An Investigation of Lumbar Spinal Nerves
Research type
Research Study
Full title
Optimising diagnosis and prediction of outcome of spinal surgery using diffusion tensor imaging and machine learning.
IRAS ID
161446
Contact name
Paul H Strutton
Contact email
Sponsor organisation
Imperial College London
Duration of Study in the UK
2 years, 11 months, 30 days
Research summary
Narrowing (stenosis) of the space within the spine can result in compression of the nerves and cause pain and weakness in the back or legs. Surgery is often carried out to open up the space to relieve the compression. However, this is sometimes not satisfactory, as many patients are left with the same or worse pain. Patient symptoms, together with an MRI scan are used to help the surgeon decide whether to perform an operation. What the scan cannot tell us is how bad the damage to the nerves is. Knowing this might give the surgeon more information to make a decision on whether to carry out the surgery and, also, may allow us to predict the success of the surgery. This study aims to develop the way MRI scans are performed and the images analysed to improve identification and permit tracing of the compressed nerves along their course in addition to assessing their function; this will be in patients with lumbar (lower back) nerve compression from herniated (slipped) intervertebral disc or spine canal narrowing . Additionally, the relationship between the imaging data and the integrity of the nerves to the muscles will be assessed with brain stimulation and muscle recordings (neurophysiology). Analysis of the images taken before and after the surgery will be carried out using advanced computing techniques which we hope will be able to identify key factors which we could then use to help predict the outcome of the surgery.
REC name
London - Fulham Research Ethics Committee
REC reference
14/LO/1846
Date of REC Opinion
27 Nov 2014
REC opinion
Further Information Favourable Opinion