Clinical trial · Interventional
AI-Assisted Chest CT Interpretation Across the Lung Cancer Care Continuum
Development of a Chest CT-Based Artificial Intelligence Model Across the Lung Cancer Care Continuum and a Prospective Randomized Crossover Reader Study of Its Clinical Decision-Support Performance
- Source
- ClinicalTrials.gov
- Retrieved
- Sep 26, 2026
- Layer
- normalized (units and labels harmonized; values unchanged)
- Run
- ING-CLINICALTRIALS-20260926-000001
Summary
Brief summary (as posted)
This investigator-initiated, single-center study consists of a retrospective artificial intelligence model-development stage and a prospective physician reader-study stage. Deidentified chest CT examinations acquired during routine clinical care between January 1, 2021, and December 31, 2024, will be used to develop, validate, and lock artificial intelligence models for lung cancer-related imaging tasks. In the prospective stage, approximately 12 to 15 physicians with experience in chest CT interpretation will complete two reading sessions in randomized order: unaided interpretation and AI-assisted interpretation. The sessions will be separated by a washout period of at least 4 weeks. The primary objective is to compare diagnostic performance between AI-assisted and unaided interpretation. Secondary objectives include reading time, diagnostic confidence, inter-reader agreement, and errors related to incorrect AI suggestions. All readings will be performed in an offline research environment. AI outputs will not be used for patient care, and the study will not add imaging examinations, treatment, or follow-up for patients.
Conditions
Conditions (1)
Free-text conditions as registered, with the CancerIndex entity they were reconciled to and the match type.
| Condition (as posted) | Mapped entity | Match | Confidence |
|---|---|---|---|
| Lung Cancer | Malignant Lung Neoplasm | CURATED_EXACT | 0.92 |
Interventions
Interventions (1)
| Intervention | Type | Mapped drug | Match |
|---|---|---|---|
| Chest CT Artificial Intelligence Decision-Support System | Device | — | UNRESOLVED |
Design
Arms and outcomes
Arms (2)
- type
- EXPERIMENTAL
- label
- Sequence AB: Unaided Then AI-Assisted Interpretation
- description
- Participants first complete an unaided chest CT interpretation session. After a washout period of at least 4 weeks, they complete an AI-assisted interpretation session.
- interventionNames
- Device: Chest CT Artificial Intelligence Decision-Support System
- type
- EXPERIMENTAL
- label
- Sequence BA: AI-Assisted Then Unaided Interpretation
- description
- Participants first complete an AI-assisted chest CT interpretation session. After a washout period of at least 4 weeks, they complete an unaided interpretation session.
- interventionNames
- Device: Chest CT Artificial Intelligence Decision-Support System
Primary outcomes (1)
- measure
Eligibility
Eligibility (as posted)
- Sex
- All
- Minimum age
- 18 Years
Show eligibility criteria text
Inclusion Criteria: * Physicians with education or training relevant to medical imaging * Experience in interpreting chest CT examinations * Ability to complete the required study training and both reading sessions * Willingness to provide written informed consent and comply with study procedures Exclusion Criteria: * Failure to complete the required study training * Inability or unwillingness to complete both reading sessions as required * Any protocol deviation likely to compromise the validity of the reader-study data
References
Publications (0)
Data not yet available