Dataset Information

Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom.

ABSTRACT: We studied the reliability of radiomic features on abdominal computed tomography (CT) images reconstructed with multiple CT image acquisition settings using the ACR (American College of Radiology) CT Phantom. Twenty-four sets of CT images of the ACR CT phantom were attained from a GE Discovery 750HD scanner using 24 different image acquisition settings, combinations of 4 tube currents (25, 50, 100, 200 Effective mAs), 3 slice thicknesses (1.25, 2.5, 5 mm), and 2 convolution kernels (STANDARD and SOFT). Polyethylene (-95 HU) and acrylic (120 HU) of the phantom model were selected for calculating real feature value; a noise-free, computer-generated phantom image series that reproduced the 2 objects and the background was used for calculating reference feature value. Feature reliability was defined as the degree of predicting reference feature value from real feature value. Radiomic features mean, std, skewness, kurtosis, gray-level co-occurrence matrix (GLCM)-energy, GLCM-contrast, GLCM-correlation, GLCM-homogeneity were investigated. The value of R ² ? 0.85 was considered to be of high reliability. The reliability of mean and std were high across all image acquisition settings. At 200 Effective mAs, all features except GLCM-homogeneity showed high reliability, whereas at 25 Effective mAs, most features (except mean and std) showed low reliability. From high to low, reliability was ranked in the following order: mean, std, skewness, kurtosis, GLCM-energy, correlation, contrast and homogeneity. CT image acquisition settings affected the reliability of radiomic features. High reliable features were attained from images reconstructed at high tube current and thick slice thickness.

SUBMITTER: Lu L

PROVIDER: S-EPMC6403036 | biostudies-literature | 2019 Mar

REPOSITORIES: biostudies-literature

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Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom.

Lu Lin L Liang Yongguang Y Schwartz Lawrence H LH Zhao Binsheng B

Tomography (Ann Arbor, Mich.) 20190301 1

We studied the reliability of radiomic features on abdominal computed tomography (CT) images reconstructed with multiple CT image acquisition settings using the ACR (American College of Radiology) CT Phantom. Twenty-four sets of CT images of the ACR CT phantom were attained from a GE Discovery 750HD scanner using 24 different image acquisition settings, combinations of 4 tube currents (25, 50, 100, 200 Effective mAs), 3 slice thicknesses (1.25, 2.5, 5 mm), and 2 convolution kernels (STANDARD and ...[more]

PMID: 30854461

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Project description:The purpose of this study was to explore the effects of CT slice thickness, reconstruction algorithm, and radiation dose on quantification of CT features to characterize lung nodules using a chest phantom. Spherical lung nodule phantoms of known densities (-630 and + 100 HU) were inserted into an anthropomorphic thorax phantom. CT scan was performed ten times with relocations. CT data were reconstructed using 12 different imaging settings; three different slice thicknesses of 1.25, 2.5, and 5.0 mm, two reconstruction kernels of sharp and standard, and two radiation dose of 30 mAs and 12 mAs. Lesions were segmented using a semiautomated method. Twenty representative CT quantitative features representing CT density and texture were compared using multiple regression analysis. In 100 HU nodule phantoms, 18 and 19 among 20 computer features showed significant difference between different mAs and reconstruction algorithms, respectively (p ≤ 0.05). 20, 19, and 19 computer features showed difference between slice thickness of 5.0 vs 1.25, 5.0 vs 2.5, and 2.5 vs 1.25 mm, respectively (p ≤ 0.05). In -630 HU nodule phantoms, 18 and 19 showed significant difference between different mAs and reconstruction algorithms, respectively (p ≤ 0.05). 18, 11, and 17 computer features showed difference between slice thickness of 5.0 vs 1.25, 5.0 vs 2.5, and 2.5 vs 1.25 mm, respectively (p ≤ 0.05). When comparing the absolute value of regression coefficient, the effect of slice thickness in 100 HU nodule and reconstruction algorithm in -630 HU nodule was greater than the effect of remaining scan parameters. The slice thickness, mAs, and reconstruction algorithm had a significant impact on the quantitative image features. In clinical studies involving deep learning or radiomics, it should be noted that differences in values can occur when using computer features obtained from different CT scan parameters in combination. Therefore, when interpreting the statistical analysis results, it is necessary to reflect the difference in the computer features depending on the scan parameters.

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Dataset Information

Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom.

Publications

Reliability of Radiomic Features Across Multiple Abdominal CT Image Acquisition Settings: A Pilot Study Using ACR CT Phantom.

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