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Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Based on Multi-Stain WSI Using Deep Learning: A Multicenter Study

Prediction of Neoadjuvant Chemotherapy Response in Breast Cancer Based on Multi-Stain WSI Using Deep Learning: A Multicenter Study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2400091648
Enrollment
Unknown
Registered
2024-10-31
Start date
2024-11-01
Completion date
Unknown
Last updated
2024-11-04

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

Conditions

Breast cancer

Interventions

Index test:A system integrating multi-stained whole-slide digital images

Sponsors

Yantai Yuhuangding Hospital
Lead Sponsor

Eligibility

Sex/Gender
Female

Inclusion criteria

Inclusion criteria: nclusion criteria: (1) patients pathologically diagnosed with breast cancer; (2) patients undergoing standardized NAC regimens, with an expectation to complete the entire course; patients currently receiving or who have completed standard NAC and are awaiting surgery were also considered eligible; (3) the ability to perform a biopsy within two weeks prior to NAC, with multi-stain pathology slides, including HE, ER, PR, Ki-67, and Her2 staining; (4) no other tumors occurred during NAC and surgery.

Exclusion criteria

Exclusion criteria: Exclusion criteria: (1) patients with severe comorbidities or other malignancies; (2) patients who did not complete the NAC regimen; (3) lack of complete clinical data for analysis; (4) pathology slide image quality not meeting study requirements.

Design outcomes

Primary

MeasureTime frame
Area under receiver operating characteristic curve;

Secondary

MeasureTime frame
Sensitivity;Specificity;Accuracy;

Countries

China

Contacts

Public ContactNing Mao

Yantai Yuhuangding Hospital

maoning@pku.edu.cn+86 131 0535 1972

Outcome results

None listed

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