The Role of ctDNA Testing Plus AI-based Pathology in Resectable LSCC

Status Recruiting

Clinical Trial Summary

The goal of this observational study is to explore whether ctDNA dynamic monitoring plus AI-based pathology can more effectively predict the therapeutic effect of neoadjuvant chemoimmunotherapy for resectable lung squamous cell carcinoma, so as to accurately guide clinical diagnosis and treatment.

Clinical Trial Description

This study is a single-center, observational, non-interventional, prospective study. 50 patients diagnosed with lung squamous cell carcinoma receiving neoadjuvant chemoimmunotherapy (ranging 2 to 4 cycles) will be planned to be enrolled in the study. Pre-treatment biopsy tissues of enrolled patients will be collected for whole exon sequencing (WES) testing, and personalized detection panel will be customized based on WES testing results. Peripheral blood will be collected 1 day before each cycle of neoadjuvant therapy, 1 day before surgery, 3 days after surgery, and 3 weeks after surgery for ctDNA testing. In addition, the prediction model of AI-based pathology will be constructed by AI deep learning based on pathological sections of pre-treatment biopsy tissues. All inclued patients will be regularly followed up for at least 5 years. ;

Study Design

Related Conditions & MeSH terms

Clinical Trial Details

NCT number	NCT05778253
Study type	Observational
Source	Second Xiangya Hospital of Central South University
Contact	Yan Hu, M.D., Ph.D.
Phone	8685296122
Email	yanhu@csu.edu.cn
Status	Recruiting
Phase
Start date	March 23, 2023
Completion date	September 23, 2029

View Details

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