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A Deep Learning Radiomics Model for Predicting Occult Peritoneal Metastases of Pancreatic Adenocarcinoma

NCT06336694 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 302

Last updated 2024-03-29

No results posted yet for this study

Summary

Occult peritoneal metastases (OPM) in patients with pancreatic ductal adenocarcinoma (PDAC) are frequently overlooked during imaging. We aimed to develop and validate a CT-based deep learning-based radiomics (DLR) model with clinical-radiological characteristics to identify OPM in patients with PDAC before treatment.

Conditions

  • Pancreatic Neoplasms

Interventions

PROCEDURE

surgery or diagnostic staging laparoscopy

diagnosis of PDAC with peritoneal examination based on the surgical (for tumors treated with surgery) or diagnostic staging laparoscopy findings (for tumors treated with radiotherapy/chemotherapy)

Sponsors & Collaborators

  • First Affiliated Hospital, Sun Yat-Sen University

    lead OTHER

Principal Investigators

  • Shi-Ting Feng, MD · First Affiliated Hospital, Sun Yat-Sen University

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2021-01-01
Primary Completion
2022-10-31
Completion
2023-07-30

Countries

  • China

Study Locations

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Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06336694 on ClinicalTrials.gov