Development and Validation of a Deep Learning Model to Predict Distant Metastases in Nasopharyngeal Carcinoma Using Whole Slide Imaging and MRI

Trial statusRecruiting
Trial phaseNot listed
Trial typeObservational
Biological sexAll
AgeNot listed
SponsorSun Yat-sen University

About this trial

An AI model was developed to predict the likelihood of distant metastasis in patients with nasopharyngeal cancer based on pathology slides and MRI scans of the primary tumor. The model was validated using data from multiple centers. It was then applied to patients with advanced stages who were recommended to undergo PET/CT scans based on the NCCN or CSCO guidelines. This AI model can accurately screen patients with high risk of distant metastasis at the time of initial diagnosis to receive PET/CT, avoid excessive examination of patients with low risk of distant metastasis, save medical resources and reduce the economic burden on patients.

Eligibility criteria

This trial does not accept healthy volunteers

Qualifiers

None

Disqualifiers

None

Trial population

Patients with pathologically confirmed nasopharyngeal carcinoma

Trial design

Design model

Cohort

Time perspective

Prospective

Treatments tested in this trial

Not listed

Trial groups

500 Participants
are grouped into 1 trial group
Group A: Prospective Validation Cohort

Trial outcomes

Primary outcomes

1

Negative predictive value

NPV measures the proportion of predicted negative cases that are actually negative. It tells us how reliable the model is when it predicts a negative outcome.

Time frame
through study completion, an average of 2 year

Secondary outcomes

1

Sensitivity, specificity, and positive predictive value

Sensitivity, specificity, and positive predictive value of AI in predicting distant metastasis at the threshold corresponding to a negative predictive value of 95%.

Time frame
through study completion, an average of 2 year

Other outcomes

Sponsors and contacts

Click on the lead sponsor to view all of their trials.

Sun Yat-sen University

Lead sponsor

First Affiliated Hospital, Sun Yat-Sen University

Collaborator

Fifth Affiliated Hospital, Sun Yat-Sen University

Collaborator

Affiliated Cancer Hospital & Institute of Guangzhou Medical University

Collaborator

The Affiliated Panyu Center Hospital of Guangzhou Medical University

Collaborator

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

Collaborator

Qingyuan People's Hospital

Collaborator