首页> 美国卫生研究院文献>Elsevier Sponsored Documents >Osteolytica: An automated image analysis software package that rapidly measures cancer-induced osteolytic lesions in in vivo models with greater reproducibility compared to other commonly used methods
【2h】

Osteolytica: An automated image analysis software package that rapidly measures cancer-induced osteolytic lesions in in vivo models with greater reproducibility compared to other commonly used methods

机译:Osteolytica:一种自动化的图像分析软件包与其他常用方法相比该软件包可以在体内模型中快速测量癌症诱导的溶骨性病变并具有更高的重现性

代理获取
本网站仅为用户提供外文OA文献查询和代理获取服务,本网站没有原文。下单后我们将采用程序或人工为您竭诚获取高质量的原文,但由于OA文献来源多样且变更频繁,仍可能出现获取不到、文献不完整或与标题不符等情况,如果获取不到我们将提供退款服务。请知悉。

摘要

Methods currently used to analyse osteolytic lesions caused by malignancies such as multiple myeloma and metastatic breast cancer vary from basic 2-D X-ray analysis to 2-D images of micro-CT datasets analysed with non-specialised image software such as ImageJ. However, these methods have significant limitations. They do not capture 3-D data, they are time-consuming and they often suffer from inter-user variability. We therefore sought to develop a rapid and reproducible method to analyse 3-D osteolytic lesions in mice with cancer-induced bone disease. To this end, we have developed Osteolytica, an image analysis software method featuring an easy to use, step-by-step interface to measure lytic bone lesions. Osteolytica utilises novel graphics card acceleration (parallel computing) and 3-D rendering to provide rapid reconstruction and analysis of osteolytic lesions. To evaluate the use of Osteolytica we analysed tibial micro-CT datasets from murine models of cancer-induced bone disease and compared the results to those obtained using a standard ImageJ analysis method. Firstly, to assess inter-user variability we deployed four independent researchers to analyse tibial datasets from the U266-NSG murine model of myeloma. Using ImageJ, inter-user variability between the bones was substantial (± 19.6%), in contrast to using Osteolytica, which demonstrated minimal variability (± 0.5%). Secondly, tibial datasets from U266-bearing NSG mice or BALB/c mice injected with the metastatic breast cancer cell line 4T1 were compared to tibial datasets from aged and sex-matched non-tumour control mice. Analyses by both Osteolytica and ImageJ showed significant increases in bone lesion area in tumour-bearing mice compared to control mice. These results confirm that Osteolytica performs as well as the current 2-D ImageJ osteolytic lesion analysis method. However, Osteolytica is advantageous in that it analyses over the entirety of the bone volume (as opposed to selected 2-D images), it is a more rapid method and it has less user variability.
机译:当前用于分析由恶性肿瘤(例如多发性骨髓瘤和转移性乳腺癌)引起的溶骨性病变的方法,从基本的2-D X射线分析到使用非专业图像软件(如ImageJ)分析的微型CT数据集的二维图像,其方法有所不同。但是,这些方法有很大的局限性。它们不捕获3D数据,非常耗时,并且经常遭受用户间差异的困扰。因此,我们寻求开发一种快速且可重现的方法来分析患有癌症诱发的骨病的小鼠的3-D溶骨性病变。为此,我们开发了Osteolytica,这是一种图像分析软件方法,具有易于使用的逐步界面来测量溶骨性病变。 Osteolytica利用新颖的图形卡加速(并行计算)和3-D渲染功能来提供对溶骨性病变的快速重建和分析。为了评估Osteolytica的使用,我们分析了由癌症诱发的骨病的鼠模型产生的胫骨微型CT数据集,并将结果与​​使用标准ImageJ分析方法获得的结果进行了比较。首先,为了评估用户间的可变性,我们部署了四名独立研究人员来分析来自骨髓瘤U266-NSG鼠模型的胫骨数据集。与使用Osteolytica的情况相比,使用ImageJ的用户之间的骨骼之间的差异很大(±19.6%),这表明差异很小(±0.5%)。其次,将来自注射转移性乳腺癌细胞系4T1的带有U266的NSG小鼠或BALB / c小鼠的胫骨数据集与年龄和性别匹配的非肿瘤对照小鼠的胫骨数据集进行比较。 Osteolytica和ImageJ的分析均显示,与对照组相比,荷瘤小鼠的骨病变面积显着增加。这些结果证实,Osteolytica的性能与目前的2-D ImageJ溶骨性病变分析方法一样好。但是,Osteolytica的优势在于它可以分析整个骨体积(与选定的2-D图像相反),它是一种更快速的方法,并且用户变异性较小。

著录项

相似文献

  • 外文文献
  • 专利
代理获取

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号