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History of Changes for Study: NCT03234725
Analysis of New Endoscopic Features and Variable Stiffness in Colonoscopy: Prospectiv Randomised Trial (ELUFIBLI)
Latest version (submitted July 9, 2019) on ClinicalTrials.gov
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Study Record Versions
Version A B Submitted Date Changes
1 July 27, 2017 None (earliest Version on record)
2 August 3, 2017 Outcome Measures, Study Description, Study Status, Study Identification, Eligibility, Groups and Interventions and Sponsor/Collaborators
3 July 9, 2019 Recruitment Status, Study Status, Contacts/Locations, Groups and Interventions and Study Design
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Study NCT03234725
Submitted Date:  July 27, 2017 (v1)

Open or close this module Study Identification
Unique Protocol ID: Deep001
Brief Title: Analysis of New Endoscopic Features and Variable Stiffness in Colonoscopy: Prospectiv Randomised Trial (ELUFIBLI)
Official Title: Prospectiv Randomised Trial to Analyse the Adventages of the New Virtual Chromoendoscopic Features and the Variabel Stiffness in Connection With Our Colonoscopic Examinations
Secondary IDs:
Open or close this module Study Status
Record Verification: July 2017
Overall Status: Recruiting
Study Start: October 1, 2016
Primary Completion: September 30, 2018 [Anticipated]
Study Completion: September 30, 2022 [Anticipated]
First Submitted: July 27, 2017
First Submitted that
Met QC Criteria:
July 27, 2017
First Posted: July 31, 2017 [Actual]
Last Update Submitted that
Met QC Criteria:
July 27, 2017
Last Update Posted: July 31, 2017 [Actual]
Open or close this module Sponsor/Collaborators
Sponsor: Bács-Kiskun County Teaching Hospital
Responsible Party: Principal Investigator
Investigator: László Madácsy Md, PhD
Official Title: Md, PhD
Affiliation: Bács-Kiskun County Teaching Hospital
Collaborators: Endo-Kapszula Privat Medical Center
Open or close this module Oversight
U.S. FDA-regulated Drug: No
U.S. FDA-regulated Device: No
Data Monitoring: Yes
Open or close this module Study Description
Brief Summary:

The aim of the present study is to develop and evaluate a computer-based methods for automated and improved detectation and classification of different colorectal laesions, especially polyps. For this purpose first, pit pattern and vascularization features of up to 1000 polyps with a size of 10 mm or smaller will be detected and stored in our web based picture database made by a zoom BLI colonoscopy. These polyps are going to be imaged and subsequently removed for histological analysis. The polyp images are analyzed by a newly developed deep learning computer algorithm. The results of the deep learning automatic classification (sensitivity, specificity, negative predictive value, positive predictive value and accuracy) are compared to those of human observers, who were blinded to the histological gold standard.

In a second approach we are planning to use LCI of the colon, rather than the usual white light. Here, we will determine, whether this technique could improve the detection of flat neoplastic lesions, laterally spreading tumors, small pedunculated adenomas and serrated polyps. The polyps are called serrated because of their appearance under the microscope after they have been removed. They tend to be located up high in the colon, far away from the rectum. They have been definitely shown to be a type of precancerous polyp and it is possible that using LCI will make it easier to see them, as they can be quite difficult to see with standard white light.

Detailed Description:

Computer-based Classification and Differentiation of Colorectal Polyps Using Fujifilm Blue Light Imaging (BLI)

Purpose

Recent studies have shown that optical chromoendoscopy with narrow-band imaging (NBI) of Fuji Intelligent Color Enhancement (FICE) is a powerful diagnostic tool for the differentiation between neoplastic and non-neoplastic colorectal polyps. Linked color imaging (LCI) and blue laser imaging (BLI) are two new imaging systems used in endoscopy which are recently developed. BLI was developed to compensate for the limitations of NBI. BLI shows a bright image of the digestive mucosa, enabling the detailed visualization of both the microstructure and microvasculature. The ELUXEO™ endoscopic system powered by Fujifilm's unique 4-LED Multi Light™ technology sets a new standard in light intensity and electronic chromoendoscopic imaging. By combining four different wavelengths and the specific application of intensified from light spectra created by the integrated light source, this technology allows to easily switch between the three imaging modes White Light, Blue Light Imaging (BLI) and Linked Colour Imaging (LCI). Blue light imaging (BLI) is a new system for image-enhanced electronic chromoendoscopy, since the 410 nm LED visualizes vascular microarchitecture, similar to narrow band imaging, and a 450 nm provides white light by excitation. According to three recently published reports, the diagnostic ability of polyp characterization using blue light imaging compares favorably with narrow band imaging. No published data are available to date regarding computer assisted polyp characterization with blue light imaging.

The aim of the present study is to develop and evaluate a computer-based method for automated classification of small colorectal polyps on the basis of pit pattern and vascularization features. In this prospective study up to 1000 polyps with a size of 10 mm or smaller should be detected and stored in our web based picture database made by a zoom BLI colonoscopy. These polyps were imaged and subsequently removed for histological analysis. The polyp images were analyzed by a newly developed deep learning computer algorithm. The proposed computer-based method consists of several steps: picture annotation, preprocessing, vessel segmentation, feature extraction and classification, parameterization, and finally train and test of the multiple neural layer algorithms. The results of the deep learning automatic classification (sensitivity, specificity, negative predictive value, positive predictive value and accuracy) were compared to those of human observers, who were blinded to the histological gold standard.

Condition Colorectal Polyps with a size less then 10 mm

Study Type:

Observational

Study Design:

Observational Model: Cohort Time Perspective: Prospective

Official Title:

Computer-based Classification and Differentiation of Colorectal Polyps Using Fujifilm Blue Light Imaging (BLI)

Linked color imaging (LCI) and magnifying blue laser imaging (BLI) are two new imaging systems used in endoscopy which are recently developed. The newly developed LCI system (FUJIFILM Co.) creates clear and bright endoscopic images by using short-wavelength narrow-band laser light combined with white laser light on the basis of BLI technology. LCI makes red areas appear redder and white areas appear whiter. Thus, it is easier to recognize a slight difference in color of the mucosa. The aim the present study to determine if using LCI of the colon, rather than the usual white light on the colon, will improve the detection of flat neoplastic lesions, laterally spreading tumors, small pedunculated adenomas and serrated polyps. The polyps are called serrated because of their appearance under the microscope after they have been removed. They tend to be located up high in the colon, far away from the rectum. They have been definitely shown to be a type of precancerous polyp and it is possible that using LCI will make it easier to see them, as they can be quite difficult to see with standard white light.

Open or close this module Conditions
Conditions: Colorectal Adenoma
Colorectal Adenomatous Polyp
Keywords: Blue light imaging
Linked color imaging
Optical histology
Adenoma detection rate
Variable stiffness
Deep learning
Open or close this module Study Design
Study Type: Observational
Observational Study Model: Cohort
Time Perspective: Prospective
Biospecimen Retention:
Biospecimen Description:
Enrollment: 1000 [Anticipated]
Number of Groups/Cohorts 2
Open or close this module Groups and Interventions
Groups/Cohorts Interventions
LCI out group
WL out group
Open or close this module Outcome Measures
Primary Outcome Measures:
1. diagnostic value of the computer algorythm
[ Time Frame: 2 years ]

diagnostic value of the computer algorythm (sensitivity, specificity, negative predictive value, positive predictive value, accuracy) [ Time Frame: 10 months ] [ Designated as safety issue: No ]
2. Number of detected serrated polyps
[ Time Frame: 2 years ]

Number of Detected Proximal Serrated lesions, flat polyps and colorectal adenomas in proximal colon
3. Number of detected polyps
[ Time Frame: 2 years ]

Quantity of total number of colorectal adenomas found in the colon during colonoscopy was recorded and compared.
4. the accuracy of the NICE criteria using FICE versus BLI Eluxeo technology
[ Time Frame: 2 years ]

the accuracy of the NICE criteria using FICE versus BLI Eluxeo technology without optical zoom for differentiating between the non-neoplastic and neoplastic histotypes in diagnoses with high-confidence on a video-library of 120 polyps reviewed by 5 experts (ML, SZM, OL, SZA, DZS). 5 experts will review pictures from a web-library of subcentimetric polyps removed and histologically verified and will assess each of the three NICE criteria (colour/vascularization/surface), and classify the lesion as neoplastic or non-neoplastic with low or high confidence.
5. Inter-observer agreement among the 5 experts
[ Time Frame: 2 years ]

Inter-observer agreement among the 5 experts [ Time Frame: up to 6 months ] [ Designated as safety issue: No ] The inter-observer agreement, among the 5 experts, on the final diagnosis (neoplastic or non-neoplastic) and on each individual NICE criterion for each polyp will be determined by using K statistics.
6. Cecal intubation rate
[ Time Frame: 2 years ]

The proportion of colonoscopy procedures resulting in successful intubation of the cecum.
7. Propofol need for deep sedation
[ Time Frame: 2 years ]

The main efficacy parameter is the amount of Propofol used for deep sedation during colonoscopy, expressed as the mean for each group.
Secondary Outcome Measures:
1. diagnostic interobserver variability based on the computer algorythm
[ Time Frame: 2 years ]

diagnostic interobserver variability based on the computer algorythm
2. the accuracy of the NICE criteria using FICE versus BLI Eluxeo technology with 50x optical zoom for differentiating between the non-neoplastic and neoplastic histotypes
[ Time Frame: 2 years ]

the accuracy of the NICE criteria using FICE versus BLI Eluxeo technology with 50x optical zoom for differentiating between the non-neoplastic and neoplastic histotypes in diagnoses with high-confidence on a video-library of 120 polyps reviewed by 5 experts (ML, SZM, OL, SZA, DZS)5 experts will review pictures from a web-library of subcentimetric polyps removed and histologically verified and will assess each of the three NICE criteria (colour/vascularization/surface), and classify the lesion as neoplastic or non-neoplastic with low or high confidence.
3. Comparison of accuracy of BLI and LCI pictures
[ Time Frame: 2 years ]

Comparison of accuracy of BLI and LCI pictures with and without zoom on the final diagnosis (neoplastic or non-neoplastic polyp) as compared to histology
4. Improvement of adenoma detection rate by using LCI imgaing comparing with that under white endoscopy
[ Time Frame: 2 years ]

Improvement of adenoma detection rate by using LCI imgaing comparing with that under white endoscopy
5. Time-to-cecum
[ Time Frame: 2 years ]

Time from initial insertion of colonoscope until successful intubation of the cecum (min)
6. Ancillary maneuvers to facilitate procedure
[ Time Frame: 2 years ]

A number of added maneuvers, including abdominal pressure, repositioning of the patient, endoscope loop reduction techniques, used to facilitate advancement of the endoscope during the procedure.
Open or close this module Eligibility
Study Population: All adult patients who did not meet the exclusion criteria were included in the study
Sampling Method: Probability Sample
Minimum Age: 18 Years
Maximum Age: 99 Years
Sex: All
Gender Based:
Accepts Healthy Volunteers: No
Criteria:

Inclusion Criteria:

  • The patient must sign, understand and provide written consent for the procedure.
  • Undergoing colonoscopy at our endoscopy unit for any indication in Propofol deep sedation
  • Intact colon and rectum
  • American Society of Anesthesiology risk class 1, 2 or 3

Exclusion Criteria:

  • Patients with inflammatory bowel disease;
  • Patients with poor bowel preparation; (Boston score <4)
  • Female patients with pregnancy;
  • Patients with mechanical bowel obstruction;
  • Patients with diverticulitis or toxic megacolon;
  • Patients with a history of radiation therapy to abdomen or pelvis;
  • Patients with a history of severe cardiovascular, pulmonary, liver or renal disease and high ASA (>3) risk of propofol sedation;
  • Personal history of coagulation disorders or use of anticoagulants;
  • Patients who are currently enrolled in another clinical investigation in which the intervention might compromise the safety of the patient's participation in this study.
Open or close this module Contacts/Locations
Locations: Hungary, Nyiri street 38
Bács Kiskun County and Teaching Hospital
[Recruiting]
Kecskemét, Nyiri street 38, Hungary, 6000
Contact:Contact: Milan Szalai, MD +36 70 414 9747 dr.szalai.milan@gmail.com
Contact:Contact: László Madácsy, MD, Phd +36 22 788 365 recepcio@endo-kapszula.hu
Contact:Principal Investigator: Laszlo Madacsy, MD, Phd
Contact:Sub-Investigator: Milan Szalai, MD
Contact:Sub-Investigator: Attila Szepes, MD
Contact:Sub-Investigator: Zsolt Dubravcsik, MD
Open or close this module IPDSharing
Plan to Share IPD: No
Open or close this module References
Citations:
Links:
Available IPD/Information:

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