Condition: Rectal Cancer · Sponsor: Sixth Affiliated Hospital, Sun Yat-sen University
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.
This description comes directly from the study's public registry record.
Xiaochun Meng · 13719166488 · mengxch3@mail.sysu.edu.cn
Peiyi Xie · 13724071514 · xiepy6@mail.sysu.edu.cn
Always discuss trial participation with your own doctor first.
| Sixth Affiliated Hospital, Sun Yat-sen University | Guangzhou, Guangdong, China | Recruiting |
| The First Affiliated Hospital of Jinan University | Guangzhou, Guangdong, China | Not Yet Recruiting |
| The Second Affiliated Hospital of Guangzhou Medical University | Guangzhou, Guangdong, China | Not Yet Recruiting |
| Fifth Affiliated Hospital, Sun Yat-sen University | Zhuhai, Guangdong, China | Not Yet Recruiting |
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Source record: clinicaltrials.gov/study/NCT05523245