AI Models to Predict Thyroid Cartilage Invasion in Laryngeal Carcinoma
CT-based Radiomics, Two-dimensional and Three-dimensional Deep Learning Models to Predict Thyroid Cartilage Invasion in Laryngeal Carcinoma: a Multicenter Study
First Affiliated Hospital of Chongqing Medical University
400 participants
Aug 13, 2023
OBSERVATIONAL
Conditions
Summary
This retrospective study was to develop and verify CT-based AI model to preoperatively predict the thyroid cartilage invasion of laryngeal cancer patients, so as to provide more accurate diagnosis and treatment basis for clinicians. In addition, the researchers investigated the prediction of survival outcomes of patients by the above optimal models.
Eligibility
Inclusion Criteria3
- Availability of complete clinical data
- Surgery-proven or biopsy-proven diagnosis of laryngeal squamous cell carcinoma
- CT examination performed within 2 weeks before surgery
Exclusion Criteria3
- Patients who received preoperative chemotherapy or radiation therapy
- CT images with significant artifacts
- Patients with tumor recurrence
Interventions
Radiomics extracts quantitative information from medical images to generate high-dimensional feature vectors for analysis. It aims to provide insights into disease processes and improve diagnosis. Deep learning utilizes neural networks with multiple layers to learn complex patterns from data. In medical imaging, it enables accurate and efficient analysis for disease detection and diagnosis.
Locations(1)
View Full Details on ClinicalTrials.gov
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NCT06463756