Literature DB >> 28664464

Early identification of MCI converting to AD: a FDG PET study.

Marco Pagani1,2, Flavio Nobili3, Silvia Morbelli4, Dario Arnaldi3, Alessandro Giuliani5, Johanna Öberg6, Nicola Girtler3,7, Andrea Brugnolo3, Agnese Picco3, Matteo Bauckneht4, Roberta Piva4, Andrea Chincarini8, Gianmario Sambuceti4, Cathrine Jonsson9, Fabrizio De Carli10.   

Abstract

PURPOSE: Mild cognitive impairment (MCI) is a transitional pathological stage between normal ageing (NA) and Alzheimer's disease (AD). Although subjects with MCI show a decline at different rates, some individuals remain stable or even show an improvement in their cognitive level after some years. We assessed the accuracy of FDG PET in discriminating MCI patients who converted to AD from those who did not.
METHODS: FDG PET was performed in 42 NA subjects, 27 MCI patients who had not converted to AD at 5 years (nc-MCI; mean follow-up time 7.5 ± 1.5 years), and 95 MCI patients who converted to AD within 5 years (MCI-AD; mean conversion time 1.8 ± 1.1 years). Relative FDG uptake values in 26 meta-volumes of interest were submitted to ANCOVA and support vector machine analyses to evaluate regional differences and discrimination accuracy.
RESULTS: The MCI-AD group showed significantly lower FDG uptake values in the temporoparietal cortex than the other two groups. FDG uptake values in the nc-MCI group were similar to those in the NA group. Support vector machine analysis discriminated nc-MCI from MCI-AD patients with an accuracy of 89% (AUC 0.91), correctly detecting 93% of the nc-MCI patients.
CONCLUSION: In MCI patients not converting to AD within a minimum follow-up time of 5 years and MCI patients converting within 5 years, baseline FDG PET and volume-based analysis identified those who converted with an accuracy of 89%. However, further analysis is needed in patients with amnestic MCI who convert to a dementia other than AD.

Entities:  

Keywords:  Alzheimer’s disease; Conversion to AD; Mild cognitive impairment; Positron emission tomography; Support vector machine; Volume of interest analysis

Mesh:

Substances:

Year:  2017        PMID: 28664464     DOI: 10.1007/s00259-017-3761-x

Source DB:  PubMed          Journal:  Eur J Nucl Med Mol Imaging        ISSN: 1619-7070            Impact factor:   9.236


  53 in total

1.  Machine learning framework for early MRI-based Alzheimer's conversion prediction in MCI subjects.

Authors:  Elaheh Moradi; Antonietta Pepe; Christian Gaser; Heikki Huttunen; Jussi Tohka
Journal:  Neuroimage       Date:  2014-10-12       Impact factor: 6.556

2.  Summary metrics to assess Alzheimer disease-related hypometabolic pattern with 18F-FDG PET: head-to-head comparison.

Authors:  Anna Caroli; Annapaola Prestia; Kewei Chen; Napatkamon Ayutyanont; Susan M Landau; Cindee M Madison; Cathleen Haense; Karl Herholz; Flavio Nobili; Eric M Reiman; William J Jagust; Giovanni B Frisoni
Journal:  J Nucl Med       Date:  2012-02-17       Impact factor: 10.057

3.  Progressive Disintegration of Brain Networking from Normal Aging to Alzheimer Disease: Analysis of Independent Components of 18F-FDG PET Data.

Authors:  Marco Pagani; Alessandro Giuliani; Johanna Öberg; Fabrizio De Carli; Silvia Morbelli; Nicola Girtler; Dario Arnaldi; Jennifer Accardo; Matteo Bauckneht; Francesca Bongioanni; Andrea Chincarini; Gianmario Sambuceti; Cathrine Jonsson; Flavio Nobili
Journal:  J Nucl Med       Date:  2017-03-09       Impact factor: 10.057

4.  Automatic classification of patients with Alzheimer's disease from structural MRI: a comparison of ten methods using the ADNI database.

Authors:  Rémi Cuingnet; Emilie Gerardin; Jérôme Tessieras; Guillaume Auzias; Stéphane Lehéricy; Marie-Odile Habert; Marie Chupin; Habib Benali; Olivier Colliot
Journal:  Neuroimage       Date:  2010-06-11       Impact factor: 6.556

5.  Predictive markers for AD in a multi-modality framework: an analysis of MCI progression in the ADNI population.

Authors:  Chris Hinrichs; Vikas Singh; Guofan Xu; Sterling C Johnson
Journal:  Neuroimage       Date:  2010-12-10       Impact factor: 6.556

6.  Prediction of Incipient Alzheimer's Disease Dementia in Patients with Mild Cognitive Impairment.

Authors:  Babak A Ardekani; Elaine Bermudez; Asim M Mubeen; Alvin H Bachman
Journal:  J Alzheimers Dis       Date:  2017       Impact factor: 4.472

7.  Optimization of Statistical Single Subject Analysis of Brain FDG PET for the Prognosis of Mild Cognitive Impairment-to-Alzheimer's Disease Conversion.

Authors:  Catharina Lange; Per Suppa; Lars Frings; Winfried Brenner; Lothar Spies; Ralph Buchert
Journal:  J Alzheimers Dis       Date:  2016       Impact factor: 4.472

8.  Diagnostic evaluation of degenerative and vascular dementia.

Authors:  C Loeb; C Gandolfo
Journal:  Stroke       Date:  1983 May-Jun       Impact factor: 7.914

9.  The relative importance of imaging markers for the prediction of Alzheimer's disease dementia in mild cognitive impairment - Beyond classical regression.

Authors:  Stefan J Teipel; Jens Kurth; Bernd Krause; Michel J Grothe
Journal:  Neuroimage Clin       Date:  2015-05-21       Impact factor: 4.881

10.  Alzheimer's disease risk assessment using large-scale machine learning methods.

Authors:  Ramon Casanova; Fang-Chi Hsu; Kaycee M Sink; Stephen R Rapp; Jeff D Williamson; Susan M Resnick; Mark A Espeland
Journal:  PLoS One       Date:  2013-11-08       Impact factor: 3.240

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  27 in total

1.  18F-FDG PET diagnostic and prognostic patterns do not overlap in Alzheimer's disease (AD) patients at the mild cognitive impairment (MCI) stage.

Authors:  Silvia Morbelli; Matteo Bauckneht; Dario Arnaldi; Agnese Picco; Matteo Pardini; Andrea Brugnolo; Ambra Buschiazzo; Marco Pagani; Nicola Girtler; Alberto Nieri; Andrea Chincarini; Fabrizio De Carli; Gianmario Sambuceti; Flavio Nobili
Journal:  Eur J Nucl Med Mol Imaging       Date:  2017-08-07       Impact factor: 9.236

2.  Controls-based denoising, a new approach for medical image analysis, improves prediction of conversion to Alzheimer's disease with FDG-PET.

Authors:  Dominik Blum; Inga Liepelt-Scarfone; Daniela Berg; Thomas Gasser; Christian la Fougère; Matthias Reimold
Journal:  Eur J Nucl Med Mol Imaging       Date:  2019-07-24       Impact factor: 9.236

3.  A Novel Metabolic Connectome Method to Predict Progression to Mild Cognitive Impairment.

Authors:  Min Wang; Zhuangzhi Yan; Shu-Yun Xiao; Chuantao Zuo; Jiehui Jiang
Journal:  Behav Neurol       Date:  2020-08-18       Impact factor: 3.342

Review 4.  Advances in Genetic and Molecular Understanding of Alzheimer's Disease.

Authors:  Laura Ibanez; Carlos Cruchaga; Maria Victoria Fernández
Journal:  Genes (Basel)       Date:  2021-08-15       Impact factor: 4.096

5.  Abnormal Spontaneous Brain Activity and Cognitive Impairment in Obstructive Sleep Apnea.

Authors:  Wei Xie; Yongqiang Shu; Xiang Liu; Kunyao Li; Panmei Li; Linghong Kong; Pengfei Yu; Ling Huang; Ting Long; Li Zeng; Haijun Li; Dechang Peng
Journal:  Nat Sci Sleep       Date:  2022-09-05

Review 6.  Glucose Metabolism, Neural Cell Senescence and Alzheimer's Disease.

Authors:  Qianqian Wang; Linyan Duan; Xingfan Li; Yifu Wang; Wenna Guo; Fangxia Guan; Shanshan Ma
Journal:  Int J Mol Sci       Date:  2022-04-14       Impact factor: 6.208

7.  Clinicopathologic Factors Associated With Reversion to Normal Cognition in Patients With Mild Cognitive Impairment.

Authors:  Zonghua Li; Michael G Heckman; Takahisa Kanekiyo; Yuka A Martens; Gregory S Day; Maria Vassilaki; Chia-Chen Liu; David A Bennett; Ronald C Petersen; Na Zhao; Guojun Bu
Journal:  Neurology       Date:  2022-03-21       Impact factor: 11.800

8.  Accuracy and generalization capability of an automatic method for the detection of typical brain hypometabolism in prodromal Alzheimer disease.

Authors:  Fabrizio De Carli; Flavio Nobili; Marco Pagani; Matteo Bauckneht; Federico Massa; Matteo Grazzini; Cathrine Jonsson; Enrico Peira; Silvia Morbelli; Dario Arnaldi
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-10-31       Impact factor: 9.236

9.  Spatial inhibition of return is impaired in mild cognitive impairment and mild Alzheimer's disease.

Authors:  Xiong Jiang; James H Howard; G William Rebeck; Raymond Scott Turner
Journal:  PLoS One       Date:  2021-06-14       Impact factor: 3.240

10.  Changes of Regional Neural Activity Homogeneity in Preclinical Alzheimer's Disease: Compensation and Dysfunction.

Authors:  Zhen Zhang; Liang Cui; Yanlu Huang; Yu Chen; Yuehua Li; Qihao Guo
Journal:  Front Neurosci       Date:  2021-06-17       Impact factor: 4.677

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