Artificial Intelligence-supported Reading Versus Standard Double Reading for the Interpretation of Magnetic Resonance Imaging in the Detection of Local Recurrence for Nasopharyngeal Carcinoma: a Randomised Controlled Multicenter Study
NCT ID: NCT06356441
Last Updated: 2024-04-10
Study Results
The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.
Basic Information
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NOT_YET_RECRUITING
10400 participants
OBSERVATIONAL
2024-04-30
2026-04-30
Brief Summary
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Detailed Description
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Conditions
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Study Design
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COHORT
PROSPECTIVE
Study Groups
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AI-supported reading
The AI model predicts the incidence of local recurrence. If the incidence is below 60%, one radiologist will interpret the MR images. If the incidence is above 60%, two radiologists will interpret the MR images. The radiologists will be provided with the predictive incidence and contours in their interpretation if desired. If two radiologists provide contradictory interpretations, a third radiologist will participate in the discussion to reach a consensus.
AI
An artificial intelligence model predicts the risk and contours of local recurrence for MR images and triages them before radiologists interpret them.
Standard double reading
The MR images will be interpreted by two radiologists, and in cases of disagreement, a third radiologist will be consulted to reach a consensus.
No interventions assigned to this group
Interventions
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AI
An artificial intelligence model predicts the risk and contours of local recurrence for MR images and triages them before radiologists interpret them.
Eligibility Criteria
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Inclusion Criteria
* The previous magnetic resonance imaging examination had showed complete remission in the primary site
* Images are acquired using a 3T magnetic resonance imaging device, including unenhanced T1-weighted and T2-weighted sequences and contrast-enhanced T1-weighted sequences
Exclusion Criteria
ALL
No
Sponsors
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Sun Yat-sen University
OTHER
Responsible Party
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Fang-Yun Xie
professor
Principal Investigators
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Fang-Yun Xie
Role: PRINCIPAL_INVESTIGATOR
Sun Yat-sen University
Locations
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Sun Yat-Sen University Cancer Center
Guangzhou, Guangdong, China
Countries
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Central Contacts
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Facility Contacts
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References
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OuYang PY, He Y, Guo JG, Liu JN, Wang ZL, Li A, Li J, Yang SS, Zhang X, Fan W, Wu YS, Liu ZQ, Zhang BY, Zhao YN, Gao MY, Zhang WJ, Xie CM, Xie FY. Artificial intelligence aided precise detection of local recurrence on MRI for nasopharyngeal carcinoma: a multicenter cohort study. EClinicalMedicine. 2023 Aug 30;63:102202. doi: 10.1016/j.eclinm.2023.102202. eCollection 2023 Sep.
Other Identifiers
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B2024-039-01
Identifier Type: -
Identifier Source: org_study_id
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