Clinical Trial Details
— Status: Recruiting
Administrative data
| NCT number |
NCT02426398 |
| Other study ID # |
STH18419 |
| Secondary ID |
|
| Status |
Recruiting |
| Phase |
|
| First received |
|
| Last updated |
|
| Start date |
March 2015 |
| Est. completion date |
December 31, 2024 |
Study information
| Verified date |
January 2024 |
| Source |
Sheffield Teaching Hospitals NHS Foundation Trust |
| Contact |
Daniel Blackburn, MBChB, PhD |
| Phone |
01142222267 |
| Email |
d.blackburn[@]shef.ac.uk |
| Is FDA regulated |
No |
| Health authority |
|
| Study type |
Observational
|
Clinical Trial Summary
This is a non-invasive study investigating whether EEG, which is used in routine clinical
care can be useful in diagnosing dementia. Novel in house developed software will analyse EEG
data for this purpose from people with Alzheimer's disease and healthy volunteers.
Description:
Participant recruitment
15 people with early AD will be recruited from the Sheffield Teaching Hospital and Sheffield
Health and Social Care NHS Trusts memory clinics. The STH clinic is neurology led and sees
working age (<65 years old) patients while the SHSC clinic sees an older (>65 years old)
population. Over 1300 new assessments are conducted every year. Approximately 65-70% are
diagnosed with dementia.
Investigators will choose patients with typical neuropsychological profiles of AD. All
patients will have previously been recruited to the Virtual Physiological Human: Dementia
Research enabled by IT. VPH-DARE@IT is recruiting 30-40 participants in each of the three
following groups (mild AD, MCI and normal controls) and thus our participants will be drawn
from this group and all will have pre-existing high-resolution 3D structural and volumetric
assessment plus resting-state fMRI scans. This resting-state fMRI data will be analysed to
examine the DMN, allowing us to directly compare measures of brain-connectivity between EEG
and fMRI and contrast the discriminatory ability of the two methodologies.
10 healthy controls will be aged matched and recruited either from Neurology clinics or be
spouses of study participants. The investigators will endeavour to recruit normal controls
who have undergone fMRI as part of the academic neuroradiology departments control population
for VPH-DARE@IT and other studies.
People with AD and 10 healthy controls will have a repeat EEG to assess the reproducibility
and robustness of the EEG measures.
EEG is normally very well tolerated and as listed in the background has been used in many
people with dementia. The Clinical Neurophysiology department is very experienced in
undertaking EEG in all patient populations from neonates to the very elderly.
Consent Participants will be identified by the clinicians working in the memory clinic or
through posters in memory clinic and at other University sites to attract normal volunteers.
A Participation Information Sheet (PIS) will be given to them either directly or via post.
Participants will have sufficient time to read the PIS and be able to ask questions. The PIS
will inform the participant of the benefits and potential risks involved in taking part in
this study. They will be made aware of the possibility that incidental changes are rarely
detected. If this is seen they would be informed and we would arrange appropriate management.
The person will be consented when they come in for the EEG recordings. Investigators will
explain to all participants that they will be able to leave the study at any time including
during the EEG recording and in those that we plan to repeat the EEG can decline the 2nd
test. The Clinical Department of Neurophysiology has experience in performing EEG in all ages
including those with dementia and cognitive impairment. The person with dementia's care-giver
or family member can come to the department and be in the room for the entire time the EEG
recording takes place.
Methodology EEG data capture
- Participants will attend the department of clinical neurophysiology and a member of the
research team will take consent. Two experienced EEG technicians will place the
electrodes and explain the procedure. We will record resting state EEG. Participants
will be told to lie still with eyes closed. It will be explained that although their
eyes are closed they must remain awake. Participants will be continuously monitored and
if they become drowsy will be re-stimulated and the time of drowsiness will be recorded.
This instruction and monitoring is the same as that used in previous EEG and fMRI
studies looking at resting state paradigms.
- The 10-10 International system of electrode placement will be used for the scalp EEG
recordings with a multichannel high sampling rate amplifier (2 KHz). This will provide
standard 10/20 electrode positions (F3, F4, F7, F8, C3, C4, Fz, Cz, T3, T4, T5, T6, P3,
P4, O1, O2, and Oz electrodes) which will be initially used to detect the more
significant spatiotemporal measurements/phenomena while offering the opportunity to
elaborate on the spatial and frequency resolution of our findings at a later stage.
Peri-ocular EOG electrode data will also be recorded to detect eye movement related slow
wave activity. Investigators will therefore be able to avoid spurious estimates of slow
wave activity in the anterior EEG regions.
- Artefact free epochs within suitable (wakeful no task eyes closed state) will be
selected and exported for further quantitative EEG analysis.
- The exported data will be stored on an external encrypted drive.
- All the analyses will be performed on custom made in-house software on a high tech
computer located within secure offices locked within Dr Sarrigannis's office housed in
the department of clinical neurophysiology.
EEG Data analyses • The error reduction ratio-causality method will be used to calculate
levels of synchronisation. The standard EEG 10-20 electrodes, including all possible
contiguous electrode combinations in pairs of two (e.g. right frontocentral versus
parietoccipital) will be used in our pilot exploration to assess the 95% confidence interval
levels of synchronisation and determine if they allow robust separation between healthy
volunteers and patients with Alzheimer's Disease.
Other Data
• Qualitative Data collection: Investigators will collect questionnaires on the tolerability
of undergoing EEG examination (please find enclosed questionnaire).
Ethical consideration Modern neuro-imaging using MRI is highly sensitive and can detect
incidental findings. Our novel EEG analyses also have the potential to detect incidental
findings. It is well known that spikes during an inter-ictal EEG have limited clinical
significance. However they are seen more frequently in people who have a liability, or
lowered threshold, for epilepsy. If any concern is raised about the EEG findings the
participant will be reviewed by Dr Blackburn and if appropriate referred onto another
neurological colleague. Any incidental findings detected by MRI will be referred to an NHS
neurologist through the VPH-DARE@IT project researchers. The Patient Information Sheet and
consent will make participants aware of these risks before they take part in the study.
Statistics This pilot project will explore EEG data to investigate the frequency and time
domain measurement that would be most appropriate for clinical use. Investigators do not know
whether this will involve linear or non-linear interaction and thus we cannot determine which
is the most appropriate statistical test. The analysis of similar EEG data sets using
parametric methods has explored this in more detail.
Power calculations As this is a proof-of-concept, pilot study to examine the robustness of a
novel methodology, it is inappropriate to conduct a formal power calculation. Our initial
findings will determine whether our EEG analyses detects functional connectivity correlates
of the synchronisation of anterior and posterior networks identified by fMRI BOLD signal
during resting state scanning. Investigators will also explore if our data is comparable to
previously published quantitative EEG on people with AD. Investigators will explore which
measures from our data can discriminate people with Alzheimer's disease from healthy
controls. These initial results will give us likely effect sizes and allow us to conduct more
accurate power calculations than are presently possible. This will be used to determine the
sample size of a larger study of people with dementia.
