Ekmekcioglu
- Sisli Hamidiye Etfal Education and Research Hospital, Nuclear Medicine Dept., University of Health Sciences, Istanbul, Turkey
| | - Valentina Garibotto
- NIMTLab, Faculty of Medicine, Geneva University, Geneva, Switzerland.,Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland
| | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Ian Law
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, University of Copenhagen, Copenhagen, Denmark
| | - Iván Peñuelas
- Department of Nuclear Medicine, Clinica Universidad de Navarra, IdiSNA, University of Navarra, Pamplona, Spain
| | - Franck Semah
- Nuclear Medicine Department, University Hospital, Lille, France
| | - Tatjana Traub-Weidinger
- Division of Nuclear Medicine, Department of Biomedical Imaging and Image-guided Therapy, Medical University of Vienna, Vienna, Austria
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam UMC, Location VUmc, Amsterdam, The Netherlands.,Radiology and Nuclear Medicine, Amsterdam UMC, Location AMC, Meibergdreef 9, Amsterdam, The Netherlands
| | | | - Silvia Morbelli
- IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Nuclear Medicine Unit, Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
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10
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Pini L, Wennberg AM, Salvalaggio A, Vallesi A, Pievani M, Corbetta M. Breakdown of specific functional brain networks in clinical variants of Alzheimer's disease. Ageing Res Rev 2021; 72:101482. [PMID: 34606986 DOI: 10.1016/j.arr.2021.101482] [Citation(s) in RCA: 28] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/27/2021] [Revised: 09/24/2021] [Accepted: 09/29/2021] [Indexed: 02/07/2023]
Abstract
Alzheimer's disease (AD) is characterized by different clinical entities. Although AD phenotypes share a common molecular substrate (i.e., amyloid beta and tau accumulation), several clinicopathological differences exist. Brain functional networks might provide a macro-scale scaffolding to explain this heterogeneity. In this review, we summarize the evidence linking different large-scale functional network abnormalities to distinct AD phenotypes. Specifically, executive deficits in early-onset AD link with the dysfunction of networks that support sustained attention and executive functions. Posterior cortical atrophy relates to the breakdown of visual and dorsal attentional circuits, while the primary progressive aphasia variant of AD may be associated with the dysfunction of the left-lateralized language network. Additionally, network abnormalities might provide in vivo signatures for distinguishing proteinopathies that mimic AD, such as TAR DNA binding protein 43 related pathologies. These network differences vis-a-vis clinical syndromes are more evident in the earliest stage of AD. Finally, we discuss how these findings might pave the way for new tailored interventions targeting the most vulnerable brain circuit at the optimal time window to maximize clinical benefits.
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11
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Mendez MF, Khattab YI, Yerstein O. Impaired visual search in posterior cortical atrophy vs. typical Alzheimer's disease. J Neurol Sci 2021; 428:117574. [PMID: 34271285 DOI: 10.1016/j.jns.2021.117574] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2021] [Revised: 07/05/2021] [Accepted: 07/08/2021] [Indexed: 10/20/2022]
Abstract
BACKGROUND Posterior cortical atrophy (PCA) is a neurocognitive disorder characterized by difficulty localizing in space. Recognizing PCA is important because it is usually missed early in its course and may result from a number of neurological disorders other than Alzheimer's disease (AD). OBJECTIVE This study aimed to clarify whether impaired visual search tasks of spatial localization distinguished patients with PCA from those with other more typical dementias as well as from healthy control (HC) subjects. METHODS Twelve patients meeting neuroimaging-supported Consensus Criteria for PCA, 12 comparably advanced patients with amnestic-predominant typical AD (tAD), and 24 HC participants were compared on tests of untimed and timed visual search, spatial neglect, mental rotation, environmental orientation, visuospatial construction, and face recognition. RESULTS Only abnormalities in untimed and timed visual search and environmental orientation distinguished the PCA patients from both the tAD group and the HC group without also distinguishing the tAD patients from HC's. The PCA patients also had a tendency to greater difficulty scanning left hemispace compared to HC's. Visuospatial constructions, although worse in PCA, and face recognition were impaired in both dementia groups. CONCLUSIONS These findings support the concept of PCA as a disorder of spatial processing and localization, indicating that visual search tasks are particularly sensitive and specific for detecting PCA and distinguishing it from more typical dementia syndromes.
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Affiliation(s)
- Mario F Mendez
- Departments of Neurology, David Geffen School of Medicine, University of California Los Angeles (UCLA), USA; Psychiatry and Behavioral Sciences, David Geffen School of Medicine, University of California Los Angeles (UCLA), USA; Neurology Service, Neurobehavior Unit, V.A. Greater Los Angeles Healthcare System, USA.
| | - Youssef I Khattab
- Departments of Neurology, David Geffen School of Medicine, University of California Los Angeles (UCLA), USA
| | - Oleg Yerstein
- Department of Neurology, Lahey Hospital and Medical Center, USA.
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12
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Yerstein O, Parand L, Liang LJ, Isaac A, Mendez MF. Benson's Disease or Posterior Cortical Atrophy, Revisited. J Alzheimers Dis 2021; 82:493-502. [PMID: 34057092 PMCID: PMC8316293 DOI: 10.3233/jad-210368] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND D. Frank Benson and colleagues first described the clinical and neuropathological features of posterior cortical atrophy (PCA) from patients in the UCLA Neurobehavior Program. OBJECTIVE We reviewed the Program's subsequent clinical experience with PCA, and its potential for clarifying this relatively rare syndrome in comparison to the accumulated literature on PCA. METHODS Using the original criteria derived from this clinic, 65 patients with neuroimaging-supported PCA were diagnosed between 1995 and 2020. RESULTS On presentation, most had visual localization complaints and related visuospatial symptoms, but nearly half had memory complaints followed by symptoms of depression. Neurobehavioral testing showed predominant difficulty with visuospatial constructions, Gerstmann's syndrome, and Balint's syndrome, but also impaired memory and naming. On retrospective application of the current Consensus Criteria for PCA, 59 (91%) met PCA criteria with a modification allowing for "significantly greater visuospatial over memory and naming deficits." There were 37 deaths (56.9%) with the median overall survival of 10.3 years (95% CI: 9.6-13.6 years), consistent with a slow neurodegenerative disorder in most patients. CONCLUSION Together, these findings recommend modifying the PCA criteria for "relatively spared" memory, language, and behavior to include secondary memory and naming difficulty and depression, with increased emphasis on the presence of Gerstmann's and Balint's syndromes.
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Affiliation(s)
- Oleg Yerstein
- Department of Neurology, Lahey Hospital and Medical Center, Burlington, MA, USA
| | - Leila Parand
- Department of Neurology, Behavioral Sciences, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA
- Neurology Service, Neurobehavior Unit, V.A. Greater Los Angeles Healthcare System, Los Angeles, CA, USA
| | - Li-Jung Liang
- Department of Medicine, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA
| | - Adrienne Isaac
- Department of Linguistics, Georgetown University, Washington, DC, USA
| | - Mario F. Mendez
- Department of Neurology, Behavioral Sciences, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA
- Neurology Service, Neurobehavior Unit, V.A. Greater Los Angeles Healthcare System, Los Angeles, CA, USA
- Department of Psychiatry and Behavioral Sciences, David Geffen School of Medicine, University of California Los Angeles (UCLA), Los Angeles, CA, USA
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13
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Raju M, Gopi VP, Anitha VS, Wahid KA. Multi-class diagnosis of Alzheimer's disease using cascaded three dimensional-convolutional neural network. Phys Eng Sci Med 2020; 43:1219-1228. [PMID: 32926392 DOI: 10.1007/s13246-020-00924-w] [Citation(s) in RCA: 14] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2020] [Accepted: 09/03/2020] [Indexed: 12/13/2022]
Abstract
Dementia is a social problem in the aging society of advanced countries. Presently, 46.8 million people affected with dementia worldwide, and it may increase to 130 million by 2050. Alzheimer's disease (AD) is the most common form of dementia. The cost of care for AD patients in 2015 was 818 billion US dollars and is expected to increase intensely due to the increasing number of patients due to the aging society. It isn't easy to cure AD, but early detection is crucial. This paper proposes a multi-class classification of AD, mild cognitive impairment (MCI), and normal control (NC) subjects using three dimensional-convolutional neural network with Support Vector Machine classifier. A cross-sectional study on structural MRI data of 465 subjects, including 132 AD patients, 181 MCI, and 152 NC, is performed in this paper. The highly complex and spatial atrophy patterns of the brain related to Alzheimer's Disease and MCI are extracted from structural MRI images using cascaded layers of the three dimensional convolutional neural network. The hectic process of segmentation and further extraction of handcrafted features is eliminated. The complete image is considered for the processing, thus incorporating every region of the brain for the classification. The features extracted using four cascaded layers of three dimensional-convolutional neural network are fed into the Support Vector Machine classifier. The proposed method achieved 97.77% accuracy which outperforms state of the art, and this algorithm is a promising indicator for the diagnosis of AD.
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Affiliation(s)
- Manu Raju
- Department of Electronics and Communication Engineering Government Engineering College Wayanad, APJ Abdul Kalam Technological University, Thiruvananthapuram, Kerala, India
| | - Varun P Gopi
- Department of Electronics and Communication Engineering, National Institute of Technology Tiruchirappalli, Tiruchirappalli, India.
| | - V S Anitha
- Department of Computer Science and Engineering, Government Engineering College Wayanad, APJ Abdul Kalam Technological University, Thiruvananthapuram, Kerala, India
| | - Khan A Wahid
- Department of Electrical and Computer Engineering, University of Saskatchewan, Saskatoon, Canada
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14
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Leocadi M, Canu E, Calderaro D, Corbetta D, Filippi M, Agosta F. An update on magnetic resonance imaging markers in AD. Ther Adv Neurol Disord 2020; 13:1756286420947986. [PMID: 33747128 PMCID: PMC7903819 DOI: 10.1177/1756286420947986] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/28/2020] [Accepted: 07/09/2020] [Indexed: 12/22/2022] Open
Abstract
The purpose of the present review is to provide an update of the available recent scientific literature on the use of magnetic resonance imaging (MRI) in Alzheimer's disease (AD). MRI is playing an increasingly important role in the characterization of the AD signatures, which can be useful in both the diagnostic process and monitoring of disease progression. Furthermore, this technique is unique in assessing brain structure and function and provides a deep understanding of in vivo evolution of cerebral pathology. In the reviewing process, we established a priori criteria and we thoroughly searched the very recent scientific literature (January 2018-March 2020) for relevant articles on this topic. In summary, we selected 73 articles out of 1654 publications retrieved from PubMed. Based on this selection, this review summarizes the recent application of MRI in clinical trials, defining the predementia stages of AD, the clinical utility of MRI, proposal of novel biomarkers and brain regions of interest, and assessing the relationship between MRI and cognitive features, risk and protective factors of AD. Finally, the value of a multiparametric approach in clinical and preclinical stages of AD is discussed.
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Affiliation(s)
- Michela Leocadi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisa Canu
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Davide Calderaro
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Davide Corbetta
- Laboratory of Movement Analysis, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Massimo Filippi
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Neurology and Neurophysiology Units, IRCCS San Raffaele Scientific Institute, and Vita-Salute San Raffaele University, Milan, Italy
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, and Vita-Salute San Raffaele University, Via Olgettina 60, Milan 20132, Italy
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15
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Glick-Shames H, Keadan T, Backner Y, Bick A, Levin N. Global Brain Involvement in Posterior Cortical Atrophy: Multimodal MR Imaging Investigation. Brain Topogr 2020; 33:600-612. [PMID: 32761400 DOI: 10.1007/s10548-020-00788-z] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/11/2020] [Accepted: 07/23/2020] [Indexed: 02/04/2023]
Abstract
Posterior cortical atrophy (PCA), considered a visual variant of Alzheimer's disease, has similar pathological characteristics yet shows a selective visual manifestation with relative preservation of other cortical areas, at least at early stages of disease. Using a gamut of imaging methods, we aim to evaluate the global aspect of this relatively local disease and describe the interplay of the involvement of the different brain components. Ten PCA patients and 14 age-matched controls underwent MRI scans. Cortical thickness was examined to identify areas of cortical thinning. Hippocampal volume was assessed using voxel-based morphometry. The integrity of 20 fiber tracts was assessed by Diffusion Tensor Imaging. Regions of difference in global functional connectivity were identified by resting-state fMRI, using multi-variant pattern analysis. Correlations were examined to evaluate the connection between grey matter atrophy, the network changes and the disease load. The patients presented bilateral cortical thinning, primarily in their brains' posterior segments. Impaired segments of white matter integrity were evident only within three fiber tracts in the left hemisphere. Four areas were identified as different in their global connectivity pattern. The visual network-related areas showed reduced connectivity and was correlated to atrophy. Right Broadman area 39 showed in addition increased connectivity to the frontal areas. Global structural and functional imaging pointed to the highly localized nature of PCA. Functional connectivity followed grey matter atrophy in visual regions. White matter involvement seemed less prominent, however damage is directly related to presence of disease and not mediated only by grey matter damage.
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Affiliation(s)
- Haya Glick-Shames
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel
| | - Tarek Keadan
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel
| | - Yael Backner
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel
| | - Atira Bick
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel
| | - Netta Levin
- fMRI Lab, Neurology Department, Hadassah-Hebrew University Medical Center, POB 12000, Jerusalem, 91120, Israel.
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16
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Kas A, Migliaccio R, Tavitian B. A future for PET imaging in Alzheimer's disease. Eur J Nucl Med Mol Imaging 2020; 47:231-234. [PMID: 31858177 DOI: 10.1007/s00259-019-04640-w] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Aurélie Kas
- Nuclear Medicine Department Pitié-Salpêtrière Hospital, APHP Sorbonne-Université, Paris, France.,Laboratoire d'Imagerie Biomédicale, Sorbonne Université, Paris, France
| | - Raffaella Migliaccio
- Neurology Departement, Pitié-Salpêtrière Hospital, Institut de la mémoire et de la maladie d'Alzheimer, IM2A, Reference Centre for Rare Dementias and Early Onset Alzheimer's Disease, Paris, France.,Institut du cerveau et de la moelle épinière, Frontlab ICM, INSERM U 1127, CNRS UMR 7225, Sorbonne Universités, Pitié-Salpêtrière Hospital, Paris, France
| | - Bertrand Tavitian
- Université de Paris, PARCC, INSERM, In vivo Imaging Research, 75015, Paris, France. .,Radiology Department, APHP Centre, Hôpital Européen Georges Pompidou, 75015, Paris, France.
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