AI-driven assessment of over-scanning in chest CT: A systematic review and meta-analysis
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View abstract on PubMed
Summary
This summary is machine-generated.Artificial intelligence (AI) can reduce radiation dose in chest CT scans by identifying and minimizing unnecessary over-scanning. AI models accurately assess over-scanning, improving patient safety and optimizing imaging protocols.
Area Of Science
- Medical Imaging
- Radiology
- Artificial Intelligence
Background
- Over-scanning in computed tomography (CT) is a common issue, leading to unnecessary radiation exposure.
- Manual over-scanning in chest CT contributes significantly to patient radiation dose.
- Optimizing scan range is crucial for effective CT acquisition and patient safety.
Purpose Of The Study
- To explore the role of artificial intelligence (AI) in addressing manual over-scanning in chest CT imaging.
- To evaluate the effectiveness of AI algorithms in assessing and reducing over-scanning.
- To determine the impact of AI on radiation dose reduction and protocol optimization.
Main Methods
- A systematic literature search was conducted across major databases (Embase, Scopus, PubMed, etc.) from December 2015 to March 2025.
- Two independent reviewers assessed article eligibility and quality using CLAIM and QUADAS-2 tools.
- Meta-analysis was used to derive summary estimates of over-scanning at scan boundaries in chest CT.
Main Results
- Five studies utilized AI algorithms to evaluate manual over-scanning in chest CT, showing high accuracy and agreement with radiologists.
- Significant over-scanning was observed at superior (13.5 mm) and inferior (30.2 mm) boundaries (p < 0.001).
- Approximately two-thirds of total over-scanning (43.2 mm) occurred at the inferior (abdominal) level.
Conclusions
- AI tools can effectively optimize chest CT imaging protocols by reducing over-scanning.
- Integration of AI enhances patient safety through real-time monitoring and retrospective analysis of radiation dose.
- AI-driven evaluation of scan range is a promising approach to minimize unnecessary radiation exposure in CT scans.
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