Clinical trial · Interventional
The Impact of AI Assistance on Radiologist Performance and Healthcare Costs in LDCT-Based Lung Cancer Screening
Evaluation of AI-Assisted Versus Conventional Human Reading for Lung Cancer Screening in Community-Based Settings: A Randomized Controlled Trial
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 8, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260908-000001
Summary
Brief summary (as posted)
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
Conditions (3)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Artificial Intelligence (AI) | — | UNRESOLVED | — |
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
| Randomized Controlled Trial | — | UNRESOLVED | — |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| AI | Other | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- EXPERIMENTAL
- label
- AI-Assisted Group
- description
- The AI-assisted group utilized AI-powered diagnostic software for interpreting low-dose computed tomography (LDCT) scans
- interventionNames
- Other: AI
- type
- NO_INTERVENTION
- label
- The manual interpretation group
- description
- The manual interpretation group relied on standard radiologist evaluation for analyzing low-dose computed tomography (LDCT) scans.
Primary outcomes (2)
- measure
- Diagnostic Accuracy
- timeFrame
- One year after entry
- description
- Sensitivity and Specificity: Comparison of AI-assisted versus manual interpretation in detecting malignant pulmonary nodules, validated against histopathological confirmation or 12-month clinical follow-up. Early Detection Rate: Proportion of stage I/II lung cancers correctly identified by each method.
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 40 Years
- Maximum age
- 74 Years
Show eligibility criteria text
Inclusion Criteria: 1. Aged 45-74 years 2. Permanent resident of participating study communities 3. No prior history of lung cancer and no lung cancer screening within the past 3 months 4. Able to comprehend and voluntarily sign informed consent, with willingness to participate in long-term follow-up Exclusion Criteria: 1. Individuals with a confirmed diagnosis of lung cancer 2. Those with severe comorbidities contraindicating CT imaging 3. Inability to understand study protocols or provide informed consent due to cognitive impairment 4. Concurrent participation in other clinical trials that may interfere with study outcomes 5. Unable to comply with follow-up requirements
References
Publications (0)
Data not yet available