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MRI image-based deep learning prediction of high risk of distant metastasis in stage II nasopharyngeal carcinoma: a multicenter retrospective study

MRI image-based deep learning prediction of high risk of distant metastasis in stage II nasopharyngeal carcinoma: a multicenter retrospective study

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2100050653
Enrollment
Unknown
Registered
2021-09-01
Start date
2021-12-01
Completion date
Unknown
Last updated
2022-05-02

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

Conditions

nasopharyngeal carcinoma

Interventions

Case series:No

Sponsors

Sun Yat-Sen University Cancer Center
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 70 Years

Inclusion criteria

Inclusion criteria: 1. Patients with nasopharyngeal carcinoma diagnosed by histopathology; 2. Patients with nasopharyngeal carcinoma diagnosed as stage II by the eighth edition of AJCC/UICC nasopharyngeal carcinoma staging; 3. Aged 18 to 70 years at the time of diagnosis; 4. Physical function status KPS score >= 70 points; 5. Complete complete anti-tumor treatment, including radiotherapy/chemotherapy; 6. Radiotherapy adopts intensity modulated radiotherapy technology; 7. All patients have MRI images of nasopharynx + neck before treatment, including T1, T2, T1 + C sequences; 8. No other tumor diseases in the past.

Exclusion criteria

Exclusion criteria: MRI image artifacts before treatment were large.

Design outcomes

Primary

MeasureTime frame
Distant Metastasis Free Survival;—

Secondary

MeasureTime frame
Overall Survival;—

Countries

China

Contacts

Public ContactXia Yunfei

Sun Yat-Sen University Cancer Center

xiayf@sysucc.org.cn+86 13602805461

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 4, 2026