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

• Published in: Journal of applied clinical medical physics Vol. 20; no. 7; pp. 151 - 159
• Main Authors: Konst, Bente, Weedon‐Fekjær, Harald, Båth, Magnus
• Format: Journal Article
• Language: English
• Published: United States John Wiley & Sons, Inc 01.07.2019; John Wiley and Sons Inc
• Subjects: Algorithms; CD-curve; contrast detail phantom; figure of merit; Humans; IQF; Medical Image Processing; Medical Imaging; Medicinsk bildbehandling; Noise; Phantoms, Imaging; planar imaging; precision; Quality control; Radiation Dosage; Radiographic Image Enhancement - instrumentation; Radiographic Image Interpretation, Computer-Assisted - methods; Radiographic Image Interpretation, Computer-Assisted - standards; Radiologi och bildbehandling; Radiology, Nuclear Medicine and Medical Imaging; Netherlands; CD-curve; contrast detail phantom; figure of merit; planar imaging; precision; IQF
• ISSN: 1526-9914; 1526-9914
• DOI: 10.1002/acm2.12649

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 26 cm 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 26 cm PMMA. Corresponding results for h were 91%, 89%, and 95%. The overlap probability for different mAs levels was 1% for 0.8 vs 1.2 mAs, 5% for 1.2 vs 1.6 mAs, 10% for 1.6 vs 2.0 mAs, and 10% for 2.0 mAs vs 2.5 mAs for 12 cm PMMA. For 20 cm PMMA, it was 0.5% for 10 vs 16 mAs, 13% for 16 vs 20 mAs, 14% for 20 vs 25 mAs, and 14% for 25 vs 32 mAs. For 26 cm 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 12 cm PMMA, the associated CI for 0.8 vs 1.2 mAs was 0.1–3.2%, and the CI for 1.2 vs 1.6 mAs 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.