Actively Recruiting
Predicting the Efficacy of Neoadjuvant Therapy in Patients With Locally Advanced Rectal Cancer Using an AI Platform Based on Multi-parametric MRI
Led by Sixth Affiliated Hospital, Sun Yat-sen University · Updated on 2026-04-23
1700
Participants Needed
4
Research Sites
283 weeks
Total Duration
On this page
Sponsors
S
Sixth Affiliated Hospital, Sun Yat-sen University
Lead Sponsor
F
Fifth Affiliated Hospital, Sun Yat-Sen University
Collaborating Sponsor
AI-Summary
What this Trial Is About
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
Official Title
Predicting the Efficacy of Neoadjuvant Therapy in Patients With Locally Advanced Rectal Cancer Using an AI Platform Based on Multi-parametric MRI
Who Can Participate
Eligibility Criteria
You may qualify if you...
- Clinical suspicion or colonoscopic pathology of rectal cancer
- Age over 18 years
- Informed consent and signed informed consent form
You will not qualify if you...
- Poor magnetic resonance image quality, such as severe artifacts
- Previous treatment for rectal cancer
- History or combination of other malignant tumours
- Not Locally Advanced Rectal Cancer (LARC)
- Not received neoadjuvant therapy or not completed neoadjuvant therapy
- No surgery
- Time interval between MRI and surgery was more than 2 weeks
- Patients were lost to follow-up and voluntarily withdrew from the study due to adverse reactions or other reasons
AI-Screening
AI-Powered Screening
Complete this quick 3-step screening to check your eligibility
Trial Site Locations
Total: 4 locations
1
Sixth Affiliated Hospital, Sun Yat-sen University
Guangzhou, Guangdong, China
Actively Recruiting
2
The First Affiliated Hospital of Jinan University
Guangzhou, Guangdong, China
Not Yet Recruiting
3
The Second Affiliated Hospital of Guangzhou Medical University
Guangzhou, Guangdong, China
Not Yet Recruiting
4
Fifth Affiliated Hospital, Sun Yat-sen University
Zhuhai, Guangdong, China
Not Yet Recruiting
Research Team
X
Xiaochun Meng
CONTACT
P
Peiyi Xie
CONTACT
How is the study designed?
Study Type
OBSERVATIONAL
Masking
N/A
Allocation
N/A
Model
N/A
Primary Purpose
N/A
Number of Arms
2
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