Comparison of Digital and Conventional Radiography Image Quality in Chest Imaging

Thesis Abstract

The quality of chest radiographs is a critical determinant of diagnostic accuracy and patient management effectiveness, with the transition from conventional to digital radiography presenting both opportunities and challenges in image quality assessment. This study aims to compare the image quality between digital and conventional chest radiography modalities to establish their relative diagnostic efficacy. The specific objectives include evaluating radiographic resolution, contrast, noise levels, and spatial accuracy in both modalities, as well as examining operator variability and workflow efficiency. The research adopts a cross-sectional comparative design, with the theoretical framework grounded in the Systems Theory, which emphasizes the interrelated components influencing image quality, and the Image Quality Model that delineates technical factors affecting radiographic clarity. The study population comprises 200 adult patients referred for routine chest radiography at a tertiary healthcare facility, with stratified random sampling employed to select participants equally divided between digital and conventional imaging groups. Data collection involves capturing chest radiographs following standardized positioning protocols using calibrated imaging equipment, with image quality assessed independently by three experienced radiologists blinded to the modality. The evaluative criteria include objective measures such as spatial resolution assessed via modulation transfer function (MTF), contrast-to-noise ratio (CNR), and subjective assessments based on a validated scoring system. Instrument validity is ensured through calibration of imaging devices and training of radiologists in scoring criteria, while reliability is confirmed through inter-rater agreement analysis using Cohen’s kappa coefficient, aiming for a minimum kappa value of 0.8. Data analysis involves descriptive statistics to summarize image quality parameters, followed by inferential statistics—most notably, ANOVA and paired t-tests—to compare means across the two modalities. Regression analysis explores predictors of image quality, including equipment parameters and operator experience. Additionally, Bland-Altman plots are utilized to assess agreement between subjective scores, while workflow efficiency is analyzed through time-motion analysis. Ethical considerations encompass obtaining institutional approval, securing informed consent from participants, and ensuring data confidentiality throughout the study. Anticipated findings suggest that digital radiography will demonstrate statistically significant improvements in spatial resolution, contrast, and noise reduction compared to conventional radiography, with digital images also exhibiting enhanced lesion detectability and lower inter-operator variability. The study expects to reveal that the transition to digital systems positively influences image quality parameters aligned with the Image Quality Model, thereby supporting their superior diagnostic performance. The research will contribute novel localized data to the ongoing discourse on radiographic quality assurance, addressing gaps in comparative analyses within similar healthcare settings and highlighting practical implications for radiographic protocol optimization. The main conclusion underscores that digital chest radiography offers substantial advantages over conventional methods in image quality, which are vital for accurate diagnosis. Recommendations include investing in advanced digital imaging equipment, implementing standardized training programs for radiographers to maximize image quality, and adopting continuous quality improvement initiatives. The study further advocates for integrating objective image quality metrics into routine quality assurance protocols and encourages future research exploring the impact of digital radiography on clinical outcomes and cost-effectiveness. Ultimately, this research aims to inform policy and clinical practice by providing empirically grounded insights into the benefits and limitations of digital versus conventional radiographic techniques in chest imaging, thereby advancing diagnostic standards and patient care quality.