亲爱的研友该休息了!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!身体可是革命的本钱,早点休息,好梦!

PhysiofUS : a tissue-motion based method for heart and breathing rate assessment in neurofunctional ultrasound imaging

呼吸 超声波 运动(物理) 超声成像 医学 计算机视觉 放射科 生物医学工程 计算机科学 解剖
作者
Nili Zucker,Samuel Diebolt,Francisco Camara Pereira,Jérôme Baranger,Isabella Hurvitz,Charlie Demené,Bruno-Félix Osmanski,Nathalie Ialy-Radio,Valérie Biran,Olivier Baud,Sophie Pezet,Thomas Deffieux,Mickaël Tanter
标识
DOI:10.1101/2024.09.22.614324
摘要

Recent studies have shown growing evidence that brain function is closely synchronised with global physiological parameters. Heart rate is linked to various cognitive processes and previous research has also demonstrated a strong correlation between neuronal activity and breathing. These findings highlight the significance of monitoring these key physiological parameters during neuroimaging as they provide valuable insights into the overall brain function. Today, in neuroimaging, assessing these parameters required additional cumbersome devices or implanted electrodes. In this work, we performed ultrafast ultrasound imaging both in rodents and human neonates, and we extracted heart and breathing rates from local tissue motion assessed by raw ultrasound data processing. Such 'PhysiofUS' automatically select two specific and optimal brain regions with pulsatile tissue signals to monitor such parameters. We validated the correspondence of these periodic signals with heart and breathing rates assessed using gold-standard electrodes in various conditions in rodents. We also validated Physio-fUS imaging in a clinical environment using conventional ECG. We show the potential of fUS imaging as an integrative tool for simultaneously monitoring physiological parameters during neurofunctional imaging. Beyond the technological improvement, this innovation could enhance our understanding of the link between breathing, heart rate and neurovascular activity both anesthetised in preclinincal research and clinical functional ultrasound imaging.

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
xiaoya完成签到,获得积分10
刚刚
3秒前
科研通AI2S应助科研通管家采纳,获得10
5秒前
12秒前
小张完成签到 ,获得积分10
16秒前
sad发布了新的文献求助10
17秒前
42秒前
希望天下0贩的0应助sad采纳,获得10
42秒前
Lucas应助魁梧的皮带采纳,获得30
44秒前
公西凝芙发布了新的文献求助10
48秒前
深情安青应助hyx9504采纳,获得10
52秒前
55秒前
魁梧的皮带完成签到,获得积分10
56秒前
59秒前
1分钟前
1分钟前
hyx9504发布了新的文献求助10
1分钟前
赘婿应助友好桐采纳,获得10
1分钟前
复杂妙海完成签到,获得积分10
1分钟前
公西凝芙完成签到,获得积分20
1分钟前
hyx9504完成签到,获得积分10
1分钟前
汉堡包应助Naturewoman采纳,获得10
1分钟前
1分钟前
monica完成签到 ,获得积分10
1分钟前
Naturewoman发布了新的文献求助10
1分钟前
qzlz发布了新的文献求助10
1分钟前
健壮的若冰完成签到 ,获得积分10
1分钟前
NexusExplorer应助Naturewoman采纳,获得10
1分钟前
1分钟前
lvgui发布了新的文献求助10
1分钟前
1分钟前
友好桐发布了新的文献求助10
1分钟前
1分钟前
Naturewoman发布了新的文献求助10
1分钟前
一路生花碎西瓜完成签到 ,获得积分10
1分钟前
1分钟前
无情愫发布了新的文献求助10
1分钟前
英俊的铭应助科研通管家采纳,获得10
2分钟前
李健的小迷弟应助lvgui采纳,获得10
2分钟前
Zeal完成签到,获得积分10
2分钟前
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
PowerCascade: A Synthetic Dataset for Cascading Failure Analysis in Power Systems 2000
Picture this! Including first nations fiction picture books in school library collections 1000
Signals, Systems, and Signal Processing 610
Unlocking Chemical Thinking: Reimagining Chemistry Teaching and Learning 555
Photodetectors: From Ultraviolet to Infrared 500
Cancer Targets: Novel Therapies and Emerging Research Directions (Part 1) 400
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 6358717
求助须知:如何正确求助?哪些是违规求助? 8172853
关于积分的说明 17210795
捐赠科研通 5413715
什么是DOI,文献DOI怎么找? 2865269
邀请新用户注册赠送积分活动 1842695
关于科研通互助平台的介绍 1690770