Cargando…

A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients

OBJECTIVE: To 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 METHODS: One hundred twenty-seven adult COVID-19 patie...

Descripción completa

Detalles Bibliográficos
Autores principales: Gang, Yadong, Chen, Xiongfeng, Li, Huan, Wang, Hanlun, Li, Jianying, Guo, Ying, Zeng, Junjie, Hu, Qiang, Hu, Jinxiang, Xu, Haibo
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7975236/
https://www.ncbi.nlm.nih.gov/pubmed/33740092
http://dx.doi.org/10.1007/s00330-020-07629-4
_version_ 1783666949421531136
author Gang, Yadong
Chen, Xiongfeng
Li, Huan
Wang, Hanlun
Li, Jianying
Guo, Ying
Zeng, Junjie
Hu, Qiang
Hu, Jinxiang
Xu, Haibo
author_facet Gang, Yadong
Chen, Xiongfeng
Li, Huan
Wang, Hanlun
Li, Jianying
Guo, Ying
Zeng, Junjie
Hu, Qiang
Hu, Jinxiang
Xu, Haibo
author_sort Gang, Yadong
collection PubMed
description OBJECTIVE: To 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 METHODS: One 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. RESULTS: The 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. CONCLUSION: The 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.
format Online
Article
Text
id pubmed-7975236
institution National Center for Biotechnology Information
language English
publishDate 2021
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-79752362021-03-19 A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients Gang, Yadong Chen, Xiongfeng Li, Huan Wang, Hanlun Li, Jianying Guo, Ying Zeng, Junjie Hu, Qiang Hu, Jinxiang Xu, Haibo Eur Radiol Imaging Informatics and Artificial Intelligence OBJECTIVE: To 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 METHODS: One 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. RESULTS: The 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. CONCLUSION: The 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. Springer Berlin Heidelberg 2021-03-19 2021 /pmc/articles/PMC7975236/ /pubmed/33740092 http://dx.doi.org/10.1007/s00330-020-07629-4 Text en © The Author(s) 2020 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Imaging Informatics and Artificial Intelligence
Gang, Yadong
Chen, Xiongfeng
Li, Huan
Wang, Hanlun
Li, Jianying
Guo, Ying
Zeng, Junjie
Hu, Qiang
Hu, Jinxiang
Xu, Haibo
A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients
title A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients
title_full A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients
title_fullStr A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients
title_full_unstemmed A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients
title_short A comparison between manual and artificial intelligence–based automatic positioning in CT imaging for COVID-19 patients
title_sort comparison between manual and artificial intelligence–based automatic positioning in ct imaging for covid-19 patients
topic Imaging Informatics and Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7975236/
https://www.ncbi.nlm.nih.gov/pubmed/33740092
http://dx.doi.org/10.1007/s00330-020-07629-4
work_keys_str_mv AT gangyadong acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT chenxiongfeng acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT lihuan acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT wanghanlun acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT lijianying acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT guoying acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT zengjunjie acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT huqiang acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT hujinxiang acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT xuhaibo acomparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT gangyadong comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT chenxiongfeng comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT lihuan comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT wanghanlun comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT lijianying comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT guoying comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT zengjunjie comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT huqiang comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT hujinxiang comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients
AT xuhaibo comparisonbetweenmanualandartificialintelligencebasedautomaticpositioninginctimagingforcovid19patients