详情页 - 四川省肿瘤医院知识库

当前位置：首页 > 详情页

Deep Convolutional Neural Network Based on Computed Tomography Images for the Preoperative Diagnosis of Occult Peritoneal Metastasis in Advanced Gastric Cancer.

文献详情

资源类型：

Pubmed体系：

作者：

机构： [1]Department of Radiology, West China Hospital, Sichuan University, Chengdu, China, [2]State Key Laboratory of Biotherapy, Department of Gastrointestinal Surgery and Laboratory of Gastric Cancer, Collaborative Innovation Center for Biotherapy, West China Hospital, Sichuan University, Chengdu, China, [3]Department of Pathology, West China Hospital, Sichuan University, Chengdu, China, 4 Institute of Advanced Research, Infervision, Beijing, China

出处：

DOI：

ISSN：

关键词： stomach neoplasms peritoneal neoplasms deep learning tomography x-ray computed neural networks computer

摘要：

We aimed to develop a deep convolutional neural network (DCNN) model based on computed tomography (CT) images for the preoperative diagnosis of occult peritoneal metastasis (OPM) in advanced gastric cancer (AGC). A total of 544 patients with AGC were retrospectively enrolled. Seventy-nine patients were confirmed with OPM during surgery or laparoscopy. CT images collected during the initial visit were randomly split into a training cohort and a testing cohort for DCNN model development and performance evaluation, respectively. A conventional clinical model using multivariable logistic regression was also developed to estimate the pretest probability of OPM in patients with gastric cancer. The DCNN model showed an AUC of 0.900 (95% CI: 0.851-0.953), outperforming the conventional clinical model (AUC = 0.670, 95% CI: 0.615-0.739; p < 0.001). The proposed DCNN model demonstrated the diagnostic detection of occult PM, with a sensitivity of 81.0% and specificity of 87.5% using the cutoff value according to the Youden index. Our study shows that the proposed deep learning algorithm, developed with CT images, may be used as an effective tool to preoperatively diagnose OPM in AGC. Copyright © 2020 Huang, Liu, Chen, He, Yu, Liu, Wu, Hu and Song.

基金：

语种：

PubmedID：

中科院(CAS)分区：

出版当年[2020]版：

大类 | 3 区医学

小类 | 3 区肿瘤学

最新[2023]版：

大类 | 3 区医学

小类 | 3 区肿瘤学

第一作者：

第一作者机构： [1]Department of Radiology, West China Hospital, Sichuan University, Chengdu, China,

共同第一作者：

通讯作者：

推荐引用方式(GB/T 7714)：

APA：

MLA：

相关文献

[1]Retrospective imaging studies of gastric cancer: Study protocol clinical trial (SPIRIT Compliant). [2]Baseline whole-lung CT features deriving from deep learning and radiomics: prediction of benign and malignant pulmonary ground-glass nodules [3]基于非均匀有理B样条的四维心脏-躯干体模及其在医学影像研究中的应用 [4]肺泡状棘球蚴病的CT表现特征 [5]参考体模和孤立性肺结节CT诊断的初步研究 [6]VX2兔脑瘤模型三维放疗解剖学靶区灌注CT与增强CT对照研究 [7]5-氟尿嘧啶缓释剂区域植入化疗在中期胃癌治疗中的应用 [8]多层螺旋CT对胰腺癌的灌注成像研究 [9]卵巢囊腺瘤与囊腺癌的CT征象及鉴别诊断价值 [10]Predicting acute pancreatitis severity with enhanced computed tomography scans using convolutional neural networks