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A prediction model for the efficacy of induction chemotherapy in locally advanced nasopharyngeal carcinoma based on the combination of neural networks optimized by ant colony algorithm and MRI radiomics

A prediction model for the efficacy of induction chemotherapy in locally advanced nasopharyngeal carcinoma based on the combination of neural networks optimized by ant colony algorithm and MRI radiomics

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500112883
Enrollment
Unknown
Registered
2025-11-20
Start date
2025-04-30
Completion date
Unknown
Last updated
2025-11-24

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

Conditions

Nasopharyngeal Carcinoma

Interventions

Response group and resistance group:None
Review Group:None

Sponsors

Guangxi Medical University Cancer Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Histopathology confirmed NPC; 2. According to the 8th edition of the International Union Against Cancer/American Joint Committee on Cancer (UICC/AJCC) staging system, all patients were in the locally advanced stage (III-IVa); 3. Untreated; 4. Received 3 cycles of IC; 5. MRI examinations were conducted before and after IC; 6. The image quality was sufficiently high; 7. No contraindications for MRI examination; 8. No other primary tumors.

Exclusion criteria

Exclusion criteria: 1. The nasopharyngeal lesion was not measurable on the pre-treatment MRI (< 5 mm); 2. No MR examination was conducted before or after IC; 3. The LANPC patient received an insufficient course of IC.

Design outcomes

Primary

MeasureTime frame
Responder;No-responder;—

Countries

China

Contacts

Public ContactHai Liao

Guangxi Medical University Cancer Hospital

42442427@qq.com+86 18077024005

Outcome results

None listed

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