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基于人工智能算法的多层螺旋 CT 对肝硬化和肝纤维化的诊断。

Diagnosis of Liver Cirrhosis and Liver Fibrosis by Artificial Intelligence Algorithm-Based Multislice Spiral Computed Tomography.

机构信息

Department of Infectious Disease, Baoji Central Hospital, Baoji, 721008 Shaanxi, China.

Department of Immunization Plan, Disease Control and Prevention of Yulin Center, Yulin, 719000 Shaanxi, China.

出版信息

Comput Math Methods Med. 2022 Mar 15;2022:1217003. doi: 10.1155/2022/1217003. eCollection 2022.

Abstract

This research was aimed at investigating the artificial intelligence (AI) segmentation algorithm-based multislice spiral computed tomography (MSCT) in the diagnosis of liver cirrhosis and liver fibrosis. Besides, it was aimed at providing new methods for the diagnosis of liver cirrhosis and liver fibrosis. All patients were divided into the control group, mild liver fibrosis group, and significant liver fibrosis group. A total of 112 patients were included, with 40 cases in the mild liver fibrosis group, 48 cases in the significant liver fibrosis group, and 24 cases who underwent computed tomography (CT) examination in the control group. In the research, deconvolution algorithm of AI segmentation algorithm was adopted to process the images. The average hepatic arterial fraction (HAF) values of patients in the control group, mild liver fibrosis group, and severe liver fibrosis group were 17.59 ± 10.03%, 18.23 ± 5.57%, and 20.98 ± 6.63%, respectively. The average MTT values of patients in the control group, mild liver fibrosis group, and severe liver fibrosis group were 12.69 ± 1.78S, 12.53 ± 2.05S, and 12.04 ± 1.57S, respectively. The average blood flow (BF) values of patients in the control group, mild liver fibrosis group, and severe liver fibrosis group were 105.68 ± 15.57 mL 100 g·min, 116.07 ± 16.5 mL·100 g·min, and 110.39 ± 16.32 mL·100 g·min, respectively. Besides, the average blood volume (BV) values of patients in the control group, mild liver fibrosis group, and significant liver fibrosis group were 15.69 ± 4.35 mL·log, 16.97 ± 2.68 mL·log, and 16.11 ± 4.87 mL·100 g, respectively. According to statistics, the differences among the average HAF, MTT, BF, and BV values showed no statistical meaning. AI segmentation algorithm-based MSCT imaging could promote the diagnosis of liver cirrhosis and liver fibrosis effectively and offer new methods to clinical diagnosis of liver cirrhosis and liver fibrosis.

摘要

本研究旨在探讨基于人工智能(AI)分割算法的多层螺旋 CT(MSCT)在肝硬化和肝纤维化诊断中的应用。旨在为肝硬化和肝纤维化的诊断提供新方法。所有患者均分为对照组、轻度肝纤维化组和重度肝纤维化组。共纳入 112 例患者,其中对照组 24 例,轻度肝纤维化组 40 例,重度肝纤维化组 48 例。在研究中,采用 AI 分割算法的反卷积算法对图像进行处理。对照组、轻度肝纤维化组和重度肝纤维化组患者的平均肝动脉分数(HAF)值分别为 17.59 ± 10.03%、18.23 ± 5.57%和 20.98 ± 6.63%。对照组、轻度肝纤维化组和重度肝纤维化组患者的平均平均通过时间(MTT)值分别为 12.69 ± 1.78S、12.53 ± 2.05S 和 12.04 ± 1.57S。对照组、轻度肝纤维化组和重度肝纤维化组患者的平均血流量(BF)值分别为 105.68 ± 15.57 mL 100 g·min、116.07 ± 16.5 mL·100 g·min 和 110.39 ± 16.32 mL·100 g·min。此外,对照组、轻度肝纤维化组和重度肝纤维化组患者的平均血容量(BV)值分别为 15.69 ± 4.35 mL·log、16.97 ± 2.68 mL·log 和 16.11 ± 4.87 mL·100 g。统计分析显示,平均 HAF、MTT、BF 和 BV 值之间的差异无统计学意义。基于 AI 分割算法的 MSCT 成像可以有效地促进肝硬化和肝纤维化的诊断,并为肝硬化和肝纤维化的临床诊断提供新方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/cd9a/8941514/58a7bbb17cb0/CMMM2022-1217003.001.jpg

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