Purpose: The novel photon-counting detector (PCD) technique acquires spectral data for virtual monoenergetic imaging (VMI) in every examination. The aim of this study was the evaluation of the impact of VMI of abdominal arterial vessels on quantitative and qualitative subjective image parameters. Methods: A total of 20 patients that underwent an arterial phase computed tomography (CT) scan of the abdomen with a novel PCD CT (Siemens NAEOTOM alpha) were analyzed regarding attenuation at different energy levels in virtual monoenergetic imaging. Contrast-to-noise ratio (CNR) and signal-to-noise ratio (SNR) were calculated and compared between the different virtual monoenergetic (VME) levels with correlation to vessel diameter. In addition, subjective image parameters (overall subjective image quality, subjective image noise and vessel contrast) were evaluated. Results: Our research showed decreasing attenuation levels with increasing energy levels in virtual monoenergetic imaging regardless of vessel diameter. CNR showed best overall results at 60 keV, and SNR at 70 keV with no significant difference to 60 keV (p = 0.294). Subjective image quality was rated best at 70 keV for overall image quality, vessel contrast and noise. Conclusions: Our data suggest that VMI at 60–70 keV provides the best objective and subjective image quality concerning vessel contrast irrespective of vessel size.

The increasing use of computed tomography (CT) has led to a rise in cumulative radiation dose due to medical imaging, raising concerns about potential long-term adverse effects. Large-scale epidemiological studies indicate a higher tumor incidence associated with CT examinations, but the underlying biological mechanisms remain largely unexplained. To gain further insights into the cellular response triggered by routine CT diagnostics, we investigated CT-induced changes of gene expression in peripheral blood cells using whole transcriptome sequencing. RNA was isolated from peripheral blood cells of 40 male patients with asymptomatic microhematuria, sampled before and after multi-phase abdominal CT (CTDIvol: 3.75–26.95 mGy, median: 6.55 mGy). On average, 22.11 million sequence reads (SD 5.71) per sample were generated to identify differentially expressed genes 6 h post-exposure by means of DESeq2. To assess the dose dependency of CT-induced effects, we additionally divided samples into three categories: low exposure (≤6.55 mGy, n = 20), medium exposure (>6.55 mGy and <12 mGy, n = 16), and high exposure (≥12 mGy, n = 4), and repeated gene expression analysis for each subset and their corresponding prae-exposure sample. CT exposure caused consistent and dose-dependent upregulation of six genes (EDA2R, AEN, FDXR, DDB2, PHLDA3, and MIR34AHG; padj < 0.1). These genes share several functional commonalities, including regulation by TP53 and involvement in the DNA damage response. The biological pathways highlighted by Gene Set Enrichment Analysis (GSEA) suggest a dose-dependent increase of cellular damage and metabolic particularities in the low-exposure subset, which may be related to a potential adaptive cellular response to low-dose irradiation. Irrespective of applied dose, AEN emerged as the most robust biomarker for CT exposure among all genes. Routine abdominal CT scans cause dose-dependent gene deregulation in association with DNA damage in peripheral blood cells after in vivo exposure. Regarding risk assessment of CT, our results support the commonly applied “As Low–As –Reasonably Achievable (ALARA)” principle. Evidence of additional gene expression changes associated with metabolic processes indicates a rather complex molecular response beyond DNA damage after CT exposure, and emphasizes the need for further targeted investigations.

Objectives: To evaluate the value of virtual monoenergetic images (VMI) from photon-counting detector CT (PCD-CT) for discriminability of severe lung injury and atelectasis in polytraumatized patients. Materials & Methods: Contrast-enhanced PCD-CT examinations of 20 polytraumatized patients with severe thoracic trauma were included in this retrospective study. Spectral PCD-CT data were reconstructed using a noise-optimized virtual monoenergetic imaging (VMI) algorithm with calculated VMIs ranging from 40 to 120 keV at 10 keV increments. Injury-to-atelectasis contrast-to-noise ratio (CNR) was calculated and compared at each energy level based on CT number measurements in severely injured as well as atelectatic lung areas. Three radiologists assessed subjective discriminability, noise perception, and overall image quality. Results: CT values for atelectasis decreased as photon energy increased from 40 keV to 120 keV (mean Hounsfield units (HU): 69 at 40 keV; 342 at 120 keV), whereas CT values for severe lung injury remained near-constant from 40 keV to 120 keV (mean HU: 42 at 40 keV; 44 at 120 keV) with significant differences at each keV level (p < 0.001). The optimal injury-to-atelectasis CNR was observed at 40 keV in comparison with the remaining energy levels (p < 0.001) except for 50 keV (p > 0.05). In line with this, VMIs at 40 keV were rated best regarding subjective discriminability. VMIs at 60–70 keV, however, provided the highest subjective observer parameters regarding subjective image noise as well as image quality. Conclusions: Discriminability between severely injured and atelectatic lung areas after thoracic trauma can be substantially improved by virtual monoenergetic imaging from PCD-CT with superior contrast and visual discriminability at 40–50 keV.