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Magnetic resonance imaging radiomics model for diagnosing massive rotator cuff tears

Feasibility of Predicting Tendon Repair in Patients with Massive Rotator Cuff Tears Using Deep Learning-Based Magnetic Resonance Imaging Radiomics Model

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600120695
Enrollment
Unknown
Registered
2026-03-18
Start date
2026-03-18
Completion date
Unknown
Last updated
2026-03-23

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

Conditions

Cases of massive rotator cuff tear

Interventions

Observation group:N/A

Sponsors

Taizhou Hospital, Zhejiang Province
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to No maximum

Inclusion criteria

Inclusion criteria: 1.The patient who underwent shoulder magnetic resonance examination and underwent surgery for severe rotator cuff injury in our hospital;

Exclusion criteria

Exclusion criteria: 1. Patient is under 18 years old; 2. Severe artifacts are present in the images; 3. The images do not contain a complete 3D sequence.

Design outcomes

Primary

MeasureTime frame
Surgical methods and the extent of tendon injury during the operation;—

Secondary

MeasureTime frame
The area, volume and fat ratio of each muscle of the rotator cuff;Prognosis 6 months to 1 year after surgery;—

Countries

China

Contacts

Public ContactDing Jianrong

Taizhou Hospital, Zhejiang Province

dingjr@enzemed.com+86 576 8519 1203

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Apr 3, 2026