Predicting Immunotherapy Response and Survival of Lung Cancer Patients Using Artificial Intelligence and Radiomics (Radiology-AI-Lung)

CT imaging data from lung cancer (NSCLC and SCLC) patients prior to the initiation of immunotherapy (and possibly also after treatment) will be collected. The processing pipeline includes automatic tumor segmentation, radiomics feature extraction, feature selection, and construction of a classification model.

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Key information

Conditions

Lung Cancer (Diagnosis) Disease Lung Diseases Lung Neoplasms Neoplasms Neoplasms by Site Pathologic Processes Pathological Conditions, Signs and Symptoms Respiratory Tract Diseases Respiratory Tract Neoplasms Thoracic Neoplasms

Age range

18 year and older

Sex eligibility

All sexes

Study type

Observational

Primary location

Union Hospital，Tongji Medical College，Huazhong University of Science and Technology

Wuhan, Hubei, 430000, China

Location status: Recruiting

Location contact

Lian Yang

CONTACT

[email protected]

18986273791

Who can participate

Healthy volunteers accepted: No

Only the study team can determine whether someone qualifies for participation.

Inclusion criteria

Patients were treated for lung cancer in Wuhan Union Hospital from July 2025 to July 2026;
Aged > 18 years old;
At least one CT scan before treatment;
Tissue biopsy pathological examination confirmed the diagnosis of the above tumors.

Exclusion criteria

Poor image quality;
Incomplete clinical data or loss of follow-up;
Presence of another primary malignancy other than lung cancer;
Unclear pathological diagnosis.

Treatment and study plan

Primary outcomes

Progression-free survival

Time frame: 1 year
disease-free survival

Time frame: 1 year
overall survival

Time frame: 1 year

Study contacts

Contact information is provided by the study sponsor or research team.

Lian Yang

CONTACT

[email protected]

18986273791

Sponsors and collaborators

Lead sponsor

Union Hospital, Tongji Medical College, Huazhong University of Science and Technology

Other

Registry information

Important dates

Study start: 2025
Primary completion: 2026
Study completion: 2026
First posted: Jul 11, 2025
Registry last updated: Jul 11, 2025

OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.

View the official ClinicalTrials.gov record (opens in a new tab)

This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.

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