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

Recruiting
Conditions
Papillary Thyroid Carcinoma; Molecular Heterogeneity; Multi-model Analysis; Artificial Intelligence; Lymph Node Metastases; Disease-free Survival
Registration Number
NCT06241092
Lead Sponsor
Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University
Brief 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).

Detailed Description

Not available

Recruitment & Eligibility

Status
RECRUITING
Sex
All
Target Recruitment
256
Inclusion Criteria

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

Exclusion Criteria

The patient requires valve or other likely surgery The patient is unable to carry out any physical activity without discomfort The patient had thyroid ache within three months prior to enrollment The patient refuses to give informed consent The patient is a candidate for coronary bypass surgery or something similar

Study & Design

Study Type
OBSERVATIONAL
Study Design
Not specified
Primary Outcome Measures
NameTimeMethod
Lymph node metastasis2021.10.1

Lymph node metastasis is frequently influenced by a myriad of factors, and tumor heterogeneity stands out as a significant contributing element.

Secondary Outcome Measures
NameTimeMethod
Disease-free survival2021.10.1

Disease-free survival is defined as the time from randomization to the first occurrence of a relapse, progression, or death from any cause, commonly used in clinical trials of adjuvant therapy after curative surgery or radiation therapy. It is also used as a primary endpoint in studies of neoadjuvant therapy and a useful endpoint for evaluating the efficacy of treatments that aim to prevent cancer recurrence research

Trial Locations

Locations (1)

Sun Yat-Sen Memorial Hospital of Sun Yat-Sen University

🇨🇳

Guangzhou, Guangdong, China

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