Artificial intelligence to codify lung CT in Covid-19 patients
Artificial intelligence to codify lung CT in Covid-19 patients
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DOI：
10.1007/s11547-020-01195-x
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发表时间：
2020-05-04
影响因子：
8.9
通讯作者：
Reginelli, Alfonso
中科院分区：
文献类型：
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作者：
Belfiore, Maria Paola;Urraro, Fabrizio;Reginelli, Alfonso
严重急性呼吸系统综合征冠状病毒2（SARS-CoV-2）的传播已经达到大流行的程度，在几周内影响到100多个国家。需要采取全球对策，使全世界的卫生系统做好准备。新冠肺炎可以通过胸部X光和计算机断层扫描（CT）诊断。无症状患者也可能有肺部病变的成像。疑似新冠肺炎患者的CT检查涉及使用高分辨率技术（HRCT）。人工智能（AI）软件已被用于促进CT诊断。人工智能软件必须是有用的，将疾病分类为不同的严重程度，将根据主观考虑编写的结构化报告与病变程度的定量客观评估相结合。在本文中，我们为放射科医生提供了一个良好工具的示例（Thoracic VCAR软件，GE Healthcare，意大利），用于Covid-19诊断（Pan等人，放射学，2020年。10.1148/radio.2020200370）。Thoracic VCAR提供肺部受累的定量测量。Thoracic VCAR可以生成清晰、快速和简洁的报告，将重要的医疗信息传达给转诊医生。在后处理阶段，软件在比色图的帮助下识别毛玻璃并将其与实变区分开来，并将其量化为相对于健康软组织的百分比。因此，AI软件可以准确计算每个区域的体积。因此，请记住，CT在识别病变方面具有很高的诊断灵敏度，但对Covid-19没有特异性，与其他传染性病毒性疾病相似，因此必须有一个人工智能软件，可以客观评价通气肺实质与受影响肺实质相比的百分比。
The spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has already assumed pandemic proportions, affecting over 100 countries in few weeks. A global response is needed to prepare health systems worldwide. Covid-19 can be diagnosed both on chest X-ray and on computed tomography (CT). Asymptomatic patients may also have lung lesions on imaging. CT investigation in patients with suspicion Covid-19 pneumonia involves the use of the high-resolution technique (HRCT). Artificial intelligence (AI) software has been employed to facilitate CT diagnosis. AI software must be useful categorizing the disease into different severities, integrating the structured report, prepared according to subjective considerations, with quantitative, objective assessments of the extent of the lesions. In this communication, we present an example of a good tool for the radiologist (Thoracic VCAR software, GE Healthcare, Italy) in Covid-19 diagnosis (Pan et al. in Radiology, 2020. 10.1148/radiol.2020200370). Thoracic VCAR offers quantitative measurements of the lung involvement. Thoracic VCAR can generate a clear, fast and concise report that communicates vital medical information to referring physicians. In the post-processing phase, software, thanks to the help of a colorimetric map, recognizes the ground glass and differentiates it from consolidation and quantifies them as a percentage with respect to the healthy parenchyma. AI software therefore allows to accurately calculate the volume of each of these areas. Therefore, keeping in mind that CT has high diagnostic sensitivity in identifying lesions, but not specific for Covid-19 and similar to other infectious viral diseases, it is mandatory to have an AI software that expresses objective evaluations of the percentage of ventilated lung parenchyma compared to the affected one.