Literature DB >> 23954175

Comparison of neuroimaging modalities for the prediction of conversion from mild cognitive impairment to Alzheimer's dementia.

Paula T Trzepacz1, Peng Yu, Jia Sun, Kory Schuh, Michael Case, Michael M Witte, Helen Hochstetler, Ann Hake.   

Abstract

In this study we compared Pittsburgh compound-B (PIB) positron emission tomography (PET) amyloid imaging, fluorodeoxyglucose PET for metabolism, and magnetic resonance imaging (MRI) for structure to predict conversion from amnestic mild cognitive impairment (MCI) to Alzheimer's dementia using data from the Alzheimer's Disease Neuroimaging Initiative cohort. Numeric neuroimaging variables generated by the Alzheimer's Disease Neuroimaging Initiative-funded laboratories for each neuroimaging modality along with apolipoprotein-E genotype (n = 29) were analyzed. Performance of these biomarkers for predicting conversion from MCI to Alzheimer's dementia at 2 years was evaluated in 50 late amnestic MCI subjects, 20 of whom converted. Multivariate modeling found that among individual modalities, MRI had the highest predictive accuracy (67%) which increased by 9% to 76% when combined with PIB-PET, producing the highest accuracy among any biomarker combination. Individually, PIB-PET generated the best sensitivity, and fluorodeoxyglucose PET had the lowest. Among individual brain regions, the temporal cortex was found to be most predictive for MRI and PIB-PET.
Copyright © 2014 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  ADNI; Alzheimer's disease; Amyloid imaging; ApoE; Biomarkers; Conversion; Dementia; FDG-PET; MRI; Mild cognitive impairment; Neuroimaging; PIB-PET

Mesh:

Substances:

Year:  2013        PMID: 23954175     DOI: 10.1016/j.neurobiolaging.2013.06.018

Source DB:  PubMed          Journal:  Neurobiol Aging        ISSN: 0197-4580            Impact factor:   4.673


  44 in total

1.  Combining multiple anatomical MRI measures improves Alzheimer's disease classification.

Authors:  Frank de Vos; Tijn M Schouten; Anne Hafkemeijer; Elise G P Dopper; John C van Swieten; Mark de Rooij; Jeroen van der Grond; Serge A R B Rombouts
Journal:  Hum Brain Mapp       Date:  2016-02-25       Impact factor: 5.038

2.  One-Shot Generative Adversarial Learning for MRI Segmentation of Craniomaxillofacial Bony Structures.

Authors:  Xu Chen; Chunfeng Lian; Li Wang; Hannah Deng; Steve H Fung; Dong Nie; Kim-Han Thung; Pew-Thian Yap; Jaime Gateno; James J Xia; Dinggang Shen
Journal:  IEEE Trans Med Imaging       Date:  2019-08-14       Impact factor: 10.048

3.  Combined Plasma and Cerebrospinal Fluid Signature for the Prediction of Midterm Progression From Mild Cognitive Impairment to Alzheimer Disease.

Authors:  Benoit Lehallier; Laurent Essioux; Javier Gayan; Roxana Alexandridis; Tania Nikolcheva; Tony Wyss-Coray; Markus Britschgi
Journal:  JAMA Neurol       Date:  2015-12-14       Impact factor: 18.302

Review 4.  A Cochrane review on brain [¹⁸F]FDG PET in dementia: limitations and future perspectives.

Authors:  Silvia Morbelli; Valentina Garibotto; Elsmarieke Van De Giessen; Javier Arbizu; Gaël Chételat; Alexander Drezgza; Swen Hesse; Adriaan A Lammertsma; Ian Law; Sabina Pappata'; Pierre Payoux; Marco Pagani
Journal:  Eur J Nucl Med Mol Imaging       Date:  2015-09       Impact factor: 9.236

5.  Transmodal Learning of Functional Networks for Alzheimer's Disease Prediction.

Authors:  Mehdi Rahim; Bertrand Thirion; Claude Comtat; Gaël Varoquaux
Journal:  IEEE J Sel Top Signal Process       Date:  2016-08-15       Impact factor: 6.856

6.  Craniomaxillofacial Bony Structures Segmentation from MRI with Deep-Supervision Adversarial Learning.

Authors:  Miaoyun Zhao; Li Wang; Jiawei Chen; Dong Nie; Yulai Cong; Sahar Ahmad; Angela Ho; Peng Yuan; Steve H Fung; Hannah H Deng; James Xia; Dinggang Shen
Journal:  Med Image Comput Comput Assist Interv       Date:  2018-09-13

7.  A point-based tool to predict conversion from mild cognitive impairment to probable Alzheimer's disease.

Authors:  Deborah E Barnes; Irena S Cenzer; Kristine Yaffe; Christine S Ritchie; Sei J Lee
Journal:  Alzheimers Dement       Date:  2014-02-01       Impact factor: 21.566

Review 8.  Recent publications from the Alzheimer's Disease Neuroimaging Initiative: Reviewing progress toward improved AD clinical trials.

Authors:  Michael W Weiner; Dallas P Veitch; Paul S Aisen; Laurel A Beckett; Nigel J Cairns; Robert C Green; Danielle Harvey; Clifford R Jack; William Jagust; John C Morris; Ronald C Petersen; Andrew J Saykin; Leslie M Shaw; Arthur W Toga; John Q Trojanowski
Journal:  Alzheimers Dement       Date:  2017-03-22       Impact factor: 21.566

9.  Domain Transfer Learning for MCI Conversion Prediction.

Authors:  Bo Cheng; Mingxia Liu; Daoqiang Zhang; Brent C Munsell; Dinggang Shen
Journal:  IEEE Trans Biomed Eng       Date:  2015-03-02       Impact factor: 4.538

10.  Amyloid load but not regional glucose metabolism predicts conversion to Alzheimer's dementia in a memory clinic population.

Authors:  Lars Frings; Sabine Hellwig; Tobias Bormann; Timo S Spehl; Ralph Buchert; Philipp T Meyer
Journal:  Eur J Nucl Med Mol Imaging       Date:  2018-03-15       Impact factor: 9.236

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