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The purpose of this study was to investigate the effect of image preprocessing on radiomic features estimation from computed tomography (CT) imaging of locally advanced rectal cancer (LARC). CT images of 20 patients with LARC were used to estimate 105 radiomic features of 7 classes (shape, first-order, GLCM, GLDM, GLRLM, GLSZM, and NGTDM). Radiomic features were estimated for 6 different isotropic resampling voxel sizes, using 10 interpolation algorithms (at fixed bin width) and 6 different bin widths (at fixed interpolation algorithm). The intraclass correlation coefficient (ICC) and the coefficient of variation (CV) were calculated to assess the variability in radiomic features estimation due to preprocessing. A repeated measures correlation analysis was performed to assess any linear correlation between radiomic feature estimate and resampling voxel size or bin width. Reproducibility of radiomic feature estimate, when assessed through ICC analysis, was nominally excellent (ICC > 0.9) for shape features, good (0.75 < ICC ≤ 0.9) or moderate (0.5 < ICC ≤ 0.75) for first-order features, and moderate or poor (0 ≤ ICC ≤ 0.5) for textural features. A number of radiomic features characterized by good or excellent reproducibility in terms of ICC showed however median CV values greater than 15%. For most textural features, a significant (p < 0.05) correlation between their estimate and resampling voxel size or bin width was found. In CT imaging of patients with LARC, the estimate of textural features, as well as of first-order features to a lesser extent, is appreciably biased by preprocessing. Accordingly, this should be taken into account when planning clinical or research studies, as well as when comparing results from different studies and performing multicenter studies. [ABSTRACT FROM AUTHOR]

Radioembolization is a valuable therapeutic option in patients with unresectable intrahepatic cholangiocarcinoma. The essential implementation of the absorbed dose calculation methods should take into account also the specific tumor radiosensitivity, expressed by the α parameter. Purpose of this study was to retrospectively calculate it in a series of patients with unresectable intrahepatic cholangiocarcinoma submitted to radioembolization. Twenty-one therapeutic procedures in 15 patients were analysed. Tumor absorbed doses were calculated processing the post-therapeutic 90Y-PET/CT images and the pre-treatment contrast-enhanced CT scans. Tumor absorbed dose and pre- and post-treatment tumor volumes were used to calculate α and α3D parameters (dividing targeted liver in n voxels of the same volume with specific voxel absorbed dose). A tumor volume reduction was observed after treatment. The median of tumor average absorbed dose was 93 Gy (95% CI 81–119) and its correlation with the residual tumor mass was statistically significant. The median of α and α3D parameters was 0.005 Gy−1 (95% CI 0.004–0.008) and 0.007 Gy−1 (95% CI 0.005–0.015), respectively. Multivariate analysis showed tumor volume and tumor absorbed dose as significant predictors of the time to tumor progression. The knowledge of radiobiological parameters gives the possibility to decide the administered activity in order to improve the outcome of the treatment. [ABSTRACT FROM AUTHOR]

Given the inherent characteristics of nonlinearity and nonstationarity of iterative reconstruction algorithms in computed tomography (CT) imaging, this study aimed to perform, for the first time, a voxel-based characterization of noise properties in CT imaging with the ASiR-V and ASiR algorithms as compared with conventional filtered back projection (FBP). Multiple repeated scans of the Catphan-504 phantom were carried out. CT images were reconstructed using FBP and ASiR/ASiR-V with different blending levels of reconstruction (20%, 40%, 60%, 80%, 100%). Noise maps and their nonuniformity index (NUI) were obtained according to the approach proposed by the report of AAPM TG-233. For the homogeneous CTP486 module, ASiR-V/ASiR allowed a noise reduction of up to 63.7%/52.9% relative to FBP. While the noise reduction values of ASiR-V-/ASiR-reconstructed images ranged up to 33.8%/39.9% and 31.2%/35.5% for air and Teflon contrast objects, respectively, these values were approximately 60%/50% for other contrast objects (PMP, LDPE, polystyrene, acrylic, Delrin). Moreover, for all contrast objects but air and Teflon, ASiR-V showed a greater noise reduction potential than ASiR when the blending level was ≥40%. While noise maps of the homogenous CTP486 module showed only a slight spatial variation of noise (NUI < 5.2%) for all reconstruction algorithms, the NUI values of iterative-reconstructed images of the nonhomogeneous CTP404 module increased nonlinearly with blending level and were 19%/15% and 6.7% for pure ASiR-V/ASiR and FBP, respectively. Overall, these results confirm the potential of ASiR-V and ASiR in reducing noise as compared with conventional FBP, suggesting, however, that the use of pure ASiR-V or ASiR might be suboptimal for specific clinical applications. [ABSTRACT FROM AUTHOR]

CT scan images with metal artefacts may reduce the image quality and diagnosis of CT scan images. Metal Artefact Reduction (MAR) can effectively reduce artifacts caused by metal implants. ASIR-V plays a role in reducing noise and improving image quality. To prove the reduction of metal image artefacts and optimization of CT scan image quality after the application of MAR and ASIR-V (30,60,90) of Head and Neck CT Scan by finding the value of SNR, CNR, anatomical information and the level of metal artefact interference after metal artefact reduction. Quasi-type experimental research design with pre-post test only without control group design. The study sample was 15 CT scan images of head and neck with purposive sampling. SNR and CNR measurements were quantitatively analyzed using the Wilk test, followed by the Wilcoxon test. Anatomical information assessment was performed qualitatively by two radiologists and analyzed by kappa test. Anatomical information and the level of metal artefact interference with CT scan images were carried out by the Friedman test, followed by the Wilcoxon test. There is a difference in SNR Pvalue (p=0.000<0.05), CNR Pvalue (p=0.000>0.05), anatomical information Pvalue (p=0.000<0.05), level of metal artefacts Pvalue (p=0.000<0.05) after using MAR and ASIR V. The use of MAR and ASIR-V methods can reduce metal artefacts in images that contain artefacts with the use of MAR + ASIR-V 90% the most optimal. [ABSTRACT FROM AUTHOR]