MedTrace Logo

The Impact of AI Assistance on Radiologist Performance and Healthcare Costs in LDCT-Based Lung Cancer Screening

NCT06988579 · Status: RECRUITING · Phase: NA · Type: INTERVENTIONAL · Enrollment: 7294

Last updated 2025-06-26

No results posted yet for this study

Summary

AI diagnostic systems show great promise for improving lung cancer screening in community healthcare settings. While not originally designed for primary care, these tools demonstrate capabilities in nodule detection and workflow optimization. However, their effectiveness in resource-limited community centers requires thorough evaluation.

This RCT compares AI-assisted versus manual CT interpretation across community health centers. Expert radiologists will establish reference standards, while an independent committee blindly evaluates cases from both groups. The study assesses diagnostic accuracy, operational efficiency, and cost-effectiveness, with blinded analysts resolving discrepancies through consensus to ensure reliable results.

Conditions

  • Lung Cancer
  • Artificial Intelligence (AI)
  • Randomized Controlled Trial

Interventions

OTHER

AI

An integrated AI-human collaborative workflow for lung cancer screening interpretation

Sponsors & Collaborators

  • The First Affiliated Hospital of Guangzhou Medical University

    lead OTHER

Study Design

Allocation
RANDOMIZED
Purpose
SCREENING
Masking
SINGLE
Model
PARALLEL

Eligibility

Min Age
40 Years
Max Age
74 Years
Sex
ALL
Healthy Volunteers
Yes

Timeline & Regulatory

Start
2024-07-01
Primary Completion
2025-10-31
Completion
2026-01-07

Countries

  • China

Study Locations

More Related Trials

Entities

Diseases

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT06988579 on ClinicalTrials.gov