Comparison of Digital and Film Radiography Image Quality in Chest Imaging

Thesis Abstract

The quality of radiographic images plays a critical role in the accurate diagnosis of chest pathologies, yet the comparative efficacy of digital and film radiography systems remains inadequately documented, particularly in low-resource clinical settings where transition to digital technology is ongoing. This study addresses the need to empirically evaluate and compare the image quality produced by digital radiography (DR) and traditional film radiography (FR) in chest imaging, with a focus on image clarity, contrast resolution, and diagnostic accuracy. The overarching aim is to determine which modality offers superior image quality to support clinical decision-making. The specific objectives are to quantify and compare the objective image quality parameters of DR and FR through radiographic analysis, to assess the subjective diagnostic quality as perceived by radiologists and clinicians, and to evaluate the relationship between image quality metrics and diagnostic confidence. Additionally, the study seeks to explore potential factors influencing image quality differences such as patient positioning, exposure settings, and processing techniques. Employing a comparative cross-sectional research design, this investigation recruited a sample of 150 adult patients undergoing routine chest radiography at a tertiary healthcare facility. The sample was stratified equally into two groups based on the imaging modality 75 patients imaged with digital radiography and 75 with film radiography. Data collection comprised acquiring standardized chest radiographs while maintaining consistent exposure parameters where feasible. Objective image quality was evaluated using quantitative metrics such as signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and spatial resolution through digital image analysis software, calibrated for the study. Subjective assessment involved a panel of five experienced radiologists who independently rated image quality on a Likert scale, considering factors like sharpness, contrast, and overall diagnostic utility. Data analysis entailed descriptive statistics to summarize objective quality metrics and subjective ratings, followed by inferential statistics including independent samples t-tests and analysis of variance (ANOVA) to identify statistically significant differences between the two modalities. Correlation analyses were conducted to explore relationships between objective metrics and radiologist ratings, while regression analysis examined predictors of perceived image quality. The theoretical framework underpinning this study incorporates the Signal Detection Theory to understand diagnostic accuracy relative to image quality, complemented by the Functional Image Quality Model, which conceptualizes image parameters as determinants of clinical interpretability. The anticipated findings include statistically significant differences favoring digital radiography in both objective measures such as higher SNR and CNR values, and subjective assessments of image clarity and diagnostic confidence. It is expected that digital images will demonstrate enhanced spatial resolution and contrast, leading to improved diagnostic accuracy. These findings will contribute novel insights into the empirical performance differences between the two imaging modalities in a clinical context often characterized by resource constraints. This research advances knowledge by providing a comprehensive comparative evaluation grounded in quantitative and qualitative analyses, informing radiographers, radiologists, and healthcare administrators about the relative advantages of digital versus film radiography. It is expected to support evidence-based decisions regarding technological investments and operational practices in chest radiology. The study concludes that digital radiography offers superior image quality, which may translate into higher diagnostic accuracy and clinical utility. Recommendations include adopting digital systems where feasible to improve patient outcomes, with considerations for optimizing imaging protocols to maximize the benefits of digital technology. Further research is suggested to explore long-term cost-effectiveness and the integration of advanced digital enhancement techniques to further enhance image quality and diagnostic performance.