tetano
Editor, Senior Moderator
Int J Mol Sci
. 2020 Sep 22;21(18):E6960.
doi: 10.3390/ijms21186960.
Imaging Diagnostics and Pathology in SARS-CoV-2-Related Diseases
Manuel Scimeca[SUP] 1 2 3 [/SUP], Nicoletta Urbano[SUP] 4 [/SUP], Rita Bonfiglio[SUP] 5 6 [/SUP], Manuela Montanaro[SUP] 5 [/SUP], Elena Bonanno[SUP] 5 7 [/SUP], Orazio Schillaci[SUP] 1 8 [/SUP], Alessandro Mauriello[SUP] 5 9 [/SUP]
Affiliations
Abstract
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.
Keywords: SARS-CoV-2; artificial intelligence; imaging diagnostic; pandemic; pathology.
. 2020 Sep 22;21(18):E6960.
doi: 10.3390/ijms21186960.
Imaging Diagnostics and Pathology in SARS-CoV-2-Related Diseases
Manuel Scimeca[SUP] 1 2 3 [/SUP], Nicoletta Urbano[SUP] 4 [/SUP], Rita Bonfiglio[SUP] 5 6 [/SUP], Manuela Montanaro[SUP] 5 [/SUP], Elena Bonanno[SUP] 5 7 [/SUP], Orazio Schillaci[SUP] 1 8 [/SUP], Alessandro Mauriello[SUP] 5 9 [/SUP]
Affiliations
- PMID: 32971906
- DOI: 10.3390/ijms21186960
Abstract
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.
Keywords: SARS-CoV-2; artificial intelligence; imaging diagnostic; pandemic; pathology.