Neoplasms

All Conditions

Symptoms and General Pathology

Adenoma

Polyps

Adenomatous Polyps

Neoplasms, Glandular and Epithelial

Neoplasms by Histologic Type

All Drugs and Chemicals

Imidacloprid

The whitdrawal of the colonoscop happen in LCI mode.

The whitdrawal of the colonoscop happen in WL mode.

Laszlo Madacsy, MD,pHd

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.

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.

Analysis of New Endoscopic Features and Variable Stiffness in Colonoscopy: Prospective Randomised Trial

Prospective Randomised Trial to Analyse the Advantages of the New Virtual Chromoendoscopy Features and the Variable Stiffness in Connection With Our Colonoscopic Examinations

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 Proximal Serrated lesions, flat polyps and colorectal adenomas in proximal colon

Quantity of total number of colorectal adenomas found in the colon during colonoscopy was recorded and compared.

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 \[ Time Frame: up to 6 months \] \[ Designated as safety issue: No \] 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.

The proportion of colonoscopy procedures resulting in successful intubation of the cecum.

The main efficacy parameter is the amount of Propofol used for deep sedation during colonoscopy, expressed as the mean for each group.

diagnostic interobserver variability based on the computer algorithm

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.

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

Improvement of adenoma detection rate by using LCI imaging comparing with that under white endoscopy

Time from initial insertion of colonoscope until successful intubation of the cecum (min)

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.

Endo-Kapszula Privat Medical Center

Bács-Kiskun County Teaching Hospital

Clinical Professor

Pathological Conditions, Anatomical

Patients who have a colonoscopy in regular care as part of the Dutch colorectal screening program, in the context of complaints or in the context of the follow-up of previously diagnosed bowel diseases. And who have at least one colorectal polyp found and resected during the examination.

Optical diagnosis of colorectal polyps made with computer-aided diagnosis (CADx) using state-of-the-art machine learning methods and deep learning architectures.

Computer-aided diagnosis (CADx)

Optical diagnosis of colorectal polyps made with BLI Adenoma Serrated International Classification (BASIC), both by exert endoscopists and novices.

BLI Adenoma Serrated International Classification (BASIC)

Ad Masclee, Prof. Dr.

Primary, this study aims to develop and validate a computer-aided diagnosis (CADx) system for the characterization of colorectal polyps.

Second, this study evaluates the effect of using a clinical classification model Blue Light Imaging Adenoma Serrated International (BASIC) on the diagnostic accuracy of the optical diagnosis of colorectal polyps compared to intuitive optical diagnosis for both expert endoscopists and novices.

Optical diagnosis of colorectal polyps, the in-vivo characterization of the histology by endoscopists, is of increasing interest for clinical endoscopy practice. Recent studies have shown that thresholds for optical diagnosis are met in highly selected groups of expert endoscopists, but the same is not true in community endoscopy practices. In order to improve optical diagnosis, imaging enhancement techniques and the use of artificial intelligence are proposed.

This observational study developes a computer-aided diagnosis (CADx) system to differentiate between benign and (pre-)malignant CRPs, using state-of-the-art machine learning methods and deep learning architectures. For the development, HDWL and BLI images are used. The CADx is trained using histology as gold standard. The CADx is externally validated using on a set of 60 colorectal polyps. This study will evaluate if the optical diagnosis of colorectal polyps can be improved with the aid of CADx.

In addition, both expert endoscopists and novices optically diagnose the colorectal polyps. In the first, pre-training phase, endoscopists optically diagnose colorectal polyps based on intuition. Afterwards, in the post-training phase, the same set of colorectal polyps is optically diagnosed based on a clinical classification system; BLI Adenoma Serrated International Classification (BASIC). This study will evaluate if the optical diagnosis of colorectal polyps can be improved with the aid of BASIC in both expert and non-expert hands.

Colorectal polyps are resected for histological evaluation. This specimen is resected because of regular care, not for study purposes.

Improving Optical Diagnosis of Colorectal Polyps Using CADx and BASIC.

Improving Optical Diagnosis of Colorectal Polyps Using Computer-aided Diagnosis (CADx) and the BLI Adenoma Serrated International Classification (BASIC).

At this moment, there is no plan to share individual participant data.

The diagnostic accuracy of characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx in comparison to the diagnostic accuracy of both expert endoscopists and novices. In which histology is the gold standard.

The diagnostic accuracy of both expert endoscopists and novices in characterizing colorectal polyps (into hyperplastic polyp, adenoma, sessile serrated adenoma, or adenocarcinoma) based on the clinical classification model BASIC, in comparison to the diagnostic accuracy based on intuition. In which histology is the gold standard.

The sensitivity, specificity, negative and positive predictive value of characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx.

Area Under ROC Curve (AUC) of CADx for characterizing colorectal polyps (into benign versus (pre-)malignant) made by CADx.

The sensitivity, specificity, negative and positive predictive value of characterizing colorectal polyps (into hyperplastic polyp, adenoma, sessile serrated adenoma, or adenocarcinoma) of both expert endoscopists and novices.

The diagnostic accuracy, sensitivity, specificity, negative and positive predictive value of both expert endoscopists and novices for optical diagnosis made with high (\>90%) confidence.

The interobserver agreement of experts, novices and CADx for characterizing colorectal polyps.

The computation time per image of CADx for characterizing colorectal polyps.

Catharina Ziekenhuis Eindhoven

Eindhoven University of Technology

Maastricht University Medical Center

Blue light imaging

Pradeep Z Bhandari, Prof

Bowel cancer is the third most common cancer in the UK. It develops through smaller growths in the bowel called polyps. Early recognition and removal of these polyps result in prevention of developing bowel cancer in an individual. However, not all polyps will lead to cancer, certain polyps are just growths of normal tissue and can be left in the bowel. We therefore need to know which polyps to remove and which ones to leave. One way of doing this is to have a better look at these polyps. This can be done by new technologies. One of them is called Blue Light Imaging (BLI). This is a new light source at the end of the camera which is activated by the push of a button. It will help us in looking at these polyps more closely.

This helps us decide which polyps to remove and which ones are safe to leave as there is always a small risk in removing a polyp. It would also give us a better idea as to when to repeat the camera test if necessary (endoscopic surveillance). By reducing the number of polyps resected and sent to the pathology labs for diagnosis, the work load on the pathology department is also reduced and in the process, providing cost savings to the Trust, The study aims to see if using Blue Light during endoscopy helps us to identify and characterize small polyps better

Advanced endoscopic imaging can facilitate the characterisation of neoplastic and non-neoplastic polyps. Accurate identification of small non-neoplastic polyps (e.g. rectosigmoid hyperplastic polyps) that do not harbour malignant potential can lead to future implementation of a 'resect and discard' or 'diagnose and leave' strategy. However, there is insufficient evidence that endoscopists are able to attain high enough levels of optical diagnostic performance in-vivo in order to implement this strategy safely. Blue Light Imaging (BLI) is a new enhanced imaging technology that enhances mucosal surface and vessel patterns. A specific BLI classification was recently developed to enable better characterisation of colorectal polyps (BLI Adenoma Serrated International Classification - BASIC). The use of this technology with the appropriate classification to enhance its performance has not yet been tested in clinical settings of polyp surveillance and screening colonoscopy amongst general endoscopists.

BLAST is a multicentre prospective observational study which will compare BLI optical diagnosis with histological assessment (as a reference standard) for patients with small polyps (\<10mm) identified at colonoscopy.

BLI Based Adenoma Surveillance Strategy

BLI Based Adenoma Surveillance Strategy: BLAST Study

Anonymised data regarding ensdoscopic findings and histological diagnosis might be shared with other researchers if the need arises.

Accuracy of BLI in optical diagnosis of small colorectal polyps

Economic implications of replacing histological diagnosis with optical diagnosis

Study title	NCT ID	Conditions	Interventions	Eligibility	Organization
Analysis of New Endoscopic Features and Variable Stiffness in Colonoscopy: Prospective Randomised Trial	NCT03234725	Colorectal Aden... Colorectal Aden...		18 Years - 99 Years	Bács-Kiskun County Teaching Hospital
Analysis of New Endoscopic Features and Variable Stiffness in Colonoscopy: Prospective Randomised Trial	NCT03234725	Colorectal Aden... Colorectal Aden...		18 Years - 99 Years	Bács-Kiskun County Teaching Hospital
Improving Optical Diagnosis of Colorectal Polyps Using CADx and BASIC.	NCT04349787	Colorectal Canc... Colorectal Poly...	Computer-aided ... BLI Adenoma Ser...	18 Years -	Maastricht University Medical Center
Analysis of New Endoscopic Features and Variable Stiffness in Colonoscopy: Prospective Randomised Trial	NCT03234725	Colorectal Aden... Colorectal Aden...		18 Years - 99 Years	Bács-Kiskun County Teaching Hospital
BLI Based Adenoma Surveillance Strategy	NCT04111601	Colorectal Poly...	Blue light imag...	18 Years -	Portsmouth Hospitals NHS Trust

Spots Global Cancer Trial Database for blue light imaging