Accurate and efficient pulmonary CT imaging workflow for COVID-19 patients by the combination of intelligent guided robot and automatic positioning technology

Yadong Gang; Xiongfeng Chen; Hanlun Wang; Jianying Li; Ying Guo; Bin Wen; Jinxiang Hu; Haibo Xu; Xinghuan Wang

doi:10.1016/j.imed.2021.04.005

Accurate and efficient pulmonary CT imaging workflow for COVID-19 patients by the combination of intelligent guided robot and automatic positioning technology

Intell Med. 2021 May;1(1):3-9. doi: 10.1016/j.imed.2021.04.005. Epub 2021 May 27.

Authors

Yadong Gang¹, Xiongfeng Chen², Hanlun Wang¹, Jianying Li³, Ying Guo³, Bin Wen⁴, Jinxiang Hu¹, Haibo Xu¹, Xinghuan Wang^{5

6}

Affiliations

¹ Department of Radiology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.
² Department of Radiology, Puren Hospital affiliated to Wuhan University of Science and Technology, Wuhan 430080, China.
³ GE Healthcare, Computed Tomography Research Center, Beijing 100176, China.
⁴ TAMI Intelligence Technology (Beijing) Co. Ltd, Beijing 100176, China.
⁵ Department of Urology, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.
⁶ Center for Evidence-based and Translational Medicine, Zhongnan Hospital of Wuhan University, Wuhan 430071, China.

Abstract

Background: The ongoing coronavirus disease 2019 (COVID-19) pandemic has put radiologists at a higher risk of infection during the computer tomography (CT) examination for the patients. To help settling these problems, we adopted a remote-enabled and automated contactless imaging workflow for CT examination by the combination of intelligent guided robot and automatic positioning technology to reduce the potential exposure of radiologists to 2019 novel coronavirus (2019-nCoV) infection and to increase the examination efficiency, patient scanning accuracy and better image quality in chest CT imaging .

Methods: From February 10 to April 12, 2020, adult COVID-19 patients underwent chest CT examinations on a CT scanner using the same scan protocol except with the conventional imaging workflow (CW group) or an automatic contactless imaging workflow (AW group) in Wuhan Leishenshan Hospital (China) were retrospectively and prospectively enrolled in this study. The total examination time in two groups was recorded and compared. The patient compliance of breath holding, positioning accuracy, image noise and signal-to-noise ratio (SNR) were assessed by three experienced radiologists and compared between the two groups.

Results: Compared with the CW group, the total positioning time of the AW group was reduced ((118.0 ± 20.0) s vs. (129.0 ± 29.0) s, P = 0.001), the proportion of scanning accuracy was higher (98% vs. 93%), and the lung length had a significant difference ((0.90±1.24) cm vs. (1.16±1.49) cm, P = 0.009). For the lesions located in the pulmonary centrilobular and subpleural regions, the image noise in the AW group was significantly lower than that in the CW group (centrilobular region: (140.4 ± 78.6) HU vs. (153.8 ± 72.7) HU, P = 0.028; subpleural region: (140.6 ± 80.8) HU vs. (159.4 ± 82.7) HU, P = 0.010). For the lesions located in the peripheral, centrilobular and subpleural regions, SNR was significantly higher in the AW group than in the CW group (centrilobular region: 6.6 ± 4.3 vs. 4.9 ± 3.7, P = 0.006; subpleural region: 6.4 ± 4.4 vs. 4.8 ± 4.0, P < 0.001).

Conclusions: The automatic contactless imaging workflow using intelligent guided robot and automatic positioning technology allows for reducing the examination time and improving the patient's compliance of breath holding, positioning accuracy and image quality in chest CT imaging.

Keywords: Artificial intelligence; Computer tomography; Coronavirus disease 2019; Robotics.