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Artificial Intelligence System Based on Raman Spectroscopy in Inflammatory Bowel Disease

NCT04888299 · Status: UNKNOWN · Phase: NA · Type: INTERVENTIONAL · Enrollment: 100

Last updated 2021-05-17

No results posted yet for this study

Summary

Inflammatory bowel diseases (IBD) are chronic inflammatory disorders that can be categorized as ulcerative colitis (UC), Crohn's disease (CD) and indeterminate colitis (IC). Deep remission has been shown to improve disease outcome. There may be a lack of concordance between endoscopic and histologic remission. IBD patients with long standing colitis are at risk of developing dysplasia and colorectal cancer (CRC). However, it can be challenging to diagnose dysplasia in IBD patients during colonoscopy, as dysplasia frequently manifests as non-pedunculated lesions that present with only subtle visible changes or are even invisible due to the surrounding inflammation, scarring, pseudopolyps, or hyperplasia. Although white light endoscopy and chromoendoscopy are the current standard modality of imaging, there is still a gap to be bridged, in terms of improving endoscopic diagnosis of dysplasia and improving concordance of endoscopic and histologic remission. Raman spectroscopy is an inelastic light scattering technique provide specific fingerprints of molecular compositions and structures of biological tissues. It may be able to provide additional diagnostic information over standard endoscopy. A second-generation Raman endoscope system for improving in vivo tissue characterization and diagnosis during colonoscopy has been developed (SPECTRA IMDx system). Preliminary data suggested its utility in the diagnosis of colorectal neoplasia during colonoscopy. There is currently a lack of data concerning the application of this novel technology in the context of IBD. Specifically, whether the spectral signals generated can be used to better classify disease remission, and thus achieve higher concordance with histology when compared to standard endoscopy. It is also unclear whether this technology can be used to differentiate dysplastic mucosa from non-dysplastic mucosal in IBD patients.

Hypotheses

1. Raman spectroscopy based artificial intelligence system has the potential to be used to differentiate disease remission from active mucosal inflammation and hence improve concordance between endoscopic and histologic remission, with the potential to decrease the need for random biopsies real-time during colonoscopy.
2. Raman spectroscopy based artificial intelligence system has the potential to differentiate dysplastic mucosa in IBD patients (low grade and high grade dysplasia; colorectal cancer) from non-dysplastic mucosa. real-time during colonoscopy.

Conditions

  • Inflammatory Bowel Diseases

Interventions

DEVICE

Raman spectroscopy (SPECTRA IMDx)

The SPECTRA IMDx comprises a laser system, a spectrometer, a computer with an analysis algorithm installed, and other ancillary parts. The SPECTRA IMDx probe is connected with the main system. The SPECTRA IMDx probe is an assembly of optical fibres and optical components arranged for maximal transmission of light energy. When in use, the laser system will emit a 785nm near infra-red laser that will be transmitted through the SPECTRA IMDx probe to the distal end. When the laser is interrogated upon a tissue surface, the light energy is absorbed and reflected. The reflected energy is then collected from the distal end of the SPECTRA IMDx probe, transmitted back to the main system, and passed through the spectrometer. The collected signal is then processed to obtain the clean Raman signal for diagnostic classification.

Sponsors & Collaborators

  • Changi General Hospital

    lead OTHER

Study Design

Allocation
NA
Purpose
DIAGNOSTIC
Masking
NONE
Model
SINGLE_GROUP

Eligibility

Min Age
21 Years
Max Age
90 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-04-14
Primary Completion
2023-04-30
Completion
2023-04-30

Countries

  • Singapore

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04888299 on ClinicalTrials.gov