Abstract
ObjectiveTo analyze and compare the imaging workflow, radiation dose, and image quality for COVID-19 patients examined using either the conventional manual positioning (MP) method or an AI-based automatic positioning (AP) method.Materials and methodsOne hundred twenty-seven adult COVID-19 patients underwent chest CT scans on a CT scanner using the same scan protocol except with the manual positioning (MP group) for the initial scan and an AI-based automatic positioning method (AP group) for the follow-up scan. Radiation dose, patient positioning time, and off-center distance of the two groups were recorded and compared. Image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and were compared between the two groups.ResultsThe AP operation was successful for all patients in the AP group and reduced the total positioning time by 28% compared with the MP group. Compared with the MP group, the AP group had significantly less patient off-center distance (AP 1.56 cm ± 0.83 vs. MP 4.05 cm ± 2.40, p < 0.001) and higher proportion of positioning accuracy (AP 99% vs. MP 92%), resulting in 16% radiation dose reduction (AP 6.1 mSv ± 1.3 vs. MP 7.3 mSv ± 1.2, p < 0.001) and 9% image noise reduction in erector spinae and lower noise and higher SNR for lesions in the pulmonary peripheral areas.ConclusionThe AI-based automatic positioning and centering in CT imaging is a promising new technique for reducing radiation dose and optimizing imaging workflow and image quality in imaging the chest.Key Points• The AI-based automatic positioning (AP) operation was successful for all patients in our study.• AP method reduced the total positioning time by 28% compared with the manual positioning (MP).• AP method had less patient off-center distance and higher proportion of positioning accuracy than MP method, resulting in 16% radiation dose reduction and 9% image noise reduction in erector spinae.
Highlights
Accurate patient positioning and centering in computed tomography (CT) remains an important issue of concern for reducing dose and image noise [1,2,3]
The artificial intelligence (AI)-based automatic positioning (AP) operation was successful for all patients in our study
AP method reduced the total positioning time by 28% compared with the manual positioning (MP)
Summary
Accurate patient positioning and centering in computed tomography (CT) remains an important issue of concern for reducing dose and image noise [1,2,3]. GE Healthcare introduced a Revolution Maxima CT, which relies on deep learning algorithms and realtime depth-sensing technology to center patients, locate desired anatomies, and perform scan automatically. This CT scanner was successfully used for diagnosing COVID-19 patients in our hospital during the pandemic. The purpose of this study was to analyze and compare the imaging workflow, patient positioning and centering accuracy, radiation dose, and image quality of COVID-19 patients who underwent several follow-up CT scans using the same CT protocol on a same CT machine but with either the conventional manual positioning (MP) mode or an AI-based automatic positioning (AP) mode. We hope our findings may provide useful information on the characteristic of intelligent CT tools and help radiologists to achieve better images at lower radiation dose more efficiently, while to reduce the potential risks of medical workers exposing to patients with infectious diseases during CT examination
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