Abstract
Computed tomography (CT) quality control (QC) is regularly performed with standard phantoms, to bar faulty equipment from medical use. Its accuracy may be improved by replacing qualitative methods based on good visual distinction with pixel value-based quantitative methods. We hypothesized that statistical texture analysis (TA) that covers the entire phantom image would be a more appropriate tool. Therefore, our study devised a novel QC method based on the TA for contrast resolution (CR) and spatial resolution (SR) and proposed new, quantitative CT QC criteria. TA of CR and SR images on an American Association of Physicists in Medicine (AAPM) CT Performance Phantom were performed with nine CT scanner models. Six texture descriptors derived from first-order statistics of grayscale image histograms were analyzed. Principal component analysis was used to reveal descriptors with high utility. For CR evaluation, contrast and softness were the most accurate descriptors. For SR evaluation, contrast, softness, and skewness were the most useful descriptors. We propose the following ranges: contrast for CR, 29.5 ± 15%, for SR, 29 ± 10%; softness for CR, <0.015, for SR, <0.014; and skewness for SR, >−1.85. Our novel TA method may improve the assessment of CR and SR of AAPM phantom images.
Highlights
Published: 16 April 2021Computed tomography (CT) is a computerized imaging technique in which manyX-ray measurements of a body are made, with an X-ray tube usually rotating around the patient during the CT scan [1,2]
The contrast medium concentrations yielding the lowest difference in contrast for all CT scanners were 0.015% or 0.02%
Based on the rotated component matrix, the contrast (0.871), and softness (0.847) indices were determined as suitable indices to evaluate the contrast resolution (CR)
Summary
X-ray measurements of a body are made, with an X-ray tube usually rotating around the patient during the CT scan [1,2]. These signals are computationally processed and, cross-sectional images of the body are reconstructed. In the past ten years, state of-the-art CT detectors and sources and several techniques, such as automatic exposure control and iterative reconstruction, have been launched; these can provide a higher image quality by using a lower radiation dose [5,6,7,8,9,10]. It is imperative that CT scanners are properly managed and quality control (QC) is accurately performed [13,14,15,16]
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