Suppr超能文献

从一个开放获取的数据集里,1000 多名 COVID-19 患者的胸部 CT 中识别出解剖变异。

Anatomical variants identified on chest computed tomography of 1000+ COVID-19 patients from an open-access dataset.

机构信息

Department of Anatomy, Faculty of Science, Mahidol University, Bangkok, Thailand.

In Silico and Clinical Anatomy Research Group (iSCAN), Bangkok, Thailand.

出版信息

Clin Anat. 2022 Sep;35(6):723-731. doi: 10.1002/ca.23873. Epub 2022 Apr 19.

Abstract

Chest computed tomography (CT) has been the preferred imaging modality during the pandemic owing to its sensitivity in detecting COVID-19 infections. Recently, a large number of COVID-19 imaging datasets have been deposited in public databases, leading to rapid advances in COVID-19 research. However, the application of these datasets beyond COVID-19-related research has been little explored. The authors believe that they could be used in anatomical research to elucidate the link between anatomy and disease and to study disease-related alterations to normal anatomy. Therefore, the present study was designed to investigate the prevalence of six well-known anatomical variants in the thorax using open-access CT images obtained from over 1000 Iranian COVID-19 patients aged between 6 and 89 years (60.9% male and 39.1% female). In brief, we found that the azygos lobe, tracheal bronchus, and cardiac bronchus were present in 0.8%, 0.2%, and 0% of the patients, respectively. Variations of the sternum, including sternal foramen, episternal ossicles, and sternalis muscle, were observed in 9.6%, 2.9%, and 1.5%, respectively. We believe anatomists could benefit from using open-access datasets as raw materials for research because these datasets are freely accessible and are abundant, though further research is needed to evaluate the uses of other datasets from different body regions and imaging modalities. Radiologists should also be aware of these common anatomical variants when examining lung CTs, especially since the use of this imaging modality has increased during the pandemic.

摘要

胸部计算机断层扫描(CT)因其在检测 COVID-19 感染方面的敏感性而成为大流行期间首选的成像方式。最近,大量 COVID-19 成像数据集已存入公共数据库,从而推动了 COVID-19 研究的快速发展。然而,这些数据集在 COVID-19 相关研究之外的应用尚未得到充分探索。作者认为,它们可被用于解剖学研究,以阐明解剖结构与疾病之间的联系,并研究与疾病相关的正常解剖结构的改变。因此,本研究旨在使用从 1000 多名年龄在 6 至 89 岁的伊朗 COVID-19 患者中获得的公开 CT 图像,调查胸部六种众所周知的解剖变异的流行情况(60.9%为男性,39.1%为女性)。简而言之,我们发现,在患者中,奇静脉叶、气管支气管和心支气管的存在率分别为 0.8%、0.2%和 0%。胸骨变异,包括胸骨切迹、胸骨骨、胸骨肌,分别为 9.6%、2.9%和 1.5%。我们认为,解剖学家可以从使用公开数据集作为研究材料中受益,因为这些数据集是免费获取的,而且数量丰富,尽管需要进一步研究来评估其他来自不同身体部位和成像方式的数据集的使用。放射科医生在检查肺部 CT 时也应注意这些常见的解剖变异,特别是在大流行期间这种成像方式的使用增加的情况下。

相似文献

4
Association of AI quantified COVID-19 chest CT and patient outcome.人工智能量化的COVID-19胸部CT与患者预后的关联。
Int J Comput Assist Radiol Surg. 2021 Mar;16(3):435-445. doi: 10.1007/s11548-020-02299-5. Epub 2021 Jan 23.

引用本文的文献

本文引用的文献

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验