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Spots Global Cancer Trial Database for Deep Learning Based MRI Radiomics in Predicting the Clinical Risk of Locally Advanced Rectal Cancer

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Trial Identification

Brief Title: Deep Learning Based MRI Radiomics in Predicting the Clinical Risk of Locally Advanced Rectal Cancer

Official Title: Deep Learning Based MRI Radiomics in Predicting the Clinical Risk of Locally Advanced Rectal Cancer

Study ID: NCT06314750

Interventions

Study Description

Brief Summary: Neoadjuvant therapy is the standard diagnosis and treatment strategy for locally advanced rectal cancer defined by MRI in order to achieve tumor regression, thus affecting the selection of surgical strategy and circumferential margin, improving the safety of operation and the prognosis of patients. This study focused on the related clinical factors such as tumor regression before and after neoadjuvant therapy, combined with preoperative high-dimensional features such as radiomics, to predict the related factors of tumor regression of locally advanced rectal cancer, and validate it with multicenter. In order to develop an accurate model that can be applied to the real world and stratify the risk of locally advanced rectal cancer patients before treatment.

Detailed Description: The patients with locally advanced rectal cancer were collected retrospectively, and the relevant information such as clinical baseline characteristics, imaging data and preoperative/postoperative pathological data were collected and integrated, applying the method of deep learning to construct the model, in order to predict and evaluate the risk factors (invasion of mesorectal fascia, status of cancer nodule, long-term prognosis, tumor recurrence, etc.) which are important in clinical diagnosis and treatment. After the model was established, prospective studies were carried out to validate the model, continue training and enrich the effectiveness of the model.

Keywords

Eligibility

Minimum Age: 20 Years

Eligible Ages: ADULT, OLDER_ADULT

Sex: ALL

Healthy Volunteers: No

Locations

Contact Details

Name: Zerong Cai, MD

Affiliation: Sixth Affiliated Hospital, Sun Yat-sen University

Role: STUDY_DIRECTOR

Useful links and downloads for this trial

Clinicaltrials.gov

Google Search Results

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