Reddy R. Imaging diagnosis of bronchogenic carcinoma (the forgotten disease) during times of COVID-19 pandemic: Current and future perspectives. World J Clin Oncol 2021; 12(6): 437-457 [PMID: 34189068 DOI: 10.5306/wjco.v12.i6.437]
Corresponding Author of This Article
Ravikanth Reddy, MD, Academic Research, Department of Radiology, St. John's Hospital, Koramangala, Bengaluru 560034, Karnataka, India. ravikanthreddy06@gmail.com
Research Domain of This Article
Oncology
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Clin Oncol. Jun 24, 2021; 12(6): 437-457 Published online Jun 24, 2021. doi: 10.5306/wjco.v12.i6.437
Imaging diagnosis of bronchogenic carcinoma (the forgotten disease) during times of COVID-19 pandemic: Current and future perspectives
Ravikanth Reddy
Ravikanth Reddy, Department of Radiology, St. John's Hospital, Bengaluru 560034, Karnataka, India
Author contributions: Reddy R wrote the first draft of the manuscript, reviewed and edited the manuscript and approved the final version of the manuscript.
Conflict-of-interest statement: There are no conflicts of interest.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Ravikanth Reddy, MD, Academic Research, Department of Radiology, St. John's Hospital, Koramangala, Bengaluru 560034, Karnataka, India. ravikanthreddy06@gmail.com
Received: January 19, 2021 Peer-review started: January 19, 2021 First decision: April 6, 2021 Revised: April 7, 2021 Accepted: June 2, 2021 Article in press: June 2, 2021 Published online: June 24, 2021 Processing time: 153 Days and 4 Hours
Abstract
Patients with bronchogenic carcinoma comprise a high-risk group for coronavirus disease 2019 (COVID-19), pneumonia and related complications. Symptoms of COVID-19 related pulmonary syndrome may be similar to deteriorating symptoms encountered during bronchogenic carcinoma progression. These resemblances add further complexity for imaging assessment of bronchogenic carcinoma. Similarities between clinical and imaging findings can pose a major challenge to clinicians in distinguishing COVID-19 super-infection from evolving bronchogenic carcinoma, as the above-mentioned entities require very different therapeutic approaches. However, the goal of bronchogenic carcinoma management during the pandemic is to minimize the risk of exposing patients to COVID-19, whilst still managing all life-threatening events related to bronchogenic carcinoma. The current pandemic has forced all healthcare stakeholders to prioritize per value resources and reorganize therapeutic strategies for timely management of patients with COVID-19 related pulmonary syndrome. Processing of radiographic and computed tomography images by means of artificial intelligence techniques can facilitate triage of patients. Modified and newer therapeutic strategies for patients with bronchogenic carcinoma have been adopted by oncologists around the world for providing uncompromised care within the accepted standards and new guidelines.
Core Tip: Unprecedented times of a pandemic pose a major challenge in maintaining adequate balance between the risk of contracting deadly coronavirus disease 2019 (COVID-19) against the dire consequences of delaying treatment for a life-threatening malignancy. Cancer survivors and patients represent a vulnerable population for COVID-19 related pulmonary syndrome, which can further complicate respiratory and cardiovascular comorbidities they possess. Risk stratification of bronchogenic carcinoma patients and priority imaging may be applied for optimal use of resources during these uncertain times of COVID-19. Utilizing artificial intelligence and deep learning modules based on pattern recognition of image findings during this pandemic has made a lasting impact across future realms.
