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Radiomics-based Artificial Intelligence System to Predict Neoadjuvant Treatment Response in Rectal Cancer

NCT04273477 · Status: UNKNOWN · Type: OBSERVATIONAL · Enrollment: 100

Last updated 2020-02-18

No results posted yet for this study

Summary

In this study, investigators utilize a radiomics prediction model to predict the tumor response to neoadjuvant chemoradiotherapy (nCRT) before the nCRT is administered for patients with locally advanced rectal cancer (LARC). Previously, the radiomics prediction model has been constructed based on the radiomics features extracted from pretreatment Magnetic Resonance Imaging (MRI) in the training set, and optimized in the external validation set. The predictive power of this radiomics prediction model to discriminate the pathologic complete response (pCR) patients from non-pCR individuals, will be further verified in this prospective, multicenter clinical study.

Conditions

Sponsors & Collaborators

  • The Third Affiliated Hospital of Kunming Medical College.

    collaborator OTHER

  • Sir Run Run Shaw Hospital

    collaborator OTHER

  • Sixth Affiliated Hospital, Sun Yat-sen University

    lead OTHER

Principal Investigators

  • Xiangbo Wan, MD, PhD · Sixth Affiliated Hospital, Sun Yat-sen University

Eligibility

Min Age
18 Years
Max Age
75 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-01-10
Primary Completion
2020-07-31
Completion
2020-12-31

Countries

  • China

Study Locations

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Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04273477 on ClinicalTrials.gov