Potential Clinical Value of Multiparametric PET in the Prediction of Alzheimer’s Disease Progression

PLOS ONE, May 2016

Objective To evaluate the potential clinical value of quantitative functional FDG PET and pathological amyloid-β PET with cerebrospinal fluid (CSF) biomarkers and clinical assessments in the prediction of Alzheimer’s disease (AD) progression. Methods We studied 82 subjects for up to 96 months (median = 84 months) in a longitudinal Alzheimer’s Disease Neuroimaging Initiative (ADNI) project. All preprocessed PET images were spatially normalized to standard Montreal Neurologic Institute space. Regions of interest (ROI) were defined on MRI template, and standard uptake values ratios (SUVRs) to the cerebellum for FDG and amyloid-β PET were calculated. Predictive values of single and multiparametric PET biomarkers with and without clinical assessments and CSF biomarkers for AD progression were evaluated using receiver operating characteristic (ROC) analysis and logistic regression model. Results The posterior precuneus and cingulate SUVRs were identified for both FDG and amyloid-β PET in predicating progression in normal controls (NCs) and subjects with mild cognitive impairment (MCI). FDG parietal and lateral temporal SUVRs were suggested for monitoring NCs and MCI group progression, respectively. 18F-AV45 global cortex attained (78.6%, 74.5%, 75.4%) (sensitivity, specificity, accuracy) in predicting NC progression, which is comparable to the 11C-PiB global cortex SUVR’s in predicting MCI to AD. A logistic regression model to combine FDG parietal and posterior precuneus SUVR and Alzheimer’s Disease Assessment Scale-Cognitive (ADAS-Cog) Total Mod was identified in predicating NC progression with (80.0%, 94.9%, 93.9%) (sensitivity, specificity, accuracy). The selected model including FDG posterior cingulate SUVR, ADAS-Cog Total Mod, and Mini-Mental State Exam (MMSE) scores for predicating MCI to AD attained (96.4%, 81.2%, 83.6%) (sensitivity, specificity, accuracy). 11C-PiB medial temporal SUVR with MMSE significantly increased 11C-PiB PET AUC to 0.915 (p<0.05) in predicating MCI to AD with (77.8%, 90.4%, 88.5%) (sensitivity, specificity, accuracy). Conclusion Quantitative FDG and 11C-PiB PET with clinical cognitive assessments significantly improved accuracy in the predication of AD progression.

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Potential Clinical Value of Multiparametric PET in the Prediction of Alzheimer’s Disease Progression

RESEARCH ARTICLE Potential Clinical Value of Multiparametric PET in the Prediction of Alzheimer’s Disease Progression Xueqi Chen1,2, Yun Zhou1,2*, Rongfu Wang1*, Haoyin Cao3, Savina Reid2, Rui Gao2,4, Dong Han5, Alzheimer’s Disease Neuroimaging Initiative¶ a11111 1 Department of Nuclear Medicine, Peking University First Hospital, Beijing, China, 2 The Russell H. Morgan Department of Radiology and Radiological Science, Johns Hopkins University School of Medicine, Baltimore, Maryland, United States of America, 3 University Hospital, Hamburg-Eppendorf, Hamburg, Germany, 4 Department of Nuclear Medicine, the First Affiliated Hospital of Xian Jiaotong University, Xi'an, Shaanxi, China, 5 Department of Computer Science and Engineering, Oakland University, Rochester, Michigan, United States of America ¶ Membership of the Alzheimer’s Disease Neuroimaging Initiative is provided in the Acknowledgments. * (YZ); (RW) OPEN ACCESS Citation: Chen X, Zhou Y, Wang R, Cao H, Reid S, Gao R, et al. (2016) Potential Clinical Value of Multiparametric PET in the Prediction of Alzheimer’s Disease Progression. PLoS ONE 11(5): e0154406. doi:10.1371/journal.pone.0154406 Editor: Kewei Chen, Banner Alzheimer's Institute, UNITED STATES Abstract Objective To evaluate the potential clinical value of quantitative functional FDG PET and pathological amyloid-β PET with cerebrospinal fluid (CSF) biomarkers and clinical assessments in the prediction of Alzheimer’s disease (AD) progression. Received: February 1, 2016 Accepted: April 13, 2016 Methods Published: May 16, 2016 We studied 82 subjects for up to 96 months (median = 84 months) in a longitudinal Alzheimer’s Disease Neuroimaging Initiative (ADNI) project. All preprocessed PET images were spatially normalized to standard Montreal Neurologic Institute space. Regions of interest (ROI) were defined on MRI template, and standard uptake values ratios (SUVRs) to the cerebellum for FDG and amyloid-β PET were calculated. Predictive values of single and multiparametric PET biomarkers with and without clinical assessments and CSF biomarkers for AD progression were evaluated using receiver operating characteristic (ROC) analysis and logistic regression model. Copyright: © 2016 Chen et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). A complete listing of ADNI subjects included in this study can be found in the Supporting Information files. Funding: Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging Results The posterior precuneus and cingulate SUVRs were identified for both FDG and amyloid-β PET in predicating progression in normal controls (NCs) and subjects with mild cognitive impairment (MCI). FDG parietal and lateral temporal SUVRs were suggested for monitoring NCs and MCI group progression, respectively. 18F-AV45 global cortex attained (78.6%, 74.5%, 75.4%) (sensitivity, specificity, accuracy) in predicting NC progression, which is comparable to the 11C-PiB global cortex SUVR’s in predicting MCI to AD. A logistic regression model to combine FDG parietal and posterior precuneus SUVR and Alzheimer’s PLOS ONE | DOI:10.1371/journal.pone.0154406 May 16, 2016 1 / 15 Potential Clinical Value of Multiparametric PET in the Prediction of Alzheimer's Disease Progression and Bioengineering, and through generous contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare; IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health (www.fnih.org). The grantee organization is the Northern California Institute for Research and Education, and the study is coordinated by the Alzheimer's Disease Cooperative Study at the University of California, San Diego. ADNI data are disseminated by the Laboratory for Neuro Imaging at the University of Southern California. This work of the author was in part supported by the China Scholarship Council (No. 201406010242). Competing Interests: The authors have the following interests: Data collection and sharing for this project was funded by the Alzheimer's Disease Neuroimaging Initiative (ADNI) (National Institutes of Health Grant U01 AG024904) and DOD ADNI (Department of Defense award number W81XWH12-2-0012). ADNI is funded by the National Institute on Aging, the National Institute of Biomedical Imaging and Bioengineering, and through generous contributions from the following: Alzheimer’s Association; Alzheimer’s Drug Discovery Foundation; Araclon Biotech; BioClinica, Inc.; Biogen Idec Inc.; Bristol-Myers Squibb Company; Eisai Inc.; Elan Pharmaceuticals, Inc.; Eli Lilly and Company; EuroImmun; F. Hoffmann-La Roche Ltd and its affiliated company Genentech, Inc.; Fujirebio; GE Healthcare IXICO Ltd.; Janssen Alzheimer Immunotherapy Research & Development, LLC.; Johnson & Johnson Pharmaceutical Research & Development LLC.; Medpace, Inc.; Merck & Co., Inc.; Meso Scale Diagnostics, LLC.; NeuroRx Research; Neurotrack Technologies; Novartis Pharmaceuticals Corporation; Pfizer Inc.; Piramal Imaging; Servier; Synarc Inc.; and Takeda Pharmaceutical Company. The Canadian Institutes of Health Research is providing funds to support ADNI clinical sites in Canada. Private sector contributions are facilitated by the Foundation for the National Institutes of Health Disease Assessment Scale-Cognitive (ADAS-Cog) Total Mod was identified in predicating NC progression with (80.0%, 94.9%, 93.9%) (sensitivity, specificity, accuracy). The selected model including FDG posterior cingulate SUVR, ADAS-Cog Total Mod, and MiniMental State Exam (MMSE) scores for predicating MCI to AD attained (96.4%, 81.2%, 83.6%) (sensitivity, specif (...truncated)


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Xueqi Chen, Yun Zhou, Rongfu Wang, Haoyin Cao, Savina Reid, Rui Gao, Dong Han, Alzheimer’s Disease Neuroimaging Initiative. Potential Clinical Value of Multiparametric PET in the Prediction of Alzheimer’s Disease Progression, PLOS ONE, 2016, Volume 11, Issue 5, DOI: 10.1371/journal.pone.0154406