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Accurate staging of axillary lymph nodes in breast cancer aided by machine learning model based on energy spectrum CT imaging

Accurate staging of axillary lymph nodes in breast cancer aided by machine learning model based on energy spectrum CT imaging

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500102106
Enrollment
Unknown
Registered
2025-05-08
Start date
2023-09-18
Completion date
Unknown
Last updated
2025-05-12

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

Conditions

Breast tumor

Interventions

Gold Standard:Pathology.
Index test:A machine learning model for diagnosis of axillary lymph node status was constructed based on energy spectrum CT imaging.

Sponsors

Suining Central Hospital
Lead Sponsor

Eligibility

Sex/Gender
Female
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.Female; 2.Age: >=18 years; 3.Confirmed as invasive breast cancer by histological method; 4.Scheduled to undergo axillary lymph node aspiration, sentinel lymph node biopsy, or axillary lymph node dissection; 5.No anti-tumor treatment has been received; 6.Patients voluntarily participate in the study and sign the Informed Consent Form.

Exclusion criteria

Exclusion criteria: 1. Suffering from other malignant tumors; 2. Acute inflammatory disease; 3. Suffering from diseases of lymphatic system or blood system; 4. Previous history of axillary surgery; 5. Special types of breast cancer: breast cancer during pregnancy or inflammatory breast cancer.

Design outcomes

Primary

MeasureTime frame
Accuracy;—

Secondary

MeasureTime frame
Sensitivity;Specificity;Positive predictive value;Negative predictive value;—

Countries

??

Contacts

Public ContactMaoshan Chen

Suining Central Hospital

snscms@126.com+86 180 0825 5330

Outcome results

None listed

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