NCT05617469

DLCS for Predicting Neoadjuvant Chemotherapy Response

Deep Learning Radio-clinical Signatures for Predicting Neoadjuvant Chemotherapy Response and Prognosis From Pretreatment CT Images of LAGC Patients

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 1,100 (estimated)
• Sponsor: Zhejiang Cancer Hospital · Academic / Other
• Sex: All
• Age: 18 Years – 80 Years
• Healthy volunteers: —

Summary

The early noninvasive screening of patients suitable for neoadjuvant chemotherapy (NCT) is essential for personalized treatment in locally advanced gastric cancer (LAGC). The aim of this study was to develop and visualized a radio-clinical biomarker from pretreatment oversampled CT images to predict the response and prognosis to NCT in LAGC patients.

Conditions

• Gastric Cancer
• CT Images
• Deep Learning
• Neoadjuvant Chemotherapy
• Tumor Regression Grade

Interventions

Type	Name	Description
OTHER	develop and visualized a radio-clinical signatures from pretreatment oversampled CT images	develop and visualized a radio-clinical signatures from pretreatment oversampled CT images to predict the neoadjuvant chemotherapy response and prognosis

Timeline

• Start date: 2022-07-01
• Primary completion: 2023-01-30
• Completion: 2023-07-31
• First posted: 2022-11-15
• Last updated: 2022-11-15

Locations

1 site across 1 country: China