Optimizing chest X-rays as a leading diagnostic modality for handling COVID-19: a diagnostic study

Recent studies have highlighted that chest CT scans are crucial for accurately diagnosing COVID-19. However, in rural areas of Indonesia, people may have difficulty assessing CT scans, leading to increased undetected cases. To address this issue, we investigated whether chest X-rays (CXR) could replace CT scans in diagnosing COVID-19 patients. A diagnostic cross-sectional-based study was conducted at Fatmawati General Hospital from January to September 2021. The study included suspected COVID-19 patients in isolation wards and ICU who were over 18, with or without comorbidities, and had complete clinical data and laboratory tests. We analyzed imaging data through reverse transcription-polymerase chain reaction (RT-PCR) tests, CXR, and chest CT scans. This study enrolled 150 eligible patients. With RT-PCR as the gold standard, we found that CXR had a sensitivity of 86.6% (95% CI: 78.9-92.3%) and chest CT scan had a sensitivity of 91.1% (95% CI: 84.2-95.6%). Similar performance was observed when detecting ground glass opacities (GGO), bilateral laterobasal, and influenza-like syndrome and dyspnea (ILI) between CXR and CT scans. Receiver operating characteristic (ROC) curves demonstrated that CXR is comparable to CT scan, especially in ground glass opacity (GGO) and consolidation (AUC=0.72; 95% CI: 0.61-0.83 and AUC=0.710; 95% CI: 0.64-0.78). The proposed CXR method can be a reliable primary imaging tool for diagnosing COVID-19 by considering ILI. However, chest CT scans remain the most effective diagnostic method for COVID-19. These findings may be useful for the utilization of CXR for diagnosing COVID-19 in areas with limited access to CT scans.

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Publication Details

Journal
International Journal of Public Health Science (IJPHS)
Published
2025-03-12
DOI
https://doi.org/10.11591/ijphs.v14i2.24653
Primary Topic
COVID-19 diagnosis using AI
Type
article
Field-Weighted Citation Impact
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article

Optimizing chest X-rays as a leading diagnostic modality for handling COVID-19: a diagnostic study

Budhi Antariksa, Nurhayati Adnan Prihartono, Helda Helda, Utami Purbasari et al.
International Journal of Public Health Science (IJPHS)
COVID-19 diagnosis using AI
article

Optimizing chest X-rays as a leading diagnostic modality for handling COVID-19: a diagnostic study

Budhi Antariksa, Nurhayati Adnan Prihartono, Helda Helda, Utami Purbasari, Fatira Ratri Audita
article en

Abstract

Recent studies have highlighted that chest CT scans are crucial for accurately diagnosing COVID-19. However, in rural areas of Indonesia, people may have difficulty assessing CT scans, leading to increased undetected cases. To address this issue, we investigated whether chest X-rays (CXR) could replace CT scans in diagnosing COVID-19 patients. A diagnostic cross-sectional-based study was conducted at Fatmawati General Hospital from January to September 2021. The study included suspected COVID-19 patients in isolation wards and ICU who were over 18, with or without comorbidities, and had complete clinical data and laboratory tests. We analyzed imaging data through reverse transcription-polymerase chain reaction (RT-PCR) tests, CXR, and chest CT scans. This study enrolled 150 eligible patients. With RT-PCR as the gold standard, we found that CXR had a sensitivity of 86.6% (95% CI: 78.9-92.3%) and chest CT scan had a sensitivity of 91.1% (95% CI: 84.2-95.6%). Similar performance was observed when detecting ground glass opacities (GGO), bilateral laterobasal, and influenza-like syndrome and dyspnea (ILI) between CXR and CT scans. Receiver operating characteristic (ROC) curves demonstrated that CXR is comparable to CT scan, especially in ground glass opacity (GGO) and consolidation (AUC=0.72; 95% CI: 0.61-0.83 and AUC=0.710; 95% CI: 0.64-0.78). The proposed CXR method can be a reliable primary imaging tool for diagnosing COVID-19 by considering ILI. However, chest CT scans remain the most effective diagnostic method for COVID-19. These findings may be useful for the utilization of CXR for diagnosing COVID-19 in areas with limited access to CT scans.

International Journal of Public Health Science (IJPHS)Vol. 14(2)
University of Indonesia (ID), Fatmawati Hospital (ID)
Openalex Percentile: Top 93%
COVID-19 diagnosis using AI
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