Purpose To investigate associations between computed tomography (CT) features of clear-cell renal cell carcinoma (ccRCC) and mutations in VHL, PBRM1, SETD2, KDM5C or BAP1 genes. Materials and Methods The institutional review board approved this retrospective, hypotheses-generating study of 233 patients with ccRCC and waived the informed consent requirement. The study was HIPAA compliant. Three radiologists independently reviewed pre-treatment CT images of all ccRCC without knowledge of their genomic profile. One radiologist measured largest diameter and enhancement parameters of each ccRCC. Associations between CT features and mutations in VHL, PBRM1, SETD2, KDM5C and BAP1 genes were tested using Fisher’s exact tests. Associations between mutations and size/enhancement were assessed using independent t-tests. Interreader agreements were calculated using Fleiss’ Kappa. Results Mutation frequencies among ccRCC were: VHL, 53.2% (124/233); PBRM1, 28.8% (67/233); SETD2, 7.3% (17/233); KDM5C, 6.9% (16/233); BAP1, 6% (14/233). Mutations of VHL were significantly associated with well-defined tumor margins (p=0.013), nodular tumor enhancement (p=0.021) and gross appearance of intratumoral vascularity (p=0.018). Mutations of KDM5C and BAP1 were significantly associated with evidence of renal vein invasion (p=0.022 and 0.046, respectively). The genotype of solid ccRCC differed significantly from the one of multicystic ccRCC. While mutations of SETD2, KDM5C and BAP1 were absent in multicystic ccRCC, mutations of VHL (p=0.016) and PBRM1 (p=0.017) were significantly more common among solid ccRCC. Interreader agreements for CT feature assessments ranged from substantial to excellent (κ=0.791–0.912). Conclusion This preliminary Radiogenomics analysis of ccRCC revealed associations between CT features and underlying mutations which warrant further investigation and validation.

Intra-individual comparisons of image quality of body CTA suggest that raw data-based iterative reconstruction allows for dose reduction >50% while maintaining image quality. Key Points • Raw data-based iterative reconstruction reduces image noise and improves image quality as compared to filtered back projection • At a similar radiation dose, raw data-based iterative reconstruction improves the sharpness of vessel contours • In body CTA a dose reduction of >50% might be possible when using raw data-based iterative reconstructions, while image quality can be maintained.

Automated attenuation-based tube potential selection based on the attenuation profile of the topogram is feasible, provides a diagnostic image quality of body CTA, and reduces overall radiation dose by 25% as compared with a standard protocol with 120 kV.

Low-dose computed tomography is an important thoracic investigation tool. Radiation dose can be less than 1 mSv with iterative reconstructions. Iterative reconstructions render more low-dose lung CTs diagnostic compared to conventional reconstructions.

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