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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

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Abstract

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.

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Authors and Affiliations

  1. Department of Radiology, Second Maternal and Child Health Hospital of Jinan City, Jinan, 271100, Shandong, China

    Chunfeng Zheng

  2. Department of Radiology, Qingdao Central Hospital, Qingdao, 266000, Shandong, China

    Lei Chen

  3. Department of Imaging, Linyi County People’s Hospital, Linyi, 251500, Shandong, China

    Jihua Jian

  4. Maternal and Child Health and Family Planning Service Center of Laiwu District, Jinan City, 271100, Shandong, China

    Juan Li

  5. Department of Radiology, Xiangshan Hospital Affiliated to Wenzhou Medical University, Ningbo, 315700, Zhejiang, China

    Zhonghui Gao

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  1. Chunfeng Zheng
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  2. Lei Chen
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  3. Jihua Jian
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  4. Juan Li
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  5. Zhonghui Gao
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Correspondence to Zhonghui Gao.

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Zheng, C., Chen, L., Jian, J. et al. Efficacy evaluation of interventional therapy for primary liver cancer using magnetic resonance imaging and CT scanning under deep learning and treatment of vasovagal reflex. J Supercomput 77, 7535–7548 (2021). https://doi.org/10.1007/s11227-020-03539-w

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  • DOI: https://doi.org/10.1007/s11227-020-03539-w

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