NCT06853457

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

A Transfer Learning Radiomics Model for Predicting Response to Initial Transarterial Embolization in Patients with Gastroenteropancreatic Neuroendocrine Tumor Liver Metastases: from Lesion-targeted to Patient-targeted Prediction

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 257 (actual)
• Sponsor: First Affiliated Hospital, Sun Yat-Sen University · Academic / Other
• Sex: All
• Age: 18 Years – 78 Years
• Healthy volunteers: Not accepted

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.

Conditions

• Neuroendocrine Tumors, NET

Timeline

• Start date: 2014-01-01
• Primary completion: 2022-09-30
• Completion: 2024-09-01
• First posted: 2025-03-03
• Last updated: 2025-03-03