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Imaging Diagnostics and Pathology in SARS-CoV-2-Related Diseases

机译:在SARS-COV-2相关疾病中的成像诊断和病理学

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In December 2019, physicians reported numerous patients showing pneumonia of unknown origin in the Chinese region of Wuhan. Following the spreading of the infection over the world, The World Health Organization (WHO) on 11 March 2020 declared the novel severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) outbreak a global pandemic. The scientific community is exerting an extraordinary effort to elucidate all aspects related to SARS-CoV-2, such as the structure, ultrastructure, invasion mechanisms, replication mechanisms, or drugs for treatment, mainly through in vitro studies. Thus, the clinical in vivo data can provide a test bench for new discoveries in the field of SARS-CoV-2, finding new solutions to fight the current pandemic. During this dramatic situation, the normal scientific protocols for the development of new diagnostic procedures or drugs are frequently not completely applied in order to speed up these processes. In this context, interdisciplinarity is fundamental. Specifically, a great contribution can be provided by the association and interpretation of data derived from medical disciplines based on the study of images, such as radiology, nuclear medicine, and pathology. Therefore, here, we highlighted the most recent histopathological and imaging data concerning the SARS-CoV-2 infection in lung and other human organs such as the kidney, heart, and vascular system. In addition, we evaluated the possible matches among data of radiology, nuclear medicine, and pathology departments in order to support the intense scientific work to address the SARS-CoV-2 pandemic. In this regard, the development of artificial intelligence algorithms that are capable of correlating these clinical data with the new scientific discoveries concerning SARS-CoV-2 might be the keystone to get out of the pandemic.
机译:2019年12月,医生报告了众多患者在武汉中国地区显示出未知起源的肺炎。在世界上感染的传播之后,世界卫生组织(世卫组织)于2020年3月11日宣布宣布新的严重急性呼吸综合征Coronavirus-2(SARS-COV-2)爆发了全球大流行。科学界正在努力阐明阐明与SARS-COV-2相关的各个方面,例如结构,超微结构,侵袭机制,复制机制或用于治疗的药物,主要是通过体外研究。因此,体内数据中的临床可以为SARS-COV-2领域的新发现提供测试台,找到新的解决方案,以对抗目前大流行。在这种戏剧性的情况下,通常不完全申请开发新的诊断程序或药物的正常科学协议,以便加快这些过程。在这种情况下,跨学科性是基本的。具体地,基于对图像的研究,例如放射学,核医学和病理学,可以通过医学学科的数据协会和解释提供巨大贡献。因此,在这里,我们突出了肺和其他人器官中SARS-COV-2感染的最新组织病理学和成像数据,例如肾脏,心脏和血管系统。此外,我们还评估了放射学,核医学和病理部门数据的可能匹配,以支持强烈的科学工作来解决SARS-COV-2大流行。在这方面,能够将这些临床数据与关于SARS-COV-2的新科学发现相关联的人工智能算法的发展可能是摆脱大流行的梯形石。

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