Actively Recruiting

Age: 18Years - 75Years
All Genders
NCT06202404

Predicting Tumor Metastasis by Employing a Target Organ/Primary Lesion Fusion Radiomics Model

Led by Fudan University · Updated on 2024-02-09

166

Participants Needed

2

Research Sites

204 weeks

Total Duration

On this page

AI-Summary

What this Trial Is About

A pre-metastatic target organ/primary lesion fusion radiomics model was developed based on the "soil-seed" theory to predict comman tumor metastasis in retrospective settings. To prospectively verify the performance of the target organ/primary lesion fusion radiomics model in predicting tumor metastasis patterns (brain metastasis in lung cancer, liver metastasis in colorectal cancer, lung metastasis in breast cancer), we designed this prospective observational trial.

CONDITIONS

Official Title

Predicting Tumor Metastasis by Employing a Target Organ/Primary Lesion Fusion Radiomics Model

Who Can Participate

Age: 18Years - 75Years
All Genders

Eligibility Criteria

Eligible

You may qualify if you...

  • ECOG performance status score between 0 and 2
  • Histological or cytological confirmation of stage III-IV non-small cell lung cancer
  • Driver gene testing performed if pathology is adenocarcinoma, including at least EGFR, ALK, ROS1, KRAS, or MET
  • Complete baseline imaging data: contrast-enhanced MRI for lung cancer, contrast-enhanced MRI/CT for colorectal cancer, and chest CT for breast cancer
  • No metastasis in the target organ on baseline imaging (no brain metastasis for lung cancer, no liver metastasis for colorectal cancer, no lung metastasis for breast cancer)
  • Received at least one systemic therapy such as chemotherapy, targeted therapy, or immunotherapy
  • Regular follow-up during and after treatment
  • Life expectancy of at least 6 months
Not Eligible

You will not qualify if you...

  • Indeterminate pathological tumor type
  • Lack of baseline imaging data before treatment
  • Presence of metastasis in the target organ on baseline imaging
  • Inability or refusal to undergo regular imaging follow-up
  • History of other malignant tumors
  • Medical conditions or findings that may interfere with results or increase risk of complications
  • Pregnant or lactating women
  • Use of long-term medications that may affect disease progression as assessed by a physician

AI-Screening

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Trial Site Locations

Total: 2 locations

1

Fudan University Shanghai Cancer Center

Shanghai, Shanghai Municipality, China, 200032

Actively Recruiting

2

Fudan University Shanghai Cancer Center

Shanghai, China

Actively Recruiting

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Research Team

X

Xiao Chu

CONTACT

How is the study designed?

Study Type

OBSERVATIONAL

Masking

N/A

Allocation

N/A

Model

N/A

Primary Purpose

N/A

Number of Arms

2

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