MedTrace Logo

Predicting the Efficacy of Neoadjuvant Therapy in Patients With Locally Advanced Rectal Cancer Using an AI Platform Based on Multi-parametric MRI

NCT05523245 · Status: RECRUITING · Type: OBSERVATIONAL · Enrollment: 1700

Last updated 2026-04-23

No results posted yet for this study

Summary

Establish a deep learning model based on multi-parameter magnetic resonance imaging to predict the efficacy of neoadjuvant therapy for locally advanced rectal cancer.This study intends to combine DCE with conventional MRI images for DL, establish a multi-parameter MRI model for predicting the efficacy of CRT, and compare it with the DL and non-artificial quantitative MRI diagnostic model constructed by conventional MRI to evaluate the role of DL in MRI predicting CRT. And this study also tries to build a DL platform to assess the efficacy of LARC neoadjuvant radiotherapy and chemotherapy, accurately assess patients' complete respose (pCR) after CRT, and provide an important basis for guiding clinical decision-making.

Conditions

Sponsors & Collaborators

  • Fifth Affiliated Hospital, Sun Yat-Sen University

    collaborator OTHER

  • Second Affiliated Hospital of Guangzhou Medical University

    collaborator OTHER

  • First Affiliated Hospital of Jinan University

    collaborator OTHER

  • Sixth Affiliated Hospital, Sun Yat-sen University

    lead OTHER

Eligibility

Min Age
18 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2022-06-24
Primary Completion
2026-12-31
Completion
2027-12-31

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

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 NCT05523245 on ClinicalTrials.gov