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A Retrospective Study on Deep Learning-Based Dose Prediction for Nasopharyngeal Carcinoma Radiotherapy.

A Retrospective Study on Deep Learning-Based Dose Prediction for Nasopharyngeal Carcinoma Radiotherapy.

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600122337
Enrollment
Unknown
Registered
2026-04-13
Start date
2026-04-13
Completion date
Unknown
Last updated
2026-04-20

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

Conditions

Malignant tumor of nasopharynx.

Interventions

Nasopharyngeal malignant tumor observation group:None

Sponsors

The First Affiliated Hospital of China Medical University
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Patients with nasopharyngeal carcinoma who have completed full-course radiotherapy.

Exclusion criteria

Exclusion criteria: 1. Exclusion criteria related to diseases: Participants who have participated in other studies 2. General exclusion criteria: Any unstable systemic diseases: including active infections, uncontrolled hypertension, congestive heart failure, myocardial infarction, severe arrhythmias requiring medication, liver, kidney or metabolic diseases.

Design outcomes

Primary

MeasureTime frame
Structural Similarity Index, SSIM;Mean Absolute Error, MAE;—

Secondary

MeasureTime frame
Conformity Index, CI;Homogeneity Index, HI;D95;Mean Dose, Dmean;Maximum Dose, Dmax;Dose-Volume Histogram, DVH;—

Countries

China

Contacts

Public ContactQiao Qiao

The First Affiliated Hospital of China Medical University

qiaojiang120@126.com+86 13889368446

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Apr 23, 2026