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

RECRUITINGSponsored by Fudan University
Actively Recruiting
SponsorFudan University
Started2024-01-01
Est. completion2025-12
Eligibility
Age18 Years – 75 Years
Healthy vol.Accepted

Summary

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.

Eligibility

Age: 18 Years – 75 YearsHealthy volunteers accepted
Inclusion Criteria:

1. ECOG performance status score 0-2;
2. Histologically or cytologically confirmed stage III-IV NSCLC;
3. If the baseline pathology is adenocarcinoma, driver gene testing (at least EGFR/ALK/ROS1/KRAS/MET) should be performed;
4. Complete imaging data of baseline stage (contrast-enhanced MR For lung cancer, contrast-enhanced MR/CT for colorectal cancer, and chest CT for breast cancer);
5. No target organ metastasis on baseline imaging (no brain/liver/lung metastasis for lung cancer/colorectal cancer/breast cancer, respectively);
6. Patients received at least one systemic therapy (chemotherapy, targeted therapy, immunotherapy, etc.) and received regular follow-up;
7. Regular follow-up during and after treatment;
8. Life expectancy ≥6 months;

Exclusion Criteria:

1. Patients with indeterminate pathological type;
2. Patients without baseline imaging data before treatment;
3. Baseline imaging examination showed that the corresponding target organ had metastasis (lung cancer/colorectal cancer/breast cancer corresponding to brain/liver/lung metastasis);
4. patients who cannot or refuse to receive regular imaging follow-up;
5. Combined history of other malignant tumors;
6. Medical examination or clinical findings or other uncontrollable conditions that the investigator considers may interfere with the results or increase the risk of treatment complications for the patient; ,
7. Lactating or pregnant women;
8. Receiving other long-term medications that may affect disease progression as assessed by a physician.

Conditions3

CancerMetastasisPredictive Cancer Model

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