Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm

This study was to explore the application value of chest computed tomography (CT) images processed by artificial intelligence (AI) algorithms in the diagnosis of neonatal bronchial pneumonia (NBP). The AI adaptive statistical iterative reconstruction (ASiR) algorithm was adopted to reconstruct the c...

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Autores principales:	Ying Sun, Liao Wu, Zhaofang Tian, Tianping Bao
Formato:	article
Lenguaje:	EN
Publicado:	Hindawi Limited 2021
Materias:	Medicine (General) R5-920 Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/21ad72dd7e584b56be5fa200e8ad74d1
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spelling	oai:doaj.org-article:21ad72dd7e584b56be5fa200e8ad74d12021-11-08T02:36:42ZChest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm2040-230910.1155/2021/6183946https://doaj.org/article/21ad72dd7e584b56be5fa200e8ad74d12021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/6183946https://doaj.org/toc/2040-2309This study was to explore the application value of chest computed tomography (CT) images processed by artificial intelligence (AI) algorithms in the diagnosis of neonatal bronchial pneumonia (NBP). The AI adaptive statistical iterative reconstruction (ASiR) algorithm was adopted to reconstruct the chest CT image to compare and analyze the effect of the reconstruction of CT image under the ASiR algorithm under different preweight and postweight values based on the objective measurement and subjective evaluation. 85 neonates with pneumonia treated in hospital from September 1, 2015, to July 1, 2020, were selected as the research objects to analyze their CT imaging characteristics. Subsequently, the peripheral blood of healthy neonates during the same period was collected, and the levels of C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were detected. The efficiency of CT examination, CRP, ESR, and combined examination in the diagnosis of NBP was analyzed. The results showed that the subjective quality score, lung window subjective score, and mediastinal window subjective score were the highest after CT image reconstruction when the preweight value of the ASiR algorithm was 50%. After treatment, 79 NBP cases (92.9%) showed ground-glass features in CT images. Compared with the healthy neonates, the levels of CRP and ESR in the peripheral blood of neonates with bronchial pneumonia were much lower (P<0.05). The accuracy rates of CT examination, CRP examination, ESR examination, CRP + ESR examination, and CRP + ESR + CT examination for the diagnosis of NBP were 80.7%, 75.3%, 75.1%, 80.3%, and 98.6%, respectively. CT technology based on AI algorithm showed high clinical application value in the feature analysis of NBP.Ying SunLiao WuZhaofang TianTianping BaoHindawi LimitedarticleMedicine (General)R5-920Medical technologyR855-855.5ENJournal of Healthcare Engineering, Vol 2021 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine (General) R5-920 Medical technology R855-855.5
spellingShingle	Medicine (General) R5-920 Medical technology R855-855.5 Ying Sun Liao Wu Zhaofang Tian Tianping Bao Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm
description	This study was to explore the application value of chest computed tomography (CT) images processed by artificial intelligence (AI) algorithms in the diagnosis of neonatal bronchial pneumonia (NBP). The AI adaptive statistical iterative reconstruction (ASiR) algorithm was adopted to reconstruct the chest CT image to compare and analyze the effect of the reconstruction of CT image under the ASiR algorithm under different preweight and postweight values based on the objective measurement and subjective evaluation. 85 neonates with pneumonia treated in hospital from September 1, 2015, to July 1, 2020, were selected as the research objects to analyze their CT imaging characteristics. Subsequently, the peripheral blood of healthy neonates during the same period was collected, and the levels of C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) were detected. The efficiency of CT examination, CRP, ESR, and combined examination in the diagnosis of NBP was analyzed. The results showed that the subjective quality score, lung window subjective score, and mediastinal window subjective score were the highest after CT image reconstruction when the preweight value of the ASiR algorithm was 50%. After treatment, 79 NBP cases (92.9%) showed ground-glass features in CT images. Compared with the healthy neonates, the levels of CRP and ESR in the peripheral blood of neonates with bronchial pneumonia were much lower (P<0.05). The accuracy rates of CT examination, CRP examination, ESR examination, CRP + ESR examination, and CRP + ESR + CT examination for the diagnosis of NBP were 80.7%, 75.3%, 75.1%, 80.3%, and 98.6%, respectively. CT technology based on AI algorithm showed high clinical application value in the feature analysis of NBP.
format	article
author	Ying Sun Liao Wu Zhaofang Tian Tianping Bao
author_facet	Ying Sun Liao Wu Zhaofang Tian Tianping Bao
author_sort	Ying Sun
title	Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm
title_short	Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm
title_full	Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm
title_fullStr	Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm
title_full_unstemmed	Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm
title_sort	chest computed tomography images in neonatal bronchial pneumonia under the adaptive statistical iterative reconstruction algorithm
publisher	Hindawi Limited
publishDate	2021
url	https://doaj.org/article/21ad72dd7e584b56be5fa200e8ad74d1
work_keys_str_mv	AT yingsun chestcomputedtomographyimagesinneonatalbronchialpneumoniaundertheadaptivestatisticaliterativereconstructionalgorithm AT liaowu chestcomputedtomographyimagesinneonatalbronchialpneumoniaundertheadaptivestatisticaliterativereconstructionalgorithm AT zhaofangtian chestcomputedtomographyimagesinneonatalbronchialpneumoniaundertheadaptivestatisticaliterativereconstructionalgorithm AT tianpingbao chestcomputedtomographyimagesinneonatalbronchialpneumoniaundertheadaptivestatisticaliterativereconstructionalgorithm
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Chest Computed Tomography Images in Neonatal Bronchial Pneumonia under the Adaptive Statistical Iterative Reconstruction Algorithm

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