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A multicenter study of a preoperative imaging–based artificial intelligence model for predicting axillary nodal status in breast cancer

Application Research of Multi-modal Imaging Analysis Based on Radiomics Fusion and Deep Learning in Predicting Metastasis of Sentinel and Non-sentinel Lymph Nodes in Breast Cancer

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120322
Enrollment
Unknown
Registered
2026-03-12
Start date
2026-03-15
Completion date
Unknown
Last updated
2026-06-08

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

Conditions

Breast cancer

Interventions

Gold Standard:Intraoperative and postoperative pathological results of sentinel and non-sentinel lymph nodes.
Index test:A multimodal fusion artificial intelligence prediction model.

Sponsors

Yunnan Cancer Hospital
Lead Sponsor

Eligibility

Sex/Gender
Female

Inclusion criteria

Inclusion criteria: 1. Patients with invasive breast cancer; 2. Breast ultrasound and mammography were performed within 3 weeks before breast surgery. 3. Perform sentinel lymph node biopsy during the operation.

Exclusion criteria

Exclusion criteria: 1. History of breast or axillary surgery, radiotherapy (RT), or neoadjuvant chemotherapy (NACT); 2. Bilateral breast cancer; 3. Another malignancy or distant metastasis; 4. Incomplete or poor-quality imaging; 5. Incomplete clinicopathological data.

Design outcomes

Primary

MeasureTime frame
AUC;—

Secondary

MeasureTime frame
Accuracy;Status of sentinel lymph nodes;Status of non-sentinel lymph nodes;sensitivity;specificity;—

Countries

China

Contacts

Public ContactGuojun Zhang

Yunnan Cancer Hospital

zhangguojun@kmmu.edu.cn+86 188 5006 4298

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026