批量资源血管生成工具(BRAT),使微血管网络的高通量显微镜筛选。

IF 8 2区 医学 Q1 ENGINEERING, BIOMEDICAL
Harriet Krek, Ashley R Murphy, Ryan McKinnon, Rose Ann Franco, Mark C Allenby
{"title":"批量资源血管生成工具(BRAT),使微血管网络的高通量显微镜筛选。","authors":"Harriet Krek, Ashley R Murphy, Ryan McKinnon, Rose Ann Franco, Mark C Allenby","doi":"10.1088/1758-5090/ae00f6","DOIUrl":null,"url":null,"abstract":"<p><p>Vessel forming assays are a valuable technology to evaluate the vasculogenic and angiogenic potential of different cell types, matrix proteins, and soluble factors. Recent advances in high-content microscopy allow for vascular morphogenesis assays to be captured in real-time and in high-throughput formats. Unfortunately, existing microvascular network (MVN) quantification algorithms are either inaccurate, not user-friendly, or manually analyse one image at a time, unfavourable to high-throughput screening. This manuscript introduces the Batch-Resourcing Angiogenesis Tool (BRAT), an open-source computer software which efficiently segments, skeletonizes, and analyses large batches of vascular network images with high accuracy. Benchmarked across diverse clinical and cultured MVN images, BRAT is the most sensitive vascular network image analysis tool (94.5%), exhibiting leading accuracy (93.3%). BRAT's multi-threaded processing automatically analyses 886 microscopy images at a speed of 0.17 s/image on a performance computer (2:29 min) or 2.31 s/image on a laptop (34:04). This is 10-to-100 fold more time-efficient than existing software, which require 12-16 s of direct user input per image. BRAT successfully compares diverse microvascular cell types cultured in 2D and 3D biomaterials. BRAT represents a powerful approach for the accurate and high-throughput screening of vessel forming assays for disease models, regenerative medicines, and therapeutic testing. BRAT is avaliable to download at:https://github.com/BMSE-UQ/BRAT-Vascular-Image-Tool.</p>","PeriodicalId":8964,"journal":{"name":"Biofabrication","volume":" ","pages":""},"PeriodicalIF":8.0000,"publicationDate":"2025-09-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The Batch-Resourcing Angiogenesis Tool (BRAT) to enable high-throughput microscopy screening of microvascular networks.\",\"authors\":\"Harriet Krek, Ashley R Murphy, Ryan McKinnon, Rose Ann Franco, Mark C Allenby\",\"doi\":\"10.1088/1758-5090/ae00f6\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Vessel forming assays are a valuable technology to evaluate the vasculogenic and angiogenic potential of different cell types, matrix proteins, and soluble factors. Recent advances in high-content microscopy allow for vascular morphogenesis assays to be captured in real-time and in high-throughput formats. Unfortunately, existing microvascular network (MVN) quantification algorithms are either inaccurate, not user-friendly, or manually analyse one image at a time, unfavourable to high-throughput screening. This manuscript introduces the Batch-Resourcing Angiogenesis Tool (BRAT), an open-source computer software which efficiently segments, skeletonizes, and analyses large batches of vascular network images with high accuracy. Benchmarked across diverse clinical and cultured MVN images, BRAT is the most sensitive vascular network image analysis tool (94.5%), exhibiting leading accuracy (93.3%). BRAT's multi-threaded processing automatically analyses 886 microscopy images at a speed of 0.17 s/image on a performance computer (2:29 min) or 2.31 s/image on a laptop (34:04). This is 10-to-100 fold more time-efficient than existing software, which require 12-16 s of direct user input per image. BRAT successfully compares diverse microvascular cell types cultured in 2D and 3D biomaterials. BRAT represents a powerful approach for the accurate and high-throughput screening of vessel forming assays for disease models, regenerative medicines, and therapeutic testing. BRAT is avaliable to download at:https://github.com/BMSE-UQ/BRAT-Vascular-Image-Tool.</p>\",\"PeriodicalId\":8964,\"journal\":{\"name\":\"Biofabrication\",\"volume\":\" \",\"pages\":\"\"},\"PeriodicalIF\":8.0000,\"publicationDate\":\"2025-09-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Biofabrication\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://doi.org/10.1088/1758-5090/ae00f6\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Biofabrication","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.1088/1758-5090/ae00f6","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 0

摘要

血管形成试验是一项有价值的技术,用于评估不同细胞类型、基质蛋白和可溶性因子的血管生成和血管生成潜力。在高含量显微镜的最新进展允许血管形态发生分析实时捕获和高通量格式。不幸的是,现有的微血管网络定量算法要么不准确,要么用户界面不友好,要么一次只能手动分析一张图像,不利于高通量筛选。本文介绍了BRAT (Batch-Resourcing Angiogenesis Tool),这是一种开源的计算机软件,可以高效地分割、骨架化和分析大批量的血管网络图像,精度高。以各种临床和培养的微血管网络图像为基准,BRAT是最敏感的血管网络图像分析工具(94.5%),具有领先的准确性(93.3%)。BRAT的多线程处理可以自动分析886张显微镜图像,在高性能计算机上的速度为0.17秒/张图像(2:29分钟),在笔记本电脑上的速度为2.31秒/张图像(34:04)。这比现有软件的时间效率高10到100倍,现有软件需要12到16秒的用户直接输入每张图像。BRAT成功地比较了在二维和三维生物材料中培养的不同微血管细胞类型。BRAT为疾病模型、再生药物和治疗测试的血管形成分析提供了准确和高通量筛选的有力方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The Batch-Resourcing Angiogenesis Tool (BRAT) to enable high-throughput microscopy screening of microvascular networks.

Vessel forming assays are a valuable technology to evaluate the vasculogenic and angiogenic potential of different cell types, matrix proteins, and soluble factors. Recent advances in high-content microscopy allow for vascular morphogenesis assays to be captured in real-time and in high-throughput formats. Unfortunately, existing microvascular network (MVN) quantification algorithms are either inaccurate, not user-friendly, or manually analyse one image at a time, unfavourable to high-throughput screening. This manuscript introduces the Batch-Resourcing Angiogenesis Tool (BRAT), an open-source computer software which efficiently segments, skeletonizes, and analyses large batches of vascular network images with high accuracy. Benchmarked across diverse clinical and cultured MVN images, BRAT is the most sensitive vascular network image analysis tool (94.5%), exhibiting leading accuracy (93.3%). BRAT's multi-threaded processing automatically analyses 886 microscopy images at a speed of 0.17 s/image on a performance computer (2:29 min) or 2.31 s/image on a laptop (34:04). This is 10-to-100 fold more time-efficient than existing software, which require 12-16 s of direct user input per image. BRAT successfully compares diverse microvascular cell types cultured in 2D and 3D biomaterials. BRAT represents a powerful approach for the accurate and high-throughput screening of vessel forming assays for disease models, regenerative medicines, and therapeutic testing. BRAT is avaliable to download at:https://github.com/BMSE-UQ/BRAT-Vascular-Image-Tool.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Biofabrication
Biofabrication ENGINEERING, BIOMEDICAL-MATERIALS SCIENCE, BIOMATERIALS
CiteScore
17.40
自引率
3.30%
发文量
118
审稿时长
2 months
期刊介绍: Biofabrication is dedicated to advancing cutting-edge research on the utilization of cells, proteins, biological materials, and biomaterials as fundamental components for the construction of biological systems and/or therapeutic products. Additionally, it proudly serves as the official journal of the International Society for Biofabrication (ISBF).
×
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
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
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 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信