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

Magnetic Resonance Imaging Based Deep Learning Model for Diagnosis and Contour of Cervical Lymph Node for Nasopharyngeal Carcinoma: a Multicenter Study

Status

UNKNOWN

Phases

Unknown

Study type

Observational

Source

ClinicalTrials.gov

Registry ID

NCT05231616

Enrollment

5000

Registered

2022-02-09

Start date

2021-01-05

Completion date

2022-12-31

Last updated

2022-02-28

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Deep Learning Model

Brief summary

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.

Interventions

None listed

Study design

Observational model

COHORT

Time perspective

PROSPECTIVE

Eligibility

Sex/Gender

ALL

Healthy volunteers

Inclusion criteria

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

Exclusion criteria

* a history of cancer

Design outcomes

Primary

Measure	Time frame
Sensitivity and specificity	2022-12-31

Countries

China

Contacts

Primary ContactFang-Yun Xie, Professor

xiefy@sysucc.org.cn+86-20-87342618

Outcome results