Colorectal AdenomaELUFIBLINCT03234725
Analysis of New Endoscopic Features and Variable Stiffness in Colonoscopy: Prospective Randomised Trial
An observational study of Colorectal Adenoma and Colorectal Adenomatous Polyp, run by Bács-Kiskun County Teaching Hospital at 1 site in Hungary.
Trial summary
The aim of the present study is to develop and evaluate a computer-based methods for automated and improved detection and classification of different colorectal lesions, especially polyps. Read more about this study
- Who is it for?
- Ages 18 to 99 years
- Conditions the study is for
- Colorectal Adenoma, Colorectal Adenomatous Polyp
- How many people
- 1,000 participants
- Where
- 1 siteHungary
- Study dates
- 1 Oct 2016to 30 Sep 2018
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 to 99 years
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: All adult patients who did not meet the exclusion criteria were included in the study
Who may be able to join
- 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
- ASA (American Society of Anesthesiology) risk class 1, 2 or 3
Who cannot join
- 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;
Show all 9Show fewer
- 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.
Trial locations and contacts
1 site in 1 country.
Hungary1 site
Bács Kiskun County and Teaching Hospital
Kecskemét, Nyiri Street 38, 6000
About this study
Official title: Prospective Randomised Trial to Analyse the Advantages of the New Virtual Chromoendoscopy Features and the Variable Stiffness in Connection With Our Colonoscopic Examinations
The aim of the present study is to develop and evaluate a computer-based methods for automated and improved detection and classification of different colorectal lesions, 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.
Read the detailed description
Computer-based Classification and Differentiation of Colorectal Polyps Using 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 (light-emitting diode) Multi Light™ technology sets a new standard in light intensity and electronic chromoendoscopy 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.
- Conditions
- Colorectal Adenoma, Colorectal Adenomatous Polyp
- Keywords
- Blue light imaging, Linked color imaging, Optical histology, Adenoma detection rate, Variable stiffness, Deep learning
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| LCI out group | The whitdrawal of the colonoscop happen in LCI mode. | |
| WL (white light) out group | The whitdrawal of the colonoscop happen in WL mode. |
What is being measured
The primary outcome is the main question the study is designed to answer.
diagnostic value of the computer algorithm
diagnostic value of the computer algorithm (sensitivity, specificity, negative predictive value, positive predictive value, accuracy) [ Time Frame: 10 months ] [ Designated as safety issue: No ]
Measured: 2 years
Number of detected serrated polyps
Number of Detected Proximal Serrated lesions, flat polyps and colorectal adenomas in proximal colon
Measured: 2 years
Number of detected polyps
Quantity of total number of colorectal adenomas found in the colon during colonoscopy was recorded and compared.
Measured: 2 years
the accuracy of the NICE (NBI International Colorectal Endoscopic) criteria using FICE versus BLI Eluxeo technology
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. 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.
Measured: 2 years
Inter-observer agreement among the 5 experts
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.
Measured: 2 years
Cecal intubation rate
The proportion of colonoscopy procedures resulting in successful intubation of the cecum.
Measured: 2 years
Propofol need for deep sedation
The main efficacy parameter is the amount of Propofol used for deep sedation during colonoscopy, expressed as the mean for each group.
Measured: 2 years
Secondary outcomes (6)
diagnostic interobserver variability based on the computer algorithm
diagnostic interobserver variability based on the computer algorithm
Measured: 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
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.
Measured: 2 years
Comparison of accuracy of BLI and LCI pictures
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
Measured: 2 years
Improvement of adenoma detection rate by using LCI imaging comparing with that under white endoscopy
Improvement of adenoma detection rate by using LCI imaging comparing with that under white endoscopy
Measured: 2 years
Time-to-cecum
Time from initial insertion of colonoscope until successful intubation of the cecum (min)
Measured: 2 years
Ancillary maneuvers to facilitate procedure
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.
Measured: 2 years
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted31 Jul 2017
- Study start1 Oct 2016
- Primary completion30 Sep 2018
- Study completion30 Sep 2018
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Other trials for Colorectal AdenomaStudies of the same condition, open and under way.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Prospective
- Enrolment
- 1,000 participants (actual)
Sponsor and investigators
- Lead sponsor
- Bács-Kiskun County Teaching Hospital
- Sponsor type
- University, hospital or other
- Collaborators
- Endo-Kapszula Privat Medical Center
- Responsible party
- Principal investigator, László Madácsy Md, PhD, Bács-Kiskun County Teaching Hospital
- Investigators
- Laszlo Madacsy, MD,pHd, Principal investigator, Bács Kiskun Coeunty Teaching Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT03234725
- Sponsor's protocol ID
- Deep001
- Acronym
- ELUFIBLI
- Status last verified
- Jul 2019
- First submitted
- 27 Jul 2017
- Last updated
- 10 Jul 2019
- Results posted
- No
- Data monitoring committee
- Yes
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- No
Study at a glance
From the registry record, last updated by the sponsor on 10 Jul 2019. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- Prospective Randomised Trial to Analyse the Advantages of the New Virtual Chromoendoscopy Features and the Variable Stiffness in Connection With Our Colonoscopic Examinations
- ClinicalTrials.gov ID
- NCT03234725
- Acronym / sponsor ID
- ELUFIBLI / Deep001
- Conditions
- Colorectal Adenoma, Colorectal Adenomatous Polyp
- Keywords
- Blue light imaging, Linked color imaging, Optical histology, Adenoma detection rate, Variable stiffness, Deep learning
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 1,000 participants (actual)
- Lead sponsor
- Bács-Kiskun County Teaching HospitalUniversity, hospital or other
- Collaborators
- Endo-Kapszula Privat Medical Center
- Study start
- 1 Oct 2016 (actual)
- Primary completion
- 30 Sep 2018 (actual)
- Study completion
- 30 Sep 2018 (actual)
- First posted
- 31 Jul 2017 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
The aim of the present study is to develop and evaluate a computer-based methods for automated and improved detection and classification of different colorectal lesions, 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 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 (light-emitting diode) Multi Light™ technology sets a new standard in light intensity and electronic chromoendoscopy 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.
Study design
- Observational model
- Cohort
- Time perspective
- Prospective
- Number of arms
- 2
| Arm | Type | Receives |
|---|---|---|
| LCI out group | – | –The whitdrawal of the colonoscop happen in LCI mode. |
| WL (white light) out group | – | –The whitdrawal of the colonoscop happen in WL mode. |
Who may qualify
- Ages
- 18 to 99 years
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- All adult patients who did not meet the exclusion criteria were included in the study
Key inclusion criteria (4 listed)
- 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
- ASA (American Society of Anesthesiology) risk class 1, 2 or 3
Key exclusion criteria (9 listed)
- 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;
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
diagnostic value of the computer algorithm
Time frame: 2 years
diagnostic value of the computer algorithm (sensitivity, specificity, negative predictive value, positive predictive value, accuracy) [ Time Frame: 10 months ] [ Designated as safety issue: No ]
Number of detected serrated polyps
Time frame: 2 years
Number of Detected Proximal Serrated lesions, flat polyps and colorectal adenomas in proximal colon
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.
the accuracy of the NICE (NBI International Colorectal Endoscopic) 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. 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.
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.
Cecal intubation rate
Time frame: 2 years
The proportion of colonoscopy procedures resulting in successful intubation of the cecum.
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.
6 secondary outcomes
diagnostic interobserver variability based on the computer algorithm
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
Time frame: 2 years
Comparison of accuracy of BLI and LCI pictures
Time frame: 2 years
Improvement of adenoma detection rate by using LCI imaging comparing with that under white endoscopy
Time frame: 2 years
Time-to-cecum
Time frame: 2 years
Ancillary maneuvers to facilitate procedure
Time frame: 2 years
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 10 Jul 2019.
- Individual participant dataSharing planned: No
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Laszlo Madacsy, MD,pHd principal investigator
Bács Kiskun Coeunty Teaching Hospital
1 site in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Colorectal Adenoma and Colorectal Adenomatous Polyp, run by Bács-Kiskun County Teaching Hospital at 1 site in Hungary.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 4 inclusion and 9 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 10 Jul 2019. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 1 site in Hungary. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
diagnostic value of the computer algorithm (time frame: 2 years). The study lists 7 primary outcomes in all. It is what the study was designed to measure, not a finding.
Where can I read the original study information?
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 10 Jul 2019; AzTrials last refreshed its copy on 30 Oct 2026.