Artificial Intelligence System Based on Raman Spectroscopy in Inflammatory Bowel Disease

NCT04888299 | Unknown

• 1 other identifier: 2021/2000
• Study Type: interventional
• Target: 100
• Locations: 1 country
• Sites: 1

Brief 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. 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. 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

Keywords

inflammatory bowel disease

Outcome Measures

Primary Outcomes (1)

• Feasibility of Raman spectroscopy to identify mucosal healing in IBD and IBD-related dysplasia against the gold standard of histopathology

  sensitivity, specificity

  24 months

Secondary Outcomes (1)

• Diagnostic performance of Raman spectroscopy for assessment of mmucosal healing in IBD and IBD-related dysplasia against the gold standard of histopathology

  24 months

Interventions

Raman spectroscopy (SPECTRA IMDx) DEVICE

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.

Eligibility Criteria

• Age: 21 Years - 90 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)

You may qualify if:

• Known or suspected diagnosis of ulcerative colitis or Crohn's disease
• Age 21 to 90 years (selected age range based on demographic of patients managed at Changi General Hospital)
• Ability to provide informed consent

You may not qualify if:

• Presence of significant coagulopathy that precludes endoscopic biopsies
• Refusal to provide consent
• Pregnant subjects
• Incarcerated status

Sponsors & Collaborators

• Changi General Hospital: lead

Study Sites (1)

Changi General Hospital

Singapore, 529889, Singapore

RECRUITING

MeSH Terms

Conditions

Inflammatory Bowel Diseases

Interventions

Spectrum Analysis, Raman

Condition Hierarchy (Ancestors)

Gastroenteritis; Gastrointestinal Diseases; Digestive System Diseases; Intestinal Diseases

Intervention Hierarchy (Ancestors)

Scattering, Radiation; Chemistry Techniques, Analytical; Investigative Techniques; Spectrum Analysis

Central Study Contacts

Tiing Leong Ang

CONTACT

+65-6788 8833; ang.tiing.leong@singhealth.com.sg

Study Design

• Study Type: interventional
• Phase: not applicable
• Allocation: NA
• Masking: NONE
• Purpose: DIAGNOSTIC
• Intervention Model: SINGLE GROUP
• Sponsor Type: OTHER
• Responsible Party: SPONSOR

Study Record Dates

• First Submitted: April 28, 2021
• First Posted: May 17, 2021
• Study Start: April 14, 2021
• Primary Completion: April 1, 2023
• Study Completion: April 1, 2023
• Last Updated: May 17, 2021

Record last verified: 2021-05

Data Sharing

• IPD Sharing: Will not share

Locations

SG (1)