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Deep learning convolutional neural network in diagnosis of serous effusion in patients with malignant tumor by tomography

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Abstract

To explore the diagnostic value of deep learning convolutional neural network (CNN)-based computed tomography (CT) scan in tumor disease images, clinical factors related to serous effusion were analyzed. The relevant case data of 224 patients with serosal effusion caused by malignant tumor treated in X Hospital from October 1 to February 2017 were selected, so did the positron emission tomography (PET) image data based on deep learning CNN. Then, the causes and diagnosis of PET effusion in each group were analyzed, and multi-factor analysis was performed on the effusion in the pleural cavity, abdominal cavity, pericardial cavity, and no effusion group. It was found through PET scan under deep learning CNN algorithm that the location of the effusion was related to the primary lesions. The malignant pleural effusion (72 cases) and pericardial effusion (19 cases) both occurred mostly in lung cancer, and the second was the digestive system tumor. The malignant peritoneal effusion concurrent lesions mainly occurred in the digestive system (18 cases of gastric cancer, 4 cases of colon cancer, 2 cases of rectal cancer, and 1 case of small intestine cancer). Malignant multiple serous cavity effusion (57 cases) mostly occurred in lung cancer (30 cases). From the analysis of clinical indicators of pulmonary infection, the infection rates of pericardial cavity (89.13%), abdominal cavity (82.3%), and thoracic cavity (83.78%) were higher in the group with effusion than in the group without effusion (65.23%), and there was a statistical difference (*P < 0.05). The total detection rate, sensitivity, specificity, and accuracy of PET scan under deep learning CNN were 82.61%, 93.24%, 76.47%, and 92.41%, respectively. In summary, PET-CT images based on deep learning CNN were of important diagnostic value for chest, ascites, pericardial effusion, and serous cavity effusion of unknown reasons. In addition, lung infection in tumor patients was an important factor aggravating serous effusion.

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Authors and Affiliations

  1. PET-CT Room, Harbin First Hospital, Harbin City, 150010, Heilongjiang Province, China

    Jiawen Zhang, Wei Ren, Yufei Cheng, Chunan Wang & Qingpeng Kan

  2. Department of Imaging, Zhangjiagang Hospital of Traditional Chinese Medicine, Zhangjiagang City, 215600, Jiangsu Province, China

    Zhiguo Zhang

  3. Department of Radiology, Changping District Hospital of Beijing, Beijing City, 102200, China

    Xu Ji

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  1. Jiawen Zhang
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  2. Zhiguo Zhang
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  3. Xu Ji
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  4. Wei Ren
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  6. Chunan Wang
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  7. Qingpeng Kan
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Correspondence to Jiawen Zhang.

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Zhang, J., Zhang, Z., Ji, X. et al. Deep learning convolutional neural network in diagnosis of serous effusion in patients with malignant tumor by tomography. J Supercomput 78, 4449–4466 (2022). https://doi.org/10.1007/s11227-021-04051-5

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  • DOI: https://doi.org/10.1007/s11227-021-04051-5

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