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A Transfer Learning Radiomics Model for Predicting Response to Initial Transarterial Embolization in Patients with Gastroenteropancreatic Neuroendocrine Tumor Liver Metastases

Completed
Conditions
Neuroendocrine Tumors, NET
Registration Number
NCT06853457
Lead Sponsor
First Affiliated Hospital, Sun Yat-Sen University
Brief Summary

To develop and validate a CT-based transfer learning radiomics model for predicting response to initial TAE in GEP-NETLM patients and compare its performance with traditional radiomics and clinical models.

Detailed Description

Not available

Recruitment & Eligibility

Status
COMPLETED
Sex
All
Target Recruitment
257
Inclusion Criteria
  • (a) Clinical diagnosed as gastroenteropancreatic neuroendocrine tumor liver metastases; (b) Received initial transarterial embolization therapy; (c) Underwent multi-phase ceCT scans pre-TAE (≤1 month) and post-TAE (4-6 weeks).
Exclusion Criteria
  • (a) Neuroendocrine carcinoma (NEC) or other malignancies. (b) Received other liver metastasis treatments. (c) Lack of Multi-phase ceCT scans records. (d) CT images with artifacts or no visible lesions.

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
The efficacy of TAEWithin one month prior and 4-6 weeks following the initial TAE.

Complete multiphase contrast-enhanced CT images were collected preoperatively and postoperatively. The efficacy of TAE was assessed based on RECIST 1.1 criteria. Patients were classified as objective responders (those achieving complete response \[CR\] or partial response \[PR\]) or non-responders (those with stable disease \[SD\] or progressive disease \[PD\]) through evaluation of target lesions.

Secondary Outcome Measures
NameTimeMethod

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