NCT05925738

Deep Learning Signature for Predicting Aggressive Histological Pattern in Resected Non-small Cell Lung Cancer

Positron Emission Tomography/ Computed Tomography (PET/CT) Based Deep Learning Signature for Predicting Aggressive Histological Pattern in Resected Non-small Cell Lung Cancer

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 1,500 (estimated)
• Sponsor: Shanghai Pulmonary Hospital, Shanghai, China · Academic / Other
• Sex: All
• Age: 20 Years – 75 Years
• Healthy volunteers: Accepted

Summary

The purpose of this study is to evaluate the performance of a PET/ CT-based deep learning signature for predicting aggressive histological pattern in resected non-small cell lung cancer based on a multicenter prospective cohort.

Conditions

• Non-small Cell Lung Cancer
• Spread Through Air Space
• Visceral Pleural Invasion
• Lymphovascular Invasion

Interventions

Type	Name	Description
DIAGNOSTIC_TEST	PET/CT-based Deep Learning Signature	Deep Learning Signature Based on PET-CT for Predicting the Aggressive Histological Pattern in Resected Non-small Cell Lung Cancer

Timeline

• Start date: 2023-05-01
• Primary completion: 2023-10-31
• Completion: 2023-10-31
• First posted: 2023-06-29
• Last updated: 2023-06-29

Locations

3 sites across 1 country: China