Literature DB >> 18777563

Discriminating accuracy of medial temporal lobe volumetry and fMRI in mild cognitive impairment.

Anne M Jauhiainen1, Maija Pihlajamäki, Susanna Tervo, Eini Niskanen, Heikki Tanila, Tuomo Hänninen, Ritva L Vanninen, Hilkka Soininen.   

Abstract

We investigated structural and functional changes in the medial temporal lobe (MTL) using magnetic resonance imaging (MRI) and compared the discriminative power of these measures with neuropsychological testing in mild cognitive impairment (MCI) and Alzheimer's disease (AD). Functional MRI (fMRI) was performed in 21 elderly controls, 14 MCI subjects, and 15 mild AD patients during encoding and cued retrieval of word-picture pairs. A region-of-interest-based approach in SPM2 was used to extract the extent of hippocampal activation. The volumes of the hippocampus and entorhinal cortex (EC) were manually outlined from anatomical MR images. Discriminant analyses were conducted to assess the ability of hippocampal fMRI, MTL volumetry, and neuropsychological measures to classify subjects into clinical groups. Entorhinal but not hippocampal volumes differed significantly between the control and MCI subjects. Both entorhinal and hippocampal volumes differed between MCI and AD patients. There were no significant differences in the extent of hippocampal fMRI activation during encoding or retrieval between the groups. Entorhinal volume was the best discriminator with a discriminating accuracy of 85.7% between controls and MCI, 86.2% between MCI and AD, and 97.2% between controls and AD. Delayed recall of a wordlist classified the subjects, second best, with a discriminating accuracy of 81.8% between controls and MCI, 75% between MCI and AD and 93.5% between controls and AD. The accuracy of hippocampal volumetry ranged from 42.9 to 69.4%, and hippocampal fMRI activation during encoding and retrieval had a classification accuracy of only 41.4-57.7% between the groups. Our results suggest that evaluation of entorhinal atrophy, in addition to the prevailing diagnostic criteria, seems promising in the identification of prodromal AD. Future technical improvements may improve the utilization of hippocampal fMRI for early diagnostic purposes.

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Year:  2009        PMID: 18777563     DOI: 10.1002/hipo.20494

Source DB:  PubMed          Journal:  Hippocampus        ISSN: 1050-9631            Impact factor:   3.899


  18 in total

1.  Minimal atrophy of the entorhinal cortex and hippocampus: progression of cognitive impairment.

Authors:  Daniel Varon; David A Loewenstein; Elizabeth Potter; Maria T Greig; Joscelyn Agron; Qian Shen; Weizhao Zhao; Maria Celeste Ramirez; Isael Santos; Warren Barker; Huntington Potter; Ranjan Duara
Journal:  Dement Geriatr Cogn Disord       Date:  2011-04-13       Impact factor: 2.959

2.  Machine-learning techniques for building a diagnostic model for very mild dementia.

Authors:  Rong Chen; Edward H Herskovits
Journal:  Neuroimage       Date:  2010-04-09       Impact factor: 6.556

3.  Automated segmentation of medial temporal lobe subregions on in vivo T1-weighted MRI in early stages of Alzheimer's disease.

Authors:  Long Xie; Laura E M Wisse; John Pluta; Robin de Flores; Virgine Piskin; Jose V Manjón; Hongzhi Wang; Sandhitsu R Das; Song-Lin Ding; David A Wolk; Paul A Yushkevich
Journal:  Hum Brain Mapp       Date:  2019-04-29       Impact factor: 5.038

Review 4.  Staging neurodegenerative disorders: structural, regional, biomarker, and functional progressions.

Authors:  Trevor Archer; Richard M Kostrzewa; Richard J Beninger; Tomas Palomo
Journal:  Neurotox Res       Date:  2011-02       Impact factor: 3.911

5.  The anteroposterior and primary-to-posterior limbic ratios as MRI-derived volumetric markers of Alzheimer's disease.

Authors:  Adolfo Jiménez-Huete; Susana Estévez-Santé
Journal:  J Neurol Sci       Date:  2017-04-27       Impact factor: 3.181

6.  Functional response in ventral temporal cortex differentiates mild cognitive impairment from normal aging.

Authors:  Brian T Gold; Yang Jiang; Greg A Jicha; Charles D Smith
Journal:  Hum Brain Mapp       Date:  2010-08       Impact factor: 5.038

7.  Automated Multi-Atlas Segmentation of Hippocampal and Extrahippocampal Subregions in Alzheimer's Disease at 3T and 7T: What Atlas Composition Works Best?

Authors:  Long Xie; Russell T Shinohara; Ranjit Ittyerah; Hugo J Kuijf; John B Pluta; Kim Blom; Minke Kooistra; Yael D Reijmer; Huiberdina L Koek; Jaco J M Zwanenburg; Hongzhi Wang; Peter R Luijten; Mirjam I Geerlings; Sandhitsu R Das; Geert Jan Biessels; David A Wolk; Paul A Yushkevich; Laura E M Wisse
Journal:  J Alzheimers Dis       Date:  2018       Impact factor: 4.472

8.  Novel age-dependent learning deficits in a mouse model of Alzheimer's disease: implications for translational research.

Authors:  K S Montgomery; R K Simmons; G Edwards; M M Nicolle; M A Gluck; C E Myers; J L Bizon
Journal:  Neurobiol Aging       Date:  2009-08-31       Impact factor: 4.673

9.  Modeling Large Sparse Data for Feature Selection: Hospital Admission Predictions of the Dementia Patients Using Primary Care Electronic Health Records.

Authors:  Gavin Tsang; Shang-Ming Zhou; Xianghua Xie
Journal:  IEEE J Transl Eng Health Med       Date:  2020-11-24       Impact factor: 3.316

10.  MRI markers for mild cognitive impairment: comparisons between white matter integrity and gray matter volume measurements.

Authors:  Yu Zhang; Norbert Schuff; Monica Camacho; Linda L Chao; Thomas P Fletcher; Kristine Yaffe; Susan C Woolley; Catherine Madison; Howard J Rosen; Bruce L Miller; Michael W Weiner
Journal:  PLoS One       Date:  2013-06-06       Impact factor: 3.240

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