AI-Based Multimodal Multi-tasks Analysis Reveals Tumor Molecular Heterogeneity, Predicts Preoperative Lymph Node Metastasis and Prognosis in Papillary Thyroid Carcinoma: A Retrospective Study

Status: Recruiting
Location: See location...
Intervention Type: Other
Study Type: Observational
SUMMARY

This study involved a comprehensive analysis of 256 PTC patients from Sun Yat-sen Memorial Hospital of Sun Yat-sen University (SYSMH) and 499 patients from The Cancer Genome Atlas. DNA-based next-generation sequencing (NGS) and single-cell RNA sequencing (scRNA-seq) were employed to capture genetic alterations and TME heterogeneity. A deep learning multimodal model was developed by incorporating matched histopathology slide images, genomic, transcriptomic, immune cells data to predict LNM and disease-free survival (DFS).

Eligibility
Participation Requirements
Sex: All
Healthy Volunteers: f
View:

• ≥ 18 years of age Diagnosis of Papillary thyroid carcinoma at least one months before trial Willing to return for required follow-up (posttest) visits

Locations
Other Locations
China
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
RECRUITING
Guangzhou
Time Frame
Start Date: 2024-04-01
Estimated Completion Date: 2025-01-20
Participants
Target number of participants: 256
Treatments
TCGA
SYSMH
Sponsors
Leads: Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

This content was sourced from clinicaltrials.gov