Real-world study finds commercial AI for pulmonary nodule detection reduces chest CT reporting times by nearly 15%.
Key Details
- 1Erasmus Medical Center analyzed reporting times before and after deploying Veye Lung Nodules AI.
- 2Median reporting time fell from 21.3 to 18.2 minutes per scan, marking a 14.6% reduction.
- 3Study included 19,433 patients and 39,323 chest CTs (20,133 post-AI).
- 4Efficiency gains equated to about 0.5 full-time equivalent radiologist workload per year.
- 5Largest time savings observed in CT thorax ECG-gated scans (−41.1%) and thoracic radiologists (−25%).
- 6Editorial underscores shift toward richer, more quantitative radiology reports enabled by AI.
Why It Matters
With growing demands on radiology departments, evidence that AI can meaningfully reduce reporting time supports more sustainable clinical workflows. Time saved by AI has the potential to enhance both diagnostic throughput and the quality of radiology reporting.

Source
AuntMinnie
Related News

•Radiology Business
UC Irvine Implements AI to Find Lung Cancer Screening Candidates
UC Irvine's radiology department developed an NLP tool to identify patients eligible for lung cancer screening from EHR notes.

•Radiology Business
Webinar to Showcase Successful AI Automation in Radiology Workflows
A webinar will provide insights from imaging leaders on expanding and optimizing AI-driven automation in radiology clinical workflows.

•Radiology Business
A Practical Guide to Evaluating Radiology AI Solutions
Experts propose a three-step approach for radiologists to assess and select AI imaging solutions.