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Peng J, Wang W, Song Q, Hou J, Jin H, Qin X, Yuan Z, Wei Y, Shu Z. 18F-FDG-PET Radiomics Based on White Matter Predicts The Progression of Mild Cognitive Impairment to Alzheimer Disease: A Machine Learning Study. Acad Radiol 2023; 30:1874-1884. [PMID: 36587998 DOI: 10.1016/j.acra.2022.12.033] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/27/2022] [Revised: 12/11/2022] [Accepted: 12/18/2022] [Indexed: 12/31/2022]
Abstract
RATIONALE AND OBJECTIVES To build a model using white-matter radiomics features on positron-emission tomography (PET) and machine learning methods to predict progression from mild cognitive impairment (MCI) to Alzheimer disease (AD). MATERIALS AND METHODS We analyzed the data of 341 MCI patients from the Alzheimer's Disease Neuroimaging Initiative, of whom 102 progressed to AD during an 8-year follow-up. The patients were divided into the training (238 patients) and test groups (103 patients). PET-based radiomics features were extracted from the white matter in the training group, and dimensionally reduced to construct a psychoradiomics signature (PS), which was combined with multimodal data using machine learning methods to construct an integrated model. Model performance was evaluated using receiver operating characteristic curves in the test group. RESULTS Clinical Dementia Rating (CDR) scores, Alzheimer's Disease Assessment Scale (ADAS) scores, and PS independently predicted MCI progression to AD on multivariate logistic regression. The areas under the curve (AUCs) of the CDR, ADAS and PS in the training and test groups were 0.683, 0.755, 0.747 and 0.737, 0.743, 0.719 respectively, and were combined using a support vector machine to construct an integrated model. The AUC of the integrated model in the training and test groups was 0.868 and 0.865, respectively (sensitivity, 0.873 and 0.839, respectively; specificity, 0.784 and 0.806, respectively). The AUCs of the integrated model significantly differed from those of other predictors in both groups (p < 0.05, Delong test). CONCLUSION Our psych radiomics signature based on white-matter PET data predicted MCI progression to AD. The integrated model built using multimodal data and machine learning identified MCI patients at a high risk of progression to AD.
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Affiliation(s)
- Jiaxuan Peng
- Jinzhou medical university, Jinzhou, Liaoning Province, China
| | - Wei Wang
- Department of Radiology, The First Affiliated Hospital of Chongqing Medical and Pharmaceutical College, Chongqin, China
| | - Qiaowei Song
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China
| | - Jie Hou
- Jinzhou medical university, Jinzhou, Liaoning Province, China
| | - Hui Jin
- Bengbu medical college, Bengbu, China
| | - Xue Qin
- Bengbu medical college, Bengbu, China
| | - Zhongyu Yuan
- Jinzhou medical university, Jinzhou, Liaoning Province, China
| | - Yuguo Wei
- Department of Pharmaceuticals Diagnosis, GE Healthcare, Hangzhou, China
| | - Zhenyu Shu
- Center for Rehabilitation Medicine, Department of Radiology, Zhejiang Provincial People's Hospital, Affiliated People's Hospital, Hangzhou Medical College, Hangzhou, Zhejiang, China.
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2
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Fu JF, Lois C, Sanchez J, Becker JA, Rubinstein ZB, Thibault E, Salvatore AN, Sari H, Farrell ME, Guehl NJ, Normandin MD, Fakhri GE, Johnson KA, Price JC. Kinetic evaluation and assessment of longitudinal changes in reference region and extracerebral [ 18F]MK-6240 PET uptake. J Cereb Blood Flow Metab 2023; 43:581-594. [PMID: 36420769 PMCID: PMC10063833 DOI: 10.1177/0271678x221142139] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/19/2022] [Revised: 10/17/2022] [Accepted: 11/06/2022] [Indexed: 11/25/2022]
Abstract
[18F]MK-6240 meningeal/extracerebral off-target binding may impact tau quantification. We examined the kinetics and longitudinal changes of extracerebral and reference regions. [18F]MK-6240 PET was performed in 24 cognitively-normal and eight cognitively-impaired subjects, with arterial samples in 13 subjects. Follow-up scans at 6.1 ± 0.5 (n = 25) and 13.3 ± 0.9 (n = 16) months were acquired. Extracerebral and reference region (cerebellar gray matter (CerGM)-based, cerebral white matter (WM), pons) uptake were evaluated using standardized uptake values (SUV90-110), spectral analysis, and distribution volume. Longitudinal changes in SUV90-110 were examined. The impact of reference region on target region outcomes, partial volume correction (PVC) and regional erosion were evaluated. Eroded WM and pons showed lower variability, lower extracerebral contamination, and lower longitudinal changes than CerGM-based regions. CerGM-based regions resulted larger cross-sectional effect sizes for group differentiation. Extracerebral signal was high in 50% of subjects and exhibited irreversible kinetics and nonsignificant longitudinal changes over one-year but was highly variable at subject-level. PVC resulted in higher variability in reference region uptake and longitudinal changes. Our results suggest that eroded CerGM may be preferred for cross-sectional, whilst eroded WM or pons may be preferred for longitudinal [18F]MK-6240 studies. For CerGM, erosion was necessary (preferred over PVC) to address the heterogenous nature of extracerebral signal.
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Affiliation(s)
- Jessie Fanglu Fu
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | - Cristina Lois
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Justin Sanchez
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - J Alex Becker
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Zoe B Rubinstein
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Emma Thibault
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Andrew N Salvatore
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
| | - Hasan Sari
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
| | | | - Nicolas J Guehl
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Marc D Normandin
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Georges El Fakhri
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Keith A Johnson
- Harvard Medical School, Department of Radiology, Boston, MA, USA
- Gordon Center for Medical Imaging, Massachusetts General Hospital, Boston, MA, USA
| | - Julie C Price
- Athinoula A. Martinos Center for Biomedical Imaging, Massachusetts General Hospital, Charlestown, MA, USA
- Harvard Medical School, Department of Radiology, Boston, MA, USA
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3
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Smith AM, Obuchowski NA, Foster NL, Klein G, Mozley PD, Lammertsma AA, Wahl RL, Sunderland JJ, Vanderheyden JL, Benzinger TLS, Kinahan PE, Wong DF, Perlman ES, Minoshima S, Matthews D. The RSNA QIBA Profile for Amyloid PET as an Imaging Biomarker for Cerebral Amyloid Quantification. J Nucl Med 2023; 64:294-303. [PMID: 36137760 PMCID: PMC9902844 DOI: 10.2967/jnumed.122.264031] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/16/2022] [Revised: 08/05/2022] [Accepted: 08/05/2022] [Indexed: 02/04/2023] Open
Abstract
A standardized approach to acquiring amyloid PET images increases their value as disease and drug response biomarkers. Most 18F PET amyloid brain scans often are assessed only visually (per regulatory labels), with a binary decision indicating the presence or absence of Alzheimer disease amyloid pathology. Minimizing technical variance allows precise, quantitative SUV ratios (SUVRs) for early detection of β-amyloid plaques and allows the effectiveness of antiamyloid treatments to be assessed with serial studies. Methods: The Quantitative Imaging Biomarkers Alliance amyloid PET biomarker committee developed and validated a profile to characterize and reduce the variability of SUVRs, increasing statistical power for these assessments. Results: On achieving conformance, sites can justify a claim that brain amyloid burden reflected by the SUVR is measurable to a within-subject coefficient of variation of no more than 1.94% when the same radiopharmaceutical, scanner, acquisition, and analysis protocols are used. Conclusion: This overview explains the claim, requirements, barriers, and potential future developments of the profile to achieve precision in clinical and research amyloid PET imaging.
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Affiliation(s)
- Anne M Smith
- Siemens Medical Solutions USA, Inc., Knoxville, Tennessee;
| | | | - Norman L Foster
- Department of Neurology, University of Utah, Salt Lake City, Utah
| | | | - P David Mozley
- Weill Medical College of Cornell University, New York, New York
| | - Adriaan A Lammertsma
- Amsterdam Department of Radiology and Nuclear Medicine, Amsterdam University Medical Centers, Location VUmc, Amsterdam, The Netherlands
- Medical Imaging Center, Department of Nuclear Medicine and Molecular Imaging, University Medical Center Groningen, University of Groningen, Groningen, The Netherlands
| | - Richard L Wahl
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
- Department of Radiation Oncology, Washington University in Saint Louis, St. Louis, Missouri
| | - John J Sunderland
- Division of Nuclear Medicine, Department of Radiology, University of Iowa, Iowa City, Iowa
| | | | - Tammie L S Benzinger
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
- Department of Radiation Oncology, Washington University in Saint Louis, St. Louis, Missouri
| | - Paul E Kinahan
- Department of Radiology, School of Medicine, University of Washington, Seattle, Washington
| | - Dean F Wong
- Mallinckrodt Institute of Radiology, Washington University School of Medicine, St. Louis, Missouri
| | | | - Satoshi Minoshima
- Department of Radiology and Imaging Sciences, University of Utah, Salt Lake City, Utah; and
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Luckett ES, Schaeverbeke J, De Meyer S, Adamczuk K, Van Laere K, Dupont P, Vandenberghe R. Longitudinal changes in 18F-Flutemetamol amyloid load in cognitively intact APOE4 carriers versus noncarriers: Methodological considerations. Neuroimage Clin 2023; 37:103321. [PMID: 36621019 PMCID: PMC9850036 DOI: 10.1016/j.nicl.2023.103321] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/23/2022] [Revised: 12/12/2022] [Accepted: 01/04/2023] [Indexed: 01/07/2023]
Abstract
PURPOSE Measuring longitudinal changes in amyloid load in the asymptomatic stage of Alzheimer's disease is of high relevance for clinical research and progress towards more efficacious, timely treatments. Apolipoprotein E ε4 (APOE4) has a well-established effect on the rate of amyloid accumulation. Here we investigated which region of interest and which reference region perform best at detecting the effect of APOE4 on longitudinal amyloid load in individuals participating in the Flemish Prevent Alzheimer's Disease Cohort KU Leuven (F-PACK). METHODS Ninety cognitively intact F-PACK participants (baseline age: 68 (52-80) years, 46 males, 42 APOE4 carriers) received structural MRI and 18F-Flutemetamol PET scans at baseline and follow-up (6.2 (3.4-10.9) year interval). Standardised uptake value ratios (SUVRs) and Centiloids (CLs) were calculated in a composite cortical volume of interest (SUVRcomp/CL) and in the precuneus (SUVRprec), and amyloid rate of change derived: (follow-up amyloid load - baseline amyloid load) / time interval (years). Four reference regions were used to derive amyloid load: whole cerebellum, cerebellar grey matter, eroded subcortical white matter, and pons. RESULTS When using whole cerebellum or cerebellar grey matter as reference region, APOE4 carriers had a significantly higher SUVRcomp amyloid rate of change than non-carriers (pcorr = 0.004, t = 3.40 (CI 0.005-0.018); pcorr = 0.036, t = 2.66 (CI 0.003-0.018), respectively). Significance was not observed for eroded subcortical white matter or pons (pcorr = 0.144, t = 2.13 (CI 0.0003-0.008); pcorr = 0.116, t = 2.22 (CI 0.005-0.010), respectively). When using CLs as the amyloid measurement, and whole cerebellum, APOE4 carriers had a higher amyloid rate of change than non-carriers (pcorr = 0.012, t = 3.05 (CI 0.499-2.359)). Significance was not observed for the other reference regions. No significance was observed with any of the reference regions and amyloid rate of change in the precuneus (SUVRprec). CONCLUSION In this cognitively intact cohort, a composite neocortical volume of interest together with whole cerebellum or cerebellar grey matter as reference region are the methods of choice for detecting APOE4-dependent differences in amyloid rate of change.
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Affiliation(s)
- Emma S Luckett
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium; Alzheimer Research Centre KU Leuven, Leuven Brain Institute, Leuven, Belgium
| | - Jolien Schaeverbeke
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium; Alzheimer Research Centre KU Leuven, Leuven Brain Institute, Leuven, Belgium
| | - Steffi De Meyer
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium; Alzheimer Research Centre KU Leuven, Leuven Brain Institute, Leuven, Belgium; Laboratory for Molecular Neurobiomarker Research, KU Leuven, Leuven, Belgium
| | | | - Koen Van Laere
- Division of Nuclear Medicine, UZ Leuven, Leuven, Belgium; Nuclear Medicine and Molecular Imaging, Department of Imaging and Pathology, KU Leuven, Leuven, Belgium
| | - Patrick Dupont
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium; Alzheimer Research Centre KU Leuven, Leuven Brain Institute, Leuven, Belgium
| | - Rik Vandenberghe
- Laboratory for Cognitive Neurology, Department of Neurosciences, Leuven Brain Institute, KU Leuven, Leuven, Belgium; Alzheimer Research Centre KU Leuven, Leuven Brain Institute, Leuven, Belgium; Neurology Department, University Hospitals Leuven, Leuven, Belgium.
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LaPoint MR, Baker SL, Landau SM, Harrison TM, Jagust WJ. Rates of β-amyloid deposition indicate widespread simultaneous accumulation throughout the brain. Neurobiol Aging 2022; 115:1-11. [PMID: 35447369 PMCID: PMC9986974 DOI: 10.1016/j.neurobiolaging.2022.03.005] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2021] [Revised: 02/10/2022] [Accepted: 03/07/2022] [Indexed: 11/18/2022]
Abstract
Amyloid plaque aggregation is a pathologic hallmark of Alzheimer's disease (AD) that occurs early in the disease. However, little is known about its progression throughout the brain. Using Pittsburgh Compound B (PIB)-PET imaging, we investigated the progression of regional amyloid accumulation in cognitively normal older adults. We found that all examined regions reached their peak accumulation rates 24-28 years after an estimated initiation corresponding to the mean baseline PIB-PET signal in amyloid-negative older adults. We also investigated the effect of increased genetic risk conferred by the apolipoprotein-E ɛ4 allele on rates of amyloid accumulation, as well as the relationship between regional amyloid accumulation and regional tau pathology, another hallmark of AD, measured with Flortaucipir-PET. Carriers of the ɛ4 allele had faster amyloid accumulation in all brain regions. Furthermore, in all regions excluding the temporal lobe, faster amyloid accumulation was associated with greater tau burden. These results indicate that amyloid accumulates near-simultaneously throughout the brain and is associated with higher AD pathology, and that genetic risk of AD is associated with faster amyloid accumulation.
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Affiliation(s)
- Molly R LaPoint
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA.
| | - Suzanne L Baker
- Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, CA 94720, USA
| | - Susan M Landau
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, CA 94720, USA
| | - Theresa M Harrison
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA
| | - William J Jagust
- Helen Wills Neuroscience Institute, University of California Berkeley, Berkeley, CA 94720, USA; Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Laboratory, CA 94720, USA
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6
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Li Y, Ng YL, Paranjpe MD, Ge Q, Gu F, Li P, Yan S, Lu J, Wang X, Zhou Y. Tracer-specific reference tissues selection improves detection of 18 F-FDG, 18 F-florbetapir, and 18 F-flortaucipir PET SUVR changes in Alzheimer's disease. Hum Brain Mapp 2022; 43:2121-2133. [PMID: 35165964 PMCID: PMC8996354 DOI: 10.1002/hbm.25774] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2021] [Revised: 12/17/2021] [Accepted: 12/30/2021] [Indexed: 01/05/2023] Open
Abstract
This study sought to identify a reference tissue‐based quantification approach for improving the statistical power in detecting changes in brain glucose metabolism, amyloid, and tau deposition in Alzheimer's disease studies. A total of 794, 906, and 903 scans were included for 18F‐FDG, 18F‐florbetapir, and 18F‐flortaucipir, respectively. Positron emission tomography (PET) and T1‐weighted images of participants were collected from the Alzheimer's disease Neuroimaging Initiative database, followed by partial volume correction. The standardized uptake value ratios (SUVRs) calculated from the cerebellum gray matter, centrum semiovale, and pons were evaluated at both region of interest (ROI) and voxelwise levels. The statistical power of reference tissues in detecting longitudinal SUVR changes was assessed via paired t‐test. In cross‐sectional analysis, the impact of reference tissue‐based SUVR differences between cognitively normal and cognitively impaired groups was evaluated by effect sizes Cohen's d and two sample t‐test adjusted by age, sex, and education levels. The average ROI t values of pons were 86.62 and 38.40% higher than that of centrum semiovale and cerebellum gray matter in detecting glucose metabolism decreases, while the centrum semiovale reference tissue‐based SUVR provided higher t values for the detection of amyloid and tau deposition increases. The three reference tissues generated comparable d images for 18F‐FDG, 18F‐florbetapir, and 18F‐flortaucipir and comparable t maps for 18F‐florbetapir and 18F‐flortaucipir, but pons‐based t map showed superior performance in 18F‐FDG. In conclusion, the tracer‐specific reference tissue improved the detection of 18F‐FDG, 18F‐florbetapir, and 18F‐flortaucipir PET SUVR changes, which helps the early diagnosis, monitoring of disease progression, and therapeutic response in Alzheimer's disease.
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Affiliation(s)
- Yanxiao Li
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China.,School of Computer Science, The University of Sydney, Sydney, New South Wales, Australia
| | - Yee Ling Ng
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China
| | - Manish D Paranjpe
- Harvard-MIT Health Sciences and Technology Program, Harvard Medical School, Boston, Massachusetts, USA
| | - Qi Ge
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China
| | - Fengyun Gu
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China.,Department of Statistics, University College Cork, Cork, Ireland
| | - Panlong Li
- School of Electrical and Information Engineering, Zhengzhou University of Light Industry, Zhengzhou, Henan, China
| | - Shaozhen Yan
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Jie Lu
- Department of Radiology and Nuclear Medicine, Xuanwu Hospital, Capital Medical University, Beijing, China
| | - Xiuying Wang
- School of Computer Science, The University of Sydney, Sydney, New South Wales, Australia
| | - Yun Zhou
- Central Research Institute, United Imaging Healthcare Group Co., Ltd, Shanghai, China
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7
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Qin Q, Fu L, Wang R, Lyu J, Ma H, Zhan M, Zhou A, Wang F, Zuo X, Wei C. Prominent Striatum Amyloid Retention in Early-Onset Familial Alzheimer's Disease With PSEN1 Mutations: A Pilot PET/MR Study. Front Aging Neurosci 2021; 13:732159. [PMID: 34603009 PMCID: PMC8480470 DOI: 10.3389/fnagi.2021.732159] [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: 06/28/2021] [Accepted: 08/13/2021] [Indexed: 11/17/2022] Open
Abstract
Background: With the advancements of amyloid imaging in recent years, this new imaging diagnostic method has aroused great interest from researchers. Till now, little is known regarding amyloid deposition specialty in patients with early-onset familial Alzheimer's disease (EOFAD), and even less is known about its role in cognitive impairments. Objectives: Our study aimed to evaluate the amyloid deposition in five patients with EOFAD, 15 patients with late-onset sporadic AD, and 12 healthy subjects utilizing 11C-labeled Pittsburgh compound-B (11C-PiB) amyloid PET imaging. Moreover, we figured out the correlation between striatal and cortical standardized uptake value ratios (SUVRs). We also investigated the correlation between 11C-PiB retention and cognitive presentation. Results: All patients with EOFAD showed high amyloid deposition in the striatum, a pattern that is not usually seen in patients with late-onset sporadic AD. The SUVR in the striatum, especially in the amygdala, showed significant correlations with cortex SUVR in EOFAD. However, neither striatal nor cortical 11C-PiB retention was related to cognitive decline. Conclusions: The amyloid distribution in patients with EOFAD differs from late-onset sporadic AD, with higher amyloid deposits in the striatum. Our study also demonstrated positive correlations in 11C-PiB retention between the striatum and other cortical areas. We revealed that the distribution of amyloid in the brain is not random but diffuses following the functional and anatomical connections. However, the degree and pattern of amyloid deposition were not correlated with cognitive deficits.
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Affiliation(s)
- Qi Qin
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Liping Fu
- Department of Nuclear Medicine, China-Japan Friendship Hospital, Beijing, China.,Department of Nuclear Medicine, The First Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Ruimin Wang
- Department of Nuclear Medicine, The First Medical Center, Chinese People's Liberation Army General Hospital, Beijing, China
| | - Jihui Lyu
- Center for Cognitive Disorders, Beijing Geriatric Hospital, Beijing, China
| | - Huixuan Ma
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Minmin Zhan
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Aihong Zhou
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Fen Wang
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Xiumei Zuo
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
| | - Cuibai Wei
- Innovation Center for Neurological Disorders and Department of Neurology, Xuanwu Hospital, National Clinical Research Center for Geriatric Diseases, Capital Medical University, Beijing, China.,Center of Alzheimer's Disease, Beijing Institute for Brain Disorders, Beijing, China.,Beijing Key Laboratory of Geriatric Cognitive Disorders, Beijing, China.,Neurodegenerative Laboratory of Ministry of Education of the People's Republic of China, Beijing, China
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A 4-Year Follow-Up of Subjects with Visually Equivocal Amyloid Positron Emission Tomography Findings from the Alzheimer's Disease Neuroimaging Initiative Cohort. Nucl Med Mol Imaging 2021; 55:71-78. [PMID: 33968273 DOI: 10.1007/s13139-021-00690-x] [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: 10/30/2020] [Revised: 01/30/2021] [Accepted: 02/16/2021] [Indexed: 10/22/2022] Open
Abstract
Background To date, the clinical significance of visually equivocal amyloid positron emission tomography (PET) has not been well established. Objective We studied the clinical significance of equivocal amyloid PET images from the Alzheimer's Disease Neuroimaging Initiative (ADNI). Methods Subjects with F-18 florbetapir PET scans at baseline who were followed up for 4 years were selected. Clinical characteristics, imaging biomarkers, cognitive function, and rate of conversion to AD were compared in subjects with visually equivocal findings. Results Of 249 subjects who completed the follow-up, 153 (61.4%), 20 (8.0%), and 129 (30.5%) were F-18 florbetapir-negative, -equivocal, and -positive, respectively. The mean standardized uptake value ratios (SUVR) of F-18 florbetapir PET were 0.75 ± 0.04, 0.85 ± 0.10, and 1.00 ± 0.09 for each group (p <0.001 between groups), and 15.0%, 70.0%, and 98.7% of patients were quantitatively above the positive threshold. The change in the SUVR of F-18 florbetapir PET was higher in the equivocal (6.09 ± 3.61%, p <0.001) and positive (3.13 ± 4.38%, p <0.001) groups than the negative group (0.88 ± 4.28%). Among the subjects with normal or subjective memory impairment and mild cognitive impairment, 5.3% with negative amyloid PET and 37.5% with positive amyloid PET converted to AD over the 4-year period. None of the equivocal amyloid PET subjects converted to AD during this period. Conclusion Approximately 8% of subjects from the ADNI cohort showed visually equivocal amyloid PET scans with intermediate load and rapid accumulation of amyloid, but did not convert to AD during the 4-year follow-up.
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9
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de Vries BM, Timmers T, Wolters EE, Ossenkoppele R, Verfaillie SCJ, Schuit RC, Scheltens P, van der Flier WM, Windhorst AD, van Berckel BNM, Boellaard R, Golla SSV. Non-invasive Standardised Uptake Value for Verification of the Use of Previously Validated Reference Region for [ 18F]Flortaucipir and [ 18F]Florbetapir Brain PET Studies. Mol Imaging Biol 2021; 23:550-559. [PMID: 33443720 PMCID: PMC8277631 DOI: 10.1007/s11307-020-01572-y] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/22/2020] [Revised: 11/20/2020] [Accepted: 12/16/2020] [Indexed: 11/24/2022]
Abstract
Purpose The simplified reference tissue model (SRTM) is commonly applied for the quantification of brain positron emission tomography (PET) studies, particularly because it avoids arterial cannulation. SRTM requires a validated reference region which is obtained by baseline-blocking or displacement studies. Once a reference region is validated, the use should be verified for each new subject. This verification normally requires volume of distribution (VT) of a reference region. However, performing dynamic scanning and arterial sampling is not always possible, specifically in elderly subjects and in advanced disease stages. The aim of this study was to investigate the use of non-invasive standardised uptake value (SUV) approaches, in comparison to VT, as a verification of the previously validated grey matter cerebellum reference region for [18F]flortaucipir and [18F]florbetapir PET imaging in Alzheimer’s disease (AD) patients and controls. Procedures Dynamic 130-min [18F]flortaucipir PET scans obtained from nineteen subjects (10 AD patients) and 90-min [18F]florbetapir dynamic scans obtained from fourteen subjects (8 AD patients) were included. Regional VT’s were estimated for both tracers and were considered the standard verification of the previously validated reference region. Non-invasive SUVs corrected for body weight (SUVBW), lean body mass (SUL), and body surface area (SUVBSA) were obtained by using later time intervals of the dynamic scans. Simulations were also performed to assess the effect of flow and specific binding (BPND) on the SUVs. Results A low SUV corresponded well with a low VT for both [18F]flortaucipir and [18F]florbetapir. Simulation confirmed that SUVs were only slightly affected by flow changes and that increases in SUV were predominantly determined by the presence of specific binding. Conclusions In situations where dynamic scanning and arterial sampling is not possible, a low SUV(80–100 min) for [18F]flortaucipir and a low SUV(50–70 min) for [18F]florbetapir may be used as indication for absence of specific binding in the grey matter cerebellum reference region. Supplementary Information The online version contains supplementary material available at 10.1007/s11307-020-01572-y.
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Affiliation(s)
- Bart M de Vries
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Tessa Timmers
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.,Alzheimer Center and Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Emma E Wolters
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.,Alzheimer Center and Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Rik Ossenkoppele
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.,Alzheimer Center and Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Sander C J Verfaillie
- Alzheimer Center and Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Robert C Schuit
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Philip Scheltens
- Alzheimer Center and Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Wiesje M van der Flier
- Alzheimer Center and Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.,Epidemiology & Biostatistics, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Albert D Windhorst
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Bart N M van Berckel
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.,Alzheimer Center and Department of Neurology, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Ronald Boellaard
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands
| | - Sandeep S V Golla
- Radiology and Nuclear Medicine, Amsterdam UMC, Vrije Universiteit Amsterdam, De Boelelaan 1117, Amsterdam, The Netherlands.
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10
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Hobson BA, Rowland DJ, Sisó S, Guignet MA, Harmany ZT, Bandara SB, Saito N, Harvey DJ, Bruun DA, Garbow JR, Chaudhari AJ, Lein PJ. TSPO PET Using [18F]PBR111 Reveals Persistent Neuroinflammation Following Acute Diisopropylfluorophosphate Intoxication in the Rat. Toxicol Sci 2020; 170:330-344. [PMID: 31087103 DOI: 10.1093/toxsci/kfz096] [Citation(s) in RCA: 17] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/17/2023] Open
Abstract
Acute intoxication with organophosphates (OPs) can trigger status epilepticus followed by persistent cognitive impairment and/or electroencephalographic abnormalities. Neuroinflammation is widely posited to influence these persistent neurological consequences. However, testing this hypothesis has been challenging, in part because traditional biometrics preclude longitudinal measures of neuroinflammation within the same animal. Therefore, we evaluated the performance of noninvasive positron emission tomography (PET), using the translocator protein (TSPO) radioligand [18F]PBR111 against classic histopathologic measures of neuroinflammation in a preclinical model of acute intoxication with the OP diisopropylfluorophosphate (DFP). Adult male Sprague Dawley rats administered pyridostigmine bromide (0.1 mg/kg, im) 30 min prior to administration of DFP (4 mg/kg, sc), atropine sulfate (2 mg/kg, im) and 2-pralidoxime (25 mg/kg, im) exhibited moderate-to-severe seizure behavior. TSPO PET performed prior to DFP exposure and at 3, 7, 14, 21, and 28 days postexposure revealed distinct lesions, as defined by increased standardized uptake values (SUV). Increased SUV showed high spatial correspondence to immunohistochemical evidence of neuroinflammation, which was corroborated by cytokine gene and protein expression. Regional SUV metrics varied spatiotemporally with days postexposure and correlated with the degree of neuroinflammation detected immunohistochemically. Furthermore, SUV metrics were highly correlated with seizure severity, suggesting that early termination of OP-induced seizures may be critical for attenuating subsequent neuroinflammatory responses. Normalization of SUV values to a cerebellar reference region improved correlations to all outcome measures and seizure severity. Collectively, these results establish TSPO PET using [18F]PBR111 as a robust, noninvasive tool for longitudinal monitoring of neuroinflammation following acute OP intoxication.
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Affiliation(s)
- Brad A Hobson
- Department of Radiology, University of California Davis School of Medicine, Sacramento, California 95817
| | - Douglas J Rowland
- Center for Molecular and Genomic Imaging, Department of Biomedical Engineering, University of California Davis College of Engineering, Davis, California 95616
| | - Sílvia Sisó
- Department of Pathology, Microbiology and Immunology
| | - Michelle A Guignet
- Department of Molecular Biosciences, University of California Davis School of Veterinary Medicine, Davis, California 95616
| | - Zachary T Harmany
- Center for Molecular and Genomic Imaging, Department of Biomedical Engineering, University of California Davis College of Engineering, Davis, California 95616
| | - Suren B Bandara
- Department of Molecular Biosciences, University of California Davis School of Veterinary Medicine, Davis, California 95616
| | - Naomi Saito
- Department of Public Health Sciences, University of California Davis School of Medicine, Davis, California 95616
| | - Danielle J Harvey
- Department of Public Health Sciences, University of California Davis School of Medicine, Davis, California 95616
| | - Donald A Bruun
- Department of Molecular Biosciences, University of California Davis School of Veterinary Medicine, Davis, California 95616
| | - Joel R Garbow
- Department of Radiology, Washington University in St. Louis, St. Louis, Missouri 63110
| | - Abhijit J Chaudhari
- Department of Radiology, University of California Davis School of Medicine, Sacramento, California 95817.,Center for Molecular and Genomic Imaging, Department of Biomedical Engineering, University of California Davis College of Engineering, Davis, California 95616
| | - Pamela J Lein
- Department of Molecular Biosciences, University of California Davis School of Veterinary Medicine, Davis, California 95616
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11
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Beyer L, Brendel M, Scheiwein F, Sauerbeck J, Hosakawa C, Alberts I, Shi K, Bartenstein P, Ishii K, Seibyl J, Cumming P, Rominger A. Improved Risk Stratification for Progression from Mild Cognitive Impairment to Alzheimer's Disease with a Multi-Analytical Evaluation of Amyloid-β Positron Emission Tomography. J Alzheimers Dis 2020; 74:101-112. [PMID: 31985461 DOI: 10.3233/jad-190818] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND Amyloid-β (Aβ) accumulation in brain of patients with suspected Alzheimer's disease (AD) can be assessed by positron emission tomography (PET) in vivo. While visual classification prevails in the clinical routine, semiquantitative PET analyses may enable more reliable evaluation of cases with a visually uncertain, borderline Aβ accumulation. OBJECTIVE We evaluated different analysis approaches (visual/semiquantitative) to find the most accurate and sensitive interpretation of Aβ-PET for predicting risk of progression from mild cognitive impairment (MCI) to AD. METHODS Based on standard uptake value (SUV) ratios of a cortical-composite volume of interest of 18F-AV45-PET from MCI subjects (n = 396, ADNI database), we compared three different reference region (cerebellar grey matter, CBL; brainstem, BST; white matter, WM) normalizations and the visual read by receiver operator characteristics for calculating a hazard ratio (HR) for progression to Alzheimer's disease dementia (ADD). RESULTS During a mean follow-up time of 45.6±13.0 months, 28% of the MCI cases (110/396) converted to ADD. Among the tested methods, the WM reference showed best discriminatory power and progression-risk stratification (HRWM of 4.4 [2.6-7.6]), but the combined results of the visual and semiquantitative analysis with all three reference regions showed an even higher discriminatory power. CONCLUSION A multi-analytical composite of visual and semiquantitative reference tissue analyses of 18F-AV45-PET gave improved risk stratification for progression from MCI to ADD relative to performance of single read-outs. This optimized approach is of special interest for prospective treatment trials, which demand a high accuracy.
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Affiliation(s)
- Leonie Beyer
- Department of Nuclear Medicine, University Hospital of Munich, LMU, Munich, Germany
| | - Matthias Brendel
- Department of Nuclear Medicine, University Hospital of Munich, LMU, Munich, Germany
| | - Franziska Scheiwein
- Department of Nuclear Medicine, University Hospital of Munich, LMU, Munich, Germany
| | - Julia Sauerbeck
- Department of Nuclear Medicine, University Hospital of Munich, LMU, Munich, Germany
| | - Chisa Hosakawa
- Department of Radiology, Kindai University, Osaka, Japan
| | - Ian Alberts
- Department of Nuclear Medicine, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Kuangyu Shi
- Department of Nuclear Medicine, Inselspital, University Hospital Bern, Bern, Switzerland
| | - Peter Bartenstein
- Department of Nuclear Medicine, University Hospital of Munich, LMU, Munich, Germany
| | - Kazunari Ishii
- Department of Radiology, Kindai University, Osaka, Japan
| | | | - Paul Cumming
- Department of Nuclear Medicine, Inselspital, University Hospital Bern, Bern, Switzerland.,School of Psychology and Counseling and IHBI, Queensland University of Technology, Brisbane, Australia
| | - Axel Rominger
- Department of Nuclear Medicine, Inselspital, University Hospital Bern, Bern, Switzerland
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12
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López-González FJ, Moscoso A, Efthimiou N, Fernández-Ferreiro A, Piñeiro-Fiel M, Archibald SJ, Aguiar P, Silva-Rodríguez J. Spill-in counts in the quantification of 18F-florbetapir on Aβ-negative subjects: the effect of including white matter in the reference region. EJNMMI Phys 2019; 6:27. [PMID: 31858289 PMCID: PMC6923310 DOI: 10.1186/s40658-019-0258-7] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2019] [Accepted: 10/25/2019] [Indexed: 12/17/2022] Open
Abstract
Background We aim to provide a systematic study of the impact of white matter (WM) spill-in on the calculation of standardized uptake value ratios (SUVRs) on Aβ-negative subjects, and we study the effect of including WM in the reference region as a compensation. In addition, different partial volume correction (PVC) methods are applied and evaluated. Methods We evaluated magnetic resonance imaging and 18F-AV-45 positron emission tomography data from 122 cognitively normal (CN) patients recruited at the Alzheimer’s Disease Neuroimaging Initiative (ADNI). Cortex SUVRs were obtained by using the cerebellar grey matter (CGM) (SUVRCGM) and the whole cerebellum (SUVRWC) as reference regions. The correlations between the different SUVRs and the WM uptake (WM-SUVRCGM) were studied in patients, and in a well-controlled framework based on Monte Carlo (MC) simulation. Activity maps for the MC simulation were derived from ADNI patients by using a voxel-wise iterative process (BrainViset). Ten WM uptakes covering the spectrum of WM values obtained from patient data were simulated for different patients. Three different PVC methods were tested (a) the regional voxel-based (RBV), (b) the iterative Yang (iY), and (c) a simplified analytical correction derived from our MC simulation. Results WM-SUVRCGM followed a normal distribution with an average of 1.79 and a standard deviation of 0.243 (13.6%). SUVRCGM was linearly correlated to WM-SUVRCGM (r = 0.82, linear fit slope = 0.28). SUVRWC was linearly correlated to WM-SUVRCGM (r = 0.64, linear fit slope = 0.13). Our MC results showed that these correlations are compatible with those produced by isolated spill-in effect (slopes of 0.23 and 0.11). The impact of the spill-in was mitigated by using PVC for SUVRCGM (slopes of 0.06 and 0.07 for iY and RBV), while SUVRWC showed a negative correlation with SUVRCGM after PVC. The proposed analytical correction also reduced the observed correlations when applied to patient data (r = 0.27 for SUVRCGM, r = 0.18 for SUVRWC). Conclusions There is a high correlation between WM uptake and the measured SUVR due to spill-in effect, and that this effect is reduced when including WM in the reference region. We also evaluated the performance of PVC, and we proposed an analytical correction that can be applied to preprocessed data.
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Affiliation(s)
- Francisco Javier López-González
- Molecular Imaging and Medical Physics Group, Radiology Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain
| | - Alexis Moscoso
- Nuclear Medicine Department and Molecular Imaging Research Group, University Hospital (SERGAS) and Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain
| | - Nikos Efthimiou
- PET Research Centre, Faculty of Health Sciences, University of Hull, Hull, UK
| | - Anxo Fernández-Ferreiro
- Pharmacy Department and Pharmacology Group, University Hospital (SERGAS) and Health Research Institute Santiago Compostela (IDIS), Santiago de Compostela, Galicia, Spain
| | - Manuel Piñeiro-Fiel
- Molecular Imaging and Medical Physics Group, Radiology Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain
| | - Stephen J Archibald
- PET Research Centre, Faculty of Health Sciences, University of Hull, Hull, UK
| | - Pablo Aguiar
- Molecular Imaging and Medical Physics Group, Radiology Department, Faculty of Medicine, Universidade de Santiago de Compostela, Galicia, Spain. .,Nuclear Medicine Department and Molecular Imaging Research Group, University Hospital (SERGAS) and Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain.
| | - Jesús Silva-Rodríguez
- Nuclear Medicine Department and Molecular Imaging Research Group, University Hospital (SERGAS) and Health Research Institute of Santiago de Compostela (IDIS), Santiago de Compostela, Galicia, Spain.,R&D Department, Qubiotech Health Intelligence SL, A Coruña, Galicia, Spain
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13
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Liu YS, Yan WJ, Tan CC, Li JQ, Xu W, Cao XP, Tan L, Yu JT. Common Variant in TREM1 Influencing Brain Amyloid Deposition in Mild Cognitive Impairment and Alzheimer’s Disease. Neurotox Res 2019; 37:661-668. [DOI: 10.1007/s12640-019-00105-y] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/31/2019] [Revised: 08/28/2019] [Accepted: 09/02/2019] [Indexed: 10/25/2022]
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14
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Kameyama M, Ishibash K, Wagatsuma K, Toyohara J, Ishii K. A pitfall of white matter reference regions used in [18F] florbetapir PET: a consideration of kinetics. Ann Nucl Med 2019; 33:848-854. [DOI: 10.1007/s12149-019-01397-y] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/22/2019] [Accepted: 08/17/2019] [Indexed: 12/16/2022]
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15
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Clinical significance of visually equivocal amyloid PET findings from the Alzheimer's Disease Neuroimaging Initiative cohort. Neuroreport 2019; 29:553-558. [PMID: 29438267 DOI: 10.1097/wnr.0000000000000986] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/26/2022]
Abstract
To evaluate the clinical and imaging characteristics of patients with visually equivocal amyloid PET images, patients from the Alzheimer's Disease Neuroimaging Initiative cohort who had fluorine-18-florbetapir PET scans both at baseline and 24 months were selected. Five nuclear medicine physicians visually assessed the PET images and classified them as either positive or negative. Images not reaching a majority agreement were classified as equivocal. Among a total of 379 patients, the number of patients in each fluorine-18-florbetapir PET negative/equivocal/positive categories was 218 (57.5%), 32 (8.4%), and 129 (34.0%). Eight to 9% of patients with normal cognition (N=12/141), mild cognitive impairment (N=20/214), and no Alzheimer's disease (N=0/24) showed equivocal PET finding for each. In negative/equivocal/positive groups, positive cerebrospinal fluid Aβ1-42 was observed in 25.7, 81.5, and 98.3%, respectively. Baseline standardized uptake value ratios of fluorine-18-florbetapir PET were 0.75±0.05, 0.86±0.09, and 1.01±0.09, respectively [F(2, 376)=603.547; P<0.001]. After 24 months of follow-up, the standardized uptake value ratios increased by 0.81±2.62, 2.81±2.90, and 2.17±3.66%, respectively [F(2, 376)=7.905, P<0.05 vs. the negative group]. Among mild cognitive impairment patients, the equivocal group showed a more rapid decline in glucose metabolism than the negative group [5.52±5.36 vs. 0.67±4.45; F(2, 122)=9.028, P<0.01]. 8.4% of the patients in this study showed a visually equivocal result of amyloid PET. These patients showed a moderate amount of amyloid accumulation and a rapid rate of accumulation.
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16
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Ottoy J, Niemantsverdriet E, Verhaeghe J, De Roeck E, Struyfs H, Somers C, Wyffels L, Ceyssens S, Van Mossevelde S, Van den Bossche T, Van Broeckhoven C, Ribbens A, Bjerke M, Stroobants S, Engelborghs S, Staelens S. Association of short-term cognitive decline and MCI-to-AD dementia conversion with CSF, MRI, amyloid- and 18F-FDG-PET imaging. NEUROIMAGE-CLINICAL 2019; 22:101771. [PMID: 30927601 PMCID: PMC6444289 DOI: 10.1016/j.nicl.2019.101771] [Citation(s) in RCA: 60] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 09/13/2018] [Revised: 01/08/2019] [Accepted: 03/10/2019] [Indexed: 12/31/2022]
Abstract
Disease-modifying treatment trials are increasingly advanced to the prodromal or preclinical phase of Alzheimer's disease (AD), and inclusion criteria are based on biomarkers rather than clinical symptoms. Therefore, it is of great interest to determine which biomarkers should be combined to accurately predict conversion from mild cognitive impairment (MCI) to AD dementia. However, up to date, only few studies performed a complete A/T/N subject characterization using each of the CSF and imaging markers, or they only investigated long-term (≥ 2 years) prognosis. This study aimed to investigate the association between cerebrospinal fluid (CSF), magnetic resonance imaging (MRI), amyloid- and 18F-FDG positron emission tomography (PET) measures at baseline, in relation to cognitive changes and conversion to AD dementia over a short-term (12-month) period. We included 13 healthy controls, 49 MCI and 16 AD dementia patients with a clinical-based diagnosis and a complete A/T/N characterization at baseline. Global cortical amyloid-β (Aβ) burden was quantified using the 18F-AV45 standardized uptake value ratio (SUVR) with two different reference regions (cerebellar grey and subcortical white matter), whereas metabolism was assessed based on 18F-FDG SUVR. CSF measures included Aβ1–42, Aβ1–40, T-tau, P-tau181, and their ratios, and MRI markers included hippocampal volumes (HV), white matter hyperintensities, and cortical grey matter volumes. Cognitive functioning was measured by MMSE and RBANS index scores. All statistical analyses were corrected for age, sex, education, and APOE ε4 genotype. As a result, faster cognitive decline was most strongly associated with hypometabolism (posterior cingulate) and smaller hippocampal volume (e.g., Δstory recall: β = +0.43 [p < 0.001] and + 0.37 [p = 0.005], resp.) at baseline. In addition, faster cognitive decline was significantly associated with higher baseline Aβ burden only if SUVR was referenced to the subcortical white matter (e.g., Δstory recall: β = −0.28 [p = 0.020]). Patients with MCI converted to AD dementia at an annual rate of 31%, which could be best predicted by combining neuropsychological testing (visuospatial construction skills) with either MRI-based HV or 18F-FDG-PET. Combining all three markers resulted in 96% specificity and 92% sensitivity. Neither amyloid-PET nor CSF biomarkers could discriminate short-term converters from non-converters. FDG-PET and MRI HV are the strongest predictors of cognitive decline and conversion to AD. Combination of visuospatial construction testing with FDG-PET or MRI HV present high predicting power of conversion. CSF and amyloid-PET seem less suitable markers of disease progression. Increased AV45-PET predicts short-term cognitive decline if SUVR is referenced to WM instead of CB.
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Affiliation(s)
- Julie Ottoy
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Jeroen Verhaeghe
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Ellen De Roeck
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Hanne Struyfs
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Charisse Somers
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Leonie Wyffels
- Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Sarah Ceyssens
- Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Sara Van Mossevelde
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Tobi Van den Bossche
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium
| | - Christine Van Broeckhoven
- Neurodegenerative Brain Diseases Group, Center for Molecular Neurology, VIB, Antwerp, Belgium; Laboratory of Neurogenetics, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | | | - Maria Bjerke
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Sigrid Stroobants
- Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), Laboratory of Neurochemistry and Behavior, Institute Born-Bunge, University of Antwerp, Antwerp, Belgium
| | - Steven Staelens
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium.
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Rate of β-amyloid accumulation varies with baseline amyloid burden: Implications for anti-amyloid drug trials. Alzheimers Dement 2018; 14:1387-1396. [PMID: 30420035 DOI: 10.1016/j.jalz.2018.05.013] [Citation(s) in RCA: 12] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/23/2017] [Revised: 05/06/2018] [Accepted: 05/28/2018] [Indexed: 12/12/2022]
Abstract
INTRODUCTION This study examined a longitudinal trajectory of β-amyloid (Aβ) accumulation at the predementia stage of Alzheimer's disease in the context of clinical trials. METHODS Analyzed were baseline (BL) and 2 years' follow-up 18F-florbetapir positron emission tomography data of 246 Aβ-positive subjects with normal cognition and mild cognitive impairment. We studied the relationship between annual accumulation rates of 18F-florbetapir and BL standard uptake value ratios in whole gray matter (SUVRGM). RESULTS Subjects with BL SUVRGM of 0.56 to 0.92 (n = 134) appeared to accumulate Aβ approximately 1.5 times faster than remaining subjects. In subjects with SUVRGM above 0.95, most regions with the highest annual accumulation rate were outside the established set of Alzheimer's disease typical regions. CONCLUSION There are global and regional variations in annual accumulation rate at the predementia stage of Alzheimer's disease. When taken into account, the sample size in anti-amyloid trials can be substantially reduced. Critically, treated and placebo groups should be matched for BL SUVRGM.
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18
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Ottoy J, Verhaeghe J, Niemantsverdriet E, Engelborghs S, Stroobants S, Staelens S. A simulation study on the impact of the blood flow-dependent component in [18F]AV45 SUVR in Alzheimer's disease. PLoS One 2017; 12:e0189155. [PMID: 29211812 PMCID: PMC5718604 DOI: 10.1371/journal.pone.0189155] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/01/2017] [Accepted: 11/20/2017] [Indexed: 01/04/2023] Open
Abstract
Background Increased brain uptake on [18F]AV45 PET is a biomarker for Alzheimer’s disease (AD). The standardised uptake value ratio (SUVR) is widely used for quantification but is subject to variability. Here we evaluate how SUVR of a cortical target region is affected by blood flow changes in the target and two frequently used reference regions. Methods Regional baseline time-activity curves (TACs) were simulated based on metabolite-corrected plasma input functions and pharmacokinetic parameters obtained from our previously acquired data in healthy control (HC; n = 10), amnestic mild cognitive impairment (aMCI; n = 15) and AD cohorts (n = 9). Blood flow changes were simulated by altering the regional tracer delivery rate K1 (and clearance rate k2) between -40% and +40% from its regional baseline value in the target region and/or cerebellar grey (CB) or subcortical white matter (WM) reference regions. The corresponding change in SUVR was calculated at 50–60 min post-injection. Results A -40% blood flow reduction in the target resulted in an increased SUVRtarget (e.g. SUVRprecuneus: +10.0±5% in HC, +2.5±2% in AD), irrespective of the used reference region. A -40% blood flow reduction in the WM reference region increased SUVRWM (+11.5±4% in HC, +13.5±3% in AD) while a blood flow reduction in CB decreased SUVRCB (-9.5±6% in HC, -5.5±2% in AD), irrespective of the used target region. A -40% flow reduction in both the precuneus and reference WM (i.e., global flow change) induced an increased SUVR (+22.5±8% in HC, +16.0±4% in AD). When considering reference CB instead, SUVR was decreased by less than -5% (both in HC and AD). Conclusion Blood flow changes introduce alterations in [18F]AV45 PET SUVR. Flow reductions in the CB and WM reference regions resulted in a decreased and increased SUVR of the target, respectively. SUVR was more affected by global blood flow changes when considering WM instead of CB normalization.
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Affiliation(s)
- Julie Ottoy
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Jeroen Verhaeghe
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
| | - Ellis Niemantsverdriet
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
| | - Sebastiaan Engelborghs
- Reference Center for Biological Markers of Dementia (BIODEM), University of Antwerp, Antwerp, Belgium
- Department of Neurology and Memory Clinic, Hospital Network Antwerp (ZNA) Hoge Beuken en Middelheim, Antwerp, Belgium
| | - Sigrid Stroobants
- Department of Nuclear Medicine, Antwerp University Hospital, Edegem, Belgium
| | - Steven Staelens
- Molecular Imaging Center Antwerp, University of Antwerp, Antwerp, Belgium
- * E-mail:
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