Literature DB >> 33998539

Neuroimaging in the Oldest-Old: A Review of the Literature.

Davis C Woodworth1,2, Kiana A Scambray1,2, María M Corrada1,2,3, Claudia H Kawas1,2,4, S Ahmad Sajjadi1,2.   

Abstract

The oldest-old, those 85 years and older, are the fastest growing segment of the population and present with the highest prevalence of dementia. Given the importance of neuroimaging measures to understand aging and dementia, the objective of this study was to review neuroimaging studies performed in oldest-old participants. We used PubMed, Google Scholar, and Web of Science search engines to identify in vivo CT, MRI, and PET neuroimaging studies either performed in the oldest-old or that addressed the oldest-old as a distinct group in analyses. We identified 60 studies and summarized the main group characteristics and findings. Generally, oldest-old participants presented with greater atrophy compared to younger old participants, with most studies reporting a relatively stable constant decline in brain volumes over time. Oldest-old participants with greater global atrophy and atrophy in key brain structures such as the medial temporal lobe were more likely to have dementia or cognitive impairment. The oldest-old presented with a high burden of white matter lesions, which were associated with various lifestyle factors and some cognitive measures. Amyloid burden as assessed by PET, while high in the oldest-old compared to younger age groups, was still predictive of transition from normal to impaired cognition, especially when other adverse neuroimaging measures (atrophy and white matter lesions) were also present. While this review highlights past neuroimaging research in the oldest-old, it also highlights the dearth of studies in this important population. It is imperative to perform more neuroimaging studies in the oldest-old to better understand aging and dementia.

Entities:  

Keywords:  Aged 80 and over; Alzheimer’s disease; aging; cognitive aging; magnetic resonance imaging; memory disorders; neuroimaging; neuropathology; positron emission tomography; tomography; x-ray computed

Mesh:

Year:  2021        PMID: 33998539      PMCID: PMC8717609          DOI: 10.3233/JAD-201578

Source DB:  PubMed          Journal:  J Alzheimers Dis        ISSN: 1387-2877            Impact factor:   4.472


  71 in total

1.  Arterial stiffness and β-amyloid progression in nondemented elderly adults.

Authors:  Timothy M Hughes; Lewis H Kuller; Emma J M Barinas-Mitchell; Eric M McDade; William E Klunk; Ann D Cohen; Chester A Mathis; Steven T Dekosky; Julie C Price; Oscar L Lopez
Journal:  JAMA Neurol       Date:  2014-05       Impact factor: 18.302

2.  Subiculum volumes associated with memory function in the oldest-old individuals aged 95 years and older.

Authors:  Yoko Eguchi; Yoshihiro Noda; Shinichiro Nakajima; Sakiko Tsugawa; Hisashi Kida; Eric Plitman; Ariel Graff-Guerrero; Mallar M Chakravarty; Midori Takayama; Yasumichi Arai; Hiroshi Matsuda; Masaru Mimura; Hidehito Niimura
Journal:  Geriatr Gerontol Int       Date:  2019-02-25       Impact factor: 2.730

3.  Age-related white matter integrity differences in oldest-old without dementia.

Authors:  Ilana J Bennett; Dana E Greenia; Pauline Maillard; S Ahmad Sajjadi; Charles DeCarli; Maria M Corrada; Claudia H Kawas
Journal:  Neurobiol Aging       Date:  2017-04-26       Impact factor: 4.673

Review 4.  Radiologic changes of the aging brain and skull.

Authors:  M LeMay
Journal:  AJR Am J Roentgenol       Date:  1984-08       Impact factor: 3.959

5.  Incidental findings on cranial imaging in nonagenarians.

Authors:  Wajd N Al-Holou; Adam Khan; Thomas J Wilson; William R Stetler; Gaurang V Shah; Cormac O Maher
Journal:  Neurosurg Focus       Date:  2011-12       Impact factor: 4.047

6.  Impact of white matter hyperintensity volume progression on rate of cognitive and motor decline.

Authors:  L C Silbert; C Nelson; D B Howieson; M M Moore; J A Kaye
Journal:  Neurology       Date:  2008-07-08       Impact factor: 9.910

7.  Amyloid, neurodegeneration, and small vessel disease as predictors of dementia in the oldest-old.

Authors:  Oscar L Lopez; William E Klunk; Chester Mathis; Rhaven L Coleman; Julie Price; James T Becker; Howard J Aizenstein; Beth Snitz; Ann Cohen; Milos Ikonomovic; Eric McDade; Steven T DeKosky; Lisa Weissfeld; Lewis H Kuller
Journal:  Neurology       Date:  2014-10-10       Impact factor: 9.910

8.  Less Daily Computer Use is Related to Smaller Hippocampal Volumes in Cognitively Intact Elderly.

Authors:  Lisa C Silbert; Hiroko H Dodge; David Lahna; Nutta-On Promjunyakul; Daniel Austin; Nora Mattek; Deniz Erten-Lyons; Jeffrey A Kaye
Journal:  J Alzheimers Dis       Date:  2016       Impact factor: 4.472

9.  Comparison of cerebral blood flow and structural penumbras in relation to white matter hyperintensities: A multi-modal magnetic resonance imaging study.

Authors:  Nutta-On Promjunyakul; David L Lahna; Jeffrey A Kaye; Hiroko H Dodge; Deniz Erten-Lyons; William D Rooney; Lisa C Silbert
Journal:  J Cereb Blood Flow Metab       Date:  2016-06-07       Impact factor: 6.200

10.  Amyloid deposition and brain structure as long-term predictors of MCI, dementia, and mortality.

Authors:  Oscar L Lopez; James T Becker; YueFang Chang; William E Klunk; Chester Mathis; Julia Price; Howard J Aizenstein; Beth Snitz; Ann D Cohen; Steven T DeKosky; Milos Ikonomovic; M Ilyas Kamboh; Lewis H Kuller
Journal:  Neurology       Date:  2018-04-25       Impact factor: 9.910

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  3 in total

1.  Evaluation of in vivo staging of amyloid deposition in cognitively unimpaired elderly aged 78-94.

Authors:  Malgorzata M Michalowska; Karl Herholz; Rainer Hinz; Chinenye Amadi; Lynn McInnes; Jose M Anton-Rodriguez; Thomas K Karikari; Kaj Blennow; Henrik Zetterberg; Nicholas J Ashton; Neil Pendleton; Stephen F Carter
Journal:  Mol Psychiatry       Date:  2022-07-20       Impact factor: 13.437

Review 2.  White Matter Alterations in Depressive Disorder.

Authors:  Enling He; Min Liu; Sizhu Gong; Xiyao Fu; Yue Han; Fang Deng
Journal:  Front Immunol       Date:  2022-05-12       Impact factor: 8.786

3.  Estimation of Human Cerebral Atrophy Based on Systemic Metabolic Status Using Machine Learning.

Authors:  Kaoru Sakatani; Katsunori Oyama; Lizhen Hu; Shin'ichi Warisawa
Journal:  Front Neurol       Date:  2022-05-02       Impact factor: 4.003

  3 in total

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