The Value of Artificial Intelligence-based 18F-FDG PET/CT in Diferential Diagnosis, Efficacy Prediction and Prognosis Prediction of T-NK Cell Lymphoma: a Clinical Study

December 18, 2024 updated by: GUO RUI, Ruijin Hospital
Based on the PET/CT imaging data of patients with T-NK cell lymphoma, machine learning and deep learning methods are used to extract imaging features, establish a T-NK cell lymphoma prediction model, and provide more scientific and accurate prognosis prediction for the clinic.

Study Overview

Status

Not yet recruiting

Conditions

Detailed Description

This study adopts a multicenter retrospective cohort study design，we provided PET/CT of 200 patients with T-NK cell lymphoma as an external validation set for model validation.

Study Type

Observational

Enrollment (Estimated)

200

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 Locations

  • China
    • Shanghai
      • Shanghai, Shanghai, China
        • Ruijin Hospital affiliated to Shanghai Jiao Tong University of Medicine

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

  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Sampling Method

Probability Sample

Study Population

Pathological histology confirmed as T-NK Cell Lymphoma at Ruijin Hospital, Shanghai JiaoTong University School of Medicine

Description

Inclusion Criteria:

1. Pathological histology confirmed as T-NK Cell Lymphoma; 2.18F-FDG PET/CT examination before treatment; 3. Using modern best practice treatment options; 4. Complete clinicopathological and follow-up data were obtained.

Exclusion Criteria:

  1. The patient had previously received antitumor therapy;
  2. The patient had a history of other tumors;
  3. Incomplete clinical information or imaging data;
  4. Concomitant other malignant tumors.

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
patients diagnosis of T-NK cell lymphoma

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Evaluation the value of Artificial Intelligence-based 18F-FDG PET/CT of T-NK Cell Lymphoma
Time Frame: Within 1 week of enrollment and after 3 months treatment
The Value of Artificial Intelligence-based 18F-FDG PET/CT in Diferential Diagnosis, Efficacy Prediction and Prognosis Prediction of T-NK Cell Lymphoma
Within 1 week of enrollment and after 3 months treatment

Secondary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Overall survival
Time Frame: 3 years
Overall survival
3 years
Progress free survival
Time Frame: 3 years
Progress free survival
3 years

Collaborators and Investigators

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

Sponsor

Ruijin Hospital

Collaborators

West China Hospital

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)

January 1, 2025

Primary Completion (Estimated)

December 31, 2027

Study Completion (Estimated)

December 31, 2027

Study Registration Dates

First Submitted

December 18, 2024

First Submitted That Met QC Criteria

December 18, 2024

First Posted (Actual)

March 25, 2025

Study Record Updates

Last Update Posted (Actual)

March 25, 2025

Last Update Submitted That Met QC Criteria

December 18, 2024

Last Verified

September 1, 2024

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • RuijinH 2024-349

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

product manufactured in and exported from the U.S.

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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