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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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Stocks J, Gibson E, Popuri K, Beg MF, Rosen H, Wang L. Spatial and Temporal Relationships Between Atrophy and Hypometabolism in Behavioral-Variant Frontotemporal Dementia. Alzheimer Dis Assoc Disord 2024; 38:112-119. [PMID: 38812447 PMCID: PMC11141524 DOI: 10.1097/wad.0000000000000611] [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: 09/18/2023] [Accepted: 02/07/2024] [Indexed: 05/31/2024]
Abstract
PURPOSE Individuals with behavioral-variant frontotemporal dementia (bvFTD) show changes in brain structure as assessed by MRI and brain function assessed by 18FDG-PET hypometabolism. However, current understanding of the spatial and temporal interplay between these measures remains limited. METHODS Here, we examined longitudinal atrophy and hypometabolism relationships in 15 bvFTD subjects with 2 to 4 follow-up MRI and PET scans (56 visits total). Subject-specific slopes of atrophy and hypometabolism over time were extracted across brain regions and correlated with baseline measures both locally, via Pearson correlations, and nonlocally, via sparse canonical correlation analyses (SCCA). RESULTS Notably, we identified a robust link between initial hypometabolism and subsequent cortical atrophy rate changes in bvFTD subjects. Network-level exploration unveiled alignment between baseline hypometabolism and ensuing atrophy rates in the dorsal attention, language, and default mode networks. SCCA identified 2 significant and highly localized components depicting the connection between baseline hypometabolism and atrophy slope over time. The first centered around bilateral orbitofrontal, frontopolar, and medial prefrontal lobes, whereas the second concentrated in the left temporal lobe and precuneus. CONCLUSIONS This study highlights 18FDG-PET as a dependable predictor of forthcoming atrophy in spatially adjacent brain regions for individuals with bvFTD.
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Affiliation(s)
- Jane Stocks
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 60611
| | - Erin Gibson
- Sunnybrook Health Sciences Centre, Toronto, ON, Canada, M4N 3M5
| | - Karteek Popuri
- School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada, V5A1S6
- Memorial University of Newfoundland, Department of Computer Science, St. John’s, NL, Canada
| | - Mirza Faisal Beg
- School of Engineering Science, Simon Fraser University, Burnaby, BC, Canada, V5A1S6
| | - Howard Rosen
- School of Medicine, University of California, San Francisco, USA, 94143
| | - Lei Wang
- Department of Psychiatry and Behavioral Sciences, Feinberg School of Medicine, Northwestern University, Chicago, IL, USA 60611
- Department of Psychiatry and Behavioral Health, Ohio State University Wexner Medical Center, Columbus, OH, USA 43210
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Liu F, Shi Y, Wu Q, Chen H, Wang Y, Cai L, Zhang N. The value of FDG combined with PiB PET in the diagnosis of patients with cognitive impairment in a memory clinic. CNS Neurosci Ther 2024; 30:e14418. [PMID: 37602885 PMCID: PMC10848040 DOI: 10.1111/cns.14418] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 07/12/2023] [Accepted: 08/07/2023] [Indexed: 08/22/2023] Open
Abstract
AIMS To analyze the value of 18 F-fluorodeoxyglucose (FDG) positron emission tomography (PET) combined with amyloid PET in cognitive impairment diagnosis. METHODS A total of 187 patients with dementia or mild cognitive impairment (MCI) who underwent 11 C-Pittsburgh compound B (PiB) and FDG PET scans in a memory clinic were included in the final analysis. RESULTS Amyloid-positive and amyloid-negative dementia patient groups showed a significant difference in the proportion of individuals presenting temporoparietal cortex (p < 0.001) and posterior cingulate/precuneus cortex (p < 0.001) hypometabolism. The sensitivity and specificity of this hypometabolic pattern for identifying amyloid pathology were 72.61% and 77.97%, respectively, in patients clinically diagnosed with AD and 60.87% and 76.19%, respectively, in patients with MCI. The initial diagnosis was changed in 32.17% of patients with dementia after considering both PiB and FDG results. There was a significant difference in both the proportion of patients showing the hypometabolic pattern and PiB positivity between dementia conversion patients and patients with a stable diagnosis of MCI (p < 0.05). CONCLUSION Temporoparietal and posterior cingulate/precuneus cortex hypometabolism on FDG PET suggested amyloid pathology in patients with cognitive impairment and is helpful in diagnostic decision-making and predicting AD dementia conversion from MCI, particularly when combined with amyloid PET.
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Affiliation(s)
- Fang Liu
- Department of NeurologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
| | - Yudi Shi
- Department of NeurologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
- Health Management CenterTianjin Medical University General Hospital Airport SiteTianjinChina
| | - Qiuyan Wu
- Department of NeurologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
| | - Huifeng Chen
- Department of NeurologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
- Department of NeurologyTianjin Medical University General Hospital Airport SiteTianjinChina
| | - Ying Wang
- PET/CT CenterTianjin Medical University General HospitalTianjinChina
| | - Li Cai
- PET/CT CenterTianjin Medical University General HospitalTianjinChina
| | - Nan Zhang
- Department of NeurologyTianjin Neurological Institute, Tianjin Medical University General HospitalTianjinChina
- Department of NeurologyTianjin Medical University General Hospital Airport SiteTianjinChina
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Thurin K, Patel V, Perez DL, Dickerson BC, Hochberg D, Quimby M, Miller MB, Feany M, Silbersweig D, McGinnis SM, Daffner KR, Gale SA. Case Study 2: A 60-Year-Old Man With Progressive Deficits in Language Output. J Neuropsychiatry Clin Neurosci 2022; 34:196-203. [PMID: 35921620 DOI: 10.1176/appi.neuropsych.22010013] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Affiliation(s)
- Kristina Thurin
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Viharkumar Patel
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - David L Perez
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Bradford C Dickerson
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Daisy Hochberg
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Megan Quimby
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Michael B Miller
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Mel Feany
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - David Silbersweig
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Scott M McGinnis
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Kirk R Daffner
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
| | - Seth A Gale
- Department of Psychiatry and Department of Neurology, Center for Cognitive and Memory Disorders, Ohio State University Wexner Medical Center, Columbus, Ohio (Thurin); Departments of Psychiatry (Thurin, Silbersweig) and Neurology (Thurin, McGinnis, Daffner, Gale), Center for Brain/Mind Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston; Department of Pathology, Division of Neuropathology, Brigham and Women's Hospital, Harvard Medical School (Patel, Miller, Feany); Departments of Neurology and Psychiatry, Divisions of Behavioral Neurology and Neuropsychiatry, Massachusetts General Hospital, Harvard Medical School (Perez); Departments of Neurology and Psychiatry, Frontotemporal Disorders Unit, Massachusetts General Hospital, Harvard Medical School (Dickerson, Hochberg, Quimby)
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Functional Imaging for Neurodegenerative Diseases. Presse Med 2022; 51:104121. [PMID: 35490910 DOI: 10.1016/j.lpm.2022.104121] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 09/14/2021] [Revised: 03/13/2022] [Accepted: 04/11/2022] [Indexed: 12/16/2022] Open
Abstract
Diagnosis and monitoring of neurodegenerative diseases has changed profoundly over the past twenty years. Biomarkers are now included in most diagnostic procedures as well as in clinical trials. Neuroimaging biomarkers provide access to brain structure and function over the course of neurodegenerative diseases. They have brought new insights into a wide range of neurodegenerative diseases and have made it possible to describe some of the imaging challenges in clinical populations. MRI mainly explores brain structure while molecular imaging, functional MRI and electro- and magnetoencephalography examine brain function. In this paper, we describe and analyse the current and potential contribution of MRI and molecular imaging in the field of neurodegenerative diseases.
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Chételat G. How to use neuroimaging biomarkers in the diagnosis framework of neurodegenerative diseases? Rev Neurol (Paris) 2022; 178:490-497. [DOI: 10.1016/j.neurol.2022.03.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2022] [Revised: 03/08/2022] [Accepted: 03/08/2022] [Indexed: 11/29/2022]
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Isella V, Crivellaro C, Formenti A, Musarra M, Pacella S, Morzenti S, Ferri F, Mapelli C, Gallivanone F, Guerra L, Appollonio I, Ferrarese C. Validity of cingulate–precuneus–temporo-parietal hypometabolism for single-subject diagnosis of biomarker-proven atypical variants of Alzheimer’s Disease. J Neurol 2022; 269:4440-4451. [PMID: 35347453 PMCID: PMC9293827 DOI: 10.1007/s00415-022-11086-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Revised: 03/14/2022] [Accepted: 03/15/2022] [Indexed: 11/14/2022]
Abstract
The aim of our study was to establish empirically to what extent reduced glucose uptake in the precuneus, posterior cingulate and/or temporo-parietal cortex (PCTP), which is thought to indicate brain amyloidosis in patients with dementia or MCI due to Alzheimer’s Disease (AD), permits to distinguish amyloid-positive from amyloid-negative patients with non-classical AD phenotypes at the single-case level. We enrolled 127 neurodegenerative patients with cognitive impairment and a positive (n. 63) or negative (n. 64) amyloid marker (cerebrospinal fluid or amy-PET). Three rating methods of FDG-PET scan were applied: purely qualitative visual interpretation of uptake images (VIUI), and visual reading assisted by a semi-automated and semi-quantitative tool: INLAB, provided by the Italian National Research Council, or Cortex ID Suite, marketed by GE Healthcare. Fourteen scans (11.0%) patients remained unclassified by VIUI or INLAB procedures, therefore, validity values were computed on the remaining 113 cases. The three rating approaches showed good total accuracy (77–78%), good to optimal sensitivity (81–93%), but poorer specificity (62–75%). VIUI showed the highest sensitivity and the lowest specificity, and also the highest proportion of unclassified cases. Cases with asymmetric temporo-parietal hypometabolism and a progressive aphasia or corticobasal clinical profile, in particular, tended to be rated as AD-like, even if biomarkers indicated non-amyloid pathology. Our findings provide formal support to the value of PCTP hypometabolism for single-level diagnosis of amyloid pathophysiology in atypical AD, but also highlight the risk of qualitative assessment to misclassify patients with non-AD PPA or CBS underpinned by asymmetric temporo-parietal hypometabolism.
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Hansen N, Stöcker W, Wiltfang J, Bartels C, Rentzsch K, Bouter C. Case Report: Semantic Variant of Primary Progressive Aphasia Associated With Anti-Glial Fibrillary Acid Protein Autoantibodies. Front Immunol 2022; 12:760021. [PMID: 35046935 PMCID: PMC8761624 DOI: 10.3389/fimmu.2021.760021] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/17/2021] [Accepted: 11/29/2021] [Indexed: 11/13/2022] Open
Abstract
Background Frontotemporal lobar degeneration is a heterogeneous disorder entailing a semantic variant of primary progressive aphasia (svPPA). A subtype of frontotemporal dementia associated with glutamate receptor subunit 3 (GluA3) antibody of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) was recently identified. Here, we describe the novelty of a svPPA associated with anti-glial fibrillary acid protein (GFAP) antibodies. Methods To diagnose this 68-year-old woman we conducted a clinical examination, neuropsychological testing, CSF analysis, MRI and 18F-fluorodeoxyglucose (18F-FDG) Positron Emission Tomography (PET)/computed tomography (CT) imaging. Results The clinical phenotype corresponds to a svPPA based on impaired confrontation naming and single-word comprehension. In addition, we observed spared speech production, impaired object knowledge, and surface dyslexia - further supporting the diagnosis of svPPA. Additional characteristic imaging features such as anterior temporal hypometabolism in 18F-FDG PET/CT confirmed patient’s svPPA diagnosis. CSF analysis revealed signs of axonal degeneration, as both tau and phosphorylated tau proteins exceeded normal levels. Her serum showed anti-GFAP autoantibodies. Conclusion We diagnosed a svPPA in this patient and report an association between serum anti-GFAP antibodies and svPPA never reported in the literature so far, thereby expanding the clinical spectrum of svPPA and anti-GFAP-antibody related disease. Further research is needed to elucidate the underlying immunopathology of this disease entity to ultimately improve treatment.
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Affiliation(s)
- Niels Hansen
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen, Germany
| | | | - Jens Wiltfang
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen, Germany.,German Center for Neurodegenerative Diseases (DZNE), Goettingen, Germany.,Neurosciences and Signaling Group, Institute of Biomedicine (iBiMED), Department of Medical Sciences, University of Aveiro, Aveiro, Portugal
| | - Claudia Bartels
- Department of Psychiatry and Psychotherapy, University Medical Center Goettingen, Goettingen, Germany
| | | | - Caroline Bouter
- Department of Nuclear Medicine, University Medical Center Göttingen, Goettingen, Germany
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Díaz-Álvarez J, Matias-Guiu JA, Cabrera-Martín MN, Pytel V, Segovia-Ríos I, García-Gutiérrez F, Hernández-Lorenzo L, Matias-Guiu J, Carreras JL, Ayala JL. Genetic Algorithms for Optimized Diagnosis of Alzheimer's Disease and Frontotemporal Dementia Using Fluorodeoxyglucose Positron Emission Tomography Imaging. Front Aging Neurosci 2022; 13:708932. [PMID: 35185510 PMCID: PMC8851241 DOI: 10.3389/fnagi.2021.708932] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/12/2021] [Accepted: 12/20/2021] [Indexed: 11/13/2022] Open
Abstract
Genetic algorithms have a proven capability to explore a large space of solutions, and deal with very large numbers of input features. We hypothesized that the application of these algorithms to 18F-Fluorodeoxyglucose Positron Emission Tomography (FDG-PET) may help in diagnosis of Alzheimer's disease (AD) and Frontotemporal Dementia (FTD) by selecting the most meaningful features and automating diagnosis. We aimed to develop algorithms for the three main issues in the diagnosis: discrimination between patients with AD or FTD and healthy controls (HC), differential diagnosis between behavioral FTD (bvFTD) and AD, and differential diagnosis between primary progressive aphasia (PPA) variants. Genetic algorithms, customized with K-Nearest Neighbor and BayesNet Naives as the fitness function, were developed and compared with Principal Component Analysis (PCA). K-fold cross validation within the same sample and external validation with ADNI-3 samples were performed. External validation was performed for the algorithms distinguishing AD and HC. Our study supports the use of FDG-PET imaging, which allowed a very high accuracy rate for the diagnosis of AD, FTD, and related disorders. Genetic algorithms identified the most meaningful features with the minimum set of features, which may be relevant for automated assessment of brain FDG-PET images. Overall, our study contributes to the development of an automated, and optimized diagnosis of neurodegenerative disorders using brain metabolism.
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Affiliation(s)
- Josefa Díaz-Álvarez
- Department of Computer Architecture and Communications, Centro Universitario de Mérida, Universidad de Extremadura, Badajoz, Spain
| | - Jordi A. Matias-Guiu
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - María Nieves Cabrera-Martín
- Department of Nuclear Medicine, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - Vanesa Pytel
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - Ignacio Segovia-Ríos
- Department of Computer Architecture and Communications, Centro Universitario de Mérida, Universidad de Extremadura, Badajoz, Spain
| | - Fernando García-Gutiérrez
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | - Laura Hernández-Lorenzo
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | - Jorge Matias-Guiu
- Department of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - José Luis Carreras
- Department of Nuclear Medicine, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - José L. Ayala
- Department of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
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Perani D, Cappa SF. The contribution of positron emission tomography to the study of aphasia. HANDBOOK OF CLINICAL NEUROLOGY 2022; 185:151-165. [PMID: 35078596 DOI: 10.1016/b978-0-12-823384-9.00008-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Subscribe] [Scholar Register] [Indexed: 10/19/2022]
Affiliation(s)
- Daniela Perani
- Faculty of Psychology, Vita-Salute San Raffaele University, Milan, Italy; In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, Nuclear Medicine Unit, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Stefano F Cappa
- Department of Humanities and Life Sciences, University Institute for Advanced Studies IUSS Pavia, Pavia, Italy; Dementia Research Center, IRCCS Mondino Foundation, Pavia, Italy.
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11
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Imaging Clinical Subtypes and Associated Brain Networks in Alzheimer’s Disease. Brain Sci 2022; 12:brainsci12020146. [PMID: 35203910 PMCID: PMC8869882 DOI: 10.3390/brainsci12020146] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2021] [Revised: 01/17/2022] [Accepted: 01/18/2022] [Indexed: 11/17/2022] Open
Abstract
Alzheimer’s disease (AD) does not present uniform symptoms or a uniform rate of progression in all cases. The classification of subtypes can be based on clinical symptoms or patterns of pathological brain alterations. Imaging techniques may allow for the identification of AD subtypes and their differentiation from other neurodegenerative diseases already at an early stage. In this review, the strengths and weaknesses of current clinical imaging methods are described. These include positron emission tomography (PET) to image cerebral glucose metabolism and pathological amyloid or tau deposits. Magnetic resonance imaging (MRI) is more widely available than PET. It provides information on structural or functional changes in brain networks and their relation to AD subtypes. Amyloid PET provides a very early marker of AD but does not distinguish between AD subtypes. Regional patterns of pathology related to AD subtypes are observed with tau and glucose PET, and eventually as atrophy patterns on MRI. Structural and functional network changes occur early in AD but have not yet provided diagnostic specificity.
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12
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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: 109] [Impact Index Per Article: 27.3] [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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13
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Cecchin D, Garibotto V, Law I, Goffin K. PET Imaging in Neurodegeneration and Neuro-oncology: Variants and Pitfalls. Semin Nucl Med 2021; 51:408-418. [PMID: 33820651 DOI: 10.1053/j.semnuclmed.2021.03.003] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
In neurodegenerative diseases, positron emission tomography (PET) imaging plays an important role in the early identification and differential diagnosis in particular in clinically challenging patients. 18F-FDG is still the most widely used and established tracer in this patient group, with different cortical and subcortical regions being preferentially affected in different neurodegenerative diseases, such as frontotemporal dementia, Alzheimer's disease or Lewy Body dementia, resulting in typical hypometabolic patterns. Over the last decades, however, the implementation of tracers specific for the pathological deposits characteristic of the different diseases, such as amyloid and tau, has revolutionized the way of classifying and reporting cases of cognitive impairment of neurodegenerative origin, providing complementary information to 18F-FDG PET. In neuro-oncology, PET imaging can be performed in several clinical indications, as highlighted in the joint European Association of Nuclear Medicine (EANM)/European Association of Neuro-Oncology (EANO)/Response assessment in neuro-oncology (RANO) practice guidelines on imaging in neuro-oncology. For assessment of glioma, amino-acid analogues, such as 11C-methionine or 18F-FET, are used whenever clinically available, as they offer excellent tumor-to-background ratios in malignant tumors. Moreover, dynamic acquisition of amino-acid analogue tracers and assessment of the shape of the time-activity curve can be used to perform noninvasive grading of brain gliomas, differentiating low from high grade presentations. In both settings, however, thorough knowledge of the normal physiological tracer distribution and the variants and pitfalls that can occur during image acquisition, processing and interpretation is mandatory in order to provide optimal diagnostic information to referring physicians and patients. Especially in neuro-oncology, this process can be aided by the active use of coregistered magnetic resonance imaging to accurately identify the imaging correlates of developmental origin, acute and chronic stroke, inflammation, infection and seizure related activity.
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Affiliation(s)
- Diego Cecchin
- Nuclear Medicine Unit, Department of Medicine DIMED, Padua University Hospital, Padua, Italy
| | - Valentina Garibotto
- Nuclear Medicine and Molecular Imaging Division, Diagnostic Department, University Hospitals of Geneva and NIMTLab, Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Ian Law
- Department of Clinical Physiology, Nuclear Medicine and PET, Rigshospitalet, Copenhagen, Denmark
| | - Karolien Goffin
- Department of Nuclear Medicine, University Hospital Leuven, Division of Nuclear Medicine and Molecular Imaging, KU Leuven, Leuven, Belgium.
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14
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Li Q, Hou W, Li L, Su M, Ren Y, Wang W, Zou K, Tian R, Sun X. The use of systematic review evidence to support the development of guidelines for positron emission tomography: a cross-sectional survey. Eur Radiol 2021; 31:6992-7002. [PMID: 33683391 DOI: 10.1007/s00330-021-07756-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2020] [Revised: 01/06/2021] [Accepted: 02/04/2021] [Indexed: 02/05/2023]
Abstract
OBJECTIVES To examine to what degree guidelines for PET and PET/CT used systematic review evidence. METHODS The latest version of guidelines for PET, PET/CT or PET/MRI published in English in PubMed until December 2019 was analysed in two categories: (1) for indications, if mainly discussing the appropriate use of PET in diverse conditions; (2) for procedures, if providing step-by-step instructions for imaging. We surveyed the general characteristics and the use of systematic review evidence for developing recommendations across all guidelines, and surveyed the citation of evidence for five recommendation topics in guidelines for procedures. RESULTS Forty-seven guidelines, published between 2004 and 2020, were included. Guidelines for indications were developed mainly on systematic reviews (13 of 19, 68.4%). Among those, 12 (63.2%) reported the level of evidence, 4 (21.1%) reported the strength of recommendations, 3 (15.8%) described external review and 7 (36.8%) involved methodologists. Guidelines for procedures were seldom developed on systematic reviews (1 of 27, 3.7%). Among those, 1 (3.7%) reported the level of evidence, 1 (3.7%) reported the strength of recommendations, 3 (11.1%) described external review and 1 (3.7%) involved methodologists. Systematic review evidence was cited by 2 (7.4%) procedure guidelines per recommendation topic in median. CONCLUSION The use of systematic review evidence for developing recommendations among PET or PET/CT guidelines was suboptimal. While our survey is an icebreaking attempt to explore a key element (i.e. use of systematic review evidence) for developing nuclear medicine guidelines, assessments of other domains of guideline quality may help capture the entire picture. KEY POINTS • The use of systematic review evidence for developing recommendations among guidelines for PET or PET/CT was suboptimal. • Only 13 (68.4%) guidelines for indications and 1 (3.7%) guideline for procedures systematically reviewed the literature during guideline development. • For each recommendation topic we examined, only a median of 2 (7.4%) procedure guidelines cited systematic review evidence.
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Affiliation(s)
- Qianrui Li
- Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.,Chinese Evidence-based Medicine Centre, Cochrane China Centre and MAGIC China Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wenxiu Hou
- Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Ling Li
- Chinese Evidence-based Medicine Centre, Cochrane China Centre and MAGIC China Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Minggang Su
- Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Yan Ren
- Chinese Evidence-based Medicine Centre, Cochrane China Centre and MAGIC China Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Wen Wang
- Chinese Evidence-based Medicine Centre, Cochrane China Centre and MAGIC China Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Kang Zou
- Chinese Evidence-based Medicine Centre, Cochrane China Centre and MAGIC China Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China
| | - Rong Tian
- Department of Nuclear Medicine, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
| | - Xin Sun
- Chinese Evidence-based Medicine Centre, Cochrane China Centre and MAGIC China Centre, West China Hospital, Sichuan University, Chengdu, Sichuan, China.
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15
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Burgos N, Cardoso MJ, Samper-González J, Habert MO, Durrleman S, Ourselin S, Colliot O. Anomaly detection for the individual analysis of brain PET images. J Med Imaging (Bellingham) 2021; 8:024003. [PMID: 33842668 PMCID: PMC8021015 DOI: 10.1117/1.jmi.8.2.024003] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/04/2020] [Accepted: 03/12/2021] [Indexed: 11/14/2022] Open
Abstract
Purpose: In clinical practice, positron emission tomography (PET) images are mostly analyzed visually, but the sensitivity and specificity of this approach greatly depend on the observer's experience. Quantitative analysis of PET images would alleviate this problem by helping define an objective limit between normal and pathological findings. We present an anomaly detection framework for the individual analysis of PET images. Approach: We created subject-specific abnormality maps that summarize the pathology's topographical distribution in the brain by comparing the subject's PET image to a model of healthy PET appearance that is specific to the subject under investigation. This model was generated from demographically and morphologically matched PET scans from a control dataset. Results: We generated abnormality maps for healthy controls, patients at different stages of Alzheimer's disease and with different frontotemporal dementia syndromes. We showed that no anomalies were detected for the healthy controls and that the anomalies detected from the patients with dementia coincided with the regions where abnormal uptake was expected. We also validated the proposed framework using the abnormality maps as inputs of a classifier and obtained higher classification accuracies than when using the PET images themselves as inputs. Conclusions: The proposed method was able to automatically locate and characterize the areas characteristic of dementia from PET images. The abnormality maps are expected to (i) help clinicians in their diagnosis by highlighting, in a data-driven fashion, the pathological areas, and (ii) improve the interpretability of subsequent analyses, such as computer-aided diagnosis or spatiotemporal modeling.
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Affiliation(s)
- Ninon Burgos
- Paris Brain Institute, Hôpital Pitié-Salpêtrière, Paris, France
- INSERM, U 1127, Hôpital Pitié-Salpêtrière, Paris, France
- CNRS, UMR 7225, Hôpital Pitié-Salpêtrière, Paris, France
- Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
- Inria, Aramis Project-Team, Hôpital Pitié-Salpêtrière, Paris, France
| | - M. Jorge Cardoso
- King’s College London, Department of Imaging and Biomedical Engineering, London, United Kingdom
| | - Jorge Samper-González
- Paris Brain Institute, Hôpital Pitié-Salpêtrière, Paris, France
- INSERM, U 1127, Hôpital Pitié-Salpêtrière, Paris, France
- CNRS, UMR 7225, Hôpital Pitié-Salpêtrière, Paris, France
- Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
- Inria, Aramis Project-Team, Hôpital Pitié-Salpêtrière, Paris, France
| | - Marie-Odile Habert
- AP-HP, Hôpital Pitié-Salpêtrière, Department of Nuclear Medicine, Paris, France
- Laboratoire d’Imagerie Biomédicale, Sorbonne Université, Inserm U 1146, CNRS UMR 7371, Hôpital Pitié-Salpêtrière, Paris, France
- Centre Acquisition et Traitement des Images, Hôpital Pitié-Salpêtrière, Paris, France
| | - Stanley Durrleman
- Paris Brain Institute, Hôpital Pitié-Salpêtrière, Paris, France
- INSERM, U 1127, Hôpital Pitié-Salpêtrière, Paris, France
- CNRS, UMR 7225, Hôpital Pitié-Salpêtrière, Paris, France
- Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
- Inria, Aramis Project-Team, Hôpital Pitié-Salpêtrière, Paris, France
| | - Sébastien Ourselin
- King’s College London, Department of Imaging and Biomedical Engineering, London, United Kingdom
| | - Olivier Colliot
- Paris Brain Institute, Hôpital Pitié-Salpêtrière, Paris, France
- INSERM, U 1127, Hôpital Pitié-Salpêtrière, Paris, France
- CNRS, UMR 7225, Hôpital Pitié-Salpêtrière, Paris, France
- Sorbonne Université, Hôpital Pitié-Salpêtrière, Paris, France
- Inria, Aramis Project-Team, Hôpital Pitié-Salpêtrière, Paris, France
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16
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Dev SI, Dickerson BC, Touroutoglou A. Neuroimaging in Frontotemporal Lobar Degeneration: Research and Clinical Utility. ADVANCES IN EXPERIMENTAL MEDICINE AND BIOLOGY 2021; 1281:93-112. [PMID: 33433871 PMCID: PMC8787866 DOI: 10.1007/978-3-030-51140-1_7] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
Abstract
Frontotemporal lobar dementia (FTLD) is a clinically and pathologically complex disease. Advances in neuroimaging techniques have provided a specialized set of tools to investigate underlying pathophysiology and identify clinical biomarkers that aid in diagnosis, prognostication, monitoring, and identification of appropriate endpoints in clinical trials. In this chapter, we review data discussing the utility of neuroimaging biomarkers in sporadic FTLD, with an emphasis on current and future clinical applications. Among those modalities readily utilized in clinical settings, T1-weighted structural magnetic resonance imaging (MRI) and 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) are best supported in differential diagnosis and as targets for clinical trial endpoints. However, a number of nonclinical neuroimaging modalities, including diffusion tensor imaging and resting-state functional connectivity MRI, show promise as biomarkers to predict progression and as clinical trial endpoints. Other neuroimaging modalities, including amyloid PET, Tau PET, and arterial spin labeling MRI, are also discussed, though more work is required to establish their utility in FTLD in clinical settings.
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Affiliation(s)
- Sheena I Dev
- Department of Psychiatry, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, USA
| | - Bradford C Dickerson
- Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, USA.
| | - Alexandra Touroutoglou
- Department of Neurology, Massachusetts General Hospital/Harvard Medical School, Charlestown, MA, USA
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17
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Massa F, Farotti L, Eusebi P, Capello E, Dottorini ME, Tranfaglia C, Bauckneht M, Morbelli S, Nobili F, Parnetti L. Reciprocal Incremental Value of 18F-FDG-PET and Cerebrospinal Fluid Biomarkers in Mild Cognitive Impairment Patients Suspected for Alzheimer's Disease and Inconclusive First Biomarker. J Alzheimers Dis 2020; 72:1193-1207. [PMID: 31683477 DOI: 10.3233/jad-190539] [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] [Indexed: 12/11/2022]
Abstract
BACKGROUND In Alzheimer's disease (AD) diagnosis, both cerebrospinal fluid (CSF) biomarkers and FDG-PET sometimes give inconclusive results. OBJECTIVE To evaluate the incremental diagnostic value of FDG-PET over CSF biomarkers, and vice versa, in patients with mild cognitive impairment (MCI) and suspected AD, in which the first biomarker resulted inconclusive. METHODS A consecutive series of MCI patients was retrospectively selected from two Memory Clinics where, as per clinical routine, either the first biomarker choice is FDG-PET and CSF biomarkers are only used in patients with uninformative FDG-PET, or vice versa. We defined criteria of uncertainty in interpretation of FDG-PET and CSF biomarkers, according to current evidence. The final diagnosis was established according to clinical-neuropsychological follow-up of at least one year (mean 4.4±2.2). RESULTS When CSF was used as second biomarker after FDG-PET, 14 out of 36 (39%) received informative results. Among these 14 patients, 11 (79%) were correctly classified with respect to final diagnosis, thus with a relative incremental value of CSF over FDG-PET of 30.6%. When FDG-PET was used as second biomarker, 26 out of 39 (67%) received informative results. Among these 26 patients, 15 (58%) were correctly classified by FDG-PET with respect to final diagnosis, thus with a relative incremental value over CSF of 38.5%. CONCLUSION Our real-world data confirm the added values of FDG-PET (or CSF) in a diagnostic pathway where CSF (or FDG-PET) was used as first biomarkers in suspected AD. These findings should be replicated in larger studies with prospective enrolment according to a Phase III design.
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Affiliation(s)
- Federico Massa
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy
| | - Lucia Farotti
- Center for Memory Disorders and Laboratory of Clinical Neurochemistry, Neurology Clinic, University of Perugia, Perugia, Italy
| | - Paolo Eusebi
- Section of Neurology, Department of Medicine, University of Perugia, Perugia, Italy.,Health Planning Service, Department of Epidemiology, Regional Health Authority of Umbria, Perugia, Italy
| | | | - Massimo E Dottorini
- Nuclear Medicine Unit, "S. Maria della Misericordia" Hospital, Perugia, Italy
| | - Cristina Tranfaglia
- Nuclear Medicine Unit, "S. Maria della Misericordia" Hospital, Perugia, Italy
| | - Matteo Bauckneht
- Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Silvia Morbelli
- Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Health Sciences (DISSAL), University of Genoa, Genoa, Italy
| | - Flavio Nobili
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, Maternal and Child Health, University of Genoa, Genoa, Italy.,Neurology Clinic, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Lucilla Parnetti
- Center for Memory Disorders and Laboratory of Clinical Neurochemistry, Neurology Clinic, University of Perugia, Perugia, Italy
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18
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Chételat G, Arbizu J, Barthel H, Garibotto V, Law I, Morbelli S, van de Giessen E, Agosta F, Barkhof F, Brooks DJ, Carrillo MC, Dubois B, Fjell AM, Frisoni GB, Hansson O, Herholz K, Hutton BF, Jack CR, Lammertsma AA, Landau SM, Minoshima S, Nobili F, Nordberg A, Ossenkoppele R, Oyen WJG, Perani D, Rabinovici GD, Scheltens P, Villemagne VL, Zetterberg H, Drzezga A. Amyloid-PET and 18F-FDG-PET in the diagnostic investigation of Alzheimer's disease and other dementias. Lancet Neurol 2020; 19:951-962. [PMID: 33098804 DOI: 10.1016/s1474-4422(20)30314-8] [Citation(s) in RCA: 250] [Impact Index Per Article: 50.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2019] [Revised: 07/22/2020] [Accepted: 08/06/2020] [Indexed: 12/14/2022]
Abstract
Various biomarkers are available to support the diagnosis of neurodegenerative diseases in clinical and research settings. Among the molecular imaging biomarkers, amyloid-PET, which assesses brain amyloid deposition, and 18F-fluorodeoxyglucose (18F-FDG) PET, which assesses glucose metabolism, provide valuable and complementary information. However, uncertainty remains regarding the optimal timepoint, combination, and an order in which these PET biomarkers should be used in diagnostic evaluations because conclusive evidence is missing. Following an expert panel discussion, we reached an agreement on the specific use of the individual biomarkers, based on available evidence and clinical expertise. We propose a diagnostic algorithm with optimal timepoints for these PET biomarkers, also taking into account evidence from other biomarkers, for early and differential diagnosis of neurodegenerative diseases that can lead to dementia. We propose three main diagnostic pathways with distinct biomarker sequences, in which amyloid-PET and 18F-FDG-PET are placed at different positions in the order of diagnostic evaluations, depending on clinical presentation. We hope that this algorithm can support diagnostic decision making in specialist clinical settings with access to these biomarkers and might stimulate further research towards optimal diagnostic strategies.
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Affiliation(s)
- Gaël Chételat
- Normandie Université, Université de Caen, Institut National de la Santé et de la Recherche Médicale, Unité 1237, Groupement d'Intérêt Public Cyceron, Caen, France.
| | - Javier Arbizu
- Department of Nuclear Medicine, University of Navarra, Clinica Universidad de Navarra, Pamplona, Spain
| | - Henryk Barthel
- Department of Nuclear Medicine, University Hospital of Leipzig, Leipzig, Germany
| | - Valentina Garibotto
- Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals and NIMTlab, Geneva University, Geneva, Switzerland
| | - Ian Law
- Department of Clinical Physiology, Nuclear Medicine and PET, Copenhagen University Hospital, Rigshospitalet, Copenhagen, Denmark
| | - Silvia Morbelli
- Nuclear Medicine Unit, Istituto di Ricovero e Cura a Carattere Scientifico Ospedale Policlinico San Martino, Genova, Italy
| | - Elsmarieke van de Giessen
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, University of Amsterdam, Amsterdam, Netherlands
| | - Federica Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, Istituto di Ricovero e Cura a Carattere, San Raffaele Scientific Institute, Milan, Italy; Vita-Salute San Raffaele University, Milan, Italy
| | - Frederik Barkhof
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Institutes of Neurology and Healthcare Engineering, University College London, London, UK
| | - David J Brooks
- Institute of Neuroscience, Newcastle University, Newcastle, UK; Department of Nuclear Medicine and PET Centre, Aarhus University Hospital, Aarhus, Denmark
| | | | - Bruno Dubois
- Centre des Maladies Cognitives et Comportementales, University Hospital of Pitié Salpêtrière, Assistance Publique-Hôpitaux de Paris, Sorbonne-Université, Paris, France
| | - Anders M Fjell
- Center for Lifespan Changes in Brain and Cognition, Department of Psychology, University of Oslo, Norway, Oslo; Department of Radiology and Nuclear Medicine, Oslo University Hospital, Oslo, Norway
| | - Giovanni B Frisoni
- Memory Clinic, Department of Rehabilitation and Geriatrics, Geneva University and University Hospitals, Geneva, Switzerland
| | - Oskar Hansson
- Clinical Memory Research Unit, Lund University, Malmö, Sweden; Memory Clinic, Skåne University Hospital, Malmö, Sweden
| | - Karl Herholz
- Wolfson Molecular Imaging Centre, Division of Neuroscience and Experimental Psychology, University of Manchester, Manchester, UK
| | - Brian F Hutton
- Institute of Nuclear Medicine, University College London, London, UK
| | | | - Adriaan A Lammertsma
- Department of Radiology and Nuclear Medicine, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California, Berkeley, Berkeley, CA, USA
| | - Satoshi Minoshima
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, UT, USA
| | - Flavio Nobili
- UO Clinica Neurologica, Istituto di Ricovero e Cura a Carattere Scientifico Ospedale Policlinico San Martino, Genova, Italy; Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Child and Mother Health, University of Genoa, Genova, Italy
| | - Agneta Nordberg
- Department of Neurobiology, Care Sciences and Society, Center for Alzheimer Research, Karolinska Institutet, Stockholm, Sweden
| | - Rik Ossenkoppele
- Department of Neurology, Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands; Clinical Memory Research Unit, Lund University, Lund, Sweden
| | - Wim J G Oyen
- Humanitas University and Humanitas Clinical and Research Center, Department of Nuclear Medicine, Milan, Italy; Rijnstate, Department of Radiology and Nuclear Medicine, Arnhem, Netherlands; Radboud UMC, Department of Radiology and Nuclear Medicine, Nijmegen, Netherlands
| | - Daniela Perani
- Vita-Salute San Raffaele University, Nuclear Medicine Unit, San Raffaele Hospital, Division of Neuroscience San Raffaele Scientific Institute, Milan, Italy
| | - Gil D Rabinovici
- Departments of Neurology, Radiology and Biomedical Imaging, University of California San Francisco, San Francisco, CA, USA
| | - Philip Scheltens
- Department of Neurology, Alzheimer Center, Amsterdam University Medical Center, Vrije Universiteit Amsterdam, Amsterdam, Netherlands
| | - Victor L Villemagne
- Department of Molecular Imaging & Therapy, Austin Health, Department of Medicine, University of Melbourne, Austin Health, Heidelberg, VIC, Australia; School of Medical and Health Sciences, Edith Cowan University, Perth, WA, Australia
| | - Henrik Zetterberg
- Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK; Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, The Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden; Clinical Neurochemistry Laboratory, Sahlgrenska University Hospital, Mölndal, Sweden; UK Dementia Research Institute at University College London, London, UK
| | - Alexander Drzezga
- Department of Nuclear Medicine, Faculty of Medicine and University Hospital Cologne, University of Cologne, Germany; German Center for Neurodegenerative Diseases, Bonn-Cologne, Germany; Institute of Neuroscience and Medicine, Molecular Organization of the Brain, Forschungszentrum Jülich, Germany
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Nuvoli S, Tanda G, Stazza ML, Madeddu G, Spanu A. Qualitative and Quantitative Analyses of Brain 18Fluoro-Deoxy-Glucose Positron Emission Tomography in Primary Progressive Aphasia. Dement Geriatr Cogn Disord 2020; 48:250-260. [PMID: 32062656 DOI: 10.1159/000504938] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/26/2019] [Accepted: 11/20/2019] [Indexed: 12/16/2022] Open
Abstract
BACKGROUND A primary progressive aphasia (PPA) diagnosis is generally based on clinical criteria, but often symptoms and signs may overlap in the different forms. Recent data have evidenced that brain 18fluoro-deoxy-glucose positron emission tomography (18F-FDG PET) could support the clinical diagnosis, since specific metabolic patterns are described for the different variants. AIMS We further evaluated the usefulness of 18F-FDG PET, by both visual qualitative (QL) and quantitative (QN) methods in the initial diagnosis of PPA, focusing on the classification of different variants. Moreover, we also analyzed the role of 18F-FDG PET in clarifying the association of PPA with the early phase of Alzheimer's disease (AD) or frontotemporal (FTD) dementias. METHODS We consecutively enrolled 35 patients with clinical symptoms of aphasia, suspect of or attributable to PPA. Patients were classified into two groups: 18 cases with clinical symptoms of aphasia but normal neuropsychological tests and an unclear classification of a specific PPA variant (group A) and 17 cases with clinical and neuropsychological signs attributable to PPA with an uncertain differential diagnosis between AD and FTD (group B). All patients underwent brain 18F-FDG PET/CT, and images were evaluated both by QL and QN, the latter applying an automated analysis program that produced brain regional metabolicmaps and normal age-matched control group comparative analysis (zscore). RESULTS 18F-FDG PET showed different patterns of bilateral cortical hypometabolism in the two groups. The combined use of QL and QN permitted to achieved a correct PPA variant diagnosis in 8 of 18 (44.4%) cases of group A and in 14 of 17 (82.3%) of group B, while only QN could support the correct classification of PPA variants in 10 of 18 (55.6%) cases of group A and in 3 of 17 (17.7%) cases of group B in whom the procedure better localized the hypometabolic areas. CONCLUSIONS Brain 18F-FDG PET had an elevated performance in the early diagnosis of PPA variants and in the advanced PPA AD/FTD classification. QL clarified the development of AD or FTD in advanced PPA cases and supported the differential diagnosis of a PPA variant in a few early cases. QN 18F-FDG PET evaluation better contributed to the early diagnosis of an unclear metabolic pattern. To correctly identify all cases, patients with diffuse cortical hypometabolism were also included. Larger series are necessary to confirm these data.
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Affiliation(s)
- Susanna Nuvoli
- Unit of Nuclear Medicine, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy,
| | - Giovanna Tanda
- Unit of Nuclear Medicine, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Maria Lina Stazza
- Unit of Nuclear Medicine, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Giuseppe Madeddu
- Unit of Nuclear Medicine, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
| | - Angela Spanu
- Unit of Nuclear Medicine, Department of Medical, Surgical and Experimental Sciences, University of Sassari, Sassari, Italy
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20
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Bejanin A, Tammewar G, Marx G, Cobigo Y, Iaccarino L, Kornak J, Staffaroni AM, Dickerson BC, Boeve BF, Knopman DS, Gorno-Tempini M, Miller BL, Jagust WJ, Boxer AL, Rosen HJ, Rabinovici GD. Longitudinal structural and metabolic changes in frontotemporal dementia. Neurology 2020; 95:e140-e154. [PMID: 32591470 PMCID: PMC7455324 DOI: 10.1212/wnl.0000000000009760] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/02/2019] [Accepted: 12/13/2019] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE To compare the sensitivity of structural MRI and 18F-fludeoxyglucose PET (18FDG-PET) to detect longitudinal changes in frontotemporal dementia (FTD). METHODS Thirty patients with behavioral variant FTD (bvFTD), 7 with nonfluent/agrammatic variant primary progressive aphasia (nfvPPA), 16 with semantic variant primary progressive aphasia (svPPA), and 43 cognitively normal controls underwent 2-4 MRI and 18FDG-PET scans (total scans/visit = 270) as part of the Frontotemporal Lobar Degeneration Neuroimaging Initiative study. Linear mixed-effects models were carried out voxel-wise and in regions of interest to identify areas showing decreased volume or metabolism over time in patients as compared to controls. RESULTS At baseline, patients with bvFTD showed bilateral temporal, dorsolateral, and medial prefrontal atrophy/hypometabolism that extended with time into adjacent structures and parietal lobe. In nfvPPA, baseline atrophy/hypometabolism in supplementary motor cortex extended with time into left greater than right precentral, dorsolateral, and dorsomedial prefrontal cortex. In svPPA, baseline atrophy/hypometabolism encompassed the anterior temporal and medial prefrontal cortex and longitudinal changes were found in temporal, orbitofrontal, and lateral parietal cortex. Across syndromes, there was substantial overlap in the brain regions showing volume and metabolism loss. Even though the pattern of metabolic decline was more extensive, metabolic changes were also more variable and sample size estimates were similar or higher for 18FDG-PET compared to MRI. CONCLUSION Our findings demonstrated the sensitivity of 18FDG-PET and structural MRI for tracking disease progression in FTD. Both modalities showed highly overlapping patterns of longitudinal change and comparable sample size estimates to detect longitudinal changes in future clinical trials.
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Affiliation(s)
- Alexandre Bejanin
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley.
| | - Gautam Tammewar
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Gabe Marx
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Yann Cobigo
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Leonardo Iaccarino
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - John Kornak
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Adam M Staffaroni
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Bradford C Dickerson
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Bradley F Boeve
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - David S Knopman
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Marilu Gorno-Tempini
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Bruce L Miller
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - William J Jagust
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Adam L Boxer
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Howard J Rosen
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
| | - Gil D Rabinovici
- From the Memory and Aging Center, Department of Neurology (A.B., G.T., G.M., Y.C., L.I., J.K., A.M.S., M.G.-T., B.L.M., A.L.B., H.J.R., G.D.R.), and Department of Radiology and Biomedical Imaging (G.D.R.), University of California San Francisco; Frontotemporal Disorders Unit (B.C.D.), Department of Neurology, Massachusetts General Hospital, Boston; and Harvard Medical School, Charleston; Department of Neurology (B.F.B., D.S.K.), Mayo Clinic, Rochester, MN; Molecular Biophysics and Integrated Bioimaging Division (W.J.J., G.D.R.), Lawrence Berkeley National Laboratory, CA; and Helen Wills Neuroscience Institute (G.D.R.), University of California Berkeley
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21
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Current role of 18F-FDG-PET in the differential diagnosis of the main forms of dementia. Clin Transl Imaging 2020. [DOI: 10.1007/s40336-020-00366-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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22
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Álvarez JD, Matias-Guiu JA, Cabrera-Martín MN, Risco-Martín JL, Ayala JL. An application of machine learning with feature selection to improve diagnosis and classification of neurodegenerative disorders. BMC Bioinformatics 2019; 20:491. [PMID: 31601182 PMCID: PMC6788103 DOI: 10.1186/s12859-019-3027-7] [Citation(s) in RCA: 27] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2019] [Accepted: 08/13/2019] [Indexed: 12/14/2022] Open
Abstract
Background The analysis of health and medical data is crucial for improving the diagnosis precision, treatments and prevention. In this field, machine learning techniques play a key role. However, the amount of health data acquired from digital machines has high dimensionality and not all data acquired from digital machines are relevant for a particular disease. Primary Progressive Aphasia (PPA) is a neurodegenerative syndrome including several specific diseases, and it is a good model to implement machine learning analyses. In this work, we applied five feature selection algorithms to identify the set of relevant features from 18F-fluorodeoxyglucose positron emission tomography images of the main areas affected by PPA from patient records. On the other hand, we carried out classification and clustering algorithms before and after the feature selection process to contrast both results with those obtained in a previous work. We aimed to find the best classifier and the more relevant features from the WEKA tool to propose further a framework for automatic help on diagnosis. Dataset contains data from 150 FDG-PET imaging studies of 91 patients with a clinic prognosis of PPA, which were examined twice, and 28 controls. Our method comprises six different stages: (i) feature extraction, (ii) expertise knowledge supervision (iii) classification process, (iv) comparing classification results for feature selection, (v) clustering process after feature selection, and (vi) comparing clustering results with those obtained in a previous work. Results Experimental tests confirmed clustering results from a previous work. Although classification results for some algorithms are not decisive for reducing features precisely, Principal Components Analisys (PCA) results exhibited similar or even better performances when compared to those obtained with all features. Conclusions Although reducing the dimensionality does not means a general improvement, the set of features is almost halved and results are better or quite similar. Finally, it is interesting how these results expose a finer grain classification of patients according to the neuroanatomy of their disease.
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Affiliation(s)
- Josefa Díaz Álvarez
- Dep. of Computer Architecture and Communications, Universidad de Extremadura, Mérida-Badajoz, Spain.
| | - Jordi A Matias-Guiu
- Dep. of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - María Nieves Cabrera-Martín
- Dep. of Neurology, Hospital Clinico San Carlos, San Carlos Research Health Institute (IdISSC), Universidad Complutense, Madrid, Spain
| | - José L Risco-Martín
- Dep. of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
| | - José L Ayala
- Dep. of Computer Architecture and Automation, Universidad Complutense, Madrid, Spain
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Utianski RL, Botha H, Martin PR, Schwarz CG, Duffy JR, Clark HM, Machulda MM, Butts AM, Lowe VJ, Jack CR, Senjem ML, Spychalla AJ, Whitwell JL, Josephs KA. Clinical and neuroimaging characteristics of clinically unclassifiable primary progressive aphasia. BRAIN AND LANGUAGE 2019; 197:104676. [PMID: 31419589 PMCID: PMC6726500 DOI: 10.1016/j.bandl.2019.104676] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/21/2018] [Revised: 07/01/2019] [Accepted: 08/04/2019] [Indexed: 05/12/2023]
Abstract
Many patients who meet core/root criteria for Primary Progressive Aphasia (PPA) are not classifiable as a recognized variant and are often excluded from neuroimaging studies. Here, we detail neurological, neuropsychological, speech and language assessments, and anatomic and molecular neuroimaging (MRI, PiB-PET, and FDG-PET) for fifteen (8 female) clinically unclassifiable PPA patients. Median age of onset was 64 years old with median 3 years disease duration at exam. Three patients were amyloid positive on PiB-PET. 14/15 patients had abnormal FDG-PETs with left predominant hypometabolism, affecting frontal, temporal, parietal, and even occipital lobes. Patients had mild to severe clinical presentations. Visualization of the FDG-PETs principal component analysis revealed patterns of hypometabolism similar to those seen in the PPA variants and suggests the brain regions affected in unclassifiable PPA patients are no different from those who are more easily classifiable. These findings may inform future modifications to the diagnostic criteria to improve diagnostic classification.
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Affiliation(s)
| | - Hugo Botha
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | - Peter R Martin
- Department of Health Science Research, Mayo Clinic, Rochester, MN, USA
| | | | - Joseph R Duffy
- Department of Neurology, Mayo Clinic, Rochester, MN, USA
| | | | - Mary M Machulda
- Department of Psychiatry & Psychology, Mayo Clinic, Rochester, MN, USA
| | | | - Val J Lowe
- Department of Radiology, Mayo Clinic, Rochester, MN, USA
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Nishida H, Hayashi Y, Ban Y, Kudo T, Harada N, Sakurai T. A Case of Crossed Logopenic Primary Progressive Aphasia in a Dextral Patient with Underlying Frontotemporal Dementia. Intern Med 2019. [PMID: 31391394 DOI: 10.2169/internalmedicine.2301-18] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/06/2022] Open
Abstract
A 61-year-old dextral woman was admitted to the hospital with difficulty finding words. Neurological examinations confirmed that her speech was affected by frequent pauses and occasional phonological paraphasia without cognitive deficits. We detected atrophy, hypoperfusion, and hypometabolism in the right perisylvian and parietal regions, expanding to the right anterior temporal lobes and right inferior frontal gyrus (opercular region) by magnetic resonance imaging, single-photon emission computed tomography, and fluorodexyglucose-positron emission tomography (PET), respectively. Amyloid-PET did not identify the accumulation of amyloid beta (Aβ) in the bilateral cerebral cortices. We herein report a case of crossed aphasia with Aβ-negative logopenic primary progressive aphasia that was likely the result of frontotemporal lobar degeneration.
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Affiliation(s)
- Hiroshi Nishida
- Department of Neurology, Gifu Prefectural General Medical Center, Japan
| | - Yuichi Hayashi
- Departments of Neurology and Geriatrics, Gifu University Graduate School of Medicine, Japan
| | - Yuichi Ban
- Department of Rehabilitation, Gifu Prefectural General Medical Center, Japan
| | - Takuya Kudo
- Department of Neurology, Gifu Prefectural General Medical Center, Japan
| | - Naoko Harada
- Department of Neurology, Gifu Prefectural General Medical Center, Japan
| | - Takeo Sakurai
- Department of Neurology, Gifu Prefectural General Medical Center, Japan
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Steinacker P, Barschke P, Otto M. Biomarkers for diseases with TDP-43 pathology. Mol Cell Neurosci 2018; 97:43-59. [PMID: 30399416 DOI: 10.1016/j.mcn.2018.10.003] [Citation(s) in RCA: 34] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/03/2018] [Revised: 10/26/2018] [Accepted: 10/29/2018] [Indexed: 01/01/2023] Open
Abstract
The discovery that aggregated transactive response DNA-binding protein 43 kDa (TDP-43) is the major component of pathological ubiquitinated inclusions in amyotrophic lateral sclerosis (ALS) and frontotemporal lobar degeneration (FTLD) caused seminal progress in the unveiling of the genetic bases and molecular characteristics of these now so-called TDP-43 proteinopathies. Substantial increase in the knowledge of clinic-pathological coherencies, especially for FTLD variants, could be made in the last decade, but also revealed a considerable complexity of TDP-43 pathology and often a poor correlation of clinical and molecular disease characteristics. To date, an underlying TDP-43 pathology can be predicted only for patients with mutations in the genes C9orf72 and GRN, but is dependent on neuropathological verification in patients without family history, which represent the majority of cases. As etiology-specific therapies for neurodegenerative proteinopathies are emerging, methods to forecast TDP-43 pathology at patients' lifetime are highly required. Here, we review the current status of research pursued to identify specific indicators to predict or exclude TDP-43 pathology in the ALS-FTLD spectrum disorders and findings on candidates for prognosis and monitoring of disease progression in TDP-43 proteinopathies with a focus on TDP-43 with its pathological forms, neurochemical and imaging biomarkers.
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Affiliation(s)
| | - Peggy Barschke
- Department of Neurology, University of Ulm, Ulm, Germany
| | - Markus Otto
- Department of Neurology, University of Ulm, Ulm, Germany.
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Nobili F, Arbizu J, Bouwman F, Drzezga A, Agosta F, Nestor P, Walker Z, Boccardi M. European Association of Nuclear Medicine and European Academy of Neurology recommendations for the use of brain 18 F-fluorodeoxyglucose positron emission tomography in neurodegenerative cognitive impairment and dementia: Delphi consensus. Eur J Neurol 2018; 25:1201-1217. [PMID: 29932266 DOI: 10.1111/ene.13728] [Citation(s) in RCA: 126] [Impact Index Per Article: 18.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2018] [Accepted: 06/20/2018] [Indexed: 12/17/2022]
Abstract
BACKGROUND AND PURPOSE Recommendations for using fluorodeoxyglucose positron emission tomography (FDG-PET) to support the diagnosis of dementing neurodegenerative disorders are sparse and poorly structured. METHODS Twenty-one questions on diagnostic issues and on semi-automated analysis to assist visual reading were defined. Literature was reviewed to assess study design, risk of bias, inconsistency, imprecision, indirectness and effect size. Critical outcomes were sensitivity, specificity, accuracy, positive/negative predictive value, area under the receiver operating characteristic curve, and positive/negative likelihood ratio of FDG-PET in detecting the target conditions. Using the Delphi method, an expert panel voted for/against the use of FDG-PET based on published evidence and expert opinion. RESULTS Of the 1435 papers, 58 papers provided proper quantitative assessment of test performance. The panel agreed on recommending FDG-PET for 14 questions: diagnosing mild cognitive impairment due to Alzheimer's disease (AD), frontotemporal lobar degeneration (FTLD) or dementia with Lewy bodies (DLB); diagnosing atypical AD and pseudo-dementia; differentiating between AD and DLB, FTLD or vascular dementia, between DLB and FTLD, and between Parkinson's disease and progressive supranuclear palsy; suggesting underlying pathophysiology in corticobasal degeneration and progressive primary aphasia, and cortical dysfunction in Parkinson's disease; using semi-automated assessment to assist visual reading. Panellists did not support FDG-PET use for pre-clinical stages of neurodegenerative disorders, for amyotrophic lateral sclerosis and Huntington disease diagnoses, and for amyotrophic lateral sclerosis or Huntington-disease-related cognitive decline. CONCLUSIONS Despite limited formal evidence, panellists deemed FDG-PET useful in the early and differential diagnosis of the main neurodegenerative disorders, and semi-automated assessment helpful to assist visual reading. These decisions are proposed as interim recommendations.
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Affiliation(s)
- F Nobili
- Department of Neuroscience (DINOGMI), University of Genoa and Polyclinic San Martino Hospital, Genoa, Italy
| | - J Arbizu
- Department of Nuclear Medicine, Clinica Universidad de Navarra, University of Navarra, Pamplona, Spain
| | - F Bouwman
- Department of Neurology and Alzheimer Center, Amsterdam Neuroscience, VU University Medical Center, Amsterdam, The Netherlands
| | - A Drzezga
- Department of Nuclear Medicine, University Hospital of Cologne, University of Cologne and German Center for Neurodegenerative Diseases (DZNE), Cologne, Germany
| | - F Agosta
- Neuroimaging Research Unit, Institute of Experimental Neurology, Division of Neuroscience, San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - P Nestor
- German Center for Neurodegenerative Diseases (DZNE), Magdeburg, Germany
| | - Z Walker
- Division of Psychiatry, Essex Partnership University NHS Foundation Trust, University College London, London, UK
| | - M Boccardi
- Department of Psychiatry, Laboratoire du Neuroimagerie du Vieillissement (LANVIE), University of Geneva, Geneva, Switzerland
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Clinical utility of FDG-PET for the differential diagnosis among the main forms of dementia. Eur J Nucl Med Mol Imaging 2018; 45:1509-1525. [PMID: 29736698 DOI: 10.1007/s00259-018-4035-y] [Citation(s) in RCA: 61] [Impact Index Per Article: 8.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/12/2018] [Accepted: 04/18/2018] [Indexed: 12/14/2022]
Abstract
AIM To assess the clinical utility of FDG-PET as a diagnostic aid for differentiating Alzheimer's disease (AD; both typical and atypical forms), dementia with Lewy bodies (DLB), frontotemporal lobar degeneration (FTLD), vascular dementia (VaD) and non-degenerative pseudodementia. METHODS A comprehensive literature search was conducted using the PICO model to extract evidence from relevant studies. An expert panel then voted on six different diagnostic scenarios using the Delphi method. RESULTS The level of empirical study evidence for the use of FDG-PET was considered good for the discrimination of DLB and AD; fair for discriminating FTLD from AD; poor for atypical AD; and lacking for discriminating DLB from FTLD, AD from VaD, and for pseudodementia. Delphi voting led to consensus in all scenarios within two iterations. Panellists supported the use of FDG-PET for all PICOs-including those where study evidence was poor or lacking-based on its negative predictive value and on the assistance it provides when typical patterns of hypometabolism for a given diagnosis are observed. CONCLUSION Although there is an overall lack of evidence on which to base strong recommendations, it was generally concluded that FDG-PET has a diagnostic role in all scenarios. Prospective studies targeting diagnostically uncertain patients for assessing the added value of FDG-PET would be highly desirable.
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Boccardi M, Festari C, Altomare D, Gandolfo F, Orini S, Nobili F, Frisoni GB. Assessing FDG-PET diagnostic accuracy studies to develop recommendations for clinical use in dementia. Eur J Nucl Med Mol Imaging 2018; 45:1470-1486. [DOI: 10.1007/s00259-018-4024-1] [Citation(s) in RCA: 17] [Impact Index Per Article: 2.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/11/2018] [Accepted: 04/13/2018] [Indexed: 12/14/2022]
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