已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

A novel computer-aided energy decision-making system improves patient treatment by microwave ablation of thyroid nodule

微波消融 烧蚀 微波食品加热 甲状腺 结核(地质) 计算机科学 医学 放射科 生物医学工程 医学物理学 内科学 生物 电信 古生物学
作者
Rui Du,Rui Wang,Hu Xu,Yuhao Xu,Zhengdong Fei,Yifeng Luo,Xiaolan Zhu,Yuefeng Li
出处
期刊:Computers in Biology and Medicine [Elsevier BV]
卷期号:188: 109823-109823
标识
DOI:10.1016/j.compbiomed.2025.109823
摘要

The current basis of microwave ablation (MWA) energy use for thyroid nodules (TN) is inadequate, leading to tissue carbonization, which is strongly associated with complications and poor prognosis. This study aims to devise a novel energy decision-making system to improve the subjective use of energy in current MWA procedures. Data from 916 subjects (1364 TN) across three medical centers were collected. In the first two sets, the single-stitch ablation needle energy (ANE) was calculated by analyzing MWA procedure videos. The causes of TN over-ablation (carbonization) were examined, and the relationship between well-ablated TN and ANE was explored based on TN attributes (volume and Young's modulus). Three-dimensional (3D) reconstruction of TN was performed, and a computer-aided model was constructed to optimize the distribution of the ANE field within the 3D-TN. Subsequently, a novel energy decision-making system was developed and tested. The third set was used for external validation. The cause of TN carbonization was found to be related to the overload of ANE with corrected Young's modulus and the selection of mismatched ablation needle power (ANP). A precise ANE model (Model 1) based on well-ablated TN and a needle-placement model (Model 2) based on the 3D-TN and ANP were subsequently constructed. The coupled new energy decision-making system (Model 1 + 2) demonstrated strong clinical generalization capabilities. In conclusion, this novel energy decision-making system can effectively improve the use of MWA energy, significantly promoting the precise treatment of TN.
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
5秒前
5秒前
充电宝应助友好的跳跳糖采纳,获得10
5秒前
6秒前
9秒前
唛仔发布了新的文献求助10
9秒前
11秒前
12秒前
CCYi发布了新的文献求助10
13秒前
所所应助lala采纳,获得10
13秒前
songjiatian发布了新的文献求助10
16秒前
小蘑菇应助崔宏玺采纳,获得10
18秒前
GingerF给Yuantian的求助进行了留言
18秒前
研究牛牛完成签到 ,获得积分10
19秒前
19秒前
19秒前
22秒前
充电宝应助NN采纳,获得10
23秒前
生生不息完成签到,获得积分20
23秒前
23秒前
超帅秋双发布了新的文献求助10
24秒前
大模型应助songjiatian采纳,获得10
26秒前
斯文败类应助科研通管家采纳,获得10
28秒前
爆米花应助科研通管家采纳,获得10
28秒前
今后应助科研通管家采纳,获得10
28秒前
Lucas应助科研通管家采纳,获得10
28秒前
molihuakai应助科研通管家采纳,获得10
28秒前
28秒前
华仔应助科研通管家采纳,获得10
29秒前
29秒前
cdercder应助任雨光采纳,获得10
32秒前
32秒前
科研通AI6.2应助任雨光采纳,获得10
32秒前
林诗萍完成签到 ,获得积分10
33秒前
33秒前
山野雾灯完成签到 ,获得积分10
35秒前
Zhang完成签到,获得积分20
36秒前
mian关注了科研通微信公众号
37秒前
科研通AI6.4应助歪比巴卜采纳,获得10
38秒前
现代尔芙发布了新的文献求助10
39秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
An Introduction to Foreign Language Learning and Teaching 750
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Governing Growth: Us Industrial Policy from Hamilton to Trump 500
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
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 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7625848
求助须知:如何正确求助?哪些是违规求助? 9200782
关于积分的说明 19727071
捐赠科研通 7196772
什么是DOI,文献DOI怎么找? 3273745
关于科研通互助平台的介绍 2435936
邀请新用户注册赠送积分活动 2269702