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

April 9, 2024 updated by: Fang-Yun Xie, Sun Yat-sen University
The aim of this randomized controlled study is to investigate whether the previously developed artificial intelligence model can triage post-radiotherapy magnetic resonance images of patients with nasopharyngeal carcinoma and assist radiologists in their interpretation.

Study Overview

Status

Not yet recruiting

Conditions

Intervention / Treatment

Study Type

Observational

Enrollment (Estimated)

10400

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

    • Guangdong
      • Guangzhou, Guangdong, China, 510060
        • Sun Yat-sen University Cancer Center
        • Contact:
        • Contact:
        • Principal Investigator:
          • Fang-Yun Xie

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

This study enrolled patients with treatment naive nasopharyngeal carcinoma who have finished radiotherapy for 6 months or more and have no tumor residue in previous examinations.

Description

Inclusion Criteria:

  • Patients with treatment naive nasopharyngeal carcinoma who had finished radiotherapy for 6 months or more
  • 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:

  • Patients are enrolled in this study for a specific magnetic resonance imaging scan and not for subsequent follow-up magnetic resonance imaging scans.

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
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.
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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Time Frame
sensitivity
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years

Secondary Outcome Measures

Outcome Measure
Time Frame
specificity
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years
positive predictive value
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years
negative predictive value
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years
total time of interpretation for all the MR images
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years
the rate of discussion with a third radiologist
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years
the detection rate of local recurrence in the AI-supported reading group
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years
the sensitivity in the subgroups of different rT-stage
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years
the incidence of cases whose recurrent risks and contours cannot be provided by the AI model
Time Frame: through study completion, an average of 2 years
through study completion, an average of 2 years

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Investigators

  • Principal Investigator: Fang-Yun Xie, Sun Yat-sen University

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Estimated)

April 1, 2024

Primary Completion (Estimated)

April 1, 2026

Study Completion (Estimated)

April 1, 2026

Study Registration Dates

First Submitted

April 4, 2024

First Submitted That Met QC Criteria

April 9, 2024

First Posted (Actual)

April 10, 2024

Study Record Updates

Last Update Posted (Actual)

April 10, 2024

Last Update Submitted That Met QC Criteria

April 9, 2024

Last Verified

April 1, 2024

More Information

Terms related to this study

Other Study ID Numbers

  • B2024-039-01

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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