Evaluation of factors that affect contrast-detail in digital X-Ray and computed tomography

The central aim of this project was to develop a new methodology of evaluation and optimisation of image quality based on low contrast-detail (LCD) detectability performance of computed tomography (CT). This method is well established in digital radiography however similar tool of image evaluation and quality optimisation for CT images are not available. In comparison with other image evaluation methods in digital radiography, the tool of LCD detectability performance—particularly the automated approach—is a good choice for image quality optimisation. This method helps to determine appropriate exposure factors to provide optimum image quality while maintaining a lower radiation dose to patients. This method is a straightforward and direct way to assess image quality as it provides quantitative evaluations of low contrast and small detail measurements of medical images. The subjectivity of image evaluation methods based on human observers is avoided via automated scoring software that is utilised in automated approach of LCD detectability performance. The trade-offs between perceived image quality, diagnosis efficacy and exposure dose can be determined by LCD detectability measurements. A newly designed LCD CT (CDCT) phantom was manufactured and dedicated software was developed with the cooperation of Artinis Medical Systems (Zetten, The Netherlands) for the new evaluation method of LCD detectability. The specifications of the phantom design were optimised based on the standard recommendations of phantom manufacturing and the requirements of the proposed new evaluation methodology. The CT inverse image quality figure (CTIQFinv) was determined as a measure of LCD detectability performance of CT images. An equation was developed and implemented in the software to calculate and objectively measure CTIQFinv values. The new proposed method of LCD detectability performance was validated by evaluating the influences of exposure factors kVp and mAs, slice thicknesses and object location on image quality in terms of CTIQFinv values based on software and radiographers’ scoring results. The results showed that the new evaluation methodology-based CDCT phantom, along with the automated measurement of CTIQFinv value, had generally shown to be consistent with a prior knowledge of image quality in relation to change of mAs, kVp and slice thickness settings. This work showed that the CDCT phantom and the measurement of CTIQFinv values can provide a measure of CT image quality in terms of LCD detectability performance. This method has a promising role for CT image evaluation and optimisation, and has the potential to effectively evaluate the effects of protocol parameters on image quality of different CT scanners and systems. Future changes to the phantom design and/or software is required to overcome some of the current limitation

Development and validation of a visual grading scale for assessing image quality of AP pelvis radiographic images

OBJECTIVE: Apply psychometric theory to develop and validate a visual grading scale for assessing visual perception of AP pelvis digital image quality. METHODS: Psychometric theory was used to guide scale development. Seven phantom and 7 cadaver images of visually and objectively predetermined quality were used to help assess scale reliability and validity. 151 volunteers scored phantom images; 184 volunteers scored cadaver images. Factor analysis and Cronbach’s alpha were used to assess scale validity and reliability. RESULTS: A 24 item scale was produced. Aggregated mean volunteer scores for each image correlated with the rank order of the visually and objectively predetermined image qualities. Scale items had good inter-item correlation (≥0.2) and high factor loadings (≥0.3). Cronbach's alpha (reliability) revealed that the scale has acceptable levels of internal reliability for both phantom and cadaver images (α= 0.8 and 0.9, respectively). Factor analysis suggested the scale is multidimensional (assessing multiple quality themes). CONCLUSION: This study represents the first full development and validation of a visual image quality scale using psychometric theory. It is likely that this scale will have clinical, training and research applications. ADVANCES IN KNOWLEDGE: This article presents data to create and validate visual grading scales for radiographic examinations. The visual grading scale, for AP pelvis examinations, can act as a validated tool for future research, teaching and clinical evaluations of image quality

Image quality and radiation dose in planar imaging — Image quality figure of merits from the CDRAD phantom

Purpose: A contrast-detail phantom such as CDRAD is frequently used for quality assurance, optimization of image quality, and several other purposes. However, it is often used without considering the uncertainty of the results. The aim of this study was to assess two figure of merits (FOM) originating from CDRAD regarding the variations of the FOMs by dose utilized to create the x-ray image. The probability of overlapping (assessing an image acquired at a lower dose as better than an image acquired at a higher dose) was determined. Methods: The CDRAD phantom located underneath 12, 20, and 26cm PMMA was imaged 16 times at five dose levels using an x-ray system with a flat-panel detector. All images were analyzed by CDRAD Analyser, version 1.1, which calculated the FOM inverse image quality figure (IQFinv) and gave contrast detail curves for each image. Inherent properties of the CDRAD phantom were used to derive a new FOM h, which describes the size of the hole with the same diameter and depth that is just visible. Data were analyzed using heteroscedastic regression of mean and variance by dose. To ease interpretation, probabilities for overlaps were calculated assuming normal distribution, with associated bootstrap confidence intervals. Results: The proportion of total variability in IQFinv, explained by the dose (R2), was 91%, 85%, and 93% for 12, 20, and 26cm PMMA. Corresponding results for h were 91%, 89%, and 95%. The overlap probability for different mAs levels was 1% for 0.8 vs 1.2mAs, 5% for 1.2 vs 1.6mAs, 10% for 1.6 vs 2.0mAs, and 10% for 2.0mAs vs 2.5mAs for 12cm PMMA. For 20cm PMMA, it was 0.5% for 10 vs 16mAs, 13% for 16 vs 20mAs, 14% for 20 vs 25mAs, and 14% for 25 vs 32mAs. For 26cm PMMA, the probability varied from 0% to 6% for various mAs levels. Even though the estimated probability for overlap was small, the 95% confidence interval (CI) showed relatively large uncertainties. For 12cm PMMA, the associated CI for 0.8 vs 1.2mAs was 0.1–3.2%, and the CI for 1.2 vs 1.6mAs was 2.1–7.8%. Conclusions: Inverse image quality figure and h are about equally related to dose level. The FOM h, which describes the size of a hole that should be seen in the image, may be a more intuitive FOM than IQFinv. However, considering the probabilities for overlap and their confidence intervals, the FOMs deduced from the CDRAD phantom are not sensitive to dose. Hence, CDRAD may not be an optimal phantom to differentiate between images acquired at different dose levels. © 2019 The Authors. Journal of Applied Clinical Medical Physics published by Wiley Periodicals, Inc. on behalf of American Association of Physicists in Medicine