AI Article Synopsis
- The spread of coronavirus has overwhelmed healthcare systems, leading to the need for effective diagnostic methods; while RT-PCR is standard, it is slow and not always sensitive, spurring interest in CT scans for quicker screening.
- A study of 188 confirmed COVID-19 patients used high-resolution chest CT to identify key findings, aiming to integrate these with AI tools for better predictive diagnostics of the disease.
- Results indicated that common CT findings included ground glass opacities and specific patterns that help evaluate disease severity, supporting the use of chest CT as a reliable method for assessing COVID-19 progression.
Article Abstract
Background And Objective: The spread of coronavirus has been challenging for the healthcare system's proper management and diagnosis during the rapid spread and control of the infection. Real-time reverse transcription-polymerase chain reaction (RT-PCR), though considered the standard testing measure, has low sensitivity and is time-consuming, which restricts the fast screening of individuals. Therefore, computer tomography (CT) is used to complement the traditional approaches and provide fast and effective screening over other diagnostic methods. This work aims to appraise the importance of chest CT findings of COVID-19 and post-COVID in the diagnosis and prognosis of infected patients and to explore the ways and means to integrate CT findings for the development of advanced Artificial Intelligence (AI) tool-based predictive diagnostic techniques.
Methods: The retrospective study includes a 188 patient database with COVID-19 infection confirmed by RT-PCR testing, including post-COVID patients. Patients underwent chest high-resolution computer tomography (HRCT), where the images were evaluated for common COVID-19 findings and involvement of the lung and its lobes based on the coverage region. The radiological modalities analyzed in this study may help the researchers in generating a predictive model based on AI tools for further classification with a high degree of reliability.
Results: Mild to moderate ground glass opacities (GGO) with or without consolidation, crazy paving patterns, and halo signs were common COVID-19 related findings. A CT score is assigned to every patient based on the severity of lung lobe involvement.
Conclusion: Typical multifocal, bilateral, and peripheral distributions of GGO are the main characteristics related to COVID-19 pneumonia. Chest HRCT can be considered a standard method for timely and efficient assessment of disease progression and management severity. With its fusion with AI tools, chest HRCT can be used as a one-stop platform for radiological investigation and automated diagnosis system.
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| http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9576693 | PMC |
| http://dx.doi.org/10.1016/j.bspc.2022.104297 | DOI Listing |
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