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Prospective Validation of Deep Learning Driven Malignancy Prediction Model in Soft Tissue Tumors on Ultrasonography and Clinical Indexes

The value of deep learning in assisting ultrasonography in diagnosing soft tissue tumors

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2200063773
Enrollment
Unknown
Registered
2022-09-16
Start date
2022-09-15
Completion date
Unknown
Last updated
2023-04-17

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

Conditions

Soft tissue tumors

Interventions

Index test:The area under the curve (AUC), sensitivity, specificity, PPV, NPV, accuracy, and Youden index of the auto-diagnosis software and doctors with different experiences in diagnosing STT by ana

Sponsors

Shenzhen Hospital of Peking University
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Clinically diagnosed as soft tissue tumors; 2. Superficial soft tissue tumors of the trunk, limbs, and head and neck; 3. Receive an ultrasound examination; 4. The patient received soft tissue tumor puncture or resection within 3 months, and underwent pathological examination after surgery; 5. All enrolled patients signed the informed consent form for this study, and the guardians signed the informed consent form for patients younger than 18 years old.

Exclusion criteria

Exclusion criteria: 1. The patient does not accept or is unable to cooperate with the ultrasound examination; 2. Cases occurring in superficial organs such as thyroid gland, breast gland, parotid gland, and lymph nodes; 3. The patient has no postoperative pathological results.

Design outcomes

Primary

MeasureTime frame
the area under the ROC curve;

Secondary

MeasureTime frame
Sensitivity;Specificity;

Countries

China

Contacts

Public ContactHaiqin Xie

Shenzhen Hospital of Peking University

xiehaiqin@126.com+86 13922802885

Outcome results

None listed

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