A Transfer Learning Radiomics Model for Predicting Response to Initial Transarterial Embolization in Patients with Gastroenteropancreatic Neuroendocrine Tumor Liver Metastases
- 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
- (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).
- (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
Name Time Method The efficacy of TAE Within 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
Name Time Method
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