Relationship between the image characteristics of artificial intelligence and EGFR gene mutation in lung adenocarcinoma
Lung Adenocarcinoma (LUAD) is a kind of Lung Cancer (LCA) with high incidence rate, which is very harmful to human body. It is hidden in the human body and is not easy to be discovered, so it brings great inconvenience to the treatment of LUAD. Artificial Intelligence (AI) technology provides techni...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-01-01
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| Series: | Frontiers in Genetics |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fgene.2022.1090180/full |
| _version_ | 1797961445777866752 |
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| author | Guoping Zhou Shuhua Xu Xiaoli Liu Jingjun Ge Qiyu He Weikang Cao Junning Ding Xinghua Kai |
| author_facet | Guoping Zhou Shuhua Xu Xiaoli Liu Jingjun Ge Qiyu He Weikang Cao Junning Ding Xinghua Kai |
| author_sort | Guoping Zhou |
| collection | DOAJ |
| description | Lung Adenocarcinoma (LUAD) is a kind of Lung Cancer (LCA) with high incidence rate, which is very harmful to human body. It is hidden in the human body and is not easy to be discovered, so it brings great inconvenience to the treatment of LUAD. Artificial Intelligence (AI) technology provides technical support for the diagnosis and treatment of LUAD and has great application space in intelligent medicine. In this paper, 164 patients with primary LUAD who underwent surgery in Hospital A from January 2020 to December 2021 were selected as the study subjects, and the correlation between the imaging characteristics of LUAD and Epidermal Growth Factor Receptor (EGFR) gene mutation was analyzed. Finally, the conclusion was drawn. In terms of the study on the correlation between EGFR mutation of LUAD and the imaging characteristics of Computed Tomography (CT), it was concluded that there were significant differences between the patient’s sex, smoking history, pulmonary nodule morphology and the EGFR gene, and there was no significant difference between the patient’s tumor size and EGFR gene; in the study of the relationship between EGFR gene mutation and CT signs of LUAD lesions, it was found that there were significant differences between the symptoms of cavity sign, hair prick sign and chest depression sign and EGFR gene, but there was no significant difference between the symptoms of lobulation sign and EGFR gene; in the study of pathological subtype and EGFR gene mutation status of LUAD patients, it was concluded that the pathological subtype was mainly micropapillary. The mutation rate was 44.44%, which was the highest; in terms of CT manifestations of adjacent structures of lung cancer and the study of EGFR gene mutation status, it was found that there was a statistical difference between the tumor with vascular convergence sign and EGFR gene mutation, and pleural effusion, pericardial effusion, pleural thickening and other signs in tumor imaging were not significantly associated with EGFR gene mutation; in terms of the study of CT manifestations of adjacent structures of LCA and EGFR gene mutation status, it was concluded that pleural effusion, pericardial effusion, pleural thickening and other signs in tumor images were not significantly associated with EGFR gene mutation; in terms of analysis and cure of LUAD, it was concluded that the cure rate of patients was relatively high, and only a few people died of ineffective treatment. This paper provided a reference for the field of intelligent medicine and physical health. |
| first_indexed | 2024-04-11T00:58:35Z |
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| id | doaj.art-18027f83105a4051ad72f9d8b9c9aba9 |
| institution | Directory Open Access Journal |
| issn | 1664-8021 |
| language | English |
| last_indexed | 2024-04-11T00:58:35Z |
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| series | Frontiers in Genetics |
| spelling | doaj.art-18027f83105a4051ad72f9d8b9c9aba92023-01-04T19:03:49ZengFrontiers Media S.A.Frontiers in Genetics1664-80212023-01-011310.3389/fgene.2022.10901801090180Relationship between the image characteristics of artificial intelligence and EGFR gene mutation in lung adenocarcinomaGuoping Zhou0Shuhua Xu1Xiaoli Liu2Jingjun Ge3Qiyu He4Weikang Cao5Junning Ding6Xinghua Kai7Department of Cardiothoracic Surgery, Dongtai Hospital of Traditional Chinese Medicine, Dongtai, ChinaDepartment of Cardiothoracic Surgery, Dongtai Hospital of Traditional Chinese Medicine, Dongtai, ChinaDepartment of Pathology, Dongtai Hospital of Traditional Chinese Medicine, Dongtai, ChinaDepartment of Radiology Imaging, Dongtai Hospital of Traditional Chinese Medicine, Dongtai, ChinaDepartment of Cardiothoracic Surgery, Dongtai Hospital of Traditional Chinese Medicine, Dongtai, ChinaDepartment of Cardiothoracic Surgery, Dongtai Hospital of Traditional Chinese Medicine, Dongtai, ChinaDepartment of Cardiothoracic Surgery, Dongtai Hospital of Traditional Chinese Medicine, Dongtai, ChinaDepartment of Cardiothoracic Surgery, Dongtai Hospital of Traditional Chinese Medicine, Dongtai, ChinaLung Adenocarcinoma (LUAD) is a kind of Lung Cancer (LCA) with high incidence rate, which is very harmful to human body. It is hidden in the human body and is not easy to be discovered, so it brings great inconvenience to the treatment of LUAD. Artificial Intelligence (AI) technology provides technical support for the diagnosis and treatment of LUAD and has great application space in intelligent medicine. In this paper, 164 patients with primary LUAD who underwent surgery in Hospital A from January 2020 to December 2021 were selected as the study subjects, and the correlation between the imaging characteristics of LUAD and Epidermal Growth Factor Receptor (EGFR) gene mutation was analyzed. Finally, the conclusion was drawn. In terms of the study on the correlation between EGFR mutation of LUAD and the imaging characteristics of Computed Tomography (CT), it was concluded that there were significant differences between the patient’s sex, smoking history, pulmonary nodule morphology and the EGFR gene, and there was no significant difference between the patient’s tumor size and EGFR gene; in the study of the relationship between EGFR gene mutation and CT signs of LUAD lesions, it was found that there were significant differences between the symptoms of cavity sign, hair prick sign and chest depression sign and EGFR gene, but there was no significant difference between the symptoms of lobulation sign and EGFR gene; in the study of pathological subtype and EGFR gene mutation status of LUAD patients, it was concluded that the pathological subtype was mainly micropapillary. The mutation rate was 44.44%, which was the highest; in terms of CT manifestations of adjacent structures of lung cancer and the study of EGFR gene mutation status, it was found that there was a statistical difference between the tumor with vascular convergence sign and EGFR gene mutation, and pleural effusion, pericardial effusion, pleural thickening and other signs in tumor imaging were not significantly associated with EGFR gene mutation; in terms of the study of CT manifestations of adjacent structures of LCA and EGFR gene mutation status, it was concluded that pleural effusion, pericardial effusion, pleural thickening and other signs in tumor images were not significantly associated with EGFR gene mutation; in terms of analysis and cure of LUAD, it was concluded that the cure rate of patients was relatively high, and only a few people died of ineffective treatment. This paper provided a reference for the field of intelligent medicine and physical health.https://www.frontiersin.org/articles/10.3389/fgene.2022.1090180/fulllung adenocarcinomaEGFR gene mutationsartificial intelligenceintelligent medicineimage characteristics |
| spellingShingle | Guoping Zhou Shuhua Xu Xiaoli Liu Jingjun Ge Qiyu He Weikang Cao Junning Ding Xinghua Kai Relationship between the image characteristics of artificial intelligence and EGFR gene mutation in lung adenocarcinoma Frontiers in Genetics lung adenocarcinoma EGFR gene mutations artificial intelligence intelligent medicine image characteristics |
| title | Relationship between the image characteristics of artificial intelligence and EGFR gene mutation in lung adenocarcinoma |
| title_full | Relationship between the image characteristics of artificial intelligence and EGFR gene mutation in lung adenocarcinoma |
| title_fullStr | Relationship between the image characteristics of artificial intelligence and EGFR gene mutation in lung adenocarcinoma |
| title_full_unstemmed | Relationship between the image characteristics of artificial intelligence and EGFR gene mutation in lung adenocarcinoma |
| title_short | Relationship between the image characteristics of artificial intelligence and EGFR gene mutation in lung adenocarcinoma |
| title_sort | relationship between the image characteristics of artificial intelligence and egfr gene mutation in lung adenocarcinoma |
| topic | lung adenocarcinoma EGFR gene mutations artificial intelligence intelligent medicine image characteristics |
| url | https://www.frontiersin.org/articles/10.3389/fgene.2022.1090180/full |
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