Correlation between physical measurements and observer evaluations of image quality in digital chest radiography

Abstract

The aim of this paper was to investigate the relationship between the physical and subjective (observer) image quality metrics in digital chest radiography. Methods: Five digital radiography systems, four with indirect flat panel detector and one with storage phosphor-based computed radiography system, were used in the study. The physical image quality assessments were carried out using effective detective quantum efficiency (eDQE) metric and subjective performance of the digital radiography systems was evaluated in terms of inverse image quality figure (IQF inv) derived from the contrast-detail (CD) diagrams using CDRAD 2.0 phantom and CDRAD phantom analyzer software. All measurements were performed for different tube voltages (70, 81, 90, 102, 110, and 125 kVp) and polymethyl methacrylate (PMMA) phantom thicknesses. An anthropomorphic chest phantom and visual grading analysis (VGA) technique based on European image quality criteria for chest radiography were used for clinical image quality evaluation. Results: The Spearman correlation coefficients were calculated for the investigation of the correlation between physical image quality and clinical image quality. The results showed strong positive correlation between the physical and clinical image quality findings. The minimum correlation coefficient was 0.91 (p < 0.011) for IQF inv vs VGA scores and 0.92 (p < 0.009) for IeDQE vs VGA scores. Conclusions: Our results confirm that clinical image quality can be predicted with both physical assessments and contrast-detail detectability studies.

Comparison of Conventional Hand Examination on Six Optimised DR Systems

“…Yalcin et al. recently published similar results, although for a different set of DR systems and using a lung/chest phantom for the visual experiments ( 25 ) . As noted previously, there is a possibility that differences in the DR system’s image processing might cause the CDRAD Analyser software to perform differently.…”

Image feature index: A novel metric for quantifying chest radiographic image quality

“…The performance of the system has been well described by the DQE and MTF. 3 However, these are not suitable for quality control at the technician level. Computed using data from the image,IFI can be an automatic and efficient tool that enables intra-and inter-technician comparisons of image quality, if reference IFI values are established for different systems, body parts and views, and pathological conditions.…”

“…The latter includes technicians adjusting the appropriate exposure settings according to the patient's shape, size, age, pathology, etc. The performance of the system has been well described by the DQE and MTF 3 . However, these are not suitable for quality control at the technician level.…”

“…Several subjective or objective methods of measuring image quality exist, and all have their shortcomings. An objective measure of image quality is the detective quantum efficiency (DQE), 2,3 which determines the efficiency with which the signal‐to‐noise ratio (SNR) of a specific spatial frequency is transferred throughout the imaging chain 3,4 . However, DQE is more frequently used to describe the performance of the imaging components (e.g., the detector), as is the case with another measure called the modulation transfer function (MTF) 3,4 .…”

“…3,4 However, DQE is more frequently used to describe the performance of the imaging components (e.g., the detector), as is the case with another measure called the modulation transfer function (MTF). 3,4 The image quality is affected by many other factors in the imaging chain, such as the exposure settings and image processing techniques. Therefore, it is necessary to assess the image quality from the observer's perspectives.…”