Computer Assisted Detection & Selection of Serrated Adenomas and Neoplastic Polyps - a New Clinical DRAft (CASSANDRA II)

July 17, 2018 updated by: Dr. Peter Klare, Technical University of Munich

The aim of the study is to develop a computer program which is able to automatically detect colorectal polyps in endoscopic video sequences. Furthermore, the program shall be able to automatically distinguish between adenomas, serrated adenomas and hyperplastic polyps on the basis of optical features of the polyps. Video sequences of polyps will be collected during routine colonoscopy procedures. All polyps will be resected endoscopically so that histopathological diagnoses (gold standard) can be notified.

In the validation phase of the study a computer program will be established which aims to distinguish between adenomas, serrated adenomas and hyperplastic polyps on the basis of optical features derived from the videos. A deep learning approach will be used for programming. Afterwards, in the testing phase of the study, videos of 100 polyps (not used in the validation phase) will be presented to the computer program. The establishment of a well- functioning computer program is the primary aim of the study.

Study Overview

Status

Unknown

Conditions

Intervention / Treatment

Detailed Description

Adenomas are polyps of the colorectum that have the potential to develop into colon cancer [1]. However, some adenomas never become malignant and if they do, progression from adenoma into cancer usually takes a long time. As a result, screening colonoscopy programs were established in order to detect and resect adenomas at an early stage [2]. After resection, polyps should be sent to pathology in order to make a histological diagnosis. Not every colorectal polyp has adenomatous histology. Approximately 40-50% of all polyps contain other benign histology (e.g. hyperplastic polyps). These polyps do not bear the risk of colon cancer.

The implementation of screening programs has led to increasing numbers of colonoscopies in the last years [3]. This approach naturally implies higher amounts of detected polyps. The removal of these polyps and consultation of a pathologist in order to make a diagnosis is time consuming and expensive. An optical- based prediction of polyp histology (adenomatous versus non- adenomatous) would enable endoscopists to save money and to inform patients faster about examination results. The approach of predicting polyp histology on the basis of optical features is called the "optical biopsy" method. The prediction is made by the endoscopists during real-time colonoscopy. The aim of this strategy is to make an optical diagnosis which enables users to resect polyps without sending the specimen to pathology. Narrow Band Imaging (NBI) is a light-filter device which can be switched on during colonoscopy. NBI is useful to better display vascular patterns of the colon mucosa. It has been shown that the use of NBI can facilitate optical classification of colorectal polyps [5]. A NBI- based classification schemes exists which can be used to assign polyps into specific polyp categories (adenomatous versus non- adenomatous) [6].

Prior to the implementation of the optical classification approach for routine use in endoscopy it is necessary to proof its feasibility and accuracy [7]. Otherwise the approach would entail the risk of wrong diagnoses which could lead to wrong recommendations on further diagnostic or therapeutic steps.

Until now, some clinical trials have shown good accuracy for the optical biopsy method [5]. However, there is growing evidence that optical biopsy does not yet meet demanded accuracy thresholds [8]. The aim of our study is to create a computer program that is able to distinguish between adenomas, serrated adenomas and hyperplastic polyps. Video sequences of colorectal polyps will be used for machine learning (validation phase). Afterwards a set of 100 videos will be used to test whether the computer program is able to distinguish between adenomatous and non- adenomatous polyps (primary endpoint). Statistical measures (accuracy, sensitivity, specificity) will be calculated. The 100 videos will also be presented to human experts who will also predict polyp diagnoses based on optical features. Comparing the accuracy of optical predictions made by the computer and by human experts will be another endpoint of the study.

Study Type

Observational

Enrollment (Anticipated)

250

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Locations

  • Germany
      • Munich, Germany, 81675
        • Klinik für Innere Medizin II am Klinikum rechts der Isar der Technischen Universität München München, Deutschland Germany

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (Adult, Older Adult)

Accepts Healthy Volunteers

No

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Patients undergoing routine colonoscopy

Description

Inclusion Criteria:

  • indication for colonoscopy
  • patients >= 18 years

Exclusion Criteria:

  • pregnant women
  • indication for colonoscopy: inflammatory bowel disease
  • indication for colonoscopy: emergency colonoscopy e.g. acute bleeding
  • contraindication for polyp resection e.g. patients on warfarin

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Routine colonoscopy Cohort
Other: Videos of polyps, resection of polyps
Ther is no study specific intervention. Video sequences will be taken if polyps are found in the colon. Polyps will then be resected routinely.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Assessment of the computer- made optical diagnosis of each colorectal polyp
Time Frame: up to 2 weeks

The predicted polyp histology (made optically by the computer program) will be assessed; the predicted diagnosis will be compared with the histopathological diagnosis (gold standard) after resection of the polyp;

(participants will be followed for the duration of hospital stay or outpatient treatment, an expected average of 2 weeks)] [Safety Issue: No] After obtaining the histopathological diagnosis of resected polyps (approximately 3 days - 2 weeks)
up to 2 weeks

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Technical University of Munich

Collaborators

Chair of Computer Aided Medical Procedures & Augmented Reality; Institut für Informatik I16 Technische Universität München

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Anticipated)

August 1, 2018

Primary Completion (Anticipated)

July 1, 2019

Study Completion (Anticipated)

October 1, 2019

Study Registration Dates

First Submitted

July 17, 2018

First Submitted That Met QC Criteria

July 17, 2018

First Posted (Actual)

July 26, 2018

Study Record Updates

Last Update Posted (Actual)

July 26, 2018

Last Update Submitted That Met QC Criteria

July 17, 2018

Last Verified

July 1, 2018

More Information

Terms related to this study

Additional Relevant MeSH Terms

Other Study ID Numbers

  • CASSANDRA II

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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