Clinical Reporting of Pneumonia Chest Radiographs by Filipino Radiographers: A Diagnostic Accuracy Study
Christopher John Tangian | Sherihan Bentangan | Mosphira Abdullah | Jocel-ann Licup | Mark Alipio
Discipline: medical sciences (non-specific)
Abstract:
Pneumonia is a leading cause of morbidity and mortality,
and chest radiography remains central to diagnosis. Global
radiologist shortages have renewed interest in
radiographer reporting, yet evidence from low and middle
income countries is scarce. This diagnostic accuracy study
assessed the performance of Filipino radiographers in
reporting pneumonia chest radiographs against a
radiologist reference standard. Ten registered
radiographers from hospitals and diagnostic centers in
Iligan City interpreted a set of 30 anonymised chest
radiographs that included 10 normal and 20 abnormal
images, with pneumonia and other pathologies.
Sensitivity, specificity, and overall agreement were
calculated for all cases and for pneumonia cases alone, and
compared with radiologist readings. For all cases, mean
sensitivity was 94.49%, specificity 39.77%, and
agreement 59.67%. For pneumonia cases, mean sensitivity
was 91.18%, specificity 55.55%, and agreement 67.00%.
Sensitivity did not differ significantly from radiologists,
while specificity and agreement did. Filipino
radiographers showed strong ability to detect abnormality
but difficulty in classifying normal studies, indicating the
need for structured reporting education and formal role
development.
References:
- Afshari Mirak, S., Shahir, K. K., & George, E. (2025). The growing nationwide radiologist shortage. Radiology, 306(2), 123–131. https://doi.org/10.1148/radiol.232625
- Alipio, M. M., Pregoner, J. D. M., & Lantajo, G. M. A. (2025). Lived experiences of radiographers assigned to veterinary clinics in the Philippines: A qualitative study. Journal of Medical Imaging and Radiation Sciences, 56(4), 101901. https://doi.org/10.1016/j.jmir.2025.101901
- Alipio, M., Cuthbertson, L., & Lantajo, G. M. A. (2022). Radiographer reporting of chest radiograph in rural health unit: A potential practice in the Philippines. IMCC Journal of Science, 2(2), 15–24. https://hal.science/hal-04225065/
- Avola, D., Cinque, L., Koperski, K., Pannone, D., Puzzuoli, D., & Sangineto, E. (2022). Study on transfer learning capabilities for pneumonia classification in chest X-rays. Computer Methods and Programs in Biomedicine, 221, 106921. https://doi.org/10.1016/j.cmpb.2022.106921
- Becker, J., Kissling, L., Thieringer, F., Bae, Y. J., Gassert, F. G., & Borggrefe, J. (2022). Artificial intelligence-based detection of pneumonia in chest radiographs in clinical practice. RöFo: Fortschritte auf dem Gebiet der Röntgenstrahlen und der Bildgebenden Verfahren, 194(6), 652–660. https://doi.org/10.1055/a-1788-6173
- Brealey, S., Scally, A., Hahn, S., Thomas, N., Godfrey, C., & Coomarasamy, A. (2005). Accuracy of radiographer plain radiograph reporting in clinical practice: A meta-analysis. Clinical Radiology, 60(2), 232–241. https://doi.org/10.1016/j.crad.2004.07.012
- Clemen, I. G., Pundirogong, J., Jabbar, J., & Alipio, M. (2023). Acceptance and attitude of Muslim pregnant women on transvaginal ultrasound scan. IMCC Journal of Science, 3(1), 57–65. https://hal.science/hal-04240119/
- DeStigter, K. K., Rizzo, M., Baird, G. L., Diko, S., & Makasa, E. (2021). Optimizing integrated imaging service delivery by tier in low- and middle-income countries. Insights into Imaging, 12, 80. https://doi.org/10.1186/s13244-021-01073-8
- Frija, G., Abanades, M., Grenier, N., & the International Society of Radiology. (2021). How to improve access to medical imaging in low- and middle-income countries. European Journal of Radiology, 137, 109788. https://doi.org/10.1016/j.ejrad.2021.109788
- Hofmeister, J., Fischbach, R., Dendl, L. M., Ertl-Wagner, B., & Gassert, F. G. (2024). Validating the accuracy of deep learning for the diagnosis of pneumonia on chest X-ray. European Radiology, 34(3), 1234–1245. https://doi.org/10.1007/s00330-023-09876-5
- Li, Y., Zhang, Z., Dai, C., Dong, Q., & Badrigilan, S. (2020). Accuracy of deep learning for automated detection of pneumonia using chest X-ray images: A systematic review and meta-analysis. Computers in Biology and Medicine, 123, 103898. https://doi.org/10.1016/j.compbiomed.2020.103898
- Miranda, D., Malic, H., & Alipio, M. (2023). Student radiographers’ knowledge and attitudes towards LGBT patients in the Philippines. IMCC Journal of Science, 3(2), 8–15. https://hal.science/hal-04241886/
- Pelias, C. C., Dagatan, J. C., Daabay, M. C., & Alipio, M. (2023). Competence of student radiographers on exposure factor selection in emergency and trauma imaging. IMCC Journal of Science, 3(1), 49–56. https://hal.science/hal-04240118/
- Piper, K., Cox, S., Paterson, A., Thomas, A., Thomas, N., & Beardmore, C. (2014). Chest reporting by radiographers: Findings of an accredited postgraduate programme. Radiography, 20(2), 94–99. https://doi.org/10.1016/j.radi.2013.10.007
- Trivett, E., Geldart, S., Lockyer, A., & Woznitza, N. (2024). An NHS trust comparison of reporting radiographers and radiologists in the detection of lung cancer on chest radiographs. Radiography, 30(2), 451–458. https://doi.org/10.1016/j.radi.2023.09.007
- Usman, C., Khan, M. A., & Ahmad, M. (2025). Pneumonia disease detection using chest X-rays and deep learning. Algorithms, 18(2), 82. https://doi.org/10.3390/a18020082
- Wood, K. (2022). How is the reporting radiographer role portrayed in published studies? A scoping review. Radiography, 28(1), 215–221. https://doi.org/10.1016/j.radi.2021.05.014
- Woznitza, N., Devaraj, A., Janes, S. M., et al. (2023). Impact of radiographer immediate reporting of chest X-rays from general practice on lung cancer diagnosis. Thorax, 78(3), 310–318. https://doi.org/10.1136/thoraxjnl-2022-219210
- Woznitza, N., Piper, K., Burke, S., & Bothamley, G. (2018). Chest X-ray interpretation by radiographers is not inferior to radiologists: A multireader, multicase comparison using the JAFROC method. Academic Radiology, 25(9), 1202–1211. https://doi.org/10.1016/j.acra.2018.01.018
ISSN 3116-3017 (Online)
ISSN 3116-3009 (Print)