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Salmon E, Collette F, Bastin C. Cerebral glucose metabolism in Alzheimer's disease. Cortex 2024; 179:50-61. [PMID: 39141935 DOI: 10.1016/j.cortex.2024.07.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/01/2024] [Revised: 07/05/2024] [Accepted: 07/25/2024] [Indexed: 08/16/2024]
Abstract
18F-fluoro-deoxy-glucose positron emission tomography (FDG-PET) is a useful paraclinical exam for the diagnosis of Alzheimer's disease (AD). In this narrative review, we report seminal studies in clinically probable AD that have shown the importance of posterior brain metabolic decrease and the paradoxical variability of the hippocampal metabolism. The FDG-PET pattern was a sensitive indicator of AD in pathologically confirmed cases and it was used for differential diagnosis of dementia conditions. In prodromal AD, the AD FDG-PET pattern was observed in converters and predicted conversion. Automated data analysis techniques provided variable accuracy according to the reported indices and machine learning methods showed variable reliability of results. FDG-PET could confirm AD clinical heterogeneity and image data driven analyses identified hypometabolic subtypes with variable involvement of the hippocampus, reminiscent if the paradoxical FDG uptake. In studies dedicated to clinical and metabolic correlations, episodic memory was related to metabolism in the default mode network (and Papez's circuit) in prodromal and mild AD stages, and specific cognitive processes were associated to precisely distributed brain metabolism. Cerebral metabolic correlates of anosognosia could also be related to current neuropsychological models. AD FDG-PET pattern was reported in preclinical AD stages and related to cognition or to conversion to mild cognitive impairment (MCI). Using other biomarkers, the AD FDG-PET pattern was confirmed in AD participants with positive PET-amyloid. Intriguing observations reported increased metabolism related to brain amyloid and/or tau deposition. Preserved glucose metabolism sometimes appear as a compensation, but it was frequently detrimental and the nature of such a preservation of glucose metabolism remains an open question. Limbic metabolic involvement was frequently related to non-AD biomarkers profile and clinical stability, and it was reported in non-AD pathologies, such as the limbic predominant age-related encephalopathy (LATE). FDG-PET abnormalities observed in the absence of classical AD proteinopathies can be useful to search for pathological mechanisms and differential diagnosis of AD.
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Affiliation(s)
- Eric Salmon
- GIGA Research, CRC Human Imaging, University of Liege, Liege, Belgium.
| | - Fabienne Collette
- GIGA Research, CRC Human Imaging, University of Liege, Liege, Belgium.
| | - Christine Bastin
- GIGA Research, CRC Human Imaging, University of Liege, Liege, Belgium.
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2
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Boccalini C, Caminiti SP, Chiti A, Frisoni GB, Garibotto V, Perani D. The diagnostic and prognostic value of tau-PET in amnestic MCI with different FDG-PET subtypes. Ann Clin Transl Neurol 2024; 11:1236-1249. [PMID: 38553802 PMCID: PMC11093253 DOI: 10.1002/acn3.52039] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/25/2024] [Revised: 02/21/2024] [Accepted: 02/26/2024] [Indexed: 05/15/2024] Open
Abstract
OBJECTIVES Mild cognitive impairment presenting with an amnestic syndrome (aMCI) and amyloid positivity is considered due to AD. Many subjects, however, can show an overall very slow progression relevant for differential diagnosis, prognosis, and treatment. This study assessed PET biomarkers, including brain glucose metabolism, tau, and amyloid load, in a series of comparable aMCI at baseline, clinically evaluated at follow-up. METHODS We included 72 aMCI subjects from Geneva Memory Center (N = 31) and ADNI cohorts (N = 41), selected based on available FDG-PET, tau-PET, amyloid-PET, and clinical follow-up (2.3 years ± 1.2). A data-driven algorithm classified brain metabolic patterns into subtypes that were then compared for clinical and PET biomarker measures and cognitive decline. Voxel-wise comparisons were performed both with FDG-PET and tau-PET data. RESULTS The algorithm classified three metabolic subtypes, namely "Hippocampal-sparing with cortical hypometabolism" (Type1; N = 27), "Hippocampal and cortical hypometabolism" (Type 2; N = 23), and "Medial temporal hypometabolism" (Type 3; N = 22). Amyloid positivity and tau accumulation in the medial temporal and neocortical regions characterized Type 1 and Type 2, whereas Type 3 showed no significant tau pathology, variable amyloid positivity, and stability at follow-up. All tau-positive patients, independently of the FDG-based subtype, showed faster cognitive decline. INTERPRETATION aMCI subjects can differ in metabolic patterns, tau and amyloid pathology, and clinical progression. Here, we complemented with PET tau biomarker the specific brain hypometabolic patterns at the individual level in the prodromal phase, contributing to the patient's classification. Tau PET is the most accurate biomarker in supporting or excluding the AD diagnosis in aMCI across metabolic subtypes and also predicting the risk of decline.
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Affiliation(s)
- Cecilia Boccalini
- Vita‐Salute San Raffaele UniversityMilanItaly
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
| | - Silvia Paola Caminiti
- Vita‐Salute San Raffaele UniversityMilanItaly
- Department of Brain and Behavioral SciencesUniversity of PaviaPaviaItaly
- Nuclear Medicine DepartmentIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Arturo Chiti
- Vita‐Salute San Raffaele UniversityMilanItaly
- Nuclear Medicine DepartmentIRCCS San Raffaele Scientific InstituteMilanItaly
| | - Giovanni B. Frisoni
- Laboratory of Neuroimaging of Aging (LANVIE)University of GenevaGenevaSwitzerland
- Memory ClinicGeneva University HospitalsGenevaSwitzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of MedicineUniversity of GenevaGenevaSwitzerland
- Division of Nuclear Medicine and Molecular ImagingGeneva University HospitalsGenevaSwitzerland
- CIBM Center for Biomedical ImagingGenevaSwitzerland
| | - Daniela Perani
- Vita‐Salute San Raffaele UniversityMilanItaly
- Nuclear Medicine DepartmentIRCCS San Raffaele Scientific InstituteMilanItaly
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Huang H, Zhang M, Zhao Y, Li Y, Jin W, Guo R, Liu W, Cai B, Li J, Yuan S, Huang X, Lin X, Liang ZP, Li B, Luo J. Simultaneous high-resolution whole-brain MR spectroscopy and [ 18F]FDG PET for temporal lobe epilepsy. Eur J Nucl Med Mol Imaging 2024; 51:721-733. [PMID: 37823910 DOI: 10.1007/s00259-023-06465-0] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2023] [Accepted: 09/28/2023] [Indexed: 10/13/2023]
Abstract
PURPOSE Precise lateralizing the epileptogenic zone in patients with drug-resistant mesial temporal lobe epilepsy (mTLE) remains challenging, particularly when routine MRI scans are inconclusive (MRI-negative). This study aimed to investigate the synergy of fast, high-resolution, whole-brain MRSI in conjunction with simultaneous [18F]FDG PET for the lateralization of mTLE. METHODS Forty-eight drug-resistant mTLE patients (M/F 31/17, age 12-58) underwent MRSI and [18F]FDG PET on a hybrid PET/MR scanner. Lateralization of mTLE was evaluated by visual inspection and statistical classifiers of metabolic mappings against routine MRI. Additionally, this study explored how disease status influences the associations between altered N-acetyl aspartate (NAA) and FDG uptake using hierarchical moderated multiple regression. RESULTS The high-resolution whole-brain MRSI data offers metabolite maps at comparable resolution to [18F]FDG PET. Visual examinations of combined MRSI and [18F]FDG PET showed an mTLE lateralization accuracy rate of 91.7% in a 48-patient cohort, surpassing routine MRI (52.1%). Notably, out of 23 MRI-negative mTLE, combined MRSI and [18F]FDG PET helped detect 19 cases. Logistical regression models combining hippocampal NAA level and FDG uptake improved lateralization performance (AUC=0.856), while further incorporating extrahippocampal regions such as amygdala, thalamus, and superior temporal gyrus increased the AUC to 0.939. Concurrent MRSI/PET revealed a moderating influence of disease duration and hippocampal atrophy on the association between hippocampal NAA and glucose uptake, providing significant new insights into the disease's trajectory. CONCLUSION This paper reports the first metabolic imaging study using simultaneous high-resolution MRSI and [18F]FDG PET, which help visualize MRI-unidentifiable lesions and may thus advance diagnostic tools and management strategies for drug-resistant mTLE.
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Affiliation(s)
- Hui Huang
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Miao Zhang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Yibo Zhao
- Beckman Institute for Advanced Sciences and Technology, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Yudu Li
- Beckman Institute for Advanced Sciences and Technology, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
- National Center for Supercomputing Applications, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Wen Jin
- Beckman Institute for Advanced Sciences and Technology, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Rong Guo
- Beckman Institute for Advanced Sciences and Technology, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
- Siemens Medical Solutions USA, Inc, Urbana, IL, 61801, USA
| | - Wei Liu
- Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Bingyang Cai
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Jiwei Li
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Siyu Yuan
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China
| | - Xinyun Huang
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Xiaozhu Lin
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China
| | - Zhi-Pei Liang
- Beckman Institute for Advanced Sciences and Technology, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
- Department of Electrical and Computer Engineering, University of Illinois at Urbana Champaign, Urbana, IL, 61801, USA
| | - Biao Li
- Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 200025, China.
| | - Jie Luo
- School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240, China.
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Cerina V, Crivellaro C, Morzenti S, Pozzi FE, Bigiogera V, Jonghi-Lavarini L, Moresco RM, Basso G, De Bernardi E. A ROI-based quantitative pipeline for 18F-FDG PET metabolism and pCASL perfusion joint analysis: Validation of the 18F-FDG PET line. Heliyon 2024; 10:e23340. [PMID: 38163125 PMCID: PMC10755331 DOI: 10.1016/j.heliyon.2023.e23340] [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: 09/29/2023] [Accepted: 12/01/2023] [Indexed: 01/03/2024] Open
Abstract
In Mild Cognitive Impairment (MCI), the study of brain metabolism, provided by 18F-FluoroDeoxyGlucose Positron Emission Tomography (18F-FDG PET) can be integrated with brain perfusion through pseudo-Continuous Arterial Spin Labeling Magnetic Resonance sequences (MR pCASL). Cortical hypometabolism identification generally relies on wide control group datasets; pCASL control groups are instead not publicly available yet, due to lack of standardization in the acquisition parameters. This study presents a quantitative pipeline to be applied to PET and pCASL data to coherently analyze metabolism and perfusion inside 16 matching cortical regions of interest (ROIs) derived from the AAL3 atlas. The PET line is tuned on 36 MCI patients and 107 healthy control subjects, to agree in identifying hypometabolic regions with clinical reference methods (visual analysis supported by a vendor tool and Statistical Parametric Mapping, SPM, with two parametrizations here identified as SPM-A and SPM-B). The analysis was conducted for each ROI separately. The proposed PET analysis pipeline obtained accuracy 78 % and Cohen's к 60 % vs visual analysis, accuracy 79 % and Cohen's к 58 % vs SPM-A, accuracy 77 % and Cohen's к 54 % vs SPM-B. Cohen's к resulted not significantly different from SPM-A and SPM-B Cohen's к when assuming visual analysis as reference method (p-value 0.61 and 0.31 respectively). Considering SPM-A as reference method, Cohen's к is not significantly different from SPM-B Cohen's к as well (p-value = 1.00). The complete PET-pCASL pipeline was then preliminarily applied on 5 MCI patients and metabolism-perfusion regional correlations were assessed. The proposed approach can be considered as a promising tool for PET-pCASL joint analyses in MCI, even in the absence of a pCASL control group, to perform metabolism-perfusion regional correlation studies, and to assess and compare perfusion in hypometabolic or normo-metabolic areas.
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Affiliation(s)
- Valeria Cerina
- PhD program in Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Italy
| | - Cinzia Crivellaro
- Nuclear Medicine, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italia
| | - Sabrina Morzenti
- Medical Physics, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italia
| | - Federico E. Pozzi
- PhD program in Neuroscience, School of Medicine and Surgery, University of Milano-Bicocca, Italy
- Neurology, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italia
- Milan center for Neuroscience (NeuroMI), University of Milano-Bicocca, Italy
| | | | | | - Rosa M. Moresco
- School of Medicine and Surgery, University of Milano-Bicocca, Italy
| | - Gianpaolo Basso
- Milan center for Neuroscience (NeuroMI), University of Milano-Bicocca, Italy
- School of Medicine and Surgery, University of Milano-Bicocca, Italy
- Neuroradiology, Fondazione IRCCS San Gerardo dei Tintori, Monza, Italia
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5
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Polito C, Conca F, Santi GC, Esposito V, Caminiti SP, Boccalini C, Berti V, Morinelli C, Mazzeo S, Marcone A, Iannaccone S, Bessi V, Sorbi S, Perani D, Cappa SF, Catricalà E. Comparing two picture naming tasks in primary progressive aphasia: Insights from behavioural and neural results. Cortex 2023; 166:1-18. [PMID: 37295234 DOI: 10.1016/j.cortex.2023.04.014] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2022] [Revised: 02/24/2023] [Accepted: 04/26/2023] [Indexed: 06/12/2023]
Abstract
Picture naming tests are widely used to evaluate language impairments in neurodegenerative diseases, especially in Primary Progressive Aphasia (PPA). The available tests differ for many factors affecting the performance, e.g. format of stimuli and their psycholinguistic properties. We aim to identify the most appropriate naming test to be used on PPA according to the clinical and research demands. We investigated the behavioural characteristics, i.e. proportion of correct responses and error type, and their neural correlates in two Italian naming tests, CaGi naming (CaGi) and naming subtest of the Screening for Aphasia in NeuroDegeneration battery (SAND), administered to 52 PPA patients who underwent an FDG-PET scan. We analysed the effectiveness of the tests in distinguishing PPA versus controls and among PPA variants, considering the psycholinguistic variables affecting performance. We explored the brain metabolic correlates of behavioural performance in the tests. SAND, differently from CaGi, has time limits for the response and its items are less frequent and acquired later. SAND and CaGi differed in terms of number of correct responses and error profile, suggesting a higher difficulty to name SAND items compared to CaGi. Semantic errors predominated in CaGi, while anomic and semantic errors were equally frequent in SAND. Both tests distinguished PPA from controls, but SAND outperformed CaGi in discriminating among PPA variants. FDG-PET imaging revealed a shared metabolic involvement of temporal areas associated with lexico-semantic processing, encompassing anterior fusiform, temporal pole, and extending to posterior fusiform in sv-PPA. Concluding, a picture naming test with response time limit and items which are less frequent and acquired later in life, as SAND, may be effective at highlighting subtle distinctions between PPA variants, improving the diagnosis. Conversely, a naming test without time limit for the response, as CaGi, may be useful for a better characterization of the nature of the naming impairment at the behavioural level, eliciting more naming errors than anomia, possibly helping in the development of rehabilitation protocols.
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Affiliation(s)
| | | | - Gaia C Santi
- ICoN Cognitive Neuroscience Center, Institute for Advanced Studies, IUSS, Pavia, Italy
| | | | - Silvia P Caminiti
- Vita-Salute San Raffaele University, 20132, Milan, Italy; In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, San Raffaele Scientific Institute, 20132, Milan, Italy; Nuclear Medicine Unit, San Raffaele Hospital, 20132, Milan, Italy
| | - Cecilia Boccalini
- Vita-Salute San Raffaele University, 20132, Milan, Italy; In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, San Raffaele Scientific Institute, 20132, Milan, Italy
| | - Valentina Berti
- Nuclear Medicine, Department of Biomedical Experimental and Clinical Sciences "Mario Serio", University of Florence, Italy
| | - Carmen Morinelli
- SOD Neurologia 1, Dipartimento Neuromuscolo-Scheletrico e Degli Organi di Senso, Azienda Ospedaliera-Universitaria Careggi, Florence, Italy
| | - Salvatore Mazzeo
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy; NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Alessandra Marcone
- Department of Rehabilitation and Functional Recovery, San Raffaele Hospital, Milan, Italy
| | - Sandro Iannaccone
- Department of Rehabilitation and Functional Recovery, San Raffaele Hospital, Milan, Italy
| | - Valentina Bessi
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy; SOD Neurologia 1, Dipartimento Neuromuscolo-Scheletrico e Degli Organi di Senso, Azienda Ospedaliera-Universitaria Careggi, Florence, Italy; NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Sandro Sorbi
- IRCCS Fondazione Don Carlo Gnocchi, Florence, Italy; SOD Neurologia 1, Dipartimento Neuromuscolo-Scheletrico e Degli Organi di Senso, Azienda Ospedaliera-Universitaria Careggi, Florence, Italy; NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health, University of Florence, Florence, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, 20132, Milan, Italy; In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, San Raffaele Scientific Institute, 20132, Milan, Italy; Nuclear Medicine Unit, San Raffaele Hospital, 20132, Milan, Italy
| | - Stefano F Cappa
- IRCCS Mondino Foundation, Pavia, Italy; ICoN Cognitive Neuroscience Center, Institute for Advanced Studies, IUSS, Pavia, Italy.
| | - Eleonora Catricalà
- ICoN Cognitive Neuroscience Center, Institute for Advanced Studies, IUSS, Pavia, Italy
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Carli G, Meles SK, Reesink FE, de Jong BM, Pilotto A, Padovani A, Galbiati A, Ferini-Strambi L, Leenders KL, Perani D. Comparison of univariate and multivariate analyses for brain [18F]FDG PET data in α-synucleinopathies. Neuroimage Clin 2023; 39:103475. [PMID: 37494757 PMCID: PMC10394024 DOI: 10.1016/j.nicl.2023.103475] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Revised: 05/18/2023] [Accepted: 07/09/2023] [Indexed: 07/28/2023]
Abstract
BACKGROUND Brain imaging with [18F]FDG-PET can support the diagnostic work-up of patients with α-synucleinopathies. Validated data analysis approaches are necessary to evaluate disease-specific brain metabolism patterns in neurodegenerative disorders. This study compared the univariate Statistical Parametric Mapping (SPM) single-subject procedure and the multivariate Scaled Subprofile Model/Principal Component Analysis (SSM/PCA) in a cohort of patients with α-synucleinopathies. METHODS We included [18F]FDG-PET scans of 122 subjects within the α-synucleinopathy spectrum: Parkinson's Disease (PD) normal cognition on long-term follow-up (PD - low risk to dementia (LDR); n = 28), PD who developed dementia on clinical follow-up (PD - high risk of dementia (HDR); n = 16), Dementia with Lewy Bodies (DLB; n = 67), and Multiple System Atrophy (MSA; n = 11). We also included [18F]FDG-PET scans of isolated REM sleep behaviour disorder (iRBD; n = 51) subjects with a high risk of developing a manifest α-synucleinopathy. Each [18F]FDG-PET scan was compared with 112 healthy controls using SPM procedures. In the SSM/PCA approach, we computed the individual scores of previously identified patterns for PD, DLB, and MSA: PD-related patterns (PDRP), DLBRP, and MSARP. We used ROC curves to compare the diagnostic performances of SPM t-maps (visual rating) and SSM/PCA individual pattern scores in identifying each clinical condition across the spectrum. Specifically, we used the clinical diagnoses ("gold standard") as our reference in ROC curves to evaluate the accuracy of the two methods. Experts in movement disorders and dementia made all the diagnoses according to the current clinical criteria of each disease (PD, DLB and MSA). RESULTS The visual rating of SPM t-maps showed higher performance (AUC: 0.995, specificity: 0.989, sensitivity 1.000) than PDRP z-scores (AUC: 0.818, specificity: 0.734, sensitivity 1.000) in differentiating PD-LDR from other α-synucleinopathies (PD-HDR, DLB and MSA). This result was mainly driven by the ability of SPM t-maps to reveal the limited or absent brain hypometabolism characteristics of PD-LDR. Both SPM t-maps visual rating and SSM/PCA z-scores showed high performance in identifying DLB (DLBRP = AUC: 0.909, specificity: 0.873, sensitivity 0.866; SPM t-maps = AUC: 0.892, specificity: 0.872, sensitivity 0.910) and MSA (MSARP: AUC: 0.921, specificity: 0.811, sensitivity 1.000; SPM t-maps: AUC: 1.000, specificity: 1.000, sensitivity 1.000) from other α-synucleinopathies. PD-HDR and DLB were comparable for the brain hypo and hypermetabolism patterns, thus not allowing differentiation by SPM t-maps or SSM/PCA. Of note, we found a gradual increase of PDRP and DLBRP expression in the continuum from iRBD to PD-HDR and DLB, where the DLB patients had the highest scores. SSM/PCA could differentiate iRBD from DLB, reflecting specifically the differences in disease staging and severity (AUC: 0.938, specificity: 0.821, sensitivity 0.941). CONCLUSIONS SPM-single subject maps and SSM/PCA are both valid methods in supporting diagnosis within the α-synucleinopathy spectrum, with different strengths and pitfalls. The former reveals dysfunctional brain topographies at the individual level with high accuracy for all the specific subtype patterns, and particularly also the normal maps; the latter provides a reliable quantification, independent from the rater experience, particularly in tracking the disease severity and staging. Thus, our findings suggest that differences in data analysis approaches exist and should be considered in clinical settings. However, combining both methods might offer the best diagnostic performance.
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Affiliation(s)
- Giulia Carli
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sanne K Meles
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Fransje E Reesink
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Bauke M de Jong
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Andrea Pilotto
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Alessandro Padovani
- Neurology Unit, Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy
| | - Andrea Galbiati
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Department of Clinical Neuroscience, Sleep Disorders Center, San Raffaele Hospital, Milan, Italy
| | - Luigi Ferini-Strambi
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Department of Clinical Neuroscience, Sleep Disorders Center, San Raffaele Hospital, Milan, Italy
| | - Klaus L Leenders
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands.
| | - Daniela Perani
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan; Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy.
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7
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Caminiti SP, Boccalini C, Nicastro N, Garibotto V, Perani D. Sex differences in brain metabolic connectivity architecture in probable dementia with Lewy bodies. Neurobiol Aging 2023; 126:14-24. [PMID: 36905876 DOI: 10.1016/j.neurobiolaging.2023.02.004] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Revised: 01/23/2023] [Accepted: 02/10/2023] [Indexed: 02/19/2023]
Abstract
We investigated how sex modulates metabolic connectivity alterations in probable dementia with Lewy bodies (pDLB). We included 131 pDLB patients (males/females: 58/73) and similarly aged healthy controls (HC) (male/female: 59/75) with available (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans. We assessed (1) sex differences in the whole-brain connectivity, identifying pathological hubs, (2) connectivity alterations in functional pathways of the neurotransmitter systems, (3) Resting State Networks (RSNs) integrity. Both pDLBM (males) and pDLBF (females) shared dysfunctional hubs in the insula, Rolandic operculum, and inferior parietal lobule, but the pDLBM group showed more severe and diffuse whole-brain connectivity alterations. Neurotransmitters connectivity analysis revealed common alterations in dopaminergic and noradrenergic pathways. Sex differences emerged particularly in the Ch4-perisylvian division, with pDLBM showing more severe alterations than pDLBF. The RSNs analysis showed no sex differences, with decreased connectivity strength in the primary visual, posterior default mode, and attention networks in both groups. Extensive connectivity changes characterize both males and females in the dementia stage, with a major vulnerability of cholinergic neurotransmitter systems in males, possibly contributing to the observed different clinical phenotypes.
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Affiliation(s)
- Silvia Paola Caminiti
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Cecilia Boccalini
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Nicolas Nicastro
- Division of Neurorehabilitation, Department of Clinical Neurosciences, Geneva University Hospitals, Geneva, Switzerland; Faculty of Medicine, University of Geneva, Geneva, Switzerland
| | - Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracers (NIMTlab), Geneva University Neurocenter and Faculty of Medicine, University of Geneva, Geneva, Switzerland; Division of Nuclear Medicine and Molecular Imaging, Geneva University Hospitals, Geneva, Switzerland; Center for Biomedical Imaging (CIBM), Geneva, Switzerland
| | - Daniela Perani
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.
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Comprehensive qualitative characterization of linguistic performance profiles in primary progressive aphasia: a multivariate study with FDG-PET. Neurobiol Aging 2022; 120:137-148. [DOI: 10.1016/j.neurobiolaging.2022.09.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Revised: 08/17/2022] [Accepted: 09/02/2022] [Indexed: 12/22/2022]
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Martini AL, Carli G, Kiferle L, Piersanti P, Palumbo P, Morbelli S, Calcagni ML, Perani D, Sestini S. Time-dependent recovery of brain hypometabolism in neuro-COVID-19 patients. Eur J Nucl Med Mol Imaging 2022; 50:90-102. [PMID: 35984451 PMCID: PMC9388976 DOI: 10.1007/s00259-022-05942-2] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2022] [Accepted: 08/08/2022] [Indexed: 12/30/2022]
Abstract
Purpose We evaluated brain metabolic dysfunctions and associations with neurological and biological parameters in acute, subacute and chronic COVID-19 phases to provide deeper insights into the pathophysiology of the disease. Methods Twenty-six patients with neurological symptoms (neuro-COVID-19) and [18F]FDG-PET were included. Seven patients were acute (< 1 month (m) after onset), 12 subacute (4 ≥ 1-m, 4 ≥ 2-m and 4 ≥ 3-m) and 7 with neuro-post-COVID-19 (3 ≥ 5-m and 4 ≥ 7–9-m). One patient was evaluated longitudinally (acute and 5-m). Brain hypo- and hypermetabolism were analysed at single-subject and group levels. Correlations between severity/extent of brain hypo- and hypermetabolism and biological (oxygen saturation and C-reactive protein) and clinical variables (global cognition and Body Mass Index) were assessed. Results The “fronto-insular cortex” emerged as the hypometabolic hallmark of neuro-COVID-19. Acute patients showed the most severe hypometabolism affecting several cortical regions. Three-m and 5-m patients showed a progressive reduction of hypometabolism, with limited frontal clusters. After 7–9 months, no brain hypometabolism was detected. The patient evaluated longitudinally showed a diffuse brain hypometabolism in the acute phase, almost recovered after 5 months. Brain hypometabolism correlated with cognitive dysfunction, low blood saturation and high inflammatory status. Hypermetabolism in the brainstem, cerebellum, hippocampus and amygdala persisted over time and correlated with inflammation status. Conclusion Synergistic effects of systemic virus-mediated inflammation and transient hypoxia yield a dysfunction of the fronto-insular cortex, a signature of CNS involvement in neuro-COVID-19. This brain dysfunction is likely to be transient and almost reversible. The long-lasting brain hypermetabolism seems to reflect persistent inflammation processes. Supplementary Information The online version contains supplementary material available at 10.1007/s00259-022-05942-2.
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Affiliation(s)
- Anna Lisa Martini
- Nuclear Medicine Unit, Department of Diagnostic Imaging, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Giulia Carli
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, the Netherlands
| | - Lorenzo Kiferle
- Neurology Unit, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Patrizia Piersanti
- Neurology Unit, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Pasquale Palumbo
- Neurology Unit, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy
| | - Silvia Morbelli
- Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy.,Department of Health Sciences, University of Genoa, Genoa, Italy
| | | | - Daniela Perani
- School of Psychology, Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy
| | - Stelvio Sestini
- Nuclear Medicine Unit, Department of Diagnostic Imaging, N.O.P. - S. Stefano, U.S.L. Toscana Centro, Prato, Italy.
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10
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Tondo G, Boccalini C, Vanoli EG, Presotto L, Muscio C, Ciullo V, Banaj N, Piras F, Filippini G, Tiraboschi P, Tagliavini F, Frisoni GB, Cappa SF, Spalletta G, Perani D. Brain Metabolism and Amyloid Load in Individuals With Subjective Cognitive Decline or Pre-Mild Cognitive Impairment. Neurology 2022; 99:e258-e269. [PMID: 35487700 PMCID: PMC9302934 DOI: 10.1212/wnl.0000000000200351] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2021] [Accepted: 02/21/2022] [Indexed: 11/15/2022] Open
Abstract
BACKGROUND AND OBJECTIVE This was a multicenter study aimed at investigating the characteristics of cognitive decline, neuropsychiatric symptoms, and brain imaging in individuals with subjective cognitive decline (SCD) and subtle cognitive decline (pre-mild cognitive impairment [pre-MCI]). METHODS Data were obtained from the Network-AD project (NET-2011-02346784). The included participants underwent baseline cognitive and neurobehavioral evaluation, FDG-PET, and amyloid PET. We used principal component analysis (PCA) to identify independent neuropsychological and neuropsychiatric dimensions and their association with brain metabolism. RESULTS A total of 105 participants (SCD = 49, pre-MCI = 56) were included. FDG-PET was normal in 45% of participants and revealed brain hypometabolism in 55%, with a frontal-like pattern as the most frequent finding (28%). Neuropsychiatric symptoms emerging from the Neuropsychiatric Inventory and the Starkstein Apathy Scale were highly prevalent in the whole sample (78%). An abnormal amyloid load was detected in the 18% of the participants who underwent amyloid PET (n = 60). PCA resulted in 3 neuropsychological factors: (1) executive/visuomotor, correlating with hypometabolism in frontal and occipital cortices and basal ganglia; (2) memory, correlating with hypometabolism in temporoparietal regions; and (3) visuospatial/constructional, correlating with hypometabolism in frontoparietal cortices. Two factors emerged from the neuropsychiatric PCA: (1) affective, correlating with hypometabolism in orbitofrontal and cingulate cortex and insula; (2) hyperactive/psychotic, correlating with hypometabolism in frontal, temporal, and parietal regions. DISCUSSION FDG-PET evidence suggests either normal brain function or different patterns of brain hypometabolism in SCD and pre-MCI. These results indicate that SCD and pre-MCI represent heterogeneous populations. Different neuropsychological and neuropsychiatric profiles emerged, which correlated with neuronal dysfunction in specific brain regions. Long-term follow-up studies are needed to assess the risk of progression to dementia in these conditions.
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Affiliation(s)
- Giacomo Tondo
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Cecilia Boccalini
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Emilia Giovanna Vanoli
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Luca Presotto
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Cristina Muscio
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Valentina Ciullo
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Nerisa Banaj
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Federica Piras
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Graziella Filippini
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Pietro Tiraboschi
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Fabrizio Tagliavini
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Giovanni Battista Frisoni
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Stefano F Cappa
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Gianfranco Spalletta
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy
| | - Daniela Perani
- From Vita-Salute San Raffaele University (G.T., C.B., D.P.); In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience (G.T., C.B., L.P., D.P.), IRCCS San Raffaele Scientific Institute; Nuclear Medicine Unit (E.G.V., L.P., D.P.), San Raffaele Hospital; Unit of Neurology and Neuropathology (P.T.), Fondazione IRCCS Istituto Neurologico Carlo Besta (C.M., G.F., F.T.), Milan; Laboratory of Neuropsychiatry (V.C., N.B., F.P., G.S.), IRCCS Santa Lucia Foundation, Rome; IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli (G.B.F.), Brescia, Italy; Memory Clinic and LANVIE-Laboratory of Neuroimaging of Aging (G.B.F.), University Hospitals and University of Geneva, Switzerland; ICoN (S.F.C.), Scuola Universitaria Superiore IUSS Pavia; and IRCCS Mondino Foundation (S.F.C.), Pavia, Italy.
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Presotto L, Bettinardi V, Bagnalasta M, Scifo P, Savi A, Vanoli EG, Fallanca F, Picchio M, Perani D, Gianolli L, De Bernardi E. Evaluation of a 2D UNet-Based Attenuation Correction Methodology for PET/MR Brain Studies. J Digit Imaging 2022; 35:432-445. [PMID: 35091873 PMCID: PMC9156597 DOI: 10.1007/s10278-021-00551-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/27/2020] [Revised: 11/10/2021] [Accepted: 11/16/2021] [Indexed: 12/15/2022] Open
Abstract
Deep learning (DL) strategies applied to magnetic resonance (MR) images in positron emission tomography (PET)/MR can provide synthetic attenuation correction (AC) maps, and consequently PET images, more accurate than segmentation or atlas-registration strategies. As first objective, we aim to investigate the best MR image to be used and the best point of the AC pipeline to insert the synthetic map in. Sixteen patients underwent a 18F-fluorodeoxyglucose (FDG) PET/computed tomography (CT) and a PET/MR brain study in the same day. PET/CT images were reconstructed with attenuation maps obtained: (1) from CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with a 2D UNet trained on MR image/attenuation map pairs. As for MR, T1-weighted and Zero Time Echo (ZTE) images were considered; as for attenuation maps, CTs and 511 keV low-resolution attenuation maps were assessed. As second objective, we assessed the ability of DL strategies to provide proper AC maps in presence of cranial anatomy alterations due to surgery. Three 11C-methionine (METH) PET/MR studies were considered. PET images were reconstructed with attenuation maps obtained: (1) from diagnostic coregistered CT (reference), (2) from MR with an atlas-based and a segmentation-based method and (3) with 2D UNets trained on the sixteen FDG anatomically normal patients. Only UNets taking ZTE images in input were considered. FDG and METH PET images were quantitatively evaluated. As for anatomically normal FDG patients, UNet AC models generally provide an uptake estimate with lower bias than atlas-based or segmentation-based methods. The intersubject average bias on images corrected with UNet AC maps is always smaller than 1.5%, except for AC maps generated on too coarse grids. The intersubject bias variability is the lowest (always lower than 2%) for UNet AC maps coming from ZTE images, larger for other methods. UNet models working on MR ZTE images and generating synthetic CT or 511 keV low-resolution attenuation maps therefore provide the best results in terms of both accuracy and variability. As for METH anatomically altered patients, DL properly reconstructs anatomical alterations. Quantitative results on PET images confirm those found on anatomically normal FDG patients.
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Affiliation(s)
- Luca Presotto
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Valentino Bettinardi
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Matteo Bagnalasta
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Paola Scifo
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Annarita Savi
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | | | - Federico Fallanca
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Maria Picchio
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy ,Vita-Salute San Raffaele University, Milan, Italy
| | - Daniela Perani
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy ,Vita-Salute San Raffaele University, Milan, Italy
| | - Luigi Gianolli
- Nuclear Medicine Department, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Elisabetta De Bernardi
- School of Medicine and Surgery, University of Milano-Bicocca, via Cadore 48, Monza, 20900 Italy ,Bicocca Bioinformatics Biostatistics and Bioimaging Centre - B4, University of Milan-Bicocca, Monza, Italy
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Spatial normalization and quantification approaches of PET imaging for neurological disorders. Eur J Nucl Med Mol Imaging 2022; 49:3809-3829. [PMID: 35624219 DOI: 10.1007/s00259-022-05809-6] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/21/2022] [Accepted: 04/19/2022] [Indexed: 12/17/2022]
Abstract
Quantification approaches of positron emission tomography (PET) imaging provide user-independent evaluation of pathophysiological processes in living brains, which have been strongly recommended in clinical diagnosis of neurological disorders. Most PET quantification approaches depend on spatial normalization of PET images to brain template; however, the spatial normalization and quantification approaches have not been comprehensively reviewed. In this review, we introduced and compared PET template-based and magnetic resonance imaging (MRI)-aided spatial normalization approaches. Tracer-specific and age-specific PET brain templates were surveyed between 1999 and 2021 for 18F-FDG, 11C-PIB, 18F-Florbetapir, 18F-THK5317, and etc., as well as adaptive PET template methods. Spatial normalization-based PET quantification approaches were reviewed, including region-of-interest (ROI)-based and voxel-wise quantitative methods. Spatial normalization-based ROI segmentation approaches were introduced, including manual delineation on template, atlas-based segmentation, and multi-atlas approach. Voxel-wise quantification approaches were reviewed, including voxel-wise statistics and principal component analysis. Certain concerns and representative examples of clinical applications were provided for both ROI-based and voxel-wise quantification approaches. At last, a recipe for PET spatial normalization and quantification approaches was concluded to improve diagnosis accuracy of neurological disorders in clinical practice.
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Fernandes M, Mari L, Chiaravalloti A, Paoli B, Nuccetelli M, Izzi F, Giambrone MP, Camedda R, Bernardini S, Schillaci O, Mercuri NB, Placidi F, Liguori C. 18F-FDG PET, cognitive functioning, and CSF biomarkers in patients with obstructive sleep apnoea before and after continuous positive airway pressure treatment. J Neurol 2022; 269:5356-5367. [PMID: 35608659 PMCID: PMC9468130 DOI: 10.1007/s00415-022-11182-z] [Citation(s) in RCA: 11] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Revised: 05/07/2022] [Accepted: 05/10/2022] [Indexed: 11/23/2022]
Abstract
Introduction Dysregulation of cerebral glucose consumption, alterations in cerebrospinal fluid (CSF) biomarkers, and cognitive impairment have been reported in patients with obstructive sleep apnoea (OSA). On these bases, OSA has been considered a risk factor for Alzheimer’s disease (AD). This study aimed to measure cognitive performance, CSF biomarkers, and cerebral glucose consumption in OSA patients and to evaluate the effects of continuous positive airway pressure (CPAP) treatment on these biomarkers over a 12-month period. Methods Thirty-four OSA patients and 34 controls underwent 18F-fluoro-2-deoxy-d-glucose positron emission tomography (18F-FDG PET), cognitive evaluation, and CSF analysis. A subgroup of 12 OSA patients treated with beneficial CPAP and performing the 12-month follow-up was included in the longitudinal analysis, and cognitive evaluation and 18F-FDG PET were repeated. Results Significantly reduced glucose consumption was observed in the bilateral praecuneus, posterior cingulate cortex, and frontal areas in OSA patients than controls. At baseline, OSA patients also showed lower β-amyloid42 and higher phosphorylated-tau CSF levels than controls. Increased total tau and phosphorylated tau levels correlated with a reduction in brain glucose consumption in a cluster of different brain areas. In the longitudinal analysis, OSA patients showed an improvement in cognition and a global increase in cerebral 18F-FDG uptake. Conclusions Cognitive impairment, reduced cerebral glucose consumption, and alterations in CSF biomarkers were observed in OSA patients, which may reinforce the hypothesis of AD neurodegenerative processes triggered by OSA. Notably, cognition and brain glucose consumption improved after beneficial CPAP treatment. Further studies are needed to evaluate the long-term effects of CPAP treatment on these AD biomarkers.
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Affiliation(s)
- Mariana Fernandes
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome "Tor Vergata", Rome, Italy
| | - Luisa Mari
- Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy
| | - Agostino Chiaravalloti
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy.,IRCCS Neuromed, Pozzilli, Italy
| | - Barbara Paoli
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome "Tor Vergata", Rome, Italy
| | - Marzia Nuccetelli
- Department of Clinical Biochemistry and Molecular Biology, University of Rome "Tor Vergata", Rome, Italy
| | - Francesca Izzi
- Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy
| | | | - Riccardo Camedda
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy
| | - Sergio Bernardini
- Department of Clinical Biochemistry and Molecular Biology, University of Rome "Tor Vergata", Rome, Italy
| | - Orazio Schillaci
- Department of Biomedicine and Prevention, University of Rome "Tor Vergata", Rome, Italy.,IRCCS Neuromed, Pozzilli, Italy
| | - Nicola Biagio Mercuri
- Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy.,IRCSS Santa Lucia Foundation, Rome, Italy
| | - Fabio Placidi
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome "Tor Vergata", Rome, Italy.,Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy
| | - Claudio Liguori
- Department of Systems Medicine, Sleep Medicine Centre, University of Rome "Tor Vergata", Rome, Italy. .,Neurology Unit, University Hospital of Rome "Tor Vergata", Rome, Italy.
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14
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Yousefzadeh-Nowshahr E, Winter G, Bohn P, Kneer K, von Arnim CAF, Otto M, Solbach C, Anderl-Straub S, Polivka D, Fissler P, Strobel J, Kletting P, Riepe MW, Higuchi M, Glatting G, Ludolph A, Beer AJ. Quantitative analysis of regional distribution of tau pathology with 11C-PBB3-PET in a clinical setting. PLoS One 2022; 17:e0266906. [PMID: 35404966 PMCID: PMC9045369 DOI: 10.1371/journal.pone.0266906] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2021] [Accepted: 03/29/2022] [Indexed: 12/28/2022] Open
Abstract
PURPOSE The recent developments of tau-positron emission tomography (tau-PET) enable in vivo assessment of neuropathological tau aggregates. Among the tau-specific tracers, the application of 11C-pyridinyl-butadienyl-benzothiazole 3 (11C-PBB3) in PET shows high sensitivity to Alzheimer disease (AD)-related tau deposition. The current study investigates the regional tau load in patients within the AD continuum, biomarker-negative individuals (BN) and patients with suspected non-AD pathophysiology (SNAP) using 11C-PBB3-PET. MATERIALS AND METHODS A total of 23 memory clinic outpatients with recent decline of episodic memory were examined using 11C-PBB3-PET. Pittsburg compound B (11C-PIB) PET was available for 17, 18F-flurodeoxyglucose (18F-FDG) PET for 16, and cerebrospinal fluid (CSF) protein levels for 11 patients. CSF biomarkers were considered abnormal based on Aβ42 (< 600 ng/L) and t-tau (> 450 ng/L). The PET biomarkers were classified as positive or negative using statistical parametric mapping (SPM) analysis and visual assessment. Using the amyloid/tau/neurodegeneration (A/T/N) scheme, patients were grouped as within the AD continuum, SNAP, and BN based on amyloid and neurodegeneration status. The 11C-PBB3 load detected by PET was compared among the groups using both atlas-based and voxel-wise analyses. RESULTS Seven patients were identified as within the AD continuum, 10 SNAP and 6 BN. In voxel-wise analysis, significantly higher 11C-PBB3 binding was observed in the AD continuum group compared to the BN patients in the cingulate gyrus, tempo-parieto-occipital junction and frontal lobe. Compared to the SNAP group, patients within the AD continuum had a considerably increased 11C-PBB3 uptake in the posterior cingulate cortex. There was no significant difference between SNAP and BN groups. The atlas-based analysis supported the outcome of the voxel-wise quantification analysis. CONCLUSION Our results suggest that 11C-PBB3-PET can effectively analyze regional tau load and has the potential to differentiate patients in the AD continuum group from the BN and SNAP group.
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Affiliation(s)
- Elham Yousefzadeh-Nowshahr
- Department of Nuclear Medicine, Medical Radiation Physics, Ulm
University, Ulm, Germany
- Department of Nuclear Medicine, Medical Center—University of Freiburg,
Faculty of Medicine, University of Freiburg, Freiburg, Germany
| | - Gordon Winter
- Department of Nuclear Medicine, Ulm University, Ulm,
Germany
| | - Peter Bohn
- Department of Nuclear Medicine, Inselspital Bern—University of Bern,
Bern, Switzerland
| | - Katharina Kneer
- Department of Nuclear Medicine, Ulm University, Ulm,
Germany
| | - Christine A. F. von Arnim
- Department of Neurology, Ulm University, Ulm, Germany
- Department of Geriatrics, University Medical Center Göttingen, Göttingen,
Germany
| | - Markus Otto
- Department of Neurology, University Hospital Halle (Saale), Halle,
Germany
| | | | | | - Dörte Polivka
- Department of Neurology, Ulm University, Ulm, Germany
| | - Patrick Fissler
- Department of Neurology, Ulm University, Ulm, Germany
- Psychiatric Services of Thurgovia (Academic Teaching Hospital of Medical
University Salzburg), Münsterlingen, Switzerland
| | - Joachim Strobel
- Department of Nuclear Medicine, Ulm University, Ulm,
Germany
| | - Peter Kletting
- Department of Nuclear Medicine, Medical Radiation Physics, Ulm
University, Ulm, Germany
- Department of Nuclear Medicine, Ulm University, Ulm,
Germany
| | - Matthias W. Riepe
- Department of Psychiatry and Psychotherapy II, Ulm University, Ulm,
Germany
| | - Makoto Higuchi
- National Institute of Radiological Sciences, Chiba,
Japan
| | - Gerhard Glatting
- Department of Nuclear Medicine, Medical Radiation Physics, Ulm
University, Ulm, Germany
- Department of Nuclear Medicine, Ulm University, Ulm,
Germany
| | - Albert Ludolph
- Department of Neurology, Ulm University, Ulm, Germany
- German Center for Neurodegerative Diseases (DZNE), Ulm,
Germany
| | - Ambros J. Beer
- Department of Nuclear Medicine, Ulm University, Ulm,
Germany
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15
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Zhang M, Huang H, Liu W, Tang L, Li Q, Wang J, Huang X, Lin X, Meng H, Wang J, Zhan S, Li B, Luo J. Combined quantitative T2 mapping and [ 18F]FDG PET could improve lateralization of mesial temporal lobe epilepsy. Eur Radiol 2022; 32:6108-6117. [PMID: 35347363 PMCID: PMC9381472 DOI: 10.1007/s00330-022-08707-5] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2021] [Revised: 02/15/2022] [Accepted: 03/01/2022] [Indexed: 01/19/2023]
Abstract
OBJECTIVES To investigate whether quantitative T2 mapping is complementary to [18F]FDG PET in epileptogenic zone detection, thus improving the lateralization accuracy for drug-resistant mesial temporal lobe epilepsy (MTLE) using hybrid PET/MR. METHODS We acquired routine structural MRI, T2-weighted FLAIR, whole brain T2 mapping, and [18F]FDG PET in 46 MTLE patients and healthy controls on a hybrid PET/MR scanner, followed with computing voxel-based z-score maps of patients in reference to healthy controls. Asymmetry indexes of the hippocampus were calculated for each imaging modality, which then enter logistic regression models as univariate or multivariate for lateralization. Stereoelectroencephalography (SEEG) recordings and clinical decisions were collected as gold standard. RESULTS Routine structural MRI and T2w-FLAIR lateralized 47.8% (22/46) of MTLE patients, and FDG PET lateralized 84.8% (39/46). T2 mapping combined with [18F]FDG PET improved the lateralization accuracy by correctly lateralizing 95.6% (44/46) of MTLE patients. The asymmetry indexes of hippocampal T2 relaxometry and PET exhibit complementary tendency in detecting individual laterality, especially for MR-negative patients. In the quantitative analysis of z-score maps, the ipsilateral hippocampus had significantly lower SUVR (LTLE, p < 0.001; RTLE, p < 0.001) and higher T2 value (LTLE, p < 0.001; RTLE, p = 0.001) compared to the contralateral hippocampus. In logistic regression models, PET/T2 combination resulted in the highest AUC of 0.943 in predicting lateralization for MR-negative patients, followed by PET (AUC = 0.857) and T2 (AUC = 0.843). CONCLUSIONS The combination of quantitative T2 mapping and [18F]FDG PET could improve lateralization for temporal lobe epilepsy. KEY POINTS • Quantitative T2 mapping and18F-FDG PET are complementary in the characterization of hippocampal alterations of MR-negative temporal lobe epilepsy patients. • The combination of quantitative T2 and18F-FDG PET obtained from hybrid PET/MR could improve lateralization for temporal lobe epilepsy.
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Affiliation(s)
- Miao Zhang
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Hui Huang
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Wei Liu
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Lihong Tang
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Qikang Li
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Jia Wang
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Xinyun Huang
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Xiaozhu Lin
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Hongping Meng
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Jin Wang
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Shikun Zhan
- grid.16821.3c0000 0004 0368 8293Department of Neurosurgery, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China
| | - Biao Li
- grid.16821.3c0000 0004 0368 8293Department of Nuclear Medicine, Ruijin Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai Jiao Tong University, Shanghai, 200240 China ,Collaborative Innovation Center for Molecular Imaging of Precision Medicine, Ruijin Center, Shanghai, 200025 China
| | - Jie Luo
- grid.16821.3c0000 0004 0368 8293School of Biomedical Engineering, Shanghai Jiao Tong University, Shanghai, 200240 China
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16
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Zhang T, Li Y, Zhao S, Xu Y, Zhang X, Wu S, Dou X, Yu C, Feng J, Ding Y, Zhu J, Chen Z, Zhang H, Tian M. High-resolution pediatric age-specific 18F-FDG PET template: a pilot study in epileptogenic focus localization. Eur J Nucl Med Mol Imaging 2021; 49:1560-1573. [PMID: 34746970 PMCID: PMC8940757 DOI: 10.1007/s00259-021-05611-w] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2021] [Accepted: 10/28/2021] [Indexed: 12/16/2022]
Abstract
Background PET imaging has been widely used in diagnosis of neurological disorders; however, its application to pediatric population is limited due to lacking pediatric age–specific PET template. This study aims to develop a pediatric age–specific PET template (PAPT) and conduct a pilot study of epileptogenic focus localization in pediatric epilepsy. Methods We recruited 130 pediatric patients with epilepsy and 102 age-matched controls who underwent 18F-FDG PET examination. High-resolution PAPT was developed by an iterative nonlinear registration-averaging optimization approach for two age ranges: 6–10 years (n = 17) and 11–18 years (n = 50), respectively. Spatial normalization to the PAPT was evaluated by registration similarities of 35 validation controls, followed by estimation of potential registration biases. In a pilot study, epileptogenic focus was localized by PAPT-based voxel-wise statistical analysis, compared with multi-disciplinary team (MDT) diagnosis, and validated by follow-up of patients who underwent epilepsy surgery. Furthermore, epileptogenic focus localization results were compared among three templates (PAPT, conventional adult template, and a previously reported pediatric linear template). Results Spatial normalization to the PAPT significantly improved registration similarities (P < 0.001), and nearly eliminated regions of potential biases (< 2% of whole brain volume). The PAPT-based epileptogenic focus localization achieved a substantial agreement with MDT diagnosis (Kappa = 0.757), significantly outperforming localization based on the adult template (Kappa = 0.496) and linear template (Kappa = 0.569) (P < 0.05). The PAPT-based localization achieved the highest detection rate (89.2%) and accuracy (80.0%). In postsurgical seizure-free patients (n = 40), the PAPT-based localization also achieved a substantial agreement with resection areas (Kappa = 0.743), and the highest detection rate (95%) and accuracy (80.0%). Conclusion The PAPT can significantly improve spatial normalization and epileptogenic focus localization in pediatric epilepsy. Future pediatric neuroimaging studies can also benefit from the unbiased spatial normalization by PAPT. Trial registration. NCT04725162: https://clinicaltrials.gov/ct2/show/NCT04725162 Supplementary Information The online version contains supplementary material available at 10.1007/s00259-021-05611-w.
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Affiliation(s)
- Teng Zhang
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
| | - Yuting Li
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
| | - Shuilin Zhao
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
| | - Yuanfan Xu
- Hangzhou Universal Medical Imaging Diagnostic Center, Hangzhou, China
| | - Xiaohui Zhang
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China
| | - Shuang Wu
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
| | - Xiaofeng Dou
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
| | - Congcong Yu
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China.,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China
| | - Jianhua Feng
- Department of Pediatrics, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Yao Ding
- Department of Neurology, Epilepsy Center, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Junming Zhu
- Department of Neurosurgery, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Zexin Chen
- Center of Clinical Epidemiology & Biostatistics, The Second Hospital of Zhejiang University School of Medicine, Hangzhou, China
| | - Hong Zhang
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China. .,Key Laboratory for Biomedical Engineering of Ministry of Education, Zhejiang University, Hangzhou, China. .,The College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou, China.
| | - Mei Tian
- Department of Nuclear Medicine and Medical PET Center, The Second Hospital of Zhejiang University School of Medicine, 88 Jiefang Road, Hangzhou, 310009, Zhejiang, China. .,Institute of Nuclear Medicine and Molecular Imaging of Zhejiang University, Hangzhou, China.
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Lau A, Beheshti I, Modirrousta M, Kolesar TA, Goertzen AL, Ko JH. Alzheimer's Disease-Related Metabolic Pattern in Diverse Forms of Neurodegenerative Diseases. Diagnostics (Basel) 2021; 11:diagnostics11112023. [PMID: 34829370 PMCID: PMC8624480 DOI: 10.3390/diagnostics11112023] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 10/29/2021] [Accepted: 10/29/2021] [Indexed: 12/13/2022] Open
Abstract
Dementia is broadly characterized by cognitive and psychological dysfunction that significantly impairs daily functioning. Dementia has many causes including Alzheimer’s disease (AD), dementia with Lewy bodies (DLB), and frontotemporal lobar degeneration (FTLD). Detection and differential diagnosis in the early stages of dementia remains challenging. Fueled by AD Neuroimaging Initiatives (ADNI) (Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. As such, the investigators within ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report.), a number of neuroimaging biomarkers for AD have been proposed, yet it remains to be seen whether these markers are also sensitive to other types of dementia. We assessed AD-related metabolic patterns in 27 patients with diverse forms of dementia (five had probable/possible AD while others had atypical cases) and 20 non-demented individuals. All participants had positron emission tomography (PET) scans on file. We used a pre-trained machine learning-based AD designation (MAD) framework to investigate the AD-related metabolic pattern among the participants under study. The MAD algorithm showed a sensitivity of 0.67 and specificity of 0.90 for distinguishing dementia patients from non-dementia participants. A total of 18/27 dementia patients and 2/20 non-dementia patients were identified as having AD-like patterns of metabolism. These results highlight that many underlying causes of dementia have similar hypometabolic pattern as AD and this similarity is an interesting avenue for future research.
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Affiliation(s)
- Angus Lau
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada; (A.L.); (I.B.); (T.A.K.)
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB R3E 0Z3, Canada
- Undergraduate Medical Education, University of Manitoba, Winnipeg, MB R3E 3P5, Canada
| | - Iman Beheshti
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada; (A.L.); (I.B.); (T.A.K.)
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB R3E 0Z3, Canada
| | - Mandana Modirrousta
- Department of Psychiatry, University of Manitoba, Winnipeg, MB R3E 3N4, Canada;
| | - Tiffany A. Kolesar
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada; (A.L.); (I.B.); (T.A.K.)
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB R3E 0Z3, Canada
| | - Andrew L. Goertzen
- Department of Radiology, University of Manitoba, Winnipeg, MB R3T 2N2, Canada;
- Graduate Program in Biomedical Engineering, University of Manitoba, Winnipeg, MB R3E 5V6, Canada
| | - Ji Hyun Ko
- Department of Human Anatomy and Cell Science, University of Manitoba, Winnipeg, MB R3E 0J9, Canada; (A.L.); (I.B.); (T.A.K.)
- Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Winnipeg, MB R3E 0Z3, Canada
- Graduate Program in Biomedical Engineering, University of Manitoba, Winnipeg, MB R3E 5V6, Canada
- Correspondence: ; Tel.: +1-204-318-2566
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18
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Waterschoot R, D'Asseler Y, Goethals I. Comparison of an in-house acquired brain F-18 FDG PET normal database with commercially available normal data. Nucl Med Commun 2021; 42:1039-1044. [PMID: 33867483 DOI: 10.1097/mnm.0000000000001427] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
INTRODUCTION Current guidelines recommend the use of semiautomated assessment of F-18 FDG PET brain studies. Accuracy is influenced by the normal data, which requires knowledge of the included subjects and how they were acquired. Due to confidentiality, such information is often not completely disclosed. Our aim was to determine the variation in FDG uptake between several commercially available and our in-house normal database. METHODS Our database contains 83 healthy subjects. Outlier detection using SPM further ensured normality, resulting in exclusion of three subjects. The remaining 80 subjects were analyzed using three commercially available software packages. Z-score data per patient and per lobe were extracted and pooled in predefined age groups (18-40, 41-60 and 61-80 years old) with a calculation of mean Z-scores and SD. Correlation between Z-score output of different software was investigated. RESULTS In the 18-40 years age group, frontotemporal hypermetabolism was found with all software. Decreased cerebellar uptake was found with two software packages. Mean Z-scores are closer to zero in the 41-60 years age group compared to the younger group, and mostly within the normal range in the 61-80 years age group with all software. A moderate to high linear correlation between Z-score output was found, but individual Z-scores varied widely. CONCLUSIONS The three software packages yielded varying Z-score output, partially explained by an age mismatch between our subjects and subjects in their normal databases. A definitive explanation for the remaining differences is lacking. This emphasizes the importance of age-matched normal data and knowledge of the included databases to allow adequate preprocessing.
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Affiliation(s)
- Robbe Waterschoot
- Department of Nuclear Medicine, Ghent University Hospital, Gent, Belgium
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19
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Iaccarino L, Sala A, Caminiti SP, Presotto L, Perani D. In vivo MRI Structural and PET Metabolic Connectivity Study of Dopamine Pathways in Alzheimer's Disease. J Alzheimers Dis 2021; 75:1003-1016. [PMID: 32390614 DOI: 10.3233/jad-190954] [Citation(s) in RCA: 20] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
Abstract
BACKGROUND Alzheimer's disease (AD) is characterized by an involvement of brain dopamine (DA) circuitry, the presence of which has been associated with emergence of both neuropsychiatric symptoms and cognitive deficits. OBJECTIVE In order to investigate whether and how the DA pathways are involved in the pathophysiology of AD, we assessed by in vivo neuroimaging the structural and metabolic alterations of subcortical and cortical DA pathways and targets. METHODS We included 54 healthy control participants, 53 amyloid-positive subjects with mild cognitive impairment due to AD (MCI-AD), and 60 amyloid-positive patients with probable dementia due to AD (ADD), all with structural 3T MRI and 18F-FDG-PET scans. We assessed MRI-based gray matter reductions in the MCI-AD and ADD groups within an anatomical a priori-defined Nigrostriatal and Mesocorticolimbic DA pathways, followed by 18F-FDG-PET metabolic connectivity analyses to evaluate network-level metabolic connectivity changes. RESULTS We found significant tissue loss in the Mesocorticolimbic over the Nigrostriatal pathway. Atrophy was evident in the ventral striatum, orbitofrontal cortex, and medial temporal lobe structures, and already plateaued in the MCI-AD stage. Degree of atrophy in Mesocorticolimbic regions positively correlated with the severity of depression, anxiety, and apathy in MCI-AD and ADD subgroups. Additionally, we observed significant alterations of metabolic connectivity between the ventral striatum and fronto-cingulate regions in ADD, but not in MCI-AD. There were no metabolic connectivity changes within the Nigrostriatal pathway. CONCLUSION Our cross-sectional data support a clinically-meaningful, yet stage-dependent, involvement of the Mesocorticolimbic system in AD. Longitudinal and clinical correlation studies are needed to further establish the relevance of DA system involvement in AD.
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Affiliation(s)
- Leonardo Iaccarino
- Vita-Salute San Raffaele University, Milan, Italy.,In vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Memory and Aging Center, Weill Institute for Neurosciences, University of California San Francisco, San Francisco, CA, USA
| | - Arianna Sala
- Vita-Salute San Raffaele University, Milan, Italy.,In vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy.,In vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Luca Presotto
- In vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy.,In vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy
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20
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Foucher JR, de Billy C, Jeanjean LC, Obrecht A, Mainberger O, Clauss JME, Schorr B, Lupu MC, de Sousa PL, Lamy J, Noblet V, Sauleau EA, Landré L, Berna F. A Brain Imaging-Based Diagnostic Biomarker for Periodic Catatonia: Preliminary Evidence Using a Bayesian Approach. Neuropsychobiology 2021; 79:352-365. [PMID: 31505494 DOI: 10.1159/000501830] [Citation(s) in RCA: 9] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Accepted: 06/24/2019] [Indexed: 11/19/2022]
Abstract
Periodic catatonia (PC) is a psychomotor phenotype with a progressive-remitting course. While it can fit any disorder diagnosis of the schizoaffective spectrum, its core features consist of a mix of hypo- and hyperkinesias resulting in distortions of expressive movements such as grimacing and parakinesias. The replication of cerebral blood flow (CBF) increases in the left supplementary motor area (L-SMA) and lateral premotor cortex (L-LPM) in acute and remitting PC patients indicates that these increases could be used as diagnostic biomarkers. In this proof-of-concept study, 2 different MRI sequences were repeated on 3 separate days to get reliable measurement values of CBF in 9 PC and 26 non-PC patients during different cognitive tasks. Each patient was compared to 37 controls. In L-SMA [-9; +10; +60] and L-LPM [-46; -12; +43], a test was positive if the t value was >2.02 (α < 0.05; two tailed). The measurements had good analytical performance. Regarding the tests, their sensitivities and specificities were significantly different from the chance level on both measures, except for L-SMA sensitivities. When combining all the tests, among regions and methods, sensitivity was 98% (95% credible interval [CI] 76-100%) and specificity 88% (72-97%). Bayesian inferences of its negative predictive values for PC were >95% regardless of the context, while its positive predictive values reached 94% but only when used in combination with clinical criteria. The case-by-case analysis suggests that non-PC patients with neurological motor deficits are at risk to be false positive.
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Affiliation(s)
- Jack René Foucher
- ICube - CNRS UMR 7357, Neurophysiology, FMTS, University of Strasbourg, Strasbourg, France, .,CEMNIS - Noninvasive Neuromodulation Center, University Hospital Strasbourg, Strasbourg, France,
| | - Clément de Billy
- ICube - CNRS UMR 7357, Neurophysiology, FMTS, University of Strasbourg, Strasbourg, France.,CEMNIS - Noninvasive Neuromodulation Center, University Hospital Strasbourg, Strasbourg, France
| | - Ludovic Christophe Jeanjean
- ICube - CNRS UMR 7357, Neurophysiology, FMTS, University of Strasbourg, Strasbourg, France.,CEMNIS - Noninvasive Neuromodulation Center, University Hospital Strasbourg, Strasbourg, France
| | - Alexandre Obrecht
- CEMNIS - Noninvasive Neuromodulation Center, University Hospital Strasbourg, Strasbourg, France.,Pôle de Psychiatrie, Santé Mentale et Addictologie, University Hospital Strasbourg, Strasbourg, France
| | - Olivier Mainberger
- ICube - CNRS UMR 7357, Neurophysiology, FMTS, University of Strasbourg, Strasbourg, France.,CEMNIS - Noninvasive Neuromodulation Center, University Hospital Strasbourg, Strasbourg, France
| | - Julie Marie Estelle Clauss
- Pôle de Psychiatrie, Santé Mentale et Addictologie, University Hospital Strasbourg, Strasbourg, France.,SAGE - CNRS UMR 7363, FMTS, University of Strasbourg, Strasbourg, France
| | - Benoit Schorr
- Pôle de Psychiatrie, Santé Mentale et Addictologie, University Hospital Strasbourg, Strasbourg, France.,Physiopathologie et Psychopathologie Cognitive de la Schizophrénie - INSERM 1114, FMTS, University of Strasbourg, Strasbourg, France
| | | | | | - Julien Lamy
- ICube - CNRS UMR 7357, Neurophysiology, FMTS, University of Strasbourg, Strasbourg, France
| | - Vincent Noblet
- ICube - CNRS UMR 7357, Neurophysiology, FMTS, University of Strasbourg, Strasbourg, France
| | - Erik André Sauleau
- Biostatistical Laboratory, iCube - CNRS UMR 7357, University of Strasbourg, Strasbourg, France
| | - Lionel Landré
- ICube - CNRS UMR 7357, Neurophysiology, FMTS, University of Strasbourg, Strasbourg, France
| | - Fabrice Berna
- Pôle de Psychiatrie, Santé Mentale et Addictologie, University Hospital Strasbourg, Strasbourg, France.,Physiopathologie et Psychopathologie Cognitive de la Schizophrénie - INSERM 1114, FMTS, University of Strasbourg, Strasbourg, France
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21
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Garibotto V, Trombella S, Antelmi L, Bosco P, Redolfi A, Tabouret-Viaud C, Rager O, Gold G, Giannakopoulos P, Morbelli S, Nobili F, Perneczky R, Didic M, Guedj E, Drzezga A, Ossenkoppele R, Berckel BV, Ratib O, Frisoni GB. A Comparison of Two Statistical Mapping Tools for Automated Brain FDG-PET Analysis in Predicting Conversion to Alzheimer's Disease in Subjects with Mild Cognitive Impairment. Curr Alzheimer Res 2021; 17:1186-1194. [PMID: 33583380 DOI: 10.2174/1567205018666210212162443] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2020] [Revised: 10/24/2020] [Accepted: 12/28/2020] [Indexed: 11/22/2022]
Abstract
OBJECTIVE Automated voxel-based analysis methods are used to detect cortical hypometabolism typical of Alzheimer's Disease (AD) on FDG-PET brain scans. We compared the accuracy of two clinically validated tools for their ability to identify those MCI subjects progressing to AD at followup, to evaluate the impact of the analysis method on FDG-PET diagnostic performance. METHODS SPMGrid and BRASS (Hermes Medical Solutions, Stockholm, Sweden) were tested on 131 MCI and elderly healthy controls from the EADC PET dataset. The concordance between the tools was tested by correlating the quantitative parameters (z- and t-values), calculated by the two software tools, and by measuring the topographical overlap of the abnormal regions (Dice score). Three independent expert readers blindly assigned a diagnosis based on the two map sets. We used conversion to AD dementia as the gold standard. RESULTS The t-map and z-map calculated with SPMGrid and BRASS, respectively, showed a good correlation (R > .50) for the majority of individual cases (128/131) and for the majority of selected regions of interest (ROIs) (98/116). The overlap of the hypometabolic patterns from the two tools was, however, poor (Dice score .36). The diagnostic performance was comparable, with BRASS showing significantly higher sensitivity (.82 versus .59) and SPMGrid showing higher specificity (.87 versus .52). CONCLUSION Despite similar diagnostic performance in predicting conversion to AD in MCI subjects, the two tools showed significant differences, and the maps provided by the tools showed limited overlap. These results underline the urgency for standardization across FDG-PET analysis methods for their use in clinical practice.
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Affiliation(s)
- Valentina Garibotto
- Laboratory of Neuroimaging and Innovative Molecular Tracer, University of Geneva, Geneva, Switzerland
| | - Sara Trombella
- Laboratory of Neuroimaging and Innovative Molecular Tracer, University of Geneva, Geneva, Switzerland
| | - Luigi Antelmi
- University of Cote d'Azur, Inria Sophia Antipolis, Epione Research Project, Nice, France
| | - Paolo Bosco
- IRCCS Fondazione Stella Maris, Viale del Tirreno 331, Pisa, Italy
| | - Alberto Redolfi
- Laboratory of Neuroinformatics, IRCCS Istituto Centro San Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Claire Tabouret-Viaud
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Olivier Rager
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, University Hospitals of Geneva, Geneva, Switzerland
| | | | | | - Silvia Morbelli
- Department of Nuclear Medicine, IRCCS AOU San Martino-IST, University of Genoa, Genoa, Italy
| | - Flavio Nobili
- Department of Nuclear Medicine, IRCCS AOU San Martino-IST, University of Genoa, Genoa, Italy
| | - Robert Perneczky
- Department of Psychiatry and Psychotherapy, Ludwig, Maximilians-Universitaet Muenchen, Munich, Germany
| | - Mira Didic
- Aix-Marseille Universite, CNRS, Ecole Centrale Marseille, UMR 7249, Institut Fresnel, Marseille, France
| | - Eric Guedj
- Aix-Marseille Universite, CNRS, Ecole Centrale Marseille, UMR 7249, Institut Fresnel, Marseille, France
| | - Alexander Drzezga
- Department of Nuclear Medicine, Technische Universitaet, Munich, Germany
| | - Rik Ossenkoppele
- Department of Nuclear Medicine and PET Research, VU University Medical Center, Amsterdam, Netherlands
| | - Bart Van Berckel
- Department of Nuclear Medicine and PET Research, VU University Medical Center, Amsterdam, Netherlands
| | - Osman Ratib
- Division of Nuclear Medicine and Molecular Imaging, Diagnostic Department, University Hospitals of Geneva, Geneva, Switzerland
| | - Giovanni B Frisoni
- Laboratory of Neuroimaging of Aging, University of Geneva, Geneva, Switzerland
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22
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Caminiti SP, Sala A, Presotto L, Chincarini A, Sestini S, Perani D, Schillaci O, Berti V, Calcagni ML, Cistaro A, Morbelli S, Nobili F, Pappatà S, Volterrani D, Gobbo CL. Validation of FDG-PET datasets of normal controls for the extraction of SPM-based brain metabolism maps. Eur J Nucl Med Mol Imaging 2021; 48:2486-2499. [PMID: 33423088 DOI: 10.1007/s00259-020-05175-1] [Citation(s) in RCA: 22] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/03/2020] [Accepted: 12/20/2020] [Indexed: 12/22/2022]
Abstract
PURPOSE An appropriate healthy control dataset is mandatory to achieve good performance in voxel-wise analyses. We aimed at evaluating [18F]FDG PET brain datasets of healthy controls (HC), based on publicly available data, for the extraction of voxel-based brain metabolism maps at the single-subject level. METHODS Selection of HC images was based on visual rating, after Cook's distance and jack-knife analyses, to exclude artefacts and/or outliers. The performance of these HC datasets (ADNI-HC and AIMN-HC) to extract hypometabolism patterns in single patients was tested in comparison with the standard reference HC dataset (HSR-HC) by means of Dice score analysis. We evaluated the performance and comparability of the different HC datasets in the assessment of single-subject SPM-based hypometabolism in three independent cohorts of patients, namely, ADD, bvFTD and DLB. RESULTS Two-step Cook's distance analysis and the subsequent jack-knife analysis resulted in the selection of n = 125 subjects from the AIMN-HC dataset and n = 75 subjects from the ADNI-HC dataset. The average concordance between SPM hypometabolism t-maps in the three patient cohorts, as obtained with the new datasets and compared to the HSR-HC standard reference dataset, was 0.87 for the AIMN-HC dataset and 0.83 for the ADNI-HC dataset. Pattern expression analysis revealed high overall accuracy (> 80%) of the SPM t-map classification according to different statistical thresholds and sample sizes. CONCLUSIONS The applied procedures ensure validity of these HC datasets for the single-subject estimation of brain metabolism using voxel-wise comparisons. These well-selected HC datasets are ready-to-use in research and clinical settings.
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Affiliation(s)
- Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy.,In vivo human molecular and structural neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Arianna Sala
- Vita-Salute San Raffaele University, Milan, Italy.,In vivo human molecular and structural neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Luca Presotto
- Nuclear Medicine Unit, San Raffaele Hospital, Via Olgettina 60, 20132, Milan, Italy
| | | | | | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy. .,In vivo human molecular and structural neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy. .,Nuclear Medicine Unit, San Raffaele Hospital, Via Olgettina 60, 20132, Milan, Italy.
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23
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Tondo G, Carli G, Santangelo R, Mattoli MV, Presotto L, Filippi M, Magnani G, Iannaccone S, Cerami C, Perani D. Biomarker-based stability in limbic-predominant amnestic mild cognitive impairment. Eur J Neurol 2020; 28:1123-1133. [PMID: 33185922 DOI: 10.1111/ene.14639] [Citation(s) in RCA: 16] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/15/2020] [Revised: 11/05/2020] [Accepted: 11/06/2020] [Indexed: 12/14/2022]
Abstract
BACKGROUND The amnestic presentation of mild cognitive impairment (aMCI) represents the most common prodromal stage of Alzheimer's disease (AD) dementia. There is, however, some evidence of aMCI with typical amnestic syndrome but showing long-term clinical stability. The ability to predict stability or progression to dementia in the aMCI condition is important, particularly for the selection of candidates in clinical trials. We aimed to establish the role of in vivo biomarkers, as assessed by cerebrospinal fluid (CSF) measures and [18 F]fluorodeoxyglucose (FDG)-positron emission tomography (PET) imaging, in predicting prognosis in a large aMCI cohort. METHODS We conducted a retrospective study, including 142 aMCI subjects who had a long follow-up (4-19 years), baseline CSF data and [18 F]FDG-PET scans individually assessed by validated voxel-based procedures, classifying subjects into either limbic-predominant or AD-like hypometabolism patterns. RESULTS The two aMCI cohorts were clinically comparable at baseline. At follow-up, the aMCI group with a limbic-predominant [18 F]FDG-PET pattern showed clinical stability over a very long follow-up (8.20 ± 3.30 years), no decline in Mini-Mental State Examination score, and only 7% conversion to dementia. Conversely, the aMCI group with an AD-like [18 F]FDG-PET pattern had a high rate of dementia progression (86%) over a shorter follow-up (6.47 ± 2.07 years). Individual [18 F]FDG-PET hypometabolism patterns predicted stability or conversion with high accuracy (area under the curve = 0.89), sensitivity (0.90) and specificity (0.89). In the limbic-predominant aMCI cohort, CSF biomarkers showed large variability and no prognostic value. CONCLUSIONS In a large series of clinically comparable subjects with aMCI at baseline, the specific [18 F]FDG-PET limbic-predominant hypometabolism pattern was associated with clinical stability, making progression to AD very unlikely. The identification of a biomarker-based benign course in aMCI subjects has important implications for prognosis and in planning clinical trials.
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Affiliation(s)
- Giacomo Tondo
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Giulia Carli
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberto Santangelo
- Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | - Maria Vittoria Mattoli
- Department of Neuroscience, Imaging and Clinical Science, G. d'Annunzio University of Chieti-Pescara, Chieti, Italy
| | - Luca Presotto
- Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy
| | - Massimo Filippi
- Vita-Salute San Raffaele University, Milan, Italy.,Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | - Giuseppe Magnani
- Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | - Sandro Iannaccone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Chiara Cerami
- Scuola Universitaria Superiore IUSS, Pavia, Italy.,Cognitive Computational Neuroscience Research Unit, IRCCS Mondino Foundation, Pavia, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, San Raffaele Hospital, Milan, Italy
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24
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Rossini PM, Cappa SF, Lattanzio F, Perani D, Spadin P, Tagliavini F, Vanacore N. The Italian INTERCEPTOR Project: From the Early Identification of Patients Eligible for Prescription of Antidementia Drugs to a Nationwide Organizational Model for Early Alzheimer's Disease Diagnosis. J Alzheimers Dis 2020; 72:373-388. [PMID: 31594234 DOI: 10.3233/jad-190670] [Citation(s) in RCA: 18] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
Alzheimer's disease is the most common age-related neurodegenerative disorder and its burden on patients, families, and society grows significantly with lifespan. Early modifications of risk-enhancing lifestyles and treatment initiation expand personal autonomy and reduce management costs. Many clinical trials with potentially disease-modifying drugs are devoted to mild cognitive impairment (MCI) prodromal-to-Alzheimer's disease. The identification of biomarkers for early diagnosis may thus be crucial for early intervention and identification of high-risk subjects, the most appropriate target of new drugs as soon as they will be discovered. INTERCEPTOR is a strategic project by the Italian Ministry of Health and the Italian Medicines Agency (AIFA), aiming to validate the best combination (highly accurate, non-invasive, available on the whole national territory and financially sustainable) of biomarkers and organizational model for early diagnosis. 500 MCI subjects will be enrolled at baseline and followed-up for 3 years for at least 400 of them in order to define a "hub & spoke" nationwide model with recruiting (spokes) centers for MCI identification and expert (hubs) centers for risk diagnosis.
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Affiliation(s)
- Paolo Maria Rossini
- Area of Neuroscience, University Policlinic A. Gemelli Foundation-IRCCS, Rome, Italy.,Institute of Neurology, Catholic University, Rome, Italy
| | - Stefano F Cappa
- University School for Advanced Studies IUSS Pavia, Pavia, Italy.,IRCCS St. John of God, Brescia, Italy
| | | | - Daniela Perani
- Nuclear Medicine Unit and Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Vita-Salute San Raffaele University, Milan, Italy
| | - Patrizia Spadin
- President "Associazione Italiana Malattia di Alzheimer" - AIMA, Italy
| | | | - Nicola Vanacore
- National Center for Disease Prevention and Health Promotion, National Institute of Health, Rome, Italy
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25
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Chanteloup G, Cordonnier M, Moreno-Ramos T, Pytel V, Matías-Guiu J, Gobbo J, Cabrera-Martín MN, Gómez-Pinedo U, Garrido C, Matías-Guiu JA. Exosomal HSP70 for Monitoring of Frontotemporal Dementia and Alzheimer's Disease: Clinical and FDG-PET Correlation. J Alzheimers Dis 2020; 71:1263-1269. [PMID: 31498123 DOI: 10.3233/jad-190545] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
We aimed to study the expression of circulating heat-shock protein HSP70 and exosomes in plasma of a cohort of patients with Alzheimer's disease (AD) and frontotemporal dementia (FTD) at different stages. We performed correlations with clinical scales and FDG-PET. HSP70 levels were higher within exosomes than free in plasma. Moderate correlations were found between exosomal HSP70 and CDR, FTLD-CDR, and extension of hypometabolism. Our results suggest modifications in the level of exosomal HSP70 during the course of neurodegeneration, regardless of AD or FTD, and therefore HSP70 could have a potential role in the follow-up of these disorders.
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Affiliation(s)
- Gäetan Chanteloup
- INSERM, UMR1231, Labex LipSTIC, Dijon, France.,Université de Bourgogne-Franche Comté, Dijon, France
| | - Marine Cordonnier
- INSERM, UMR1231, Labex LipSTIC, Dijon, France.,Université de Bourgogne-Franche Comté, Dijon, France
| | - Teresa Moreno-Ramos
- Department of Neurology and Laboratory of Neurobiology, Hospital Clinico San Carlos, Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Vanesa Pytel
- Department of Neurology and Laboratory of Neurobiology, Hospital Clinico San Carlos, Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Jorge Matías-Guiu
- Department of Neurology and Laboratory of Neurobiology, Hospital Clinico San Carlos, Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Jessica Gobbo
- Cancer Centre Georges François Leclerc, Dijon, France
| | - María Nieves Cabrera-Martín
- Department of Nuclear Medicine. Hospital Clinico San Carlos, Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Ulises Gómez-Pinedo
- Department of Neurology and Laboratory of Neurobiology, Hospital Clinico San Carlos, Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Carmen Garrido
- INSERM, UMR1231, Labex LipSTIC, Dijon, France.,Université de Bourgogne-Franche Comté, Dijon, France.,Cancer Centre Georges François Leclerc, Dijon, France
| | - Jordi A Matías-Guiu
- Department of Neurology and Laboratory of Neurobiology, Hospital Clinico San Carlos, Health Research Institute "San Carlos" (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
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26
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Catricalà E, Polito C, Presotto L, Esposito V, Sala A, Conca F, Gasparri C, Berti V, Filippi M, Pupi A, Sorbi S, Iannaccone S, Magnani G, Cappa SF, Perani D. Neural correlates of naming errors across different neurodegenerative diseases: An FDG-PET study. Neurology 2020; 95:e2816-e2830. [PMID: 33004608 DOI: 10.1212/wnl.0000000000010967] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/18/2020] [Accepted: 07/23/2020] [Indexed: 12/19/2022] Open
Abstract
OBJECTIVE To investigate the types of errors produced in a picture naming task by patients with neurodegenerative dementia due to different etiologies and their neural correlates. METHODS The same standardized picture naming test was administered to a consecutive sample of patients (n = 148) who had been studied with [18F] FDG-PET. The errors were analyzed in 3 categories (visual, semantic, and phonologic). The PET data were analyzed using an optimized single-subject procedure, and the statistical parametric mapping multiple regression design was used to explore the correlation between each type of error and brain hypometabolism in the whole group. Metabolic connectivity analyses were run at the group level on 7 left hemisphere cortical areas corresponding to an a priori defined naming network. RESULTS Semantic errors were predominant in most patients, independent of clinical diagnosis. In the whole group analysis, visual errors correlated with hypometabolism in the right inferior occipital lobe and in the left middle occipital lobe. Semantic errors correlated with hypometabolism in the left fusiform gyrus, the inferior and middle temporal gyri, and the temporal pole. Phonologic errors were associated with hypometabolism in the left superior and middle temporal gyri. Both positive (occipital-posterior fusiform) and negative (anterior fusiform gyrus and the superior anterior temporal lobe) connectivity changes were associated with semantic errors. CONCLUSIONS Naming errors reflect the dysfunction of separate stages of the naming process and are specific markers for different patterns of brain involvement. These correlations are not limited to primary progressive aphasia but extend to other neurodegenerative dementias.
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Affiliation(s)
- Eleonora Catricalà
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Cristina Polito
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Luca Presotto
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Valentina Esposito
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Arianna Sala
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Francesca Conca
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Celeste Gasparri
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Valentina Berti
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Massimo Filippi
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Alberto Pupi
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Sandro Sorbi
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Sandro Iannaccone
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Giuseppe Magnani
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
| | - Stefano F Cappa
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy.
| | - Daniela Perani
- From the Faculty of Psychology (E.C., F.C., C.G., S.F.C.), Institute for Advanced Studies, IUSS, Pavia; Nuclear Medicine Unit (C.P., V.B., A.P.), Department of Experimental and Clinical Biomedical Sciences, and NEUROFARBA, Department of Neuroscience, Psychology, Drug Research and Child Health (S.S.), University of Florence; Nuclear Medicine Unit (L.P., A.S., D.P.), IRCCS San Raffaele Hospital, Milan; Faculty of Psychology (V.E., A.S., D.P.), Vita-Salute San Raffaele University, Milan; Department of Neurology and INSPE (M.F., G.M.), San Raffaele Scientific Institute, Milan; Clinical Neuroscience Department (S.I.), San Raffaele Turro Hospital, Milan; IRCCS Fondazione Don Carlo Gnocchi (S.S.), Florence, and IRCCS Fondazione Istituto Neurologico Casimiro Mondino (S.F.C.), Pavia, Italy
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27
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Brugnolo A, De Carli F, Pagani M, Morbelli S, Jonsson C, Chincarini A, Frisoni GB, Galluzzi S, Perneczky R, Drzezga A, van Berckel BNM, Ossenkoppele R, Didic M, Guedj E, Arnaldi D, Massa F, Grazzini M, Pardini M, Mecocci P, Dottorini ME, Bauckneht M, Sambuceti G, Nobili F. Head-to-Head Comparison among Semi-Quantification Tools of Brain FDG-PET to Aid the Diagnosis of Prodromal Alzheimer's Disease. J Alzheimers Dis 2020; 68:383-394. [PMID: 30776000 DOI: 10.3233/jad-181022] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
BACKGROUND Several automatic tools have been implemented for semi-quantitative assessment of brain [18]F-FDG-PET. OBJECTIVE We aimed to head-to-head compare the diagnostic performance among three statistical parametric mapping (SPM)-based approaches, another voxel-based tool (i.e., PALZ), and a volumetric region of interest (VROI-SVM)-based approach, in distinguishing patients with prodromal Alzheimer's disease (pAD) from controls. METHODS Sixty-two pAD patients (MMSE score = 27.0±1.6) and one hundred-nine healthy subjects (CTR) (MMSE score = 29.2±1.2) were enrolled in five centers of the European Alzheimer's Disease Consortium. The three SPM-based methods, based on different rationales, included 1) a cluster identified through the correlation analysis between [18]F-FDG-PET and a verbal memory test (VROI-1), 2) a VROI derived from the comparison between pAD and CTR (VROI-2), and 3) visual analysis of individual maps obtained by the comparison between each subject and CTR (SPM-Maps). The VROI-SVM approach was based on 6 VROI plus 6 VROI asymmetry values derived from the pAD versus CTR comparison thanks to support vector machine (SVM). RESULTS The areas under the ROC curves between pAD and CTR were 0.84 for VROI-1, 0.83 for VROI-2, 0.79 for SPM maps, 0.87 for PALZ, and 0.95 for VROI-SVM. Pairwise comparisons of Youden index did not show statistically significant differences in diagnostic performance between VROI-1, VROI-2, SPM-Maps, and PALZ score whereas VROI-SVM performed significantly (p < 0.005) better than any of the other methods. CONCLUSION The study confirms the good accuracy of [18]F-FDG-PET in discriminating healthy subjects from pAD and highlights that a non-linear, automatic VROI classifier based on SVM performs better than the voxel-based methods.
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Affiliation(s)
- Andrea Brugnolo
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Mother-Child health (DINOGMI), University of Genoa, Italy.,Clinical Psychology Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Fabrizio De Carli
- Institute of Bioimaging and Molecular Physiology, Consiglio Nazionale delle Ricerche (CNR), Genoa, Italy
| | - Marco Pagani
- Institute of Cognitive Sciences and Technologies, Consiglio Nazionale delle Ricerche (CNR), Rome, Italy.,Department of Nuclear Medicine, Karolinska Hospital, Stockholm, Sweden
| | - Slivia Morbelli
- Department of Health Sciences (DISSAL), University of Genoa, Italy.,Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Cathrine Jonsson
- Medical Radiation Physics and Nuclear Medicine, Imaging and Physiology, Karolinska University Hospital, Stockholm, Sweden
| | | | - Giovanni B Frisoni
- LENITEM Laboratory of Epidemiology and Neuroimaging, IRCCS S. Giovanni di Dio-FBF, Brescia, Italy.,University Hospitals and University of Geneva, Geneva, Switzerland
| | - Samantha Galluzzi
- LENITEM Laboratory of Epidemiology and Neuroimaging, IRCCS S. Giovanni di Dio-FBF, Brescia, Italy
| | - Robert Perneczky
- Department of Psychiatry and Psychotherapy, University Hospital, LMU Munich, Germany.,Department of Psychiatry and Psychotherapy, Technische Universität München, Munich, Germany.,German Center for Neurodegenerative Diseases (DZNE) Munich, Germany.,Neuroepidemiology and Ageing Research Unit, School of Public Health, Faculty of Medicine, The Imperial College London of Science, Technology and Medicine, London, UK
| | - Alexander Drzezga
- Department of Nuclear Medicine, University Hospital of Cologne, Germany; previously at Department of Nuclear Medicine, Technische Universität, Munich, Germany
| | - Bart N M van Berckel
- Department of Nuclear Medicine & PET Research, VU University Medical Center, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Department of Nuclear Medicine & PET Research, VU University Medical Center, Amsterdam, The Netherlands
| | - Mira Didic
- APHM, CHU Timone, Service de Neurologie et Neuropsychologie, Aix-Marseille University, Marseille, France
| | - Eric Guedj
- APHM, CHU Timone, Service de Médecine Nucléaire, CERIMED, Institut Fresnel, CNRS, Ecole Centrale Marseille, Aix-Marseille University, France
| | - Dario Arnaldi
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Mother-Child health (DINOGMI), University of Genoa, Italy.,Neurology Clinics, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Federico Massa
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Mother-Child health (DINOGMI), University of Genoa, Italy
| | - Matteo Grazzini
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Mother-Child health (DINOGMI), University of Genoa, Italy
| | - Matteo Pardini
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Mother-Child health (DINOGMI), University of Genoa, Italy.,Neurology Clinics, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Patrizia Mecocci
- Section of Gerontology and Geriatrics, University of Perugia, Perugia, Italy
| | - Massimo E Dottorini
- Department of Diagnostic Imaging, Nuclear Medicine Unit, Perugia General Hospital, Perugia, Italy
| | - Matteo Bauckneht
- Department of Health Sciences (DISSAL), University of Genoa, Italy.,Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Gianmario Sambuceti
- Department of Health Sciences (DISSAL), University of Genoa, Italy.,Nuclear Medicine Unit, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
| | - Flavio Nobili
- Department of Neuroscience, Rehabilitation, Ophthalmology, Genetics, and Mother-Child health (DINOGMI), University of Genoa, Italy.,Neurology Clinics, IRCCS Ospedale Policlinico San Martino, Genoa, Italy
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28
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Matías-Guiu JA, Gómez-Pinedo U, Forero L, Pytel V, Cano F, Moreno-Ramos T, Cabrera-Martín MN, Matías-Guiu J, González-Rosa JJ. Plasma Neurofilament Light Chain in Primary Progressive Aphasia and Related Disorders: Clinical Significance and Metabolic Correlates. J Alzheimers Dis 2019; 72:773-782. [DOI: 10.3233/jad-190838] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Affiliation(s)
- Jordi A. Matías-Guiu
- Department of Neurology and Laboratory of Neurobiology, Hospital Clínico San Carlos, San Carlos Health Research Institute (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Ulises Gómez-Pinedo
- Department of Neurology and Laboratory of Neurobiology, Hospital Clínico San Carlos, San Carlos Health Research Institute (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Lucía Forero
- Department of Neurology, Puerta del Mar University Hospital, Cádiz, Spain
| | - Vanesa Pytel
- Department of Neurology and Laboratory of Neurobiology, Hospital Clínico San Carlos, San Carlos Health Research Institute (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Fátima Cano
- Department of Psychology, Universidad de Cádiz, Cádiz, Spain
- Biomedical Research and Innovation Institute of Cádiz (INiBICA), Cádiz, Spain
| | - Teresa Moreno-Ramos
- Department of Neurology and Laboratory of Neurobiology, Hospital Clínico San Carlos, San Carlos Health Research Institute (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - María Nieves Cabrera-Martín
- Department of Nuclear Medicine, Hospital Clínico San Carlos, San Carlos Health Research Institute (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Jorge Matías-Guiu
- Department of Neurology and Laboratory of Neurobiology, Hospital Clínico San Carlos, San Carlos Health Research Institute (IdISCC), Universidad Complutense de Madrid, Madrid, Spain
| | - Javier J. González-Rosa
- Department of Psychology, Universidad de Cádiz, Cádiz, Spain
- Biomedical Research and Innovation Institute of Cádiz (INiBICA), Cádiz, Spain
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29
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Kogan RV, de Jong BA, Renken RJ, Meles SK, van Snick PJ, Golla S, Rijnsdorp S, Perani D, Leenders KL, Boellaard R. Factors affecting the harmonization of disease-related metabolic brain pattern expression quantification in [ 18F]FDG-PET (PETMETPAT). ALZHEIMER'S & DEMENTIA: DIAGNOSIS, ASSESSMENT & DISEASE MONITORING 2019; 11:472-482. [PMID: 31294076 PMCID: PMC6595051 DOI: 10.1016/j.dadm.2019.04.002] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
Abstract
Introduction The implementation of spatial-covariance [18F]fluorodeoxyglucose positron emission tomography–based disease-related metabolic brain patterns as biomarkers has been hampered by intercenter imaging differences. Within the scope of the JPND-PETMETPAT working group, we illustrate the impact of these differences on Parkinson's disease–related pattern (PDRP) expression scores. Methods Five healthy controls, 5 patients with idiopathic rapid eye movement sleep behavior disorder, and 5 patients with Parkinson's disease were scanned on one positron emission tomography/computed tomography system with multiple image reconstructions. In addition, one Hoffman 3D Brain Phantom was scanned on several positron emission tomography/computed tomography systems using various reconstructions. Effects of image contrast on PDRP scores were also examined. Results Human and phantom raw PDRP scores were systematically influenced by scanner and reconstruction effects. PDRP scores correlated inversely to image contrast. A Gaussian spatial filter reduced contrast while decreasing intercenter score differences. Discussion Image contrast should be considered in harmonization efforts. A Gaussian filter may reduce noise and intercenter effects without sacrificing sensitivity. Phantom measurements will be important for correcting PDRP score offsets.
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Affiliation(s)
- Rosalie V. Kogan
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
- Corresponding author. Tel.: +31-50-3613541; Fax: +31-50-3611687.
| | - Bas A. de Jong
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Remco J. Renken
- Neuroimaging Center, Department of Neuroscience, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sanne K. Meles
- Department of Neurology, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Paul J.H. van Snick
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Sandeep Golla
- Department of Radiology and Nuclear Medicine, VU University Medical Center, Amsterdam, The Netherlands
| | - Sjoerd Rijnsdorp
- Department of Medical Physics, Catharina Hospital, Eindhoven, The Netherlands
| | - Daniela Perani
- San Raffaele University and Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy
| | - Klaus L. Leenders
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
| | - Ronald Boellaard
- Department of Nuclear Medicine and Molecular Imaging, University of Groningen, University Medical Center Groningen, Groningen, The Netherlands
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30
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Katako A, Shelton P, Goertzen AL, Levin D, Bybel B, Aljuaid M, Yoon HJ, Kang DY, Kim SM, Lee CS, Ko JH. Machine learning identified an Alzheimer's disease-related FDG-PET pattern which is also expressed in Lewy body dementia and Parkinson's disease dementia. Sci Rep 2018; 8:13236. [PMID: 30185806 PMCID: PMC6125295 DOI: 10.1038/s41598-018-31653-6] [Citation(s) in RCA: 47] [Impact Index Per Article: 7.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2018] [Accepted: 08/23/2018] [Indexed: 01/17/2023] Open
Abstract
Utilizing the publicly available neuroimaging database enabled by Alzheimer's disease Neuroimaging Initiative (ADNI; http://adni.loni.usc.edu/ ), we have compared the performance of automated classification algorithms that differentiate AD vs. normal subjects using Positron Emission Tomography (PET) with fluorodeoxyglucose (FDG). General linear model, scaled subprofile modeling and support vector machines were examined. Among the tested classification methods, support vector machine with Iterative Single Data Algorithm produced the best performance, i.e., sensitivity (0.84) × specificity (0.95), by 10-fold cross-validation. We have applied the same classification algorithm to four different datasets from ADNI, Health Science Centre (Winnipeg, Canada), Dong-A University Hospital (Busan, S. Korea) and Asan Medical Centre (Seoul, S. Korea). Our data analyses confirmed that the support vector machine with Iterative Single Data Algorithm showed the best performance in prediction of future development of AD from the prodromal stage (mild cognitive impairment), and that it was also sensitive to other types of dementia such as Parkinson's Disease Dementia and Dementia with Lewy Bodies, and that perfusion imaging using single photon emission computed tomography may achieve a similar accuracy to that of FDG-PET.
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Affiliation(s)
- Audrey Katako
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre, Winnipeg, Manitoba, Canada
| | - Paul Shelton
- Section of Neurology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Andrew L Goertzen
- Section of Nuclear Medicine, Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Daniel Levin
- Section of Nuclear Medicine, Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Bohdan Bybel
- Section of Nuclear Medicine, Department of Radiology, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada
| | - Maram Aljuaid
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada.,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre, Winnipeg, Manitoba, Canada
| | - Hyun Jin Yoon
- Department of Nuclear Medicine, College of Medicine, Dong-A University, Busan, South Korea
| | - Do Young Kang
- Department of Nuclear Medicine, College of Medicine, Dong-A University, Busan, South Korea
| | - Seok Min Kim
- Institute of Parkinson's Clinical Research, Ulsan University College of Medicine, Seoul, South Korea
| | - Chong Sik Lee
- Institute of Parkinson's Clinical Research, Ulsan University College of Medicine, Seoul, South Korea.,Department of Neurology, Asan Medical Center, Seoul, South Korea
| | - Ji Hyun Ko
- Department of Human Anatomy and Cell Science, Max Rady College of Medicine, Rady Faculty of Health Sciences, University of Manitoba, Winnipeg, Manitoba, Canada. .,Neuroscience Research Program, Kleysen Institute for Advanced Medicine, Health Sciences Centre, Winnipeg, Manitoba, Canada.
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31
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Tomše P, Peng S, Pirtošek Z, Zaletel K, Dhawan V, Eidelberg D, Ma Y, Trošt M. The effects of image reconstruction algorithms on topographic characteristics, diagnostic performance and clinical correlation of metabolic brain networks in Parkinson's disease. Phys Med 2018; 52:104-112. [PMID: 30139598 DOI: 10.1016/j.ejmp.2018.06.637] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 04/19/2018] [Revised: 06/25/2018] [Accepted: 06/27/2018] [Indexed: 12/22/2022] Open
Abstract
PURPOSE The purpose of this study was to evaluate the effects of different image reconstruction algorithms on topographic characteristics and diagnostic performance of the Parkinson's disease related pattern (PDRP). METHODS FDG-PET brain scans of 20 Parkinson's disease (PD) patients and 20 normal controls (NC) were reconstructed with six different algorithms in order to derive six versions of PDRP. Additional scans of 20 PD, 25 atypical parkinsonism (AP) patients and 20 NC subjects were used for validation. PDRP versions were compared by assessing differences in topographies, individual subject scores and correlations with patient's clinical ratings. Discrimination of PD from NC and AP subjects was evaluated across cohorts. RESULTS The region weights of the six PDRPs highly correlated (R ≥ 0.991; p < 0.0001). All PDRPs' expressions were significantly elevated in PD relative to NC and AP subjects (p < 0.0001) and correlated with clinical ratings (R ≥ 0.47; p < 0.05). Subject scores of the six PDRPs highly correlated within each of individual healthy and parkinsonian groups (R ≥ 0.972, p < 0.0001) and were consistent across the algorithms when using the same reconstruction methods in PDRP derivation and validation. However, when derivation and validation reconstruction algorithms differed, subject scores were notably lower compared to the reference PDRP, in all subject groups. CONCLUSION PDRP proves to be highly reproducible across FDG-PET image reconstruction algorithms in topography, ability to differentiate PD from NC and AP subjects and clinical correlation. When calculating PDRP scores in scans that have different reconstruction algorithms and imaging systems from those used for PDRP derivation, a calibration with NC subjects is advisable.
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Affiliation(s)
- Petra Tomše
- Department of Nuclear Medicine, University Medical Centre Ljubljana, Zaloška cesta 7, 1000 Ljubljana, Slovenia.
| | - Shichun Peng
- Center for Neurosciences, The Feinstein Institute for Medical Research, 350 Community Dr, Manhasset, NY 11030, USA.
| | - Zvezdan Pirtošek
- Department of Neurology, University Medical Centre Ljubljana, Zaloška cesta 2, 1000 Ljubljana, Slovenia; Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1104 Ljubljana, Slovenia.
| | - Katja Zaletel
- Department of Nuclear Medicine, University Medical Centre Ljubljana, Zaloška cesta 7, 1000 Ljubljana, Slovenia.
| | - Vijay Dhawan
- Center for Neurosciences, The Feinstein Institute for Medical Research, 350 Community Dr, Manhasset, NY 11030, USA.
| | - David Eidelberg
- Center for Neurosciences, The Feinstein Institute for Medical Research, 350 Community Dr, Manhasset, NY 11030, USA.
| | - Yilong Ma
- Center for Neurosciences, The Feinstein Institute for Medical Research, 350 Community Dr, Manhasset, NY 11030, USA.
| | - Maja Trošt
- Department of Neurology, University Medical Centre Ljubljana, Zaloška cesta 2, 1000 Ljubljana, Slovenia; Department of Nuclear Medicine, University Medical Centre Ljubljana, Zaloška cesta 7, 1000 Ljubljana, Slovenia; Faculty of Medicine, University of Ljubljana, Vrazov trg 2, 1104 Ljubljana, Slovenia.
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Cerami C, Dodich A, Iannaccone S, Magnani G, Santangelo R, Presotto L, Marcone A, Gianolli L, Cappa SF, Perani D. A biomarker study in long-lasting amnestic mild cognitive impairment. ALZHEIMERS RESEARCH & THERAPY 2018; 10:42. [PMID: 29695292 PMCID: PMC5918759 DOI: 10.1186/s13195-018-0369-8] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2017] [Accepted: 03/19/2018] [Indexed: 01/09/2023]
Abstract
Background Mild cognitive impairment (MCI) is a heterogeneous syndrome resulting from Alzheimer’s disease (AD) as well as to non-AD and non-neurodegenerative conditions. A subset of patients with amnestic MCI (aMCI) present with an unusually long-lasting course, a slow rate of clinical neuropsychological progression, and evidence of focal involvement of medial temporal lobe structures. In the present study, we explored positron emission tomography (PET) and cerebrospinal fluid (CSF) biomarkers in a sample of subjects with aMCI with such clinical features in order to provide in vivo evidence to improve disease characterisation in this subgroup. Methods Thirty consecutive subjects with aMCI who had long-lasting memory impairment (more than 4 years from symptom onset) and a very slow rate of cognitive progression were included. All subjects underwent fluorodeoxyglucose-positron emission tomography (FDG-PET) metabolic imaging. A measure of cerebral amyloid load, by PET and/or CSF, was obtained in 26 of 30 subjects. The mean clinical follow-up was 58.3 ± 10.1 months. Results No patient progressed to dementia during the follow-up. The typical AD FDG-PET pattern of temporoparietal hypometabolism was not present in any of the subjects. In contrast, a selective medial temporal lobe hypometabolism was present in all subjects, with an extension to frontolimbic regions in some subjects. PET imaging showed absent or low amyloid load in the majority of samples. The values were well below those reported in prodromal AD, and they were slightly elevated in only two subjects, consistent with the CSF β-amyloid (1–42) protein values. Notably, no amyloid load was present in the hippocampal structures. Conclusions FDG-PET and amyloid-PET together with CSF findings questioned AD pathology as a unique neuropathological substrate in this aMCI subgroup with long-lasting disease course. The possibility of alternative pathological conditions, such as argyrophilic grain disease, primary age-related tauopathy or age-related TDP-43 proteinopathy, known to spread throughout the medial temporal lobe and limbic system structures should be considered in these patients with MCI.
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Affiliation(s)
- Chiara Cerami
- Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy. .,Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy.
| | - Alessandra Dodich
- Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy.,Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Sandro Iannaccone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | | | | | - Luca Presotto
- Nuclear Medicine Department, San Raffaele Hospital, Milan, Italy
| | - Alessandra Marcone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Luigi Gianolli
- Nuclear Medicine Department, San Raffaele Hospital, Milan, Italy
| | - Stefano F Cappa
- NeTS Center, Istituto Universitario di Studi Superiori, Pavia, Italy.,IRCCS S. Giovanni di Dio Fatebenefratelli, Brescia, Italy
| | - Daniela Perani
- Division of Neuroscience, San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Department, San Raffaele Hospital, Milan, Italy.,Università Vita-Salute San Raffaele, Milan, Italy
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Iaccarino L, Chiotis K, Alongi P, Almkvist O, Wall A, Cerami C, Bettinardi V, Gianolli L, Nordberg A, Perani D. A Cross-Validation of FDG- and Amyloid-PET Biomarkers in Mild Cognitive Impairment for the Risk Prediction to Dementia due to Alzheimer's Disease in a Clinical Setting. J Alzheimers Dis 2018; 59:603-614. [PMID: 28671117 DOI: 10.3233/jad-170158] [Citation(s) in RCA: 43] [Impact Index Per Article: 7.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023]
Abstract
Assessments of brain glucose metabolism (18F-FDG-PET) and cerebral amyloid burden (11C-PiB-PET) in mild cognitive impairment (MCI) have shown highly variable performances when adopted to predict progression to dementia due to Alzheimer's disease (ADD). This study investigates, in a clinical setting, the separate and combined values of 18F-FDG-PET and 11C-PiB-PET in ADD conversion prediction with optimized data analysis procedures. Respectively, we investigate the accuracy of an optimized SPM analysis for 18F-FDG-PET and of standardized uptake value ratio semiquantification for 11C-PiB-PET in predicting ADD conversion in 30 MCI subjects (age 63.57±7.78 years). Fourteen subjects converted to ADD during the follow-up (median 26.5 months, inter-quartile range 30 months). Receiver operating characteristic analyses showed an area under the curve (AUC) of 0.89 and of 0.81 for, respectively, 18F-FDG-PET and 11C-PiB-PET. 18F-FDG-PET, compared to 11C-PiB-PET, showed higher specificity (1.00 versus 0.62, respectively), but lower sensitivity (0.79 versus 1.00). Combining the biomarkers improved classification accuracy (AUC = 0.96). During the follow-up time, all the MCI subjects positive for both PET biomarkers converted to ADD, whereas all the subjects negative for both remained stable. The difference in survival distributions was confirmed by a log-rank test (p = 0.002). These results indicate a very high accuracy in predicting MCI to ADD conversion of both 18F-FDG-PET and 11C-PiB-PET imaging, the former showing optimal performance based on the SPM optimized parametric assessment. Measures of brain glucose metabolism and amyloid load represent extremely powerful diagnostic and prognostic biomarkers with complementary roles in prodromal dementia phase, particularly when tailored to individual cases in clinical settings.
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Affiliation(s)
- Leonardo Iaccarino
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Konstantinos Chiotis
- Department of NVS, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden
| | - Pierpaolo Alongi
- Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy.,Department of Radiological Sciences, Nuclear Medicine Unit, San Raffaele G.Giglio Institute, Cefalù, Italy
| | - Ove Almkvist
- Department of NVS, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden.,Department of Psychology, Stockholm University, Stockholm, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Anders Wall
- Department of Surgical Sciences, Radiology, Uppsala University, Uppsala, Sweden.,PET Centre, Uppsala University Hospital, Uppsala, Sweden
| | - Chiara Cerami
- In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Department of Clinical Neurosciences, Neurological Rehabilitation Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | | | - Luigi Gianolli
- Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | - Agneta Nordberg
- Department of NVS, Center for Alzheimer Research, Translational Alzheimer Neurobiology, Karolinska Institutet, Stockholm, Sweden.,Department of Geriatric Medicine, Karolinska University Hospital Huddinge, Stockholm, Sweden
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy.,In Vivo Human Molecular and Structural Neuroimaging Unit, Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy.,Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
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Caminiti SP, Ballarini T, Sala A, Cerami C, Presotto L, Santangelo R, Fallanca F, Vanoli EG, Gianolli L, Iannaccone S, Magnani G, Perani D. FDG-PET and CSF biomarker accuracy in prediction of conversion to different dementias in a large multicentre MCI cohort. Neuroimage Clin 2018; 18:167-177. [PMID: 29387532 PMCID: PMC5790816 DOI: 10.1016/j.nicl.2018.01.019] [Citation(s) in RCA: 91] [Impact Index Per Article: 15.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/31/2017] [Revised: 11/15/2017] [Accepted: 01/18/2018] [Indexed: 01/29/2023]
Abstract
Background/aims In this multicentre study in clinical settings, we assessed the accuracy of optimized procedures for FDG-PET brain metabolism and CSF classifications in predicting or excluding the conversion to Alzheimer's disease (AD) dementia and non-AD dementias. Methods We included 80 MCI subjects with neurological and neuropsychological assessments, FDG-PET scan and CSF measures at entry, all with clinical follow-up. FDG-PET data were analysed with a validated voxel-based SPM method. Resulting single-subject SPM maps were classified by five imaging experts according to the disease-specific patterns, as "typical-AD", "atypical-AD" (i.e. posterior cortical atrophy, asymmetric logopenic AD variant, frontal-AD variant), "non-AD" (i.e. behavioural variant FTD, corticobasal degeneration, semantic variant FTD; dementia with Lewy bodies) or "negative" patterns. To perform the statistical analyses, the individual patterns were grouped either as "AD dementia vs. non-AD dementia (all diseases)" or as "FTD vs. non-FTD (all diseases)". Aβ42, total and phosphorylated Tau CSF-levels were classified dichotomously, and using the Erlangen Score algorithm. Multivariate logistic models tested the prognostic accuracy of FDG-PET-SPM and CSF dichotomous classifications. Accuracy of Erlangen score and Erlangen Score aided by FDG-PET SPM classification was evaluated. Results The multivariate logistic model identified FDG-PET "AD" SPM classification (Expβ = 19.35, 95% C.I. 4.8-77.8, p < 0.001) and CSF Aβ42 (Expβ = 6.5, 95% C.I. 1.64-25.43, p < 0.05) as the best predictors of conversion from MCI to AD dementia. The "FTD" SPM pattern significantly predicted conversion to FTD dementias at follow-up (Expβ = 14, 95% C.I. 3.1-63, p < 0.001). Overall, FDG-PET-SPM classification was the most accurate biomarker, able to correctly differentiate either the MCI subjects who converted to AD or FTD dementias, and those who remained stable or reverted to normal cognition (Expβ = 17.9, 95% C.I. 4.55-70.46, p < 0.001). Conclusions Our results support the relevant role of FDG-PET-SPM classification in predicting progression to different dementia conditions in prodromal MCI phase, and in the exclusion of progression, outperforming CSF biomarkers.
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Key Words
- AD, Alzheimer's disease
- AUC, area under curve
- Alzheimer's disease dementia
- CBD, corticobasal degeneration
- CDR, Clinical Dementia Rating
- CSF, cerebrospinal fluid
- Clinical setting
- DLB, dementia with Lewy bodies
- EANM, European Association of Nuclear Medicine
- Erlangen Score
- FDG, fluorodeoxyglucose
- FTD, frontotemporal dementia
- Frontotemporal dementia
- LR+, positive likelihood ratio
- LR-, negative likelihood ratio
- MCI, mild cognitive impairment
- PET, positron emission tomography
- PSP, progressive supranuclear palsy
- Prognosis
- aMCI, single-domain amnestic mild cognitive impairment
- bvFTD, behavioral variant of frontotemporal dementia
- md aMCI, multi-domain amnestic mild cognitive impairment
- md naMCI, multi-domain non-amnestic mild cognitive impairment
- naMCI, single-domain non-amnestic mild cognitive impairment
- p-tau, phosphorylated tau
- t-tau, total tau
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Affiliation(s)
- Silvia Paola Caminiti
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Tommaso Ballarini
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Arianna Sala
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Chiara Cerami
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Luca Presotto
- Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy
| | - Roberto Santangelo
- Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | | | | | - Luigi Gianolli
- Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy
| | - Sandro Iannaccone
- Clinical Neuroscience Department, San Raffaele Turro Hospital, Milan, Italy
| | - Giuseppe Magnani
- Department of Neurology and INSPE, San Raffaele Scientific Institute, Milan, Italy
| | - Daniela Perani
- Vita-Salute San Raffaele University, Milan, Italy; Division of Neuroscience, IRCCS San Raffaele Scientific Institute, Milan, Italy; Nuclear Medicine Unit, IRCCS San Raffaele Hospital, Milan, Italy.
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