Deep-learning based model for prediction of spondyloarthritis progression using multi-parameter quantitative MRI

Status

Active, not recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2200061165

Enrollment

Unknown

Registered

2022-06-15

Start date

2022-06-01

Completion date

Unknown

Last updated

2023-03-26

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

Conditions

Spondyloarthritis

Interventions

One:None

Two:None

Eligibility

Sex/Gender

All

Age

18 Years to 100 Years

Inclusion criteria

Inclusion criteria: Patients diagnosed as spondyloarthritis by the rheumatologists in Peking University Shenzhen Hospital will be recruited from the Rheumatology Department. Inclusion critera are 1.Aged>18 years old 2. Confirmation of having spondyloarthritis by two rheumatologists including at least one senior rheumatologist. 3. Fulfill the ASAS classification critera for spondyloarthritis or the 1984 New York criteria for Ankylosing spondylitis.

Exclusion criteria

Exclusion criteria: Exclusion criteria: 1. Fully ankylosed spine shown on radiographic evaluation of the spine. 2. With contraindications to MRI, including metal implants that are not suitable for MRI scan, cardiac pacemaker/Cochlear implant, severe claustrophobia and pregnancy. 3. Metal implants in the pelvis.

Design outcomes

Primary

Measure	Time frame
Modified stoke ankylosing spondylitis spinal score, mSASSS;	—

Countries

China

Contacts

Public ContactChen Min

Peking University Shenzhen Hospital

chenmin@bjmu.edu.cn15210596510

Outcome results

None listed

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