Citespace-based visualization analysis of the imaging research progress of gastric cancer_CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY

Authors：

ZHANG Xiao ^1,2 , HUANG Wei ² ,  SONG Bin ¹

1. Department of Radiology, West China Hospital, Sichuan University, Chengdu 610041, P. R. China;
2. Department of Radiology, People’s Hospital of Leshan City, Leshan, Sichuan 614000, P. R. China;

Corresponding?author：

SONG Bin, Email: cjr.songbin@vip.163.com

Keywords：

gastric cancer; Citespace; imaging; visualization analysis

DOI：

10.7507/1007-9424.202012144

Video：

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Objective To realize the current status and hot issues in the field of gastric cancer imaging research, and to provide references for radiologists and gastrointestinal surgeons to grasp the overall overview of gastric cancer imaging.Method We downloaded the relevant literatures of gastric cancer imaging published in 2010–2020 in the Web of Science database, and used Citespace 5.7.R3 software for related visual analysis.Results A total of 726 articles in the field of gastric cancer imaging research were retrieved and screened. The number of gastric cancer imaging studies published from 2010 to 2020 was on the rise, with the top three countries published in China, Japan, and the United States. The clusters of co-cited literature on gastric cancer imaging: confocal laser microendoscopy, gastric cancer, gastric mucosal intestinal metaplasia, preoperative T staging, convolutional neural network, deep learning, advanced gastric cancer, in vivo differentiation, early stage gastric cancer, surgical treatment, perigastric lymph nodes, nearest neighbor algorithm, and so on. Hot words in recent research fields included: risk factors, characteristics, deep learning, chemotherapy, and neural networks.Conclusion The imaging diagnosis of early gastric cancer and the application of artificial intelligence are the research hotspots in this field.

Citation： ZHANG Xiao, HUANG Wei, SONG Bin. Citespace-based visualization analysis of the imaging research progress of gastric cancer. CHINESE JOURNAL OF BASES AND CLINICS IN GENERAL SURGERY, 2021, 28(2): 256-259. doi: 10.7507/1007-9424.202012144 Copy

1.	Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2018, 68(6): 394-424.
2.	鄭榮壽, 孫可欣, 張思維, 等. 2015年中國惡性腫瘤流行情況分析. 中華腫瘤雜志, 2019, 41(1): 19-28.
3.	中華人民共和國國家衛生健康委員會醫政醫管局胃癌診療規范 (2018年版). 國衛辦醫函〔2018〕1125號.
4.	Amin MB, Edge SB, Greene FL, et al. AJCC Cancer Staging Manual. 8th ed. New York: Springer, 2017: 203-220.
5.	李杰. Citespace科技文本挖掘及可視化. 第2版, 北京: 首都經濟貿易大學出版社, 2017: 77-136.
6.	黃子星, 李謀, 于浩鵬, 等. 基于CiteSpace的胰腺神經內分泌腫瘤影像研究的科學知識圖譜分析. 中國普外基礎與臨床雜志, 2019, 26(1): 96-101.
7.	Chen C. Science MAPPING: a systematic review of the literature. J Data Inf Sci, 2017, 2(2): 1-40.
8.	Sherman RE, Anderson SA, Dal Pan GJ, et al. Real-world evidence-what is it and what can it tell us? N Engl J Med, 2016, 375(23): 2293-2297.
9.	陳心足, 胡建昆. 胃癌規范化診療進展. 華西醫學, 2018, 33(4): 379-384.
10.	季福建, 房學東, 姜俊男, 等. 胃癌多學科綜合治療進展. 中華消化外科雜志, 2016, 15(3): 299-302.
11.	何文琪, 伍兵. 胃癌術前cTN分期的影像研究進展. 國際醫學放射學雜志, 2019, 42(1): 76-80.
12.	劉丹, 伍兵. 胃癌影像學的研究進展. 中國普外基礎與臨床雜志, 2018, 25(9): 1124-1129.
13.	Horiuchi Y, Aoyama K, Tokai Y, et al. Convolutional neural network for differentiating gastric cancer from gastritis using magnified endoscopy with narrow band imaging. Dig Dis Sci, 2020, 65(5): 1355-1363.
14.	Huang Z, Liu D, Chen X, et al. Retrospective imaging studies of gastric cancer: Study protocol clinical trial (SPIRIT Compliant). Medicine (Baltimore), 2020, 99(8): e19157.

1. Bray F, Ferlay J, Soerjomataram I, et al. Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 2018, 68(6): 394-424.
2. 鄭榮壽, 孫可欣, 張思維, 等. 2015年中國惡性腫瘤流行情況分析. 中華腫瘤雜志, 2019, 41(1): 19-28.
3. 中華人民共和國國家衛生健康委員會醫政醫管局胃癌診療規范 (2018年版). 國衛辦醫函〔2018〕1125號.
4. Amin MB, Edge SB, Greene FL, et al. AJCC Cancer Staging Manual. 8th ed. New York: Springer, 2017: 203-220.
5. 李杰. Citespace科技文本挖掘及可視化. 第2版, 北京: 首都經濟貿易大學出版社, 2017: 77-136.
6. 黃子星, 李謀, 于浩鵬, 等. 基于CiteSpace的胰腺神經內分泌腫瘤影像研究的科學知識圖譜分析. 中國普外基礎與臨床雜志, 2019, 26(1): 96-101.
7. Chen C. Science MAPPING: a systematic review of the literature. J Data Inf Sci, 2017, 2(2): 1-40.
8. Sherman RE, Anderson SA, Dal Pan GJ, et al. Real-world evidence-what is it and what can it tell us? N Engl J Med, 2016, 375(23): 2293-2297.
9. 陳心足, 胡建昆. 胃癌規范化診療進展. 華西醫學, 2018, 33(4): 379-384.
10. 季福建, 房學東, 姜俊男, 等. 胃癌多學科綜合治療進展. 中華消化外科雜志, 2016, 15(3): 299-302.
11. 何文琪, 伍兵. 胃癌術前cTN分期的影像研究進展. 國際醫學放射學雜志, 2019, 42(1): 76-80.
12. 劉丹, 伍兵. 胃癌影像學的研究進展. 中國普外基礎與臨床雜志, 2018, 25(9): 1124-1129.
13. Horiuchi Y, Aoyama K, Tokai Y, et al. Convolutional neural network for differentiating gastric cancer from gastritis using magnified endoscopy with narrow band imaging. Dig Dis Sci, 2020, 65(5): 1355-1363.
14. Huang Z, Liu D, Chen X, et al. Retrospective imaging studies of gastric cancer: Study protocol clinical trial (SPIRIT Compliant). Medicine (Baltimore), 2020, 99(8): e19157.

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Citespace-based visualization analysis of the imaging research progress of gastric cancer

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