Deep Learning Model for Diagnosis and Contour of Cervical Lymph Node for Nasopharyngeal Carcinoma

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

UNKNOWN

Total Enrollment

5000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2021-01-05

Study Completion Date

2022-12-31

Brief Summary

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The diagnosis of cervical lymph node in nasopharyngeal carcinoma is difficult. Magnetic resonance imaging based deep learning model may be a noninvasive and rapid diagnostic method for cervical lymph node. Thus, the investigators aimed to develop and externally validate a deep learning model to assist in the diagnosis and localization of metastatic lymph nodes in nasopharyngeal carcinoma.

Detailed Description

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Conditions

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Deep Learning Model

Study Design

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Observational Model Type

COHORT

Study Time Perspective

PROSPECTIVE

Eligibility Criteria

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Inclusion Criteria

* Pathological diagnosis of nasopharyngeal carcinoma; Cervival lymph nodes confirmed by pathology

Exclusion Criteria

* a history of cancer

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Responsible Party

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Fang-Yun Xie

Professor

Responsibility Role PRINCIPAL_INVESTIGATOR

Locations

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Sun Yat-sen University Cancer Center

Guangzhou, Guangdong, China

Site Status RECRUITING

Countries

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China

Central Contacts

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Fang-Yun Xie, Professor

Role: CONTACT

Phone: +86-20-87342618

Email: [email protected]

Facility Contacts

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Fang-Yun Xie, professor

Role: primary

Other Identifiers

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B2020-334

Identifier Type: -

Identifier Source: org_study_id