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CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis

The aim of the study was to explore the CT images of the iterative reconstruction algorithm to evaluate the curative effect of continuous blood purification combined with nursing intervention in the treatment of severe acute pancreatitis (SAP). A total of 100 patients with SAP treated by the bedside...

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Autores principales: Liu, Yanyan, Gu, Mingli, Liu, Liping, Cui, Lunmeng, Xing, Aimin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Hindawi 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979709/
https://www.ncbi.nlm.nih.gov/pubmed/35414803
http://dx.doi.org/10.1155/2022/2622316
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author Liu, Yanyan
Gu, Mingli
Liu, Liping
Cui, Lunmeng
Xing, Aimin
author_facet Liu, Yanyan
Gu, Mingli
Liu, Liping
Cui, Lunmeng
Xing, Aimin
author_sort Liu, Yanyan
collection PubMed
description The aim of the study was to explore the CT images of the iterative reconstruction algorithm to evaluate the curative effect of continuous blood purification combined with nursing intervention in the treatment of severe acute pancreatitis (SAP). A total of 100 patients with SAP treated by the bedside continuous venous hemofiltration purification method in a hospital were selected. The control group (n = 50) was given a routine treatment, and the observation group (n = 50) was treated with the continuous blood filtration mode for blood purification based on the routine treatment. In the CT image scanning of periodontitis patients, the iterative reconstruction algorithm was introduced to reduce image noise, and the CT values under the algorithm were statistically analyzed. The results showed that IL-1, IL-6, and IL-8 after treatment were significantly lower than those before treatment (P < 0.05). The symptoms effectively improved with continuous blood purification combined with nursing intervention in patients with SAP. After the use of the iterative reconstruction algorithm, the image quality, image information, and image MSE significantly improved. The image noise with 50% dose reduction was the lowest, but the reconstruction algorithm improved the low contrast resolution (P < 0.05). CT images based on the reconstruction algorithm can clearly display the lesion characteristics of the patients, and the reconstruction algorithm is feasible to improve the spatial resolution of CT images.
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spelling pubmed-89797092022-04-11 CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis Liu, Yanyan Gu, Mingli Liu, Liping Cui, Lunmeng Xing, Aimin Contrast Media Mol Imaging Research Article The aim of the study was to explore the CT images of the iterative reconstruction algorithm to evaluate the curative effect of continuous blood purification combined with nursing intervention in the treatment of severe acute pancreatitis (SAP). A total of 100 patients with SAP treated by the bedside continuous venous hemofiltration purification method in a hospital were selected. The control group (n = 50) was given a routine treatment, and the observation group (n = 50) was treated with the continuous blood filtration mode for blood purification based on the routine treatment. In the CT image scanning of periodontitis patients, the iterative reconstruction algorithm was introduced to reduce image noise, and the CT values under the algorithm were statistically analyzed. The results showed that IL-1, IL-6, and IL-8 after treatment were significantly lower than those before treatment (P < 0.05). The symptoms effectively improved with continuous blood purification combined with nursing intervention in patients with SAP. After the use of the iterative reconstruction algorithm, the image quality, image information, and image MSE significantly improved. The image noise with 50% dose reduction was the lowest, but the reconstruction algorithm improved the low contrast resolution (P < 0.05). CT images based on the reconstruction algorithm can clearly display the lesion characteristics of the patients, and the reconstruction algorithm is feasible to improve the spatial resolution of CT images. Hindawi 2022-03-28 /pmc/articles/PMC8979709/ /pubmed/35414803 http://dx.doi.org/10.1155/2022/2622316 Text en Copyright © 2022 Yanyan Liu et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Liu, Yanyan
Gu, Mingli
Liu, Liping
Cui, Lunmeng
Xing, Aimin
CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis
title CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis
title_full CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis
title_fullStr CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis
title_full_unstemmed CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis
title_short CT Image Features Based on the Reconstruction Algorithm for Continuous Blood Purification Combined with Nursing Intervention in the Treatment of Severe Acute Pancreatitis
title_sort ct image features based on the reconstruction algorithm for continuous blood purification combined with nursing intervention in the treatment of severe acute pancreatitis
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8979709/
https://www.ncbi.nlm.nih.gov/pubmed/35414803
http://dx.doi.org/10.1155/2022/2622316
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