TY - JOUR
T1 - Vascular Implications of COVID-19
T2 - Role of Radiological Imaging, Artificial Intelligence, and Tissue Characterization: A Special Report
AU - Khanna, Narendra N.
AU - Maindarkar, Mahesh
AU - Puvvula, Anudeep
AU - Paul, Sudip
AU - Bhagawati, Mrinalini
AU - Ahluwalia, Puneet
AU - Ruzsa, Zoltan
AU - Sharma, Aditya
AU - Munjral, Smiksha
AU - Kolluri, Raghu
AU - Krishnan, Padukone R.
AU - Singh, Inder M.
AU - Laird, John R.
AU - Fatemi, Mostafa
AU - Alizad, Azra
AU - Dhanjil, Surinder K.
AU - Saba, Luca
AU - Balestrieri, Antonella
AU - Faa, Gavino
AU - Paraskevas, Kosmas I.
AU - Misra, Durga Prasanna
AU - Agarwal, Vikas
AU - Sharma, Aman
AU - Teji, Jagjit
AU - Al-Maini, Mustafa
AU - Nicolaides, Andrew
AU - Rathore, Vijay
AU - Naidu, Subbaram
AU - Liblik, Kiera
AU - Johri, Amer M.
AU - Turk, Monika
AU - Sobel, David W.
AU - Pareek, Gyan
AU - Miner, Martin
AU - Viskovic, Klaudija
AU - Tsoulfas, George
AU - Protogerou, Athanasios D.
AU - Mavrogeni, Sophie
AU - Kitas, George D.
AU - Fouda, Mostafa M.
AU - Kalra, Manudeep K.
AU - Suri, Jasjit S.
N1 - Publisher Copyright:
© 2022 by the authors.
PY - 2022/8
Y1 - 2022/8
N2 - The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and carotid vessels due to SARS-CoV-2. This special report addresses an important gap in the literature in understanding (i) the pathophysiology of vascular damage and the role of medical imaging in the visualization of the damage caused by SARS-CoV-2, and (ii) further understanding the severity of COVID-19 using artificial intelligence (AI)-based tissue characterization (TC). PRISMA was used to select 296 studies for AI-based TC. Radiological imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound were selected for imaging of the vasculature infected by COVID-19. Four kinds of hypotheses are presented for showing the vascular damage in radiological images due to COVID-19. Three kinds of AI models, namely, machine learning, deep learning, and transfer learning, are used for TC. Further, the study presents recommendations for improving AI-based architectures for vascular studies. We conclude that the process of vascular damage due to COVID-19 has similarities across vessel types, even though it results in multi-organ dysfunction. Although the mortality rate is ~2% of those infected, the long-term effect of COVID-19 needs monitoring to avoid deaths. AI seems to be penetrating the health care industry at warp speed, and we expect to see an emerging role in patient care, reduce the mortality and morbidity rate.
AB - The SARS-CoV-2 virus has caused a pandemic, infecting nearly 80 million people worldwide, with mortality exceeding six million. The average survival span is just 14 days from the time the symptoms become aggressive. The present study delineates the deep-driven vascular damage in the pulmonary, renal, coronary, and carotid vessels due to SARS-CoV-2. This special report addresses an important gap in the literature in understanding (i) the pathophysiology of vascular damage and the role of medical imaging in the visualization of the damage caused by SARS-CoV-2, and (ii) further understanding the severity of COVID-19 using artificial intelligence (AI)-based tissue characterization (TC). PRISMA was used to select 296 studies for AI-based TC. Radiological imaging techniques such as magnetic resonance imaging (MRI), computed tomography (CT), and ultrasound were selected for imaging of the vasculature infected by COVID-19. Four kinds of hypotheses are presented for showing the vascular damage in radiological images due to COVID-19. Three kinds of AI models, namely, machine learning, deep learning, and transfer learning, are used for TC. Further, the study presents recommendations for improving AI-based architectures for vascular studies. We conclude that the process of vascular damage due to COVID-19 has similarities across vessel types, even though it results in multi-organ dysfunction. Although the mortality rate is ~2% of those infected, the long-term effect of COVID-19 needs monitoring to avoid deaths. AI seems to be penetrating the health care industry at warp speed, and we expect to see an emerging role in patient care, reduce the mortality and morbidity rate.
KW - COVID-19
KW - artificial intelligence
KW - carotid
KW - coronary
KW - coronavirus
KW - pulmonary
KW - renal
KW - vascular damage
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U2 - 10.3390/jcdd9080268
DO - 10.3390/jcdd9080268
M3 - Review article
AN - SCOPUS:85136726310
SN - 2308-3425
VL - 9
JO - Journal of Cardiovascular Development and Disease
JF - Journal of Cardiovascular Development and Disease
IS - 8
M1 - 268
ER -