Dataset Information

Robustness of CT radiomics features: consistency within and between single-energy CT and dual-energy CT.

ABSTRACT:

Objectives

To evaluate inter- and intra- scan mode and scanner repeatability and reproducibility of radiomics features within and between single-energy CT (SECT) and dual-energy CT (DECT).

Methods

A standardized phantom with sixteen rods of clinical-relevant densities was scanned on seven DECT-capable scanners and three SECT-only scanners. The acquisition parameters were selected to present typical abdomen-pelvic examinations with the same voxel size. Images of SECT at 120 kVp and corresponding 120 kVp-like virtual monochromatic images (VMIs) in DECT which were generated according to scanners were analyzed. Regions of interest were drawn with rigid registrations to avoid variations due to segmentation. Radiomics features were extracted via Pyradiomics platform. Test-retest repeatability was evaluated by Bland-Altman analysis for repeated scans. Intra-scanner reproducibility for different scan modes was tested by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC). Inter-scanner reproducibility among different scanners for same scan mode was assessed by coefficient of variation (CV) and quartile coefficient of dispersion (QCD).

Results

The test-retest analysis presented that 92.91% and 87.02% of the 94 assessed features were repeatable for SECT 120kVp and DECT 120 kVp-like VMIs, respectively. The intra-scanner analysis for SECT 120kVp vs DECT 120 kVp-like VMIs demonstrated that 10.76% and 10.28% of features were with ICC > 0.90 and CCC > 0.90, respectively. The inter-scanner analysis showed that 17.09% and 27.73% of features for SECT 120kVp were with CV < 10% and QCD < 10%, and 15.16% and 32.78% for DECT 120 kVp-like VMIs, respectively.

Conclusions

The majority of radiomics features were non-reproducible within and between SECT and DECT.

Key points

• Although the test-retest analysis showed high repeatability for radiomics features, the overall reproducibility of radiomics features within and between SECT and DECT was low. • Only about one-tenth of radiomics features extracted from SECT images and corresponding DECT images did match each other, even their average photon energy levels were considered alike, indicating that the scan mode potentially altered the radiomics features. • Less than one-fifth of radiomics features were reproducible among multiple SECT and DECT scanners, regardless of their fixed acquisition and reconstruction parameters, suggesting the necessity of scanning protocol adjustment and post-scan harmonization process.

SUBMITTER: Chen Y

PROVIDER: S-EPMC9279234 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Similar Datasets

Project description:ObjectivesTo evaluate robustness of dual-energy CT (DECT) radiomics features of virtual unenhanced (VUE) image and virtual monoenergetic image (VMI) among different imaging platforms.MethodsA phantom with sixteen clinical-relevant densities was scanned on ten DECT platforms with comparable scan parameters. Ninety-four radiomic features were extracted via Pyradiomics from VUE images and VMIs at energy level of 70 keV (VMI70keV). Test-retest repeatability was assessed by Bland-Altman analysis. Inter-platform reproducibility of VUE images and VMI70keV was evaluated by coefficient of variation (CV) and quartile coefficient of dispersion (QCD) among platforms, and by intraclass correlation coefficient (ICC) and concordance correlation coefficient (CCC) between platform pairs. The correlation between variability of CT number radiomics reproducibility was estimated.Results92.02% and 92.87% of features were repeatable between scan-rescans for VUE images and VMI70keV, respectively. Among platforms, 11.30% and 28.39% features of VUE images, and 15.16% and 28.99% features of VMI70keV were with CV < 10% and QCD < 10%. The average percentages of radiomics features with ICC > 0.90 and CCC > 0.90 between platform pairs were 10.00% and 9.86% in VUE images and 11.23% and 11.23% in VMI70keV. The CT number inter-platform reproducibility using CV and QCD showed negative correlations with percentage of the first-order radiomics features with CV < 10% and QCD < 10%, in both VUE images and VMI70keV (r2 0.3870-0.6178, all p < 0.001).ConclusionsThe majority of DECT radiomics features were non-reproducible. The differences in CT number were considered as an indicator of inter-platform DECT radiomics variation. Critical relevance statement: The majority of radiomics features extracted from the VUE images and the VMI70keV were non-reproducible among platforms, while synchronizing energy levels of VMI to reduce the CT number value variability may be a potential way to mitigate radiomics instability.

Project description:Purpose To develop, in a phantom environment, a method to obtain multidetector computed tomographic (CT) data sets at multiple radiation exposure levels within the same patient and to validate its use for potential dose reduction by using different image reconstruction algorithms for the detection of liver metastases. Materials and Methods The American College of Radiology CT accreditation phantom was scanned by using a dual-source multidetector CT platform. By adjusting the radiation output of each tube, data sets at six radiation exposure levels (100%, 75%, 50%, 37.5%, 25%, and 12.5%) were reconstructed from two consecutive dual-source single-energy (DSSE) acquisitions, as well as a conventional single-source acquisition. A prospective, HIPAA-compliant, institutional review board-approved study was performed by using the same DSSE strategy in 19 patients who underwent multidetector CT of the liver for metastatic colorectal cancer. All images were reconstructed by using conventional weighted filtered back projection (FBP) and sinogram-affirmed iterative reconstruction with strength level of 3 (SAFIRE-3). Objective image quality metrics were compared in the phantom experiment by using multiple linear regression analysis. Generalized linear mixed-effects models were used to analyze image quality metrics and diagnostic performance for lesion detection by readers. Results The phantom experiment showed comparable image quality between DSSE and conventional single-source acquisition. In the patient study, the mean size-specific dose estimates for the six radiation exposure levels were 13.0, 9.8, 5.8, 4.4, 3.2, and 1.4 mGy. For each radiation exposure level, readers' perception of image quality and lesion conspicuity was consistently ranked superior with SAFIRE-3 when compared with FBP (P ≤ .05 for all comparisons). Reduction of up to 62.5% in radiation exposure by using SAFIRE-3 yielded similar reader rankings of image quality and lesion conspicuity when compared with routine-dose FBP. Conclusion A method was developed and validated to synthesize multidetector CT data sets at multiple radiation exposure levels within the same patient. This technique may provide a foundation for future clinical trials aimed at estimating potential radiation dose reduction by using iterative reconstructions. © RSNA, 2016 Online supplemental material is available for this article.