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Development, validation, and clinical evaluation of an AI model for calcaneal fractures based on multimodal imaging

Development, validation, and clinical evaluation of an AI model for calcaneal fractures based on multimodal imaging

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600117640
Enrollment
Unknown
Registered
2026-01-27
Start date
2026-02-01
Completion date
Unknown
Last updated
2026-02-02

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

Conditions

Calcaneal fracture

Interventions

Gold Standard:Two senior radiologists who have received specialist training and possess professional practical experience in foot and ankle medicine interpret each case independently based on CT image
Index test:The indicator test is an artificial intelligence-assisted diagnostic system for calcaneal fractures based on multimodal imaging (preoperative CT and postoperative X-ray/DR). The system can

Sponsors

Hefei First People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Preoperative or whole-foot CT scans are available; 2. Postoperative X-rays (standard lateral + axial/Harris views) are available, and if used for "CT reference standard" assessment, corresponding postoperative CT scans within a similar time window are required; 3. Images are readable and usable for measurement/annotation (quality meets minimum standards).

Exclusion criteria

Exclusion criteria: 1. Poor image quality prevents the measurement of key parameters or the completion of annotation/interpretation. 2. A history of severe foot deformity significantly affects the assessment of anatomical structures. 3. Imaging examinations strongly suggest infection or other conditions that may significantly alter imaging findings.

Design outcomes

Primary

MeasureTime frame
Diagnostic performance and agreement (AI-assisted vs standard reading) for calcaneal fracture classification;Diagnostic performance for calcaneal fracture detection (AI-assisted vs standard reading);

Secondary

MeasureTime frame
Reading efficiency: interpretation time and report editing time (AI-assisted vs standard reading);Accuracy and calibration of postoperative X-ray–based risk stratification and escalation recommendation;

Countries

China

Contacts

Public ContactShaobin Wang

Hefei First People's Hospital

shaobin@mail.ustc.edu.cn+86 551 82139070

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Feb 7, 2026