AI Models to Predict Thyroid Cartilage Invasion in Laryngeal Carcinoma

Chongqing Medical University

Status: Enrolling

Conditions: Thyroid Cartilage; Laryngeal Carcinoma

Treatments: Other: AI

Study type: Observational

Funder types: Other

Identifiers

NCT06463756

2024-Chenx

Details and patient eligibility

About

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.

Full description

Laryngeal squamous cell carcinoma (LSCC), as one of the most common head and neck tumors, is the eighth leading cause of cancer-associated death worldwide. The treatment decisions has a profound impact on both tumor control and functional prognosis of LSCC patients. And these decisions are primarily based on tumor staging, with the invasion of the thyroid cartilage serving as a crucial determinant. Consequently, the presence of thyroid cartilage invasion indicates an advanced stage (T3 or T4) diagnosis for the LSCC patients. For patients without thyroid cartilage invasion, partial laryngectomy may be considered to preserve laryngeal function. However, for patients with advanced laryngeal carcinoma and thyroid cartilage invasion extending beyond the larynx, total laryngectomy is often necessary to completely remove the tumor and extend survival time. Therefore, accurate assessment of thyroid cartilage invasion is vital for treatment decision-making and prognosis evaluation for LSCC patients.

Enrollment: 400 estimated patients

Sex: All

Ages: 18 to 81 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Availability of complete clinical data
2. Surgery-proven or biopsy-proven diagnosis of laryngeal squamous cell carcinoma
3. CT examination performed within 2 weeks before surgery

Exclusion criteria

1. Patients who received preoperative chemotherapy or radiation therapy
2. CT images with significant artifacts
3. Patients with tumor recurrence

Trial design

400 participants in 3 patient groups

training cohort

Description:

No interventions

Treatment:

Other: AI

internal validation cohort

Description:

No interventions

Treatment:

Other: AI

external validation cohort

Description:

No interventions

Treatment:

Other: AI