en.Wedoany.com Reported - A recent study shows that artificial intelligence can significantly improve efficiency during the CT image acquisition phase. Canon Medical, in collaboration with Royal Bournemouth Hospital, compared two CT systems—the Aquilion ONE INSIGHT edition, equipped with an AI-assisted platform, and the Aquilion ONE GENESIS edition, without AI assistance—finding that the AI-assisted system reduced scan time by up to 53% and decreased user interactions by 45%.
The study, published in the Journal of Medical Imaging and Radiation Sciences, noted that healthcare systems are under pressure to expand diagnostic capacity and reduce wait times. This pressure is particularly acute for radiology teams, who are required to perform more scans with the same resources while managing increasingly complex workflows. While previous applications of AI in radiology have focused primarily on image interpretation, the findings of this study highlight AI's potential to make an impact earlier in the process.
The study evaluated four routine CT protocols, with 12 certified diagnostic radiographers using standardized settings to scan with both systems. The protocols included brain, chest, abdomen, and pelvis imaging. In every case, the use of the AI-assisted platform resulted in faster acquisition times and reduced manual input requirements.
Each step of the traditional scanning workflow involves a series of manual steps, from patient positioning to selecting scan parameters, adding time and complexity for radiographers. In contrast, the AI-assisted platform employs technologies such as 3D landmark scanning and anatomical landmark detection to support automated scan planning and positioning, helping to determine the correct scan range and field of view, thereby reducing the need for manual adjustments and streamlining the overall process. Previous related studies have also shown that such automated methods can reduce overscanning in routine chest, abdomen, and pelvis imaging, helping to lower unnecessary radiation doses for patients.
Researchers also found no significant correlation between radiographers' experience levels and performance outcomes, suggesting that the technology may help achieve more consistent workflows across teams with varying levels of expertise. Huw Jones, CT Business Manager at Canon Medical Systems UK, stated that if the time and steps required for each scan can be reduced, it not only improves efficiency but also creates more time for patient care, thereby enhancing the patient experience. In the long run, even small time savings per scan can translate into meaningful operational gains.
Overall, these findings indicate that AI-assisted acquisition platforms have the potential to effectively improve CT workflows, helping departments enhance examination capacity while maintaining consistency in daily practice. As imaging demand continues to grow, the role of such solutions in streamlining and accelerating scans is increasingly recognized for supporting clinical teams and patient care pathways.
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