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Prospective Assessment of Bone Tumor Risk from Multimodal Multiview Radiography Images via Clinically Applicable Deep Learning

Prospective Assessment of Bone Tumor Risk from Multimodal Multiview Radiography Images via Clinically Applicable Deep Learning

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500102778
Enrollment
Unknown
Registered
2025-05-20
Start date
2025-06-01
Completion date
Unknown
Last updated
2025-05-26

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

Conditions

Bone Tumor

Interventions

Gold Standard:Pathological result
Index test:AI-Assisted Diagnostic System Based on Deep Learning Models

Sponsors

Department of Radiology, The Affiliated Hospital of Qingdao University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: Inclusion Criteria: (1) Osteolytic lesions located in the long bones of the limbs (including bones of the hands and feet); (2) Postoperative histopathological confirmation of bone tumor; (3) Availability of X-ray imaging; (4) Complete clinical and pathological data.

Exclusion criteria

Exclusion criteria: Exclusion Criteria: (1) Poor-quality X-ray images that hinder analysis; (2) X-ray images available but lacking corresponding clinical and pathological data; (3) Lesions located in non-limb bones (e.g., spine, pelvis) or non-osteolytic lesions.

Design outcomes

Primary

MeasureTime frame
Area under receiver operating characteristic curve;—

Secondary

MeasureTime frame
Sensitivity;Specificity;Accuracy;—

Countries

China

Contacts

Public ContactDapeng Hao

Department of Radiology, The Affiliated Hospital of Qingdao University

haodp2021@qdu.edu.cn+86 186 6180 2582

Outcome results

None listed

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