Anglia Ruskin Research Online (ARRO)
Browse

Technical note: can resting state functional MRI assist in routine clinical diagnosis?

Download (370.59 kB)
journal contribution
posted on 2023-07-26, 14:29 authored by Paula Harman, Christine Law, Shahina Pardhan, ZhiHao Henry Lin, Mark Johnson, Silke Walter, Klaus Fassbender, Richard Aspinall, Iris Q. Grunwald
Despite some differences in clinical presentation, it is often difficult to differentiate between dementia with Lewy bodies (DLB), clinical Alzheimer’s dementia (AD) and Parkinson’s disease dementia. However, differentiation can be crucial, especially as patients with DLB characteristically have a hypersensitivity to most antiemetic and neuroleptic drugs as they affect the cholinergic and dopaminergic system, potentially leading to life-threatening catatonia, loss of cognitive function and muscle rigidity. The aim of this study is to evaluate if resting state (RS) functional MRI (fMRI) can be used in routine practice on a 1.5 T scanner to differentiate between AD and DLB on an individual basis. We age- and gender-matched a known DLB patient with an AD patient and a human control (HC). Individual independent component analysis was carried out. Region of interest seeds were chosen from the midcingulate and insula regions. Functional connectivity from insula to midcingulate and within the midcingulate network (part of the Salience network) was lower in DLB than AD or HC. RS-fMRI on a 1.5 T scanner, in a routine clinical setting, detected abnormal functional connectivity patterns and allowed differentiation of DLB and AD in a routine clinical setting. This is the first evaluation of RS-fMRI in a routine clinical setting. It shows that incorporating RS-fMRI into the clinical scanning protocol can assist in early diagnosis and likely assist in monitoring the natural history of the disease or disease modifying treatments.

History

Refereed

  • Yes

Volume

4

Issue number

4

Page range

20180030

Publication title

BJR Case Reports

ISSN

2055-7159

Publisher

British Institute of Radiology

File version

  • Published version

Language

  • eng

Legacy posted date

2018-11-14

Legacy creation date

2018-11-14

Legacy Faculty/School/Department

ARCHIVED Faculty of Medical Science (until September 2018)

Usage metrics

    ARU Outputs

    Categories

    No categories selected

    Keywords

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC