Computed Tomography Image Features under Convolutional Neural Network Algorithm in Analysis of Inflammatory Factor Level and Prognosis of Patients with Hepatitis B Virus-Associated Acute-on-Chronic Liver Failure

This study aimed to explore the application value of three-dimensional (3D) convolutional neural networks (3D-CNN)-based computed tomography (CT) image intelligent segmentation model in the identification of lesions of patients with hepatitis B virus-associated acute-on-chronic liver failure (HBV-AC...

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Autores principales: Zhibing Xie, Li Ding, Yongzhong Li
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Publicado: Hindawi Limited 2021
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spelling oai:doaj.org-article:77b9b7f41594401faaa8aadcfde6882d2021-11-22T01:10:29ZComputed Tomography Image Features under Convolutional Neural Network Algorithm in Analysis of Inflammatory Factor Level and Prognosis of Patients with Hepatitis B Virus-Associated Acute-on-Chronic Liver Failure2040-230910.1155/2021/2110612https://doaj.org/article/77b9b7f41594401faaa8aadcfde6882d2021-01-01T00:00:00Zhttp://dx.doi.org/10.1155/2021/2110612https://doaj.org/toc/2040-2309This study aimed to explore the application value of three-dimensional (3D) convolutional neural networks (3D-CNN)-based computed tomography (CT) image intelligent segmentation model in the identification of lesions of patients with hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF). A total of 30 patients with HBV-ACLF, 30 patients with chronic HBV hospitalized in hospital, and 30 healthy volunteers were selected as subjects. Liver function and serum inflammatory factors were measured in each group, and the 3D-CNN algorithm model was applied to CT imaging. The results showed that the levels of interleukin (IL)-6, IL-26, and IL-37 in the HBV-ACLF group were the highest, which were 128.43 ± 45.16 pg/mL, 1237.47 ± 536.22 pg/mL, and 50.83 ± 7.62 pg/mL, respectively. Total bilirubin (TBIL) (P=0.035) and IL-26 (P=0.013) were independent predictors that affected the prognosis of HBV-ACLF patients. The results of lesion segmentation showed that the Dice coefficient of 3D-CNN low-density focus and enhanced focus segmentation was the highest (0.821 ± 0.07 and 0.773 ± 0.071), and the marked area was close to the area manually drawn by the doctor. 3D CNN was superior to other algorithms in the number of nodular lesions detected (533), sensitivity (97.5%), and missed detection rate (0.52%) (P<0.05). In short, IL-26 may become a useful biomarker in the treatment of HBV-ACLF. The 3D-CNN model improved the segmentation performance of lesions in CT images of HBV-ACLF patients, which provided a reference for the diagnosis and prognosis of HBV-ACLF.Zhibing XieLi DingYongzhong LiHindawi 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
Zhibing Xie
Li Ding
Yongzhong Li
Computed Tomography Image Features under Convolutional Neural Network Algorithm in Analysis of Inflammatory Factor Level and Prognosis of Patients with Hepatitis B Virus-Associated Acute-on-Chronic Liver Failure
description This study aimed to explore the application value of three-dimensional (3D) convolutional neural networks (3D-CNN)-based computed tomography (CT) image intelligent segmentation model in the identification of lesions of patients with hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF). A total of 30 patients with HBV-ACLF, 30 patients with chronic HBV hospitalized in hospital, and 30 healthy volunteers were selected as subjects. Liver function and serum inflammatory factors were measured in each group, and the 3D-CNN algorithm model was applied to CT imaging. The results showed that the levels of interleukin (IL)-6, IL-26, and IL-37 in the HBV-ACLF group were the highest, which were 128.43 ± 45.16 pg/mL, 1237.47 ± 536.22 pg/mL, and 50.83 ± 7.62 pg/mL, respectively. Total bilirubin (TBIL) (P=0.035) and IL-26 (P=0.013) were independent predictors that affected the prognosis of HBV-ACLF patients. The results of lesion segmentation showed that the Dice coefficient of 3D-CNN low-density focus and enhanced focus segmentation was the highest (0.821 ± 0.07 and 0.773 ± 0.071), and the marked area was close to the area manually drawn by the doctor. 3D CNN was superior to other algorithms in the number of nodular lesions detected (533), sensitivity (97.5%), and missed detection rate (0.52%) (P<0.05). In short, IL-26 may become a useful biomarker in the treatment of HBV-ACLF. The 3D-CNN model improved the segmentation performance of lesions in CT images of HBV-ACLF patients, which provided a reference for the diagnosis and prognosis of HBV-ACLF.
format article
author Zhibing Xie
Li Ding
Yongzhong Li
author_facet Zhibing Xie
Li Ding
Yongzhong Li
author_sort Zhibing Xie
title Computed Tomography Image Features under Convolutional Neural Network Algorithm in Analysis of Inflammatory Factor Level and Prognosis of Patients with Hepatitis B Virus-Associated Acute-on-Chronic Liver Failure
title_short Computed Tomography Image Features under Convolutional Neural Network Algorithm in Analysis of Inflammatory Factor Level and Prognosis of Patients with Hepatitis B Virus-Associated Acute-on-Chronic Liver Failure
title_full Computed Tomography Image Features under Convolutional Neural Network Algorithm in Analysis of Inflammatory Factor Level and Prognosis of Patients with Hepatitis B Virus-Associated Acute-on-Chronic Liver Failure
title_fullStr Computed Tomography Image Features under Convolutional Neural Network Algorithm in Analysis of Inflammatory Factor Level and Prognosis of Patients with Hepatitis B Virus-Associated Acute-on-Chronic Liver Failure
title_full_unstemmed Computed Tomography Image Features under Convolutional Neural Network Algorithm in Analysis of Inflammatory Factor Level and Prognosis of Patients with Hepatitis B Virus-Associated Acute-on-Chronic Liver Failure
title_sort computed tomography image features under convolutional neural network algorithm in analysis of inflammatory factor level and prognosis of patients with hepatitis b virus-associated acute-on-chronic liver failure
publisher Hindawi Limited
publishDate 2021
url https://doaj.org/article/77b9b7f41594401faaa8aadcfde6882d
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