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Efficacy evaluation of interventional therapy for primary liver cancer using magnetic resonance imaging and CT scanning under deep learning and treatment of vasovagal reflex

机译:磁共振成像在深层学习中使用磁共振成像和CT扫描对原发性肝癌介入治疗的功效评价及仿血管养反射

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摘要

To investigate the application of Magnetic Resonance Imaging (MRI) combined with Computed Tomography (CT) scan images based on deep learning in the evaluation of postoperative TACE efficacy as well as the prevention and treatment measures of Vasovagal Reflex (VVR). A total of 256 patients who were diagnosed with primary liver cancer in our hospital and were treated with Transcatheter Arterial Chemoembolization (TACE) for liver cancer. They were divided into a combined group (110 cases) and a control group (146 cases). The combined group underwent MRI and CT after the operation. The control group only underwent an MRI examination. To explore the role of CT and MRI images based on deep learning in the evaluation of interventional therapy for liver cancer, the MRI and CT images were processed by establishing a Convolutional Neural Networks (CNN) model. Then, the image information was counted and analyzed. The segmentation effect of the residual situation of the MRI and CT image enhancement regions processed by the deep learning model was relatively good, and can accurately display the presence of the lesion. Also, the diagnostic efficiency was above 0.7, and the diagnostic efficiency was better. The sensitivity, specificity, accuracy, and negative predictive value of diagnosis in the control group were significantly lower than those in the combined group (P 0.05). After the measurement, the minimum short diameter of the control group was significantly higher than that of the combined group (P 0.05). Proposed specific preventive measures for VVR from the three aspects, before, during, and after TACE surgery, can reduce the adverse consequences caused by VVR. The methods of the investigation can improve the accuracy of the effect evaluation after TACE treatment, reduce the occurrence of complications and adverse consequences, thereby improving the therapeutic effect of liver cancer patients.
机译:研究磁共振成像(MRI)的应用基于深度学习在术后TACE疗效评估中与计算机断层扫描(CT)扫描图像相结合,以及血管无水反射(VVR)的预防和治疗措施。共有256名患者被诊断出在我们院内患有原发性肝癌,并用经截觉表动脉化疗栓塞(TACE)治疗肝癌。它们分为组合组(110例)和对照组(146例)。合并组在运作后接受MRI和CT。对照组只经历了MRI检查。为了探讨CT和MRI图像的作用,基于深度学习在评估肝癌的介入治疗中,通过建立卷积神经网络(CNN)模型来处理MRI和CT图像。然后,计算和分析图像信息。深度学习模型处理MRI和CT图像增强区的残余情况的分割效果相对较好,并且可以准确地显示病变的存在。此外,诊断效率高于0.7,诊断效率更好。对照组诊断的敏感性,特异性,准确性和负预测值显着低于组合基团(P <0.05)。测量后,对照组的最小短直径明显高于组合基团(P <0.05)。提出了来自三个方面的VVR的具体预防措施,之前,期间和TACE手术后,可以降低VVR引起的不良后果。调查方法可以提高TACE治疗后效果评价的准确性,降低并发症的发生和不良后果,从而提高肝癌患者的治疗效果。

著录项

  • 来源
    《Journal of supercomputing》 |2021年第7期|7535-7548|共14页
  • 作者单位

    Second Maternal & Child Hlth Hosp Jinan City Dept Radiol Jinan 271100 Shandong Peoples R China;

    Qingdao Cent Hosp Dept Radiol Qingdao 266000 Shandong Peoples R China;

    Linyi Cty Peoples Hosp Dept Imaging Linyi 251500 Shandong Peoples R China;

    Maternal & Child Hlth & Family Planning Serv Ctr Jinan 271100 Shandong Peoples R China;

    Wenzhou Med Univ Dept Radiol Xiangshan Hosp Ningbo 315700 Zhejiang Peoples R China;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    Deep learning; Combination of MRI and CT; TACE; Primary liver cancer; VVR;

    机译:深入学习;MRI和CT的组合;TACE;原发性肝癌;VVR;

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