Preoperative prediction of lymphovascular space invasion in endometrioid adenocarcinoma: an MRI-based radiomics nomogram with consideration of the peritumoral region

医学 列线图 无线电技术 接收机工作特性 磁共振成像 放射科 淋巴血管侵犯 逻辑回归 肿瘤科 内科学 癌症 转移
作者
Bin Yan,Yuxia Jia,Zhihao Li,Caixia Ding,Jianrong Lu,Jixin Liu,Yuchen Zhang
出处
期刊:Acta Radiologica [SAGE]
卷期号:64 (9): 2636-2645 被引量:4
标识
DOI:10.1177/02841851231181681
摘要

Lymphovascular space invasion (LVSI) of endometrial cancer (EC) is a postoperative histological index, which is associated with lymph node metastases. A preoperative acknowledgement of LVSI status might aid in treatment decision-making.To explore the utility of multiparameter magnetic resonance imaging (MRI) and radiomic features obtained from intratumoral and peritumoral regions for predicting LVSI in endometrioid adenocarcinoma (EEA).A total of 334 EEA tumors were retrospectively analyzed. Axial T2-weighted (T2W) imaging and apparent diffusion coefficient (ADC) mapping were conducted. Intratumoral and peritumoral regions were manually annotated as the volumes of interest (VOIs). A support vector machine was applied to train the prediction models. Multivariate logistic regression analysis was used to develop a nomogram based on clinical and tumor morphological parameters and the radiomics score (RadScore). The predictive performance of the nomogram was assessed by the area under the receiver operator characteristic curve (AUC) in the training and validation cohorts.Among the features obtained from different imaging modalities (T2W imaging and ADC mapping) and VOIs, the RadScore had the best performance in predicting LVSI classification (AUCtrain = 0.919, and AUCvalidation = 0.902). The nomogram based on age, CA125, maximum anteroposterior tumor diameter on sagittal T2W images, tumor area ratio, and RadScore was established to predict LVSI had AUC values in the training and validation cohorts of 0.962 (sensitivity 94.0%, specificity 86.0%) and 0.965 (sensitivity 90.0%, specificity 85.3%), respectively.The intratumoral and peritumoral imaging features were complementary, and the MRI-based radiomics nomogram might serve as a non-invasive biomarker to preoperatively predict LVSI in patients with EEA.
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
刚刚
蓝色sea完成签到,获得积分10
刚刚
李雪松完成签到 ,获得积分10
刚刚
1秒前
Akim应助plcukyu采纳,获得10
1秒前
大脑袋应助ajc采纳,获得20
2秒前
Matsuteru_完成签到,获得积分20
3秒前
熙欢完成签到,获得积分20
3秒前
火星上的映安完成签到 ,获得积分10
3秒前
小罗同学完成签到,获得积分10
4秒前
4秒前
4秒前
Raymond完成签到,获得积分10
4秒前
苗条的一一完成签到,获得积分10
5秒前
gz000111完成签到,获得积分10
5秒前
mengwensi关注了科研通微信公众号
5秒前
英俊的采萱完成签到,获得积分10
5秒前
5秒前
可爱的函函应助张三采纳,获得10
5秒前
友好的牛排完成签到,获得积分10
7秒前
LIAO发布了新的文献求助10
7秒前
田様应助科研通管家采纳,获得10
7秒前
传奇3应助科研通管家采纳,获得10
7秒前
Hello应助科研通管家采纳,获得10
8秒前
科研通AI2S应助科研通管家采纳,获得10
8秒前
小黄应助科研通管家采纳,获得10
8秒前
juana应助科研通管家采纳,获得10
8秒前
CodeCraft应助科研通管家采纳,获得10
8秒前
思源应助科研通管家采纳,获得10
8秒前
小黄应助科研通管家采纳,获得10
8秒前
搜集达人应助科研通管家采纳,获得10
8秒前
共享精神应助科研通管家采纳,获得10
8秒前
英姑应助科研通管家采纳,获得10
8秒前
爆米花应助科研通管家采纳,获得10
8秒前
充电宝应助科研通管家采纳,获得30
9秒前
9秒前
小黄应助科研通管家采纳,获得10
9秒前
小黄应助科研通管家采纳,获得10
9秒前
饱满含玉完成签到,获得积分10
9秒前
蔻蔻完成签到,获得积分10
10秒前
高分求助中
Continuum Thermodynamics and Material Modelling 3000
Production Logging: Theoretical and Interpretive Elements 2700
Mechanistic Modeling of Gas-Liquid Two-Phase Flow in Pipes 2500
Structural Load Modelling and Combination for Performance and Safety Evaluation 800
Conference Record, IAS Annual Meeting 1977 610
Virulence Mechanisms of Plant-Pathogenic Bacteria 500
白土三平研究 500
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 有机化学 生物化学 物理 纳米技术 计算机科学 内科学 化学工程 复合材料 基因 遗传学 物理化学 催化作用 量子力学 光电子学 冶金
热门帖子
关注 科研通微信公众号,转发送积分 3555970
求助须知:如何正确求助?哪些是违规求助? 3131555
关于积分的说明 9391776
捐赠科研通 2831407
什么是DOI,文献DOI怎么找? 1556440
邀请新用户注册赠送积分活动 726584
科研通“疑难数据库(出版商)”最低求助积分说明 715890