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Comparing 3D, 2.5D and 2D deep-learning, radiomics, and fusion models for differentiating between spinal tuberculosis and spinal metastasis based on MR imaging: a multicenter, retrospective, diagnostic study

Comparing 3D, 2.5D and 2D deep-learning, radiomics, and fusion models for differentiating between spinal tuberculosis and spinal metastasis based on MR imaging: a multicenter, retrospective, diagnostic study

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500105629
Enrollment
Unknown
Registered
2025-07-08
Start date
2025-07-10
Completion date
Unknown
Last updated
2025-07-14

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

Conditions

Spinal tuberculosis and spinal metastasis

Interventions

Spinal tuberculosis group:None
Spinal metastases group:None

Sponsors

Sun Yat-Sen Memorial Hospital, Sun Yat-sen University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. This study includes patients who visited our hospital, Shanghai Changzheng Hospital, and Guangzhou Panyu District Hospital of Traditional Chinese Medicine from January 2019 to December 2024 and were diagnosed with spinal metastases or spinal tuberculosis for surgical treatment; 2. Have a clear histopathological diagnosis after surgery; 3. Clinical information and high-quality preoperative spine MR images can be obtained.

Exclusion criteria

Exclusion criteria: 1.MR poor image quality; 2. The target spinal lesion has had previous surgery.

Design outcomes

Primary

MeasureTime frame
Accuracy;—

Countries

China

Contacts

Public ContactWenjie Gao

Sun Yat-Sen Memorial Hospital, Sun Yat-sen University

1121134961@qq.com+86 20 3407 1700

Outcome results

None listed

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