Research on predicting the invasiveness, genetic status, and prognosis of colorectal cancer based on radiomics and deep learning

Status

Active, not recruiting

Phases

Early Phase 1

Study type

Observational

Source

ChiCTR

Registry ID

ChiCTR2500101240

Enrollment

Unknown

Registered

2025-04-22

Start date

2025-05-01

Completion date

Unknown

Last updated

2025-04-28

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

Conditions

Rectal cancer

Interventions

Gold Standard:Clinical outcome

Index test:Artificial intelligence predicts the genetic status and prognosis of colorectal cancer

Eligibility

Sex/Gender

All

Inclusion criteria

Inclusion criteria: 1. Colorectal cancer patients confirmed by histopathology and who have completed imaging examinations before surgery; 2. Not receiving radiation therapy or chemotherapy before surgery; 3. Complete CT or MRI examination within two weeks before surgery.

Exclusion criteria

Exclusion criteria: 1. Lack of clinical, imaging, or pathological data; 2. Received treatment for other malignant tumors before surgery; 3. The quality of CT or MRI images is insufficient to meet the analysis requirements.

Design outcomes

Primary

Measure	Time frame
Invasiveness, genetic status, and prognosis;accuracy;specificity;sensitivity;	—

Countries

China

Contacts

Public ContactYang Yunjun

The First People's Hospital of Foshan

xuzf23@163.com+86 18038866342

Outcome results

None listed

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