Ignite Creation Date:
2025-12-24 @ 3:07 PM
Ignite Modification Date:
2026-01-31 @ 6:20 AM
Study NCT ID:
NCT06697392
Status:
ACTIVE_NOT_RECRUITING
Last Update Posted:
2024-11-20
First Post:
2024-11-17
Is NOT Gene Therapy:
True
Has Adverse Events:
False
Brief Title:
Ultrasound-based Artificial Intelligence for Classification of Carpal Tunnel Syndrome
Sponsor:
Organization:
Raw JSON
{'hasResults': False, 'derivedSection': {'miscInfoModule': {'versionHolder': '2025-12-24'}, 'conditionBrowseModule': {'meshes': [{'id': 'D002349', 'term': 'Carpal Tunnel Syndrome'}], 'ancestors': [{'id': 'D020423', 'term': 'Median Neuropathy'}, {'id': 'D020422', 'term': 'Mononeuropathies'}, {'id': 'D010523', 'term': 'Peripheral Nervous System Diseases'}, {'id': 'D009468', 'term': 'Neuromuscular Diseases'}, {'id': 'D009422', 'term': 'Nervous System Diseases'}, {'id': 'D009408', 'term': 'Nerve Compression Syndromes'}, {'id': 'D012090', 'term': 'Cumulative Trauma Disorders'}, {'id': 'D013180', 'term': 'Sprains and Strains'}, {'id': 'D014947', 'term': 'Wounds and Injuries'}]}}, 'protocolSection': {'designModule': {'studyType': 'OBSERVATIONAL', 'designInfo': {'timePerspective': 'PROSPECTIVE', 'observationalModel': 'OTHER'}, 'enrollmentInfo': {'type': 'ESTIMATED', 'count': 500}, 'patientRegistry': False}, 'statusModule': {'overallStatus': 'ACTIVE_NOT_RECRUITING', 'startDateStruct': {'date': '2024-11-15', 'type': 'ACTUAL'}, 'expandedAccessInfo': {'hasExpandedAccess': False}, 'statusVerifiedDate': '2024-11', 'completionDateStruct': {'date': '2026-12-30', 'type': 'ESTIMATED'}, 'lastUpdateSubmitDate': '2024-11-17', 'studyFirstSubmitDate': '2024-11-17', 'studyFirstSubmitQcDate': '2024-11-17', 'lastUpdatePostDateStruct': {'date': '2024-11-20', 'type': 'ACTUAL'}, 'studyFirstPostDateStruct': {'date': '2024-11-20', 'type': 'ACTUAL'}, 'primaryCompletionDateStruct': {'date': '2025-06-30', 'type': 'ESTIMATED'}}, 'outcomesModule': {'primaryOutcomes': [{'measure': 'grading of CTS', 'timeFrame': 'baseline'}]}, 'oversightModule': {'isUsExport': False, 'oversightHasDmc': True, 'isFdaRegulatedDrug': False, 'isFdaRegulatedDevice': False}, 'conditionsModule': {'keywords': ['carpal tunnel syndrome', 'ultrasound', 'artificial intelligence'], 'conditions': ['Carpal Tunnel Syndrome (CTS)', 'Ultrasound', 'Artificial Intelligence (AI)']}, 'referencesModule': {'references': [{'pmid': '32030660', 'type': 'BACKGROUND', 'citation': 'Chan HP, Samala RK, Hadjiiski LM, Zhou C. Deep Learning in Medical Image Analysis. Adv Exp Med Biol. 2020;1213:3-21. doi: 10.1007/978-3-030-33128-3_1.'}, {'pmid': '37082094', 'type': 'BACKGROUND', 'citation': 'Wielemborek PT, Kapica-Topczewska K, Pogorzelski R, Bartoszuk A, Kochanowicz J, Kulakowska A. Carpal tunnel syndrome conservative treatment: a literature review. Postep Psychiatr Neurol. 2022 Jun;31(2):85-94. doi: 10.5114/ppn.2022.116880. Epub 2022 May 31.'}, {'pmid': '36980446', 'type': 'BACKGROUND', 'citation': 'Lam KHS, Wu YT, Reeves KD, Galluccio F, Allam AE, Peng PWH. Ultrasound-Guided Interventions for Carpal Tunnel Syndrome: A Systematic Review and Meta-Analyses. Diagnostics (Basel). 2023 Mar 16;13(6):1138. doi: 10.3390/diagnostics13061138.'}]}, 'descriptionModule': {'briefSummary': "Carpal tunnel syndrome (CTS) is one of the most prevalent peripheral neuropathies, impacting approximately 4% of the general population. It is typically classified into three degrees: mild, moderate, and severe. Accurate grading of carpal tunnel syndrome (CTS) is essential for determining appropriate treatment options, thereby playing a crucial role in optimizing patient outcomes. Electrophysiological testing (EST) is a key parameter for grading carpal tunnel syndrome (CTS). However, it is limited by several factors, including its invasive nature, poor reproducibility, and reduced sensitivity for detecting early-stage disease. Recently, ultrasound has gained widespread acceptance among clinicians for the assessment and grading of CTS. Nonetheless, radiologists often encounter challenges in this process due to the variability in image quality, differences in experience, and inherent subjectivity.\n\nTo address these issues, artificial intelligence presents a promising solution. Therefore, this study aims to develop a deep learning model for grading CTS by leveraging multimodal imaging features, including B-mode ultrasound, superb microvascular imaging (SMI), and elastography. Additionally, the investigators intend to validate the model's effectiveness by testing it with images from various clinical centers, ensuring its generalizability across different clinical settings."}, 'eligibilityModule': {'sex': 'ALL', 'stdAges': ['ADULT', 'OLDER_ADULT'], 'maximumAge': '80 Years', 'minimumAge': '18 Years', 'samplingMethod': 'PROBABILITY_SAMPLE', 'studyPopulation': 'The investigators intend to perform ultrasound examinations for patients with idiopathic CTS adhering to specific inclusion and exclusion criteria, aiming to develop and test the efficacy of AI model for CTS grading.', 'healthyVolunteers': False, 'eligibilityCriteria': 'Inclusion Criteria:\n\n* those who have complained about associated symptoms about CTS, including pain, numbness, and weakness of hand.\n* those who perform ultrasound examinations of median nerve within 1 week of the symptom.\n* those who have electrophysilogical test results as reference standard.\n\nExclusion Criteria:\n\n* those who had a surgery in the affected hand.\n* those who had a trauma or fracture in the affected hand.\n* those who had rheumatoid-related conditions, autoimmune diseases, and endocrine disorders.'}, 'identificationModule': {'nctId': 'NCT06697392', 'briefTitle': 'Ultrasound-based Artificial Intelligence for Classification of Carpal Tunnel Syndrome', 'organization': {'class': 'OTHER', 'fullName': "Peking University People's Hospital"}, 'officialTitle': 'Ultrasound-based Artificial Intelligence for Grading of Carpal Tunnel Syndrome, a Multicenter Study in China', 'orgStudyIdInfo': {'id': '2024PHB019-001(5)'}}, 'armsInterventionsModule': {'armGroups': [{'label': 'Prospective test set', 'interventionNames': ['Other: ultrasound examination']}], 'interventions': [{'name': 'ultrasound examination', 'type': 'OTHER', 'description': 'The investigators intend to perform ultrasound examinations for the participants with CTS.', 'armGroupLabels': ['Prospective test set']}]}, 'contactsLocationsModule': {'locations': [{'zip': '100032', 'city': 'Beijing', 'state': 'Beijing. PR', 'country': 'China', 'facility': "Peking University People's Hospital", 'geoPoint': {'lat': 39.9075, 'lon': 116.39723}}]}, 'ipdSharingStatementModule': {'ipdSharing': 'UNDECIDED'}, 'sponsorCollaboratorsModule': {'leadSponsor': {'name': "Peking University People's Hospital", 'class': 'OTHER'}, 'responsibleParty': {'type': 'PRINCIPAL_INVESTIGATOR', 'investigatorTitle': 'Doctor', 'investigatorFullName': 'Shi Xiaochen', 'investigatorAffiliation': "Peking University People's Hospital"}}}}