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Radiomics and deep learning techniques based on contrast-enhanced CT images for predicting the depth of invasion of esophageal squamous cell carcinoma

Radiomics and deep learning techniques based on contrast-enhanced CT images for predicting the depth of invasion of esophageal squamous cell carcinoma

Status
Active, not recruiting
Phases
Unknown
Study type
Observational
Source
ChiCTR
Registry ID
ChiCTR2600126249
Enrollment
Unknown
Registered
2026-06-05
Start date
2026-06-09
Completion date
Unknown
Last updated
2026-06-08

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

Conditions

Esophageal squamous cell carcinoma

Interventions

Observation group:None

Sponsors

Meizhou People's Hospital
Lead Sponsor

Eligibility

Sex/Gender
All

Inclusion criteria

Inclusion criteria: 1. Patients who have undergone radical resection; 2. Patients who have not received neoadjuvant radiotherapy or neoadjuvant chemoradiotherapy or other preoperative treatments; 3. Complete clinicopathological data (including complete postoperative pathology reports); 4. Underwent routine preoperative examinations such as enhanced chest and abdominal CT, with complete and available data.

Exclusion criteria

Exclusion criteria: 1. Patients who received neoadjuvant chemoradiotherapy, immunotherapy, or other anti-tumor treatments before surgery; 2. Cases with poor CT image quality, severe motion artifacts, or metal artifacts, making image analysis impossible; 3. Patients clinically diagnosed with distant metastasis (M1) or with non-squamous carcinoma; 4. Cases with incomplete clinical, pathological, or imaging data that cannot meet the requirements of the study.

Design outcomes

Primary

MeasureTime frame
Depth of esophageal cancer tumor invasion;Accuracy;

Countries

China

Contacts

Public ContactKang Qiwei

Meizhou People's Hospital

kangqiwei@163.com+86 753 213 1836

Outcome results

None listed

Source: ChiCTR (via WHO ICTRP) · Data processed: Jun 11, 2026