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Deep Radiomics-based Fusion Model Predicting Bevacizumab Treatment Response and Outcome in Patients With Colorectal Liver Metastases

NCT06023173 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 307

Last updated 2023-09-14

No results posted yet for this study

Summary

This multi-modal deep radiomics model, using PET/CT, clinical and histopathological data, was able to identify patients with bevacizumab-sensitive unresectable colorectal cancer liver metastases, providing a favorable approach for precise patient treatment.

Conditions

  • The Patients With CRLM Who Benefit More From Bevacizumab

Interventions

DIAGNOSTIC_TEST

Deep radiomics-based fusion model

This multi-modal deep radiomics model, using PET/CT, clinical and histopathological data, was able to identify patients with bevacizumab-sensitive CRLM, providing a favorable approach for precise patient treatment.

Sponsors & Collaborators

  • Fudan University

    lead OTHER

Principal Investigators

  • Jianmin Xu, MD · Fudan University

Eligibility

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

Timeline & Regulatory

Start
2013-10-01
Primary Completion
2023-01-01
Completion
2023-01-01

Countries

  • China

Study Locations

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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 NCT06023173 on ClinicalTrials.gov