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Multimodal Deep Learning for Lymph Node Metastasis in Thyroid Cancer

NCT ID: NCT07299318

Last Updated: 2025-12-23

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

NOT_YET_RECRUITING

Total Enrollment

3200 participants

Study Classification

OBSERVATIONAL

Study Start Date

2026-01-01

Study Completion Date

2026-05-01

Brief Summary

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Papillary thyroid carcinoma (PTC) is the most common endocrine malignancy in clinical practice, accounting for approximately 85% of all thyroid malignancies. The occurrence of cervical lymph node metastasis further increases the risk of local tumor recurrence and distant metastasis, thereby reducing patient survival rates. Pathological examinations reveal that approximately 30-80% of PTC patients have lymph node metastasis. Early detection of metastatic lymph nodes and the development of individualized treatment plans are crucial for improving patient prognosis. Currently, the primary method for diagnosing lymph node metastasis is ultrasound-guided fine-needle aspiration, but its accuracy is limited by sample quality and carries a risk of false-negative results. In recent years, deep learning technology has demonstrated significant potential in the field of medical image analysis. Therefore, the investigators aim to develop a deep learning model based on neck ultrasound to more accurately predict lymph node metastasis.

Detailed Description

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Conditions

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Papillary Thyroid Carcinoma

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Papillary thyroid carcinoma group

not intervention

Intervention Type OTHER

This is a retrospective observational study in which participants will not undergo any interventions, and only data collection and analysis will be performed on the participants.

Interventions

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not intervention

This is a retrospective observational study in which participants will not undergo any interventions, and only data collection and analysis will be performed on the participants.

Intervention Type OTHER

Eligibility Criteria

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Inclusion Criteria

Cases aged 18-80 years who underwent thyroid ultrasound examination and postoperative pathological examination of the thyroid.

Cases with a first-time diagnosis of papillary thyroid carcinoma. Cases who underwent lymph node dissection

Exclusion Criteria

Cases aged \<18 years or \>80 years. Cases with poor-quality ultrasound images. Cases with incompletely visualized nodules. Cases with images showing multiple distinct lesions. Cases belonging to special populations. Cases with concurrent other tumors. Cases with a history of thyroid cancer resection
Minimum Eligible Age

18 Years

Maximum Eligible Age

80 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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West China Hospital

OTHER

Sponsor Role lead

Responsible Party

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Yu Feng

Clinical Doctorate

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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West China hospital of Sichuan University

Chengdu, Sichuan, China

Site Status

Countries

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China

Central Contacts

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Jianyong Lei

Role: CONTACT

Phone: +86 19983137992

Email: [email protected]

Yu Feng

Role: CONTACT

Email: [email protected]

Facility Contacts

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Jianyong Lei

Role: primary

Yu Feng

Role: backup

Other Identifiers

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2025(2352)

Identifier Type: -

Identifier Source: org_study_id