Original Research

Using Artificial Intelligence for COVID-19 Chest X-ray Diagnosis

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References

Emerging diseases such as COVID-19 present numerous challenges to HCPs, governments, and businesses, as well as to individual members of society. As evidenced with COVID-19, the time from first recognition of an emerging pathogen to the development of methods for reliable diagnosis and treatment can be months, even with a concerted international effort. The gold standard for diagnosis of COVID-19 is by reverse transcriptase PCR (RT-PCR) technologies; however, early RT-PCR testing produced less than optimal results. 20-22 Even after the development of reliable tests for detection, making test kits readily available to health care providers on an adequate scale presents an additional challenge as evident with COVID-19.

Use of X-ray vs Computed Tomography

The lack of availability of diagnostic RTPCR with COVID-19 initially placed increased reliability on presumptive diagnoses via imaging in some situations. 23 Most of the literature evaluating radiographs of patients with COVID-19 focuses on chest computed tomography (CT) findings, with initial results suggesting CT was more accurate than early RT-PCR methodologies.21,22,24 The Radiological Society of North America Expert consensus statement on chest CT for COVID-19 states that CT findings can even precede positivity on RT-PCR in some cases. 22 However, currently it does not recommend the use of CT scanning as a screening tool. Furthermore, the actual sensitivity and specificity of CT interpretation by radiologists for COVID-19 are unknown. 22

Characteristic CT findings include ground-glass opacities (GGOs) and consolidation most commonly in the lung periphery, though a diffuse distribution was found in a minority of patients. 21,23,25-27 Lomoro and colleagues recently summarized the CT findings from several reports that described abnormalities as most often bilateral and peripheral, subpleural, and affecting the lower lobes.26 Not surprisingly, CT appears more sensitive at detecting changes with COVID-19 than does CXR, with reports that a minority of patients exhibited CT changes before changes were visible on CXR. 23,26

We focused our study on the potential of AI in the examination of CXRs in patients with COVID-19, as there are several limitations to the routine use of CT scans with conditions such as COVID-19. Aside from the more considerable time required to obtain CTs, there are issues with contamination of CT suites, sometimes requiring a dedicated COVID-19 CT scanner. 23,28 The time constraints of decontamination or limited utilization of CT suites can delay or disrupt services for patients with and without COVID-19. Because of these factors, CXR may be a better resource to minimize the risk of infection to other patients. Also, accurate assessment of abnormalities on CXR for COVID-19 may identify patients in whom the CXR was performed for other purposes. 23 CXR is more readily available than CT, especially in more remote or underdeveloped areas. 28 Finally, as with CT, CXR abnormalities are reported to have appeared before RT-PCR tests became positive for a minority of patients. 23

CXR findings described in patients with COVID-19 are similar to those of CT and include GGOs, consolidation, and hazy increased opacities. 23,25,26,28,29 Like CT, the majority of patients who received CXR demonstrated greater involvement in the lower zones and peripherally. 23,25,26,28,29 Most patients showed bilateral involvement. However, while these findings are common in patients with COVID-19, they are not specific and can be seen in other conditions, such as other viral pneumonia, bacterial pneumonia, injury from drug toxicity, inhalation injury, connective tissue disease, and idiopathic conditions.

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