NCT05523245

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

• Status: Recruiting
• Phase: —
• Study type: Observational
• Enrollment: 1,700 (estimated)
• Sponsor: Sixth Affiliated Hospital, Sun Yat-sen University · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Not accepted

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

• Rectal Cancer

Timeline

• Start date: 2022-06-24
• Primary completion: 2026-12-01
• Completion: 2027-12-01
• First posted: 2022-08-31
• Last updated: 2025-06-04

Locations

4 sites across 1 country: China