Barrett Esophagus, Esophageal Cancer
Conditions
Keywords
endoscopy, Raman spectroscopy
Brief summary
To develop and endoscopic Raman spectroscopy probe for delivery down and channel in an endoscope to make near instant assessments of the condition of the oesophagus without the need for expensive and distressing tissue removal (biopsies).
Detailed description
The investigators have already shown that it is possible to tell the difference between healthy and diseased tissue in the laboratory by looking at the light emitted by tissue when illuminated with a low power laser. The investigators intend to use this technique, known as Raman Spectroscopy to tell if tissue in the oesophagus is cancerous, healthy or at some stage before full blown cancer, which is termed pre-cancer. It has been shown in the laboratory that this method will be at least as accurate as the conventional methods used now, but will provide the surgeon with instant results without the delay and cost of a laboratory analysis by pathologists. A miniature probe has been developed that slides through a channel in the endoscope (telescope) to the surface of the oesophagus to make near instant assessments of its condition without the need for expensive and distressing tissue removal (biopsies). This project plans to move this technique from the laboratory to the clinic by demonstrating that the method is safe and reliable for use in real patients.
Interventions
Oesophageal endoscopy with biopsy
Sponsors
Study design
Eligibility
Inclusion criteria
* Barrett's oesophagus
Exclusion criteria
* Unfit for endoscopic and biopsy assessment
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Device safety testing (no detectable damage in biopsy samples when reviewed by histopathology) | 6 months | Testing of the device for clinical application to demonstrate its use is safe and that is able to acquire diagnostic-quality (see outcome 2) spectra in less than 5 seconds from within the oesophagus. Samples illuminated will be biopsied and sent for routine histopathological analysis. |
Secondary
| Measure | Time frame | Description |
|---|---|---|
| Diagnostic model developed (algorithm able to discriminate disease with >50% specificity and >50% sensitivity) | 6 months | Computer model using multivariate analysis able to discriminate between diseased and non-diseased tissue. The target specificity and sensitivity are low due to small study group sizes. |
Countries
United Kingdom