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

• Published in: Contrast media and molecular imaging Vol. 2022; no. 1; p. 2622316
• Main Authors: Liu, Yanyan, Gu, Mingli, Liu, Liping, Cui, Lunmeng, Xing, Aimin
• Format: Journal Article
• Language: English
• Published: England Hindawi 2022
• Subjects: Acute Disease; Algorithms; Humans; Pancreatitis - diagnostic imaging; Pancreatitis - therapy; Radiation Dosage; Radiographic Image Interpretation, Computer-Assisted - methods; Tomography, X-Ray Computed - methods
• ISSN: 1555-4309; 1555-4317
• DOI: 10.1155/2022/2622316

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.