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ResNet-based risk assessment of creeping fat CT in Crohn's disease and its multi-omics characterization

ResNet-based risk assessment of crawling fat CT in Crohn's disease and its multi-omics characterization

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500098375
Enrollment
Unknown
Registered
2025-03-06
Start date
2025-05-16
Completion date
Unknown
Last updated
2025-03-10

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

Conditions

Crohn’s disease

Interventions

Sponsors

The First Affiliated Hospital of Zhejiang Chinese MedicalUniversity(Zhejiang Provincial Hospital of Chinese Medicine)
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients with clinically confirmed CD who underwent small bowel CT (computed tomography enterography (CTE)); 2. Patients with complete clinical data; 3. Patients who did not undergo abdominal surgery prior to the CTE scan; 4. Patients without disease progression for at least 12 months of follow-up.

Exclusion criteria

Exclusion criteria: 1. Penetrating disease, stenosis, previous history of bowel resection, or consideration of CD-related surgery on initial admission;2. Concomitant malignancy or metabolic disease (e.g., hyperthyroidism or diabetes mellitus) that may affect adipose tissue distribution or function. 3. Steroid hormone or biologic medications within three months. 4. Poor quality of CTE images.

Design outcomes

Primary

MeasureTime frame
Deep learning models for creeping fat risk stratification;

Secondary

MeasureTime frame
Fecal metabolites ;Intestinal flora;

Countries

China

Contacts

Public ContactFeini Zhou

The First Affiliated Hospital of Zhejiang Chinese MedicalUniversity(Zhejiang Provincial Hospital

53805129@qq.com+86 136 1671 7790

Outcome results

None listed

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