A Randomized Study Comparing Autofluorescence Imaging(AFI) Followed by Narrow Band Imaging(NBI) With Videoendoscopy for the Detection of High Risk Lesions of Stomach

NCT ID: NCT01132534

Last Updated: 2010-06-16

Basic Information

• Recruitment Status: COMPLETED
• Total Enrollment: 64 participants
• Study Classification: OBSERVATIONAL
• Study Start Date: 2007-06-30
• Study Completion Date: 2008-04-30

Brief Summary

Videoendoscopy is the standard tool for examination of gastrointestinal tract. However, precancerous lesions and early gastric cancer can be easily missed by routine videoendoscopy. Autofluorescence Imaging (AFI) and Narrow band imaging (NBI) are 2 new imaging systems used in endoscopy which are recently developed. AFI based on the presence of natural tissue fluorescence on the gastrointestinal tract. By computation of the difference in the reflecting images, the system can reveal early cancers that are not detectable by standard endoscopy. NBI is a high resolution imaging using lights with narrowed wavelength range, which able to enhance the fine structure of the mucosa. Recent studies suggested combined AFI and NBI can improve the detection of early esophageal and gastric cancers.

The investigators are conducting a prospective randomized cross-over study to compare the accuracy between this combined AFI/NBI imaging with standard videoendoscopy in the detection of precancerous lesions and gastric cancer in a high risk population inSingapore. The investigators hypothesis is that this new combined imaging system improves the investigators detection of high risk lesions of stomach.

Detailed Description

Gastric cancer remains one of the leading causes of cancer deaths worldwide. Early detection and diagnosis of gastric cancer improves the outcomes of treatment. However, most of gastric cancers detected in Singapore are late and advanced in stages.

Videoendoscopy is the standard tool for examination of gastrointestinal tract. Despite the improvement of technology, early gastric cancers can be easily missed by routine examination, because there are few morphological changes. Therefore, a functional imaging modality, that can distinguish abnormal lesion from surrounding normal mucosa may complement the current videoendoscopy.

Autofluorescence Imaging (AFI) based on the presence of natural tissue fluorescence on the gastrointestinal tract. When the mucosa was exposed by an excitation light, certain endogenous molecules (fluorophores) will emit fluorescence light of longer wavelength. The fluorescent light can be detected and spectrally analyzed. By computation of the difference in the reflecting images, the system can specify lesions, including malignancies from the adjacent mucosa, and can reveal early cancers that are not detectable by standard endoscopy.

Narrow band imaging (NBI) is another novel optical imaging technique based on high resolution imaging, which aims at enhancing the fine structure of the mucosa. In NBI, the band widths of the red, blue, green components of the excitation light are narrowed to certain wavelength ranges, which allow better contrast of the superficial mucosa and the vascular structure. NBI has a maximum zoom capacity of 115 times. Abnormal lesions are detected by the presence of abnormal mucosal and vascular patterns.

Recent studies suggested that these AFI and NBI systems can be complementary to each other. The resolution of AFI is low but it can be used as a 'red flag' technique to screen any suspicious lesions from the normal mucosa. On the other hand, NBI produces high resolution images which allows detailed examination and subsequent target biopsy of the suspicious lesions based on AFI. Preliminary reports from Japan and the Netherlands suggested this combined imaging method improves the detection of early esophageal and gastric cancers. Recently, a new endoscopy system has been developed that incorporates standard videoendoscopy system with both AFI and NBI modes. By pressing a switch, the endoscopy system can switch from normal white light to either a narrow band light or autofluorescence mode. This novel system reduces the convenience and discomfort for the patients to avoid repeated intubation. The purpose of this study is to prospectively evaluate this combined imaging modality for detection of high risk gastric lesions and early cancers by comparing it with standard videoendoscopy in a randomized fashion.

Conditions

Gastric Cancer

Study Design

• Observational Model Type: CASE_CROSSOVER
• Study Time Perspective: PROSPECTIVE

Study Groups

SE then AFI/NBI

Patients will be randomised to be examined by standard videoendoscopy (SE) then combined AFI/NBI during the esophagogastroduodenoscopy (EGD) examination at same setting.

No interventions assigned to this group

AFI/NBI then SE

Patients will be randomised to be examined by combined AFI/NBI then standard videoendoscopy (SE) during the EGD examination at same setting.

No interventions assigned to this group

Eligibility Criteria

Inclusion Criteria

1. Age >=50

2. Ethnic Chinese

3. Presenting symptom - dyspepsia

Exclusion Criteria

1. Patients who are unable to give an informed consent.

2. Patients with previous surgery of the stomach.

3. Patients presented with active gastrointestinal bleeding.

• Minimum Eligible Age: 50 Years
• Eligible Sex: ALL
• Accepts Healthy Volunteers: Yes

Sponsors

National University of Singapore

OTHER

Sponsor Role: collaborator

National University Hospital, Singapore

OTHER

Sponsor Role: lead

Responsible Party

National University Hospital, Singapore

Principal Investigators

Jimmy BY So, MBChB

Role: PRINCIPAL_INVESTIGATOR

National University Hospital, Singapore

References

So J, Rajnakova A, Chan YH, Tay A, Shah N, Salto-Tellez M, Teh M, Uedo N. Endoscopic tri-modal imaging improves detection of gastric intestinal metaplasia among a high-risk patient population in Singapore. Dig Dis Sci. 2013 Dec;58(12):3566-75. doi: 10.1007/s10620-013-2843-2. Epub 2013 Sep 1.

Reference Type: DERIVED

PMID: 23996468 (View on PubMed)

Other Identifiers

DSRB D/07/163

Identifier Type: -

Identifier Source: org_study_id