Post-Neoadjuvant Treatment MRI Based AI System to Predict pCR for Rectal Cancer
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- STATUS
- Recruiting
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- participants needed
- 322
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- sponsor
- Sixth Affiliated Hospital, Sun Yat-sen University
Summary
In this study, investigators seek for a better way to identify the potential pathologic complete response (pCR) patients form non-pCR patients with locally advanced rectal cancer (LARC), based on their post-neoadjuvant treatment Magnetic Resonance Imaging (MRI) data.
Previously, a post neoadjuvant treatment MRI based radiomics AI model had been constructed and trained. The predictive power of this artificial intelligence system and expert radiologist to identify pCR patients from non-pCR LARC patients will be compared in this randomized controlled, prospective, multicenter, observational clinical study.
Description
This is a randomized controlled, multicenter, prospective, observational clinical study for seeking out a better way to predict the pathologic complete response (pCR) in patients with locally advanced rectal cancer (LARC) based on the post- neoadjuvant treatment Magnetic Resonance Imaging (MRI) data. Patients who have been pathologically diagnosed as rectal adenocarcinoma and defined as clinical II-III staging without distant metastasis will be enrolled from the Sixth Affiliated Hospital of Sun Yat-sen University, Sir Run Run Shaw Hospital and the Third Affiliated Hospital of Kunming Medical College. All participants should follow a standard treatment protocol, including neoadjuvant treatment, total mesorectum excision (TME) surgery and adjuvant chemotherapy. Patients with LARC who received neoadjuvant treatment will be randomly assigned into two arms, and their post-neoadjuvant treatment MRI images will be used to predict their pathologic response (pCR vs. non-pCR). Patients in arm A assign to the artificial intelligence prediction system. While in group B, the patients assign to the expert radiologist prediction. The pathologist will provide the final pathology report of TME surgery specimen (pCR or non-pCR) as a standard. The predictive efficacy of these two arms will be compared in this randomized controlled, multicenter clinical study among patients with locally advanced rectal cancer.
Details
Condition | Colorectal Cancer, Colorectal Cancer, Rectal Cancer, Rectal Cancer |
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Age | 18years - 75years |
Treatment | the artificial intelligence, the radiologists |
Clinical Study Identifier | NCT04278274 |
Sponsor | Sixth Affiliated Hospital, Sun Yat-sen University |
Last Modified on | 16 February 2024 |
How to participate?
Additional screening procedures may be conducted by the study team before you can be confirmed eligible to participate.
Learn moreIf you are confirmed eligible after full screening, you will be required to understand and sign the informed consent if you decide to enroll in the study. Once enrolled you may be asked to make scheduled visits over a period of time.
Learn moreComplete your scheduled study participation activities and then you are done. You may receive summary of study results if provided by the sponsor.
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