Recruiting NCT07050576

Lymph Node Metastasis in Early Esophageal Squamous Cell Carcinoma

— Observational ESCC Lymph Node Metastasis Radiomics

For patients and families

In plain language

An automatic summary of structured registry data. It is an orientation aid, not a substitute for the official protocol or a physician assessment.

What is being studied: The protocol lists: The prediction model of lymph node metastasis in early esophageal squamous cell carcinoma.
Who it may be relevant to: Registry conditions: ESCC, Lymph Node Metastasis, Radiomics. Basic parameters: No limits · All.
What needs checking: Age, condition and sex are only basic indicators. Prior treatment, laboratory values and other mandatory requirements appear in the eligibility criteria below.
Where it takes place: China
Next step: Save the trial, show it to the treating physician, and confirm current recruitment with the study center. Costs, documents and travel →

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Official title

Deep Learning and Radiomics for Prediction of Lymph Node Metastasis in Early-stage Esophageal Squamous Cell Carcinoma

Overview

This study aims to develop a predictive model using deep learning and radiomics to assess the likelihood of lymph node metastasis in patients with early-stage esophageal squamous cell carcinoma (ESCC). Lymph node metastasis is a critical factor in determining the treatment approach and prognosis for ESCC patients. By analyzing medical imaging data, we hope to create a non-invasive method that can assist doctors in making more accurate treatment decisions. This research could improve patient outcomes by enabling earlier and more tailored interventions.

Interventions

Diagnostic test The prediction model of lymph node metastasis in early esophageal squamous cell carcinoma
The predictive performance of the model was validated in the test set. The optimal prediction model was determined based on the AUC and ACC. To assess the robustness of the chosen model, ROC analysis was conducted on the external validation set.

Primary outcome measures

AUC(the area under the curve) values of the model [Time frame: 4 years]

Eligibility criteria

Inclusion criteria

Patients with pathologically confirmed early-stage (T1) ESCC
Preoperative contrast-enhanced CT data within 2 weeks before surgery
Without any treatment before surgical resection

Exclusion criteria

Patients who underwent neoadjuvant therapy or endoscopic treatment
Insufficient CT imaging or poor CT quality
Incomplete pathology results
Presence of metastatic disease

Criteria are shown verbatim from the registry (in English). Final eligibility is always assessed by the study center.

Healthy volunteers: No

Study design

Observational model: Case-control

Study locations

China · 1 center

The First Affiliated Hospital of Anhui Medical University — Hefei

Identifiers

NCT: NCT07050576 · Early-ESCC-LNM-2024

Primary sources (government registries)

ClinicalTrials.gov (US NIH)

View this study on ClinicalTrials.gov ↗