Ignite Creation Date:
2025-12-25 @ 4:23 AM
Ignite Modification Date:
2025-12-26 @ 3:26 AM
Study NCT ID:
NCT04607720
Status:
UNKNOWN
Last Update Posted:
2020-10-29
First Post:
2020-10-18
Is NOT Gene Therapy:
False
Has Adverse Events:
False
Brief Title:
Clinical Research on a Novel Deep-learning Based System in Pancreatic Mass Diagnosis
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}}, 'protocolSection': {'designModule': {'phases': ['NA'], 'studyType': 'INTERVENTIONAL', 'designInfo': {'allocation': 'RANDOMIZED', 'maskingInfo': {'masking': 'DOUBLE', 'whoMasked': ['PARTICIPANT', 'OUTCOMES_ASSESSOR']}, 'primaryPurpose': 'DIAGNOSTIC', 'interventionModel': 'CROSSOVER'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 100}}, 'statusModule': {'overallStatus': 'UNKNOWN', 'lastKnownStatus': 'RECRUITING', 'startDateStruct': {'date': '2020-01-01', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2020-10', 'completionDateStruct': {'date': '2022-06-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2020-10-23', 'studyFirstSubmitDate': '2020-10-18', 'studyFirstSubmitQcDate': '2020-10-23', 'lastUpdatePostDateStruct': {'date': '2020-10-29', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2020-10-29', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2021-12-31', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'accuracy', 'timeFrame': '1 year', 'description': 'compare the diagnostic rates of AI-CH-EUS and artificial-CH-EUS for benign and malignant pancreatic masses'}, {'measure': 'sensitivity', 'timeFrame': '1 year', 'description': 'compare the diagnostic rates of AI-CH-EUS and artificial-CH-EUS for benign and malignant pancreatic masses'}, {'measure': 'specificity', 'timeFrame': '1 year', 'description': 'compare the diagnostic rates of AI-CH-EUS and artificial-CH-EUS for benign and malignant pancreatic masses'}, {'measure': 'positive predictive value', 'timeFrame': '1 year', 'description': 'compare the diagnostic rates of AI-CH-EUS and artificial-CH-EUS for benign and malignant pancreatic masses'}, {'measure': 'negative predictive value', 'timeFrame': '1 year', 'description': 'compare the diagnostic rates of AI-CH-EUS and artificial-CH-EUS for benign and malignant pancreatic masses'}, {'measure': 'the diagnosis rate of first needle aspiration', 'timeFrame': '1 year', 'description': 'compared the diagnosis rate of AI-EUS-FNA and artificial-EUS-FNA first needle aspiration for benign and malignant pancreatic masses'}], 'secondaryOutcomes': [{'measure': 'core tissue length', 'timeFrame': '1 year', 'description': 'To evaluate the specimen quality through core tissue length of AI-EUS-FNA and artificial-EUS-FNA'}]}, 'oversightModule': {'oversightHasDmc': False, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'conditions': ['Solid Pancreatic Masses']}, 'referencesModule': {'references': [{'pmid': '36606571', 'type': 'DERIVED', 'citation': 'Tang A, Tian L, Gao K, Liu R, Hu S, Liu J, Xu J, Fu T, Zhang Z, Wang W, Zeng L, Qu W, Dai Y, Hou R, Tang S, Wang X. Contrast-enhanced harmonic endoscopic ultrasound (CH-EUS) MASTER: A novel deep learning-based system in pancreatic mass diagnosis. Cancer Med. 2023 Apr;12(7):7962-7973. doi: 10.1002/cam4.5578. Epub 2023 Jan 6.'}]}, 'descriptionModule': {'briefSummary': 'In this study, a single-center, prospective, self-control, and blind design was adopted.', 'detailedDescription': 'It is planned to enroll 100 patients with solid pancreatic masses who are to be diagnosed with contrast-enhanced harmonic endoscopy ultrasonography (CH-EUS) follow by EUS-guided fine-needle aspiration (EUS-FNA). First, all patients will be diagnosed both by the AI-assisted diagnosis system and the endoscopists under CH-EUS; Second, to compare the EUS-FNA under the guidance of the AI-assisted ultrasound diagnosis system and the EUS-FNA under manual identification, patients were randomly assigned to undergo EUS-FNA with or without the guidance of AI-assisted diagnosis system for the first two passes.'}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '90 Years', 'minimumAge': '18 Years', 'healthyVolunteers': False, 'eligibilityCriteria': "Inclusion Criteria:\n\n* 1\\. Age ≥18 years old, \\<90 years old 2.The patient is confirmed to be a solid pancreatic mass in imaging examinations (MRI, CT or ultrasound), and CH-EUS is required for auxiliary diagnosis 3. Agree to participate in this study and sign the CH-EUS informed consent form\n\nExclusion Criteria:\n\n* Subjects who meet any of the following criteria cannot be selected for this trial:\n\nFirst. The patient's physical condition does not meet the requirements of conventional ultrasound endoscopic puncture:\n\n1. Poor physical condition, including hemoglobin ≤8.0g/dl, severe cardiopulmonary insufficiency, etc.\n2. Blood coagulation dysfunction (platelet count \\<50×1012, international standardized ratio\\> 1.5) or taking oral anticoagulants such as aspirin or warfarin within a week\n3. Anesthesia assessment failed\n4. Had acute pancreatitis within 2 weeks\n5. Pregnancy or breastfeeding\n6. Known history of allergy to sulfur hexafluoride or other components\n7. Recent acute coronary syndrome or clinically unstable ischemic heart attack\n8. Heart disease patients with right-to-left shunt, patients with severe pulmonary hypertension (pulmonary artery pressure\\> 90mmHg), patients with uncontrolled systemic hypertension and patients with adult respiratory distress syndrome.\n\nSecond. Disagree to participate in this study\n\nThird. There are other problems that do not meet the requirements of this research or that affect the results of the research:\n\n1. Pancreatic disease has undergone surgery or chemotherapy beforehand\n2. The patient was diagnosed with pancreatic cystic disease or duodenal stenosis\n3. Mental illness, drug addiction, inability to express themselves or other diseases that may affect follow-up"}, 'identificationModule': {'nctId': 'NCT04607720', 'briefTitle': 'Clinical Research on a Novel Deep-learning Based System in Pancreatic Mass Diagnosis', 'organization': {'class': 'OTHER', 'fullName': 'The Third Xiangya Hospital of Central South University'}, 'officialTitle': 'Clinical Research on a Noval Deep-learning Based System in Benign and Malignant Pancreatic Masses Diagnosing Under Harmonic Contrast-enhanced Endoscopic Ultrasound', 'orgStudyIdInfo': {'id': '2020-CH-EUS-AI'}}, 'armsInterventionsModule': {'armGroups': [{'type': 'EXPERIMENTAL', 'label': 'the artificial-EUS-FNA group', 'description': 'the first two passes were made without the AI-assisted diagnosis system guidance during EUS-FNA, and then two passes were made under guidance from the AI-assisted diagnosis system', 'interventionNames': ['Procedure: artificial-EUS-FNA', 'Procedure: AI-EUS-FNA']}, {'type': 'EXPERIMENTAL', 'label': 'the AI-EUS-FNA group', 'description': 'the first two passes were made with the AI-assisted diagnosis system guidance and then another two manual passes without the AI-assisted diagnosis system guidance.', 'interventionNames': ['Procedure: artificial-EUS-FNA', 'Procedure: AI-EUS-FNA']}], 'interventions': [{'name': 'artificial-EUS-FNA', 'type': 'PROCEDURE', 'description': 'The ultrasound endoscopists manually determined the region of interest (ROI) according to CH-EUS, and punctured 2 needles in the tumor area with a 22G needle, and each needle moved 15-20 times back and forth in the lesion. After puncture, insert the needle core, rinse the needle with 0.1ml sterile saline, and further apply air flushing to ensure that each tissue is sent to the slide.', 'armGroupLabels': ['the AI-EUS-FNA group', 'the artificial-EUS-FNA group']}, {'name': 'AI-EUS-FNA', 'type': 'PROCEDURE', 'description': 'In the AI-assisted diagnosis system, the assisted targeting EUS-FNA unit is applied, and the ultrasound endoscopist selects the region of interest (ROI) according to the thermogram to perform targeted EUS-FNA puncture(2 needles in the same way).', 'armGroupLabels': ['the AI-EUS-FNA group', 'the artificial-EUS-FNA group']}]}, 'contactsLocationsModule': {'locations': [{'zip': '410013', 'city': 'Changsha', 'state': 'Hunan', 'status': 'RECRUITING', 'country': 'China', 'contacts': [{'name': 'Wang Xiaoyan, MD', 'role': 'CONTACT', 'email': 'wxy20011@163.com', 'phone': '+8613974889301'}], 'facility': 'The Third Xiangya Hospital of Central South University', 'geoPoint': {'lat': 28.19874, 'lon': 112.97087}}], 'centralContacts': [{'name': 'Wang Xiao, MD', 'role': 'CONTACT', 'email': 'wxy20011@163.com', 'phone': '+8613974889301'}], 'overallOfficials': [{'name': 'Li Tian, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'The Third Xiangya Hospital of Central South University'}, {'name': 'Anliu Tang, MD', 'role': 'PRINCIPAL_INVESTIGATOR', 'affiliation': 'The Third Xiangya Hospital of Central South University'}]}, 'ipdSharingStatementModule': {'ipdSharing': 'NO'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': 'The Third Xiangya Hospital of Central South University', 'class': 'OTHER'}, 'responsibleParty': {'type': 'SPONSOR'}}}}