Contrast-enhancing staining agents for ex vivo contrast-enhanced computed tomography: A review

T. Balcaen , S. Vangrunderbeeck , W.M. De Borggraeve , G. Kerckhofs
{"title":"Contrast-enhancing staining agents for ex vivo contrast-enhanced computed tomography: A review","authors":"T. Balcaen ,&nbsp;S. Vangrunderbeeck ,&nbsp;W.M. De Borggraeve ,&nbsp;G. Kerckhofs","doi":"10.1016/j.tmater.2025.100052","DOIUrl":null,"url":null,"abstract":"<div><div><em>Ex vivo</em> microCT imaging has emerged as a powerful tool for 3D histology of biological tissues, offering significant advantages in terms of spatial resolution, simplicity of protocols and acquisition speed. Among the various techniques available, contrast-enhanced computed tomography (CECT) is particularly favored for its ability to simultaneously visualize soft and mineralized tissue types through the use of contrast agents (CAs), making it suitable for laboratory-based microCT devices. This review focuses on contrast-enhancing staining agents (CESAs), a subclass of CAs, which enrich the X-ray attenuating atom content in soft tissues through interactions. Within this review, CESAs are categorized based on their chemical composition into organic, mixed (<em>i.e.</em> heavy metal and organic ligand) and inorganic compounds, each with specific properties and applications. Despite the growing interest and numerous studies on CESAs, the selection process often relies on trial-and-error, anecdotal knowledge, or commercial availability. This review aims to enhance understanding of the chemical interactions and distribution patterns of CESAs within biological tissues, by discussing a selection of studies grouping observations by tissues and organs, to gain a better understanding of consistent affinity patterns. The findings highlight the complexity and accompanying challenges of predicting CESA distribution. This review will provide a foundation for both intelligent CESA selection and design, tailored to specific research needs as well as a guide for the application expert in choosing relevant literature for designing their experiments.</div></div>","PeriodicalId":101254,"journal":{"name":"Tomography of Materials and Structures","volume":"7 ","pages":"Article 100052"},"PeriodicalIF":0.0000,"publicationDate":"2025-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Tomography of Materials and Structures","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2949673X25000051","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Ex vivo microCT imaging has emerged as a powerful tool for 3D histology of biological tissues, offering significant advantages in terms of spatial resolution, simplicity of protocols and acquisition speed. Among the various techniques available, contrast-enhanced computed tomography (CECT) is particularly favored for its ability to simultaneously visualize soft and mineralized tissue types through the use of contrast agents (CAs), making it suitable for laboratory-based microCT devices. This review focuses on contrast-enhancing staining agents (CESAs), a subclass of CAs, which enrich the X-ray attenuating atom content in soft tissues through interactions. Within this review, CESAs are categorized based on their chemical composition into organic, mixed (i.e. heavy metal and organic ligand) and inorganic compounds, each with specific properties and applications. Despite the growing interest and numerous studies on CESAs, the selection process often relies on trial-and-error, anecdotal knowledge, or commercial availability. This review aims to enhance understanding of the chemical interactions and distribution patterns of CESAs within biological tissues, by discussing a selection of studies grouping observations by tissues and organs, to gain a better understanding of consistent affinity patterns. The findings highlight the complexity and accompanying challenges of predicting CESA distribution. This review will provide a foundation for both intelligent CESA selection and design, tailored to specific research needs as well as a guide for the application expert in choosing relevant literature for designing their experiments.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
求助全文
约1分钟内获得全文 去求助
来源期刊
自引率
0.00%
发文量
0
期刊最新文献
Development of AI crack segmentation models for additive manufacturing Contrast-enhancing staining agents for ex vivo contrast-enhanced computed tomography: A review Visualizing pulp fibers using X-ray tomography: Enhancing the contrast by labeling with iron oxide nanoparticles and the use of immersion oil 3D mineral quantification of particulate materials with rare earth mineral inclusions: Achieving sub-voxel resolution by considering the partial volume and blurring effect Geo-SegNet: A contrastive learning enhanced U-net for geomaterial segmentation
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1