The purpose of this study is to examine the role of an automatic polyp detection software (henceforth referred to as the research software) as a support system during colonoscopy; a procedure during which a physician uses a colonoscope or scope, to look inside a patient's rectum and colon. The scope is a flexible tube with a camera-to see the lining of the colon. The research software is used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy.
The research software used in this study was programmed by a company in Shanghai, which develops artificial intelligence software for computer aided diagnostics.
The research software was developed using a large repository (database or databases) of polyp images where expert colonoscopists outlined polyps and suspicious lesions. The software was subsequently developed and validated using several databases of images and video to operate in near real-time or within minutes of photographing the tissue. It is intended to point out polyps and suspicious lesions on a separate screen that stands behind the primary monitor during colonoscopy. It is not expected to change the colonoscopy procedure in any way, and the physician will make the final determination on whether or not to biopsy or remove any lesion in the colon wall.
The research software will not record any video data during the colonoscopy procedure. In the future, this software may help gastroenterologists detect precancerous areas and decrease the incidence of colon cancer in the United States.
Condition or disease | Intervention/treatment | Phase |
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Polyp, Adenomatous Colo-rectal Cancer | Device: Computer Aided Diagnostic Software | Not Applicable |
Length of Study - The duration of the study is expected to be 8-12 months. Enrollment of study patients will cease when approximately 250 patients have been enrolled.
Study Design- Design will be a multi-center, prospective, unblinded randomized control trial. Patients referred for either screening or surveillance colonoscopy will be included.
Equipment: Aside from standard of care scope used, a second computer monitor that will stand behind the standard monitor used during colonoscopy. Additionally , a computer system unit with an operating system.
Standard Clinical Procedure Typically, intravenous sedation using a combination of benzodiazepine and narcotic medications (with or without propofol under the supervision of a trained anesthesiologist) are used for colonoscopy. Continuous pulse oximetry and blood pressure monitoring is used throughout the procedure. Supplemental oxygen is used as needed. Patients are usually placed in the left lateral decubitus position and the colonoscope is introduced into the rectum. The colonoscope is advanced under direct visualization until the cecum and appendiceal orifice is reached. The colonoscope is usually retroflexed within the rectum. The colonoscopist carefully inspects each segment of colon during advancement and then again on withdrawal of the colonoscope. Any suspicious lesions encountered during insertion or withdrawal are inspected by the colonoscopist and a final determination is made by the clinician on whether or not to remove a given lesion. Any lesion that is deemed suspicious or polypoid is removed by en-bloc polypectomy, piecemeal polypectomy, or may be referred for endoscopic mucosal resection (EMR) at a later date. After the procedure, patients recover in the post-procedural recovery room. After the procedure, results are discussed with the patient. The ability of colonoscopy to detect lesions is discussed with the patient as well as the fact that a small percentage of polyps and other lesions may be missed during the test.
Study Procedure Patients will receive a colonoscopy with a gastroenterologist. During the standard clinical procedural protocol and for the study period, colonoscopists will have the benefit of a second monitor that will project the polyp detection algorithm in real-time over the video output of the colonoscopy. The algorithm will detect suspicious, polyp-like lesions within the lumen of the colon, and during the procedure a research assistant will view the second monitor at all times and record a time stamp for any potential polyps on an intra-procedural data collection sheet.
Data Collection Variables collected and measured will include colonoscopist(s) performing the procedure, number of adenomas noted per procedure, adenoma detection rate for a given colonoscopist, number of polyps detected per procedure, polyp detection rate (the proportion of colonoscopic examinations performed that detect one or more polyps), cecal intubation rate, time needed to reach the cecum, time needed to withdraw colonoscope both when polyps are identified (and thus need to be removed) and on normal colonoscopy, level of sedation, and complications: Acute if within 48 hours of procedure & delayed if within 3-30 days after procedure.
Data Analysis - Normally distributed continuous variables will be summarized using means and standard deviations while non-normally distributed continuous variables will be summarized using medians and ranges.
Study Type : | Interventional (Clinical Trial) |
Estimated Enrollment : | 200 participants |
Allocation: | Randomized |
Intervention Model: | Parallel Assignment |
Intervention Model Description: | In this study, the colonoscopist will carefully inspect segments of colon during advancement and then again on withdrawal of the colonoscope. Those who qualify will be randomized into two arms, as detailed in the bullets below: scope Insertion will be the same for both arms, without the aid of the research software. Below are two groups that qualifying subjects will be randomized into:
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Masking: | None (Open Label) |
Primary Purpose: | Diagnostic |
Official Title: | Computer Aided Detection of Polyps in the Colon |
Actual Study Start Date : | May 7, 2019 |
Estimated Primary Completion Date : | December 2020 |
Estimated Study Completion Date : | December 2020 |
Arm | Intervention/treatment |
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Experimental: Arm-1 Standard Colonoscopy/AI-Assisted Combined Colonoscopy
Normal scope insertion and withdrawal first, followed by a second withdrawal with the research software running on a separate screen to catch any additional polyps missed during the first withdrawal.
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Device: Computer Aided Diagnostic Software
The research software is deep learning algorithm used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy. In its current form, the automatic polyp detection system is installed on a computer system unit that utilizes an an operating system.
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Experimental: Arm-2 AI-Assisted Combined Colonoscopy/Standard Colonoscopy
Normal scope insertion but first withdrawal with the research software running on a separate screen, followed by a second withdrawal without the research software running.
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Device: Computer Aided Diagnostic Software
The research software is deep learning algorithm used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy. In its current form, the automatic polyp detection system is installed on a computer system unit that utilizes an an operating system.
|
Adenoma Miss Rate (AMR), to determine if the combination technique identifies more adenomas compared to the standard technique.
AMR will be calculated as the number of adenomas detected on the second pass or portion in either group divided by the total number of adenomas detected during both passes
To determine the accuracy of the polyp detection software by determining if the combination technique identifies more polyps compared to the standard technique: Per-patient true positive, false positive and false negative will be recorded.
True positives will be defined as lesions that are detected for >2 seconds by the research software and are deemed to be consistent in appearance with a polyp by the endoscopist. False positives will be defined as lesions that are detected for > 2 seconds by the research software but are ultimately deemed by the endoscopist to have a gross appearance not consistent with polyp. False negatives will be defined as lesions that are not detected, or detected for <2 seconds by the research software, but are deemed by the endoscopist to be consistent with polyp
Ages Eligible for Study: | 22 Years and older (Adult, Older Adult) |
Sexes Eligible for Study: | All |
Accepts Healthy Volunteers: | No |
Inclusion Criteria:
Exclusion Criteria:
Contact: Tyler M. Berzin, MD | [617] 632-8623 | tberzin@bidmc.harvard.edu | |
Contact: Jeremy R Glissen Brown, MD | jglissen@bidmc.harvard.edu |
United States, Illinois | |
University of Chicago | Recruiting |
Chicago, Illinois, United States, 60637 | |
Contact: Kristi Kearney, RN 773-834-7414 kkearney@medicine.bsd.uchicago.edu | |
Principal Investigator: Neil Sengupta, MD | |
United States, Massachusetts | |
Beth Israel Deaconess Medical Center | Recruiting |
Boston, Massachusetts, United States, 02130 | |
Contact: Tyler M Berzin, MD 617-632-8623 tberzin@bidmc.harvard.edu | |
Principal Investigator: Tyler M Berzin, MD | |
United States, New York | |
NYU Langone | Recruiting |
New York, New York, United States, 10016 | |
Contact: Gigi Ghiasian 201-410-6849 GhonchGhiasian@nyulangone.org | |
Principal Investigator: Seth Gross, MD | |
United States, Texas | |
Baylor College of Medicine | Recruiting |
Houston, Texas, United States, 77030 | |
Contact: Chandra Kovvali 713-798-2308 chandralekha.Kovvali@bcm.edu | |
Principal Investigator: Nabil Mansour, MD |
Principal Investigator: | Tyler M Berzin, MD | Beth Israel Deaconess Medical Center |
Tracking Information | |||||||||||||||
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First Submitted Date ICMJE | April 20, 2019 | ||||||||||||||
First Posted Date ICMJE | April 24, 2019 | ||||||||||||||
Last Update Posted Date | June 22, 2020 | ||||||||||||||
Actual Study Start Date ICMJE | May 7, 2019 | ||||||||||||||
Estimated Primary Completion Date | December 2020 (Final data collection date for primary outcome measure) | ||||||||||||||
Current Primary Outcome Measures ICMJE |
Adenoma Miss Rate (AMR) [ Time Frame: One Hour ] Adenoma Miss Rate (AMR), to determine if the combination technique identifies more adenomas compared to the standard technique.
AMR will be calculated as the number of adenomas detected on the second pass or portion in either group divided by the total number of adenomas detected during both passes
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Original Primary Outcome Measures ICMJE | Same as current | ||||||||||||||
Change History | |||||||||||||||
Current Secondary Outcome Measures ICMJE |
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Original Secondary Outcome Measures ICMJE | Same as current | ||||||||||||||
Current Other Pre-specified Outcome Measures | Not Provided | ||||||||||||||
Original Other Pre-specified Outcome Measures | Not Provided | ||||||||||||||
Descriptive Information | |||||||||||||||
Brief Title ICMJE | Computer Aided Detection of Polyps in the Colon | ||||||||||||||
Official Title ICMJE | Computer Aided Detection of Polyps in the Colon | ||||||||||||||
Brief Summary |
The purpose of this study is to examine the role of an automatic polyp detection software (henceforth referred to as the research software) as a support system during colonoscopy; a procedure during which a physician uses a colonoscope or scope, to look inside a patient's rectum and colon. The scope is a flexible tube with a camera-to see the lining of the colon. The research software is used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy. The research software used in this study was programmed by a company in Shanghai, which develops artificial intelligence software for computer aided diagnostics. The research software was developed using a large repository (database or databases) of polyp images where expert colonoscopists outlined polyps and suspicious lesions. The software was subsequently developed and validated using several databases of images and video to operate in near real-time or within minutes of photographing the tissue. It is intended to point out polyps and suspicious lesions on a separate screen that stands behind the primary monitor during colonoscopy. It is not expected to change the colonoscopy procedure in any way, and the physician will make the final determination on whether or not to biopsy or remove any lesion in the colon wall. The research software will not record any video data during the colonoscopy procedure. In the future, this software may help gastroenterologists detect precancerous areas and decrease the incidence of colon cancer in the United States. |
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Detailed Description |
Length of Study - The duration of the study is expected to be 8-12 months. Enrollment of study patients will cease when approximately 250 patients have been enrolled. Study Design- Design will be a multi-center, prospective, unblinded randomized control trial. Patients referred for either screening or surveillance colonoscopy will be included. Equipment: Aside from standard of care scope used, a second computer monitor that will stand behind the standard monitor used during colonoscopy. Additionally , a computer system unit with an operating system. Standard Clinical Procedure Typically, intravenous sedation using a combination of benzodiazepine and narcotic medications (with or without propofol under the supervision of a trained anesthesiologist) are used for colonoscopy. Continuous pulse oximetry and blood pressure monitoring is used throughout the procedure. Supplemental oxygen is used as needed. Patients are usually placed in the left lateral decubitus position and the colonoscope is introduced into the rectum. The colonoscope is advanced under direct visualization until the cecum and appendiceal orifice is reached. The colonoscope is usually retroflexed within the rectum. The colonoscopist carefully inspects each segment of colon during advancement and then again on withdrawal of the colonoscope. Any suspicious lesions encountered during insertion or withdrawal are inspected by the colonoscopist and a final determination is made by the clinician on whether or not to remove a given lesion. Any lesion that is deemed suspicious or polypoid is removed by en-bloc polypectomy, piecemeal polypectomy, or may be referred for endoscopic mucosal resection (EMR) at a later date. After the procedure, patients recover in the post-procedural recovery room. After the procedure, results are discussed with the patient. The ability of colonoscopy to detect lesions is discussed with the patient as well as the fact that a small percentage of polyps and other lesions may be missed during the test. Study Procedure Patients will receive a colonoscopy with a gastroenterologist. During the standard clinical procedural protocol and for the study period, colonoscopists will have the benefit of a second monitor that will project the polyp detection algorithm in real-time over the video output of the colonoscopy. The algorithm will detect suspicious, polyp-like lesions within the lumen of the colon, and during the procedure a research assistant will view the second monitor at all times and record a time stamp for any potential polyps on an intra-procedural data collection sheet. Data Collection Variables collected and measured will include colonoscopist(s) performing the procedure, number of adenomas noted per procedure, adenoma detection rate for a given colonoscopist, number of polyps detected per procedure, polyp detection rate (the proportion of colonoscopic examinations performed that detect one or more polyps), cecal intubation rate, time needed to reach the cecum, time needed to withdraw colonoscope both when polyps are identified (and thus need to be removed) and on normal colonoscopy, level of sedation, and complications: Acute if within 48 hours of procedure & delayed if within 3-30 days after procedure. Data Analysis - Normally distributed continuous variables will be summarized using means and standard deviations while non-normally distributed continuous variables will be summarized using medians and ranges. |
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Study Type ICMJE | Interventional | ||||||||||||||
Study Phase ICMJE | Not Applicable | ||||||||||||||
Study Design ICMJE | Allocation: Randomized Intervention Model: Parallel Assignment Intervention Model Description: In this study, the colonoscopist will carefully inspect segments of colon during advancement and then again on withdrawal of the colonoscope. Those who qualify will be randomized into two arms, as detailed in the bullets below: scope Insertion will be the same for both arms, without the aid of the research software. Below are two groups that qualifying subjects will be randomized into:
Primary Purpose: Diagnostic |
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Condition ICMJE |
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Intervention ICMJE | Device: Computer Aided Diagnostic Software
The research software is deep learning algorithm used to aid in the detection of polyps (abnormal tissue growths in the wall of the colon and adenomas (pre-cancerous growths) during colonoscopy. In its current form, the automatic polyp detection system is installed on a computer system unit that utilizes an an operating system.
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Study Arms ICMJE |
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Publications * |
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* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline. |
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Recruitment Information | |||||||||||||||
Recruitment Status ICMJE | Recruiting | ||||||||||||||
Estimated Enrollment ICMJE |
200 | ||||||||||||||
Original Estimated Enrollment ICMJE | Same as current | ||||||||||||||
Estimated Study Completion Date ICMJE | December 2020 | ||||||||||||||
Estimated Primary Completion Date | December 2020 (Final data collection date for primary outcome measure) | ||||||||||||||
Eligibility Criteria ICMJE |
Inclusion Criteria:
Exclusion Criteria:
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Sex/Gender ICMJE |
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Ages ICMJE | 22 Years and older (Adult, Older Adult) | ||||||||||||||
Accepts Healthy Volunteers ICMJE | No | ||||||||||||||
Contacts ICMJE |
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Listed Location Countries ICMJE | United States | ||||||||||||||
Removed Location Countries | |||||||||||||||
Administrative Information | |||||||||||||||
NCT Number ICMJE | NCT03925337 | ||||||||||||||
Other Study ID Numbers ICMJE | 2018P000564 | ||||||||||||||
Has Data Monitoring Committee | No | ||||||||||||||
U.S. FDA-regulated Product |
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IPD Sharing Statement ICMJE |
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Responsible Party | Tyler Berzin, Beth Israel Deaconess Medical Center | ||||||||||||||
Study Sponsor ICMJE | Beth Israel Deaconess Medical Center | ||||||||||||||
Collaborators ICMJE | Not Provided | ||||||||||||||
Investigators ICMJE |
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PRS Account | Beth Israel Deaconess Medical Center | ||||||||||||||
Verification Date | June 2020 | ||||||||||||||
ICMJE Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP |