Deep learning predicts resistance to neoadjuvant chemotherapy for locally advanced gastric cancer: a multicenter study

被引:0
作者
Jiayi Zhang
Yanfen Cui
Kaikai Wei
Zhenhui Li
Dandan Li
Ruirui Song
Jialiang Ren
Xin Gao
Xiaotang Yang
机构
[1] University of Science and Technology of China,Division of Life Sciences and Medicine, School of Biomedical Engineering (Suzhou)
[2] Cancer Hospital,Department of Radiology, Shanxi Province Cancer Hospital, Shanxi Hospital Affiliated to Cancer Hospital, Chinese Academy of Medical Sciences
[3] Affiliated to Shanxi Medical University,Medical Imaging Department, Suzhou Institute of Biomedical Engineering and Technology
[4] Chinese Academy of Sciences,Department of Radiology
[5] Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application,Department of Radiology
[6] The Sixth Affiliated Hospital of Sun Yat-Sen University,undefined
[7] The Third Affiliated Hospital of Kunming Medical University,undefined
[8] Yunnan Cancer Hospital,undefined
[9] Yunnan Cancer Center,undefined
[10] GE Healthcare China,undefined
来源
Gastric Cancer | 2022年 / 25卷
关键词
Locally advanced gastric cancer; Neoadjuvant chemotherapy; Pre-treatment computed tomography; Deep learning;
D O I
暂无
中图分类号
学科分类号
摘要
引用
收藏
页码:1050 / 1059
页数:9
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  • [1] Bray F(2018)Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries CA 68 394-424
  • [2] Ferlay J(2000)Current status and future perspectives in gastric cancer management Cancer Treat Rev 26 243-255
  • [3] Soerjomataram I(2012)Contrast-enhanced ultrasonography assessment of gastric cancer response to neoadjuvant chemotherapy World J Gastroenterol WJG 18 7026-10
  • [4] Siegel RL(2020)Interpretation of the development of neoadjuvant therapy for gastric cancer based on the vicissitudes of the NCCN guidelines World J Gast Oncol 12 37-1248
  • [5] Torre LA(2020)Diffusion kurtosis imaging in the prediction of poor responses of locally advanced gastric cancer to neoadjuvant chemotherapy Eur J Radiol 128 406-e2121143
  • [6] Jemal A(2018)Computed tomography-based radiomics for prediction of neoadjuvant chemotherapy outcomes in locally advanced gastric cancer: a pilot study Chin J Cancer Res 30 1-11
  • [7] Roukos D(2014)Computed Tomography (CT) Perfusion as an early prognostic marker for treatment response to neoadjuvant chemotherapy in gastroesophageal junction cancer and gastric cancer-a prospective study PLoS ONE 9 1234-4279
  • [8] Ang J(2012)Radiomics: the process and the challenges Magn Reson Imaging 30 e2121143-E2979
  • [9] Hu L(2021)Advanced gastric cancer: CT radiomics prediction and early detection of downstaging with neoadjuvant chemotherapy Eur Radiol 4 1-e2032269
  • [10] Huang P-T(2021)Development and validation of a computed tomography-based radiomics signature to predict response to neoadjuvant chemotherapy for locally advanced gastric cancer JAMA Netw Open 20 4271-549