Clinical Trial Details
— Status: Not yet recruiting
Administrative data
| NCT number |
NCT05460143 |
| Other study ID # |
319284 |
| Secondary ID |
|
| Status |
Not yet recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
March 1, 2023 |
| Est. completion date |
September 1, 2025 |
Study information
| Verified date |
March 2023 |
| Source |
University of Cambridge |
| Contact |
Emilia Butters, MSc |
| Phone |
07462064164 |
| Email |
eb857[@]cam.ac.uk |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
Dementia is associated with a variety of neurovascular and neurometabolic abnormalities.
Traditional imaging techniques used to investigate such abnormalities, such as Positron
Emission Tomography and functional Magnetic Resonance Imaging, are not always well tolerated,
have expensive start up and running costs, and are limited with regards to the types of
experiments that can be performed as they can be highly sensitive to movement, are noisy, and
have physical restrictions.
Near-infrared spectroscopy (NIRS) is a non-invasive neuroimaging technique which uses light
in the near-infrared spectrum to detect relative changes in concentration of oxygenated and
deoxygenated haemoglobin, and the oxidation state of Cytochrome C Oxidase. As such, NIRS can
provide measures of brain oxygenation and metabolism. NIRS is less sensitive to movement, is
well tolerated and has few contraindications. It is thus a promising candidate for use in
clinics or in peoples' homes for monitoring dementia.
In the present study, the investigators aim to use both dual-wavelength and broadband NIRS in
a range of dementia subtypes, including Alzheimer's Disease and Dementia with Lewy Bodies,
and severities, including Mild Cognitive Impairment, to identify how brain oxygenation and
metabolism is altered in dementia and across various clinical subgroups. The investigators
also aim to determine the relationship between brain oxygenation and metabolism in dementia,
and use machine learning approaches to identify optical biomarkers for dementia.
Description:
There are several different types of dementia including Alzheimer's Disease (AD) and Dementia
with Lewy Bodies (DLB). Due to the overlapping symptomatology across types of dementia and
the lack of objective biomarkers currently available for dementia, misdiagnosis rates are
high. Additionally, the transition from what is commonly thought to be an intermediate stage,
termed Mild Cognitive Impairment (MCI), to dementia, is not well defined. Neurovascular and
metabolic dysfunction has been strongly linked to neurodegeneration and dementia, however, a
mechanistic understanding of this link has not been fully developed.
Near-Infrared Spectroscopy (NIRS) is a non-invasive, non-ionising and portable neuroimaging
technique which uses light to quantify changes in concentration of oxygenated and
deoxygenated haemoglobin in the brain. As such, it is a highly attractive alternative to
functional Magnetic Resonance Imaging as it allows access to a larger variety of individuals,
can be used at the bedside or in patients' own homes, and is significantly less intrusive.
To identify how the brain's haemodynamics and metabolism is altered in dementia, this study
will use NIRS in 25 patients with AD, 25 patients with DLB, 50 patients with MCI and 100
age-matched healthy controls. This study will be conducted by the School of Technology and
the School of Clinical Medicine at the University of Cambridge.
Firstly, the investigators will perform several cognitive tests in these patient groups
whilst measuring brain activity using a state-of-the-art, dual-wavelength, high-density NIRS
device to map how the brain's haemodynamics are altered in dementia. Secondly, the
investigators will perform further cognitive tests using broadband NIRS to measure how
neurometabolism is altered across the patient groups. The investigators will also relate the
optical data to several facets of cognition that these cognitive tests will measure including
memory, attention, and motor function. Several questionnaires will also be administered to
assess non-cognitive symptoms such as depression and sleep disturbances. If participants in
the patient groups have not had a Magnetic Resonance Imaging (MRI) scan, or did one over two
years ago, they will also undertake an MRI scan to enable the localisation of brain activity,
measured by NIRS, accounting for individual differences in brain structure and atrophy
patterns.
The investigators shall compare all patient groups (AD, DLB, MCI) with healthy controls to
determine how the brain's haemodynamics and metabolism are altered in dementia, as well as
how this relates to both behavioural scores (collected during cognitive testing) and clinical
scores (using either data collected from questionnaires or patient's own clinical history).
Through combining the two NIRS techniques, the investigators shall also determine the nature
of the relationship between the blood oxygenation in the surrounding vasculature and the
intra-neuronal metabolic activity, and how this relationship may be altered in dementia and
across different types of dementia. Additionally, the investigators shall apply computational
methods, such as machine learning, to identify haemodynamic and/or metabolic signatures for
use as biomarkers in the clinic.
