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A multicenter study of radiomics and deep learning models to evaluate images of colorectal tumors and related diseases

A multicenter study of radiomics and deep learning models to evaluate images of colorectal tumors and related diseases

Status
Recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2500108799
Enrollment
Unknown
Registered
2025-09-05
Start date
2023-01-01
Completion date
Unknown
Last updated
2025-09-08

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

Conditions

Colorectal cancer

Interventions

Case series :none

Sponsors

Sir Run Run Shaw Hospital, Zhejiang University School of Medicine
Lead Sponsor

Eligibility

Sex/Gender
All
Age
18 Years to 90 Years

Inclusion criteria

Inclusion criteria: 1. Age >= 18 years old; 2. Colorectal-related MR, CT and other imaging examinations, and abdominal examination.

Exclusion criteria

Exclusion criteria: 1. Artifacts such as breathing movements are so obvious that they cannot meet the diagnostic requirements; 2. Lack of important clinical data, such as incomplete MR/CT imaging examination, basic data and laboratory examination data, and lack of pathological diagnosis results after treatment; 3. The patient's diagnosis is unclear, such as neither pathological diagnosis nor clinical diagnosis.

Design outcomes

Primary

MeasureTime frame
Detection rate;—

Countries

China

Contacts

Public ContactSun Jihong

Sir Run Run Shaw Hospital, Zhejiang University School of Medicine

sunjihong@zju.edu.cn+86 138 5717 6538

Outcome results

None listed

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