Prediction of the Depth of Tumor Invasion in Gastric Cancer: Potential Role of CT Radiomics

医学 队列 无线电技术 放射科 阶段(地层学) 回顾性队列研究 癌症 外科肿瘤学 内科学 古生物学 生物
作者
Yue Wang,Wei Liu,Yu Yang,Jingjuan Liu,Lin Jiang,Huadan Xue,Jing Lei,Zhengyu Jin,Jianchun Yu
出处
期刊:Academic Radiology [Elsevier BV]
卷期号:27 (8): 1077-1084 被引量:38
标识
DOI:10.1016/j.acra.2019.10.020
摘要

Rationale and Objectives The aim of this study was to investigate the value of computed tomography (CT) radiomics for the differentiation between T2 and T3/4 stage lesions in gastric cancer. Materials and methods A total of 244 consecutive patients with pathologically proven gastric cancer were retrospectively included and split into a training cohort (171 patients) and a test cohort (73 patients). Preoperative arterial phase and portal phase contrast enhanced CT images were retrieved for tumor segmentation and feature extraction by using a dedicated postprocessing software. The random forest method was used to build the classifier models. Results The performance of single phase radiomics models were favorable in the differentiation between T2 and T3/4 stage tumors. Arterial phase-based radiomics model exhibited areas under the curve of 0.899 (95% CI: 0.812–0.955) in the training cohort and 0.825 (95% CI: 0.718–0.904) in the test cohort. Portal phase-based radiomics model showed areas under the curve of 0.843 (95% CI: 0.746–0.914) and 0.818 (95% CI: 0.711–0.899) in the training and test cohort, respectively. Conclusion CT radiomics approach has a potential role in differentiation between T2 and T3/4 stage tumors in gastric cancer. The aim of this study was to investigate the value of computed tomography (CT) radiomics for the differentiation between T2 and T3/4 stage lesions in gastric cancer. A total of 244 consecutive patients with pathologically proven gastric cancer were retrospectively included and split into a training cohort (171 patients) and a test cohort (73 patients). Preoperative arterial phase and portal phase contrast enhanced CT images were retrieved for tumor segmentation and feature extraction by using a dedicated postprocessing software. The random forest method was used to build the classifier models. The performance of single phase radiomics models were favorable in the differentiation between T2 and T3/4 stage tumors. Arterial phase-based radiomics model exhibited areas under the curve of 0.899 (95% CI: 0.812–0.955) in the training cohort and 0.825 (95% CI: 0.718–0.904) in the test cohort. Portal phase-based radiomics model showed areas under the curve of 0.843 (95% CI: 0.746–0.914) and 0.818 (95% CI: 0.711–0.899) in the training and test cohort, respectively. CT radiomics approach has a potential role in differentiation between T2 and T3/4 stage tumors in gastric cancer.
最长约 10秒,即可获得该文献文件

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
u2u2完成签到,获得积分10
刚刚
cldg完成签到,获得积分10
1秒前
ruychou完成签到,获得积分20
1秒前
1秒前
1秒前
南溪完成签到,获得积分10
1秒前
2秒前
2秒前
yckbz完成签到,获得积分10
2秒前
pengyang完成签到,获得积分10
2秒前
Cheese完成签到,获得积分10
3秒前
3秒前
4秒前
maz123456完成签到,获得积分10
4秒前
cx发布了新的文献求助10
4秒前
4秒前
世界小奇完成签到,获得积分10
4秒前
tudouni发布了新的文献求助10
4秒前
5秒前
wayne完成签到,获得积分10
5秒前
5秒前
tangpc完成签到,获得积分10
5秒前
彭于晏应助毛绒绒窝铺采纳,获得10
5秒前
6秒前
乘云去发布了新的文献求助10
6秒前
漠尘完成签到,获得积分10
7秒前
不敢装睡完成签到,获得积分10
7秒前
CC发布了新的文献求助10
7秒前
文清发布了新的文献求助10
7秒前
追寻道天完成签到,获得积分10
7秒前
感性的穆完成签到,获得积分10
8秒前
凌慕完成签到,获得积分10
8秒前
wade发布了新的文献求助10
8秒前
高大靖仇发布了新的文献求助10
8秒前
王冉冉完成签到,获得积分10
8秒前
8秒前
flj7038完成签到,获得积分10
9秒前
赘婿应助zc32q采纳,获得10
9秒前
Nuna完成签到,获得积分20
9秒前
沉静傲霜完成签到,获得积分10
10秒前
高分求助中
Adhesion Science: Principles & Practice 1234
Signals, Systems, and Signal Processing 610
Introduction to Cosmetic Formulation and Technology, 2nd Edition 400
Petrology and Plate Tectonics,2025 400
Burger's Medicinal Chemistry and Drug Discovery 400
Programming for Chemical Engineers Using C, C++, and MATLAB 320
Birth of Twins After Genome Editing for HIV Resistance 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 物理 内科学 复合材料 催化作用 物理化学 光电子学 电极 细胞生物学 基因 无机化学
热门帖子
关注 科研通微信公众号,转发送积分 6690130
求助须知:如何正确求助?哪些是违规求助? 8433754
关于积分的说明 18018474
捐赠科研通 5916869
什么是DOI,文献DOI怎么找? 2984584
邀请新用户注册赠送积分活动 1960542
关于科研通互助平台的介绍 1899111