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RECRUITING
NCT07895277
NA

Longitudinal AI-Assisted Management of Indeterminate Pulmonary Nodules

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

View on ClinicalTrials.gov

Summary

Patients with indeterminate lung nodules often face a choice between continued CT surveillance and invasive investigation. This trial compares management with or without access to an AI report that matches nodules across real serial CT scans, measures change, and estimates validated malignancy or invasiveness risks. The principal question is whether offering the report reduces lung resections that yield benign pathology over 24 months. Diagnostic delay, cancer stage, treatment opportunity, complications, and longer-term cancer outcomes are also assessed.

Official title: Study of Imaging Evolution of Pulmonary Nodules and Artificial Intelligence-Assisted Diagnostic and Management Strategies

Key Details

Gender

All

Age Range

35 Years - Any

Study Type

INTERVENTIONAL

Enrollment

6000

Start Date

2025-01-01

Completion Date

2027-12-01

Last Updated

2026-10-26

Healthy Volunteers

No

Interventions

DEVICE

AI-Assisted Longitudinal CT Assessment and Pulmonary Nodule Management

AI software analyzes serial clinically acquired chest CT scans to match pulmonary nodules, quantify changes in volume and solid components, and provide malignancy or invasiveness risk estimates. Intervention-arm clinicians review the AI report alongside CT images during management consultations. The baseline report is targeted within one working day after randomization. The same locked model is reapplied to clinically indicated follow-up CT scans during the 24-month intervention period. Clinicians retain responsibility for final decisions; AI findings cannot independently override clinically indicated evaluation. If processing fails or images are unsuitable, usual care proceeds. Both arms follow the same structured nodule-management pathway, but the control arm has no access to trial AI reports.

Locations (1)

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

Wuhan, Hubei, China