Ignite Creation Date:
2025-12-24 @ 2:22 PM
Ignite Modification Date:
2025-12-26 @ 6:39 AM
Study NCT ID:
NCT04227795
Status:
COMPLETED
Last Update Posted:
2020-03-04
First Post:
2020-01-10
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
AI-assisted Detection of Missed Colonic Polyps
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D003111', 'term': 'Colonic Polyps'}, {'id': 'D003110', 'term': 'Colonic Neoplasms'}], 'ancestors': [{'id': 'D007417', 'term': 'Intestinal Polyps'}, {'id': 'D011127', 'term': 'Polyps'}, {'id': 'D020763', 'term': 'Pathological Conditions, Anatomical'}, {'id': 'D013568', 'term': 'Pathological Conditions, Signs and Symptoms'}, {'id': 'D015179', 'term': 'Colorectal Neoplasms'}, {'id': 'D007414', 'term': 'Intestinal Neoplasms'}, {'id': 'D005770', 'term': 'Gastrointestinal Neoplasms'}, {'id': 'D004067', 'term': 'Digestive System Neoplasms'}, {'id': 'D009371', 'term': 'Neoplasms by Site'}, {'id': 'D009369', 'term': 'Neoplasms'}, {'id': 'D004066', 'term': 'Digestive System Diseases'}, {'id': 'D005767', 'term': 'Gastrointestinal Diseases'}, {'id': 'D003108', 'term': 'Colonic Diseases'}, {'id': 'D007410', 'term': 'Intestinal Diseases'}]}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'NA', 'maskingInfo': {'masking': 'NONE'}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'SINGLE_GROUP'}, 'enrollmentInfo': {'type': 'ACTUAL', 'count': 52}}, 'statusModule': {'overallStatus': 'COMPLETED', 'startDateStruct': {'date': '2020-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2020-03', 'completionDateStruct': {'date': '2020-03-01', 'type': 'ACTUAL'}, 'lastUpdateSubmitDate': '2020-03-02', 'studyFirstSubmitDate': '2020-01-10', 'studyFirstSubmitQcDate': '2020-01-13', 'lastUpdatePostDateStruct': {'date': '2020-03-04', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-01-14', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2020-02-01', 'type': 'ACTUAL'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'Adenoma miss rate', 'timeFrame': 'During the colonoscopy procedure', 'description': 'The number of patient had at least one missed adenoma'}], 'secondaryOutcomes': [{'measure': 'Total number of adenoma missed', 'timeFrame': 'During the colonoscopy procedure', 'description': 'The total number of missed polyps for all subjects'}, {'measure': 'Colonic polyp miss rate', 'timeFrame': 'During the colonoscopy procedure', 'description': 'The number of patient had at least one missed adenoma'}, {'measure': 'Total number of missed polyps', 'timeFrame': 'During the colonoscopy procedure', 'description': 'The total number of missed polyps for all subjects'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['Artificial intelligence', 'Colonoscopy', 'Deep learning', 'Detection', 'Computer-aided'], 'conditions': ['Colon Adenoma', 'Colonic Polyp', 'Colon Cancer']}, 'referencesModule': {'references': [{'pmid': '32376335', 'type': 'DERIVED', 'citation': 'Lui TKL, Hui CKY, Tsui VWM, Cheung KS, Ko MKL, Foo DCC, Mak LY, Yeung CK, Lui TH, Wong SY, Leung WK. New insights on missed colonic lesions during colonoscopy through artificial intelligence-assisted real-time detection (with video). Gastrointest Endosc. 2021 Jan;93(1):193-200.e1. doi: 10.1016/j.gie.2020.04.066. Epub 2020 May 4.'}]}, 'descriptionModule': {'briefSummary': 'A prospective validation of real time deep learning artificial intelligence model for detection of missed colonic polyps', 'detailedDescription': 'Consecutive adult patients, age 40 or above, who were scheduled to have outpatient colonoscopy in the Queen Mary Hospital were invited to participate. Patients were excluded if they were unable to provide informed consent, considered to be unsafe for taking biopsy or polypectomy including patients with bleeding tendency and those with severe comorbid illnesses. Also, patients with history of inflammatory bowel disease, familial adenomatous polyposis, Peutz-Jeghers syndrome or other polyposis syndromes were excluded.\n\nThe primary endoscopist conducted the colonoscopic examination in the usual manner. All colonoscopy procedures were performed with high-definition colonoscopes (EVIS-EXERA 290 video system, Olympus Optical, Tokyo, Japan). The colonoscopy was first advanced to the cecum in all patients as confirmed by identification of the appendiceal orifice and ileocecal valve or by intubation of the ileum. After cecal intubation, the colonoscopy was slowly withdrawn to the rectum by the primary endoscopist. The AI real time detection was then activated with the output displayed in a different monitor and was only viewed by an independent investigator, who was an experienced endoscopist. The primary endoscopist was blinded to the AI real time detection result al.\n\nThe colon was divided into three segments during the examination: right side, transverse and left side colon, using hepatic flexure and splenic flexure as dividing landmark. All polyps were marked for size (measured with biopsy forceps), location and morphology according to the Paris classification, and then removed or biopsied for histological examination. After examination of each segment, segmental unblinding of the AI results were provided by the independent viewer. If additional polyps were detected by AI but not by the endoscopist, that segment were reexamined to look for the missed polyp. If no additional polyp was detected by the AI, the next colonic segment was examined. Missed lesions were defined as lesions identified by AI and then confirmed on reexamination by the endoscopist.\n\nThe first withdrawal time (minus the polypectomy site) was measured. The Boston Bowel Preparation Scale score (BPPS) was used for evaluation of bowel cleanliness.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '90 Years', 'minimumAge': '40 Years', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* consecutive adult patients, age 40 or above, who were scheduled to have outpatient colonoscopy in the Queen Mary Hospital were invited to participate\n\nExclusion Criteria:\n\n* Patients were excluded if they were unable to provide informed consent, considered to be unsafe for taking biopsy or polypectomy including patients with bleeding tendency and those with severe comorbid illnesses.\n* Also, patients with history of inflammatory bowel disease, familial adenomatous polyposis, Peutz-Jeghers syndrome or other polyposis syndromes were excluded.'}, 'identificationModule': {'nctId': 'NCT04227795', 'briefTitle': 'AI-assisted Detection of Missed Colonic Polyps', 'organization': {'class': 'OTHER', 'fullName': 'The University of Hong Kong'}, 'officialTitle': 'Artificial Intelligence-Assisted Real-time Detection of Missed Lesions During Colonoscopy: A Prospective Study', 'orgStudyIdInfo': {'id': 'UW 19-309'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'Artificial intelligence-Assisted real time colonoscopy', 'description': 'AI assisted real-time detection of colonic lesions', 'interventionNames': ['Device: Artificial intelligence-Assisted real time colonoscopy']}], 'interventions': [{'name': 'Artificial intelligence-Assisted real time colonoscopy', 'type': 'DEVICE', 'description': 'The colonoscopy was performed under artificial intelligence assistance', 'armGroupLabels': ['Artificial intelligence-Assisted real time colonoscopy']}]}, 'contactsLocationsModule': {'locations': [{'city': 'Hong Kong', 'country': 'Hong Kong', 'facility': 'Queen Mary Hospital', 'geoPoint': {'lat': 22.27832, 'lon': 114.17469}}], 'overallOfficials': [{'name': 'Ka Luen, Thomas Lui', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'Queen Mary Hospital, the University of Hong Kong'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'The University of Hong Kong', 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Clinical Professor', 'investigatorFullName': 'LEUNG Wai Keung', 'investigatorAffiliation': 'The University of Hong Kong'}}}}