Clinical trial · Observational
Predicting the Efficacy of Neoadjuvant Therapy in Patients With Locally Advanced Rectal Cancer Using an AI Platform Based on Multi-parametric MRI
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Rectal Cancer | Malignant Rectal Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (0)
Data not yet available
Design
Arms and outcomes
Arms (2)
- label
- complete response
- description
- Patients receiving neoadjuvant therapy achieved pathological complete response before LARC.
- label
- non complete response
- description
- Patients receiving neoadjuvant therapy did not achieve pathological complete response before LARC.
Primary outcomes (1)
- measure
- The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves of models in prediction tumor response
- timeFrame
- baseline and pre-operation
- description
- The area under curve (AUC) of Receiver Operating Characteristic (ROC) curves of models in identifying the pCR candidates from non-pCR individuals among neoadjuvant therapy treated LARC patients will be calculated.
Secondary outcomes (4)
- measure
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Clinical suspicion or colonoscopic pathology of rectal cancer * Age over 18 years * Informed consent and signed informed consent form Exclusion Criteria: * 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
References
Publications (0)
Data not yet available