Comparison of Virtual Non-Contrast Images Generated by Spectral Detector Computed Tomography and Conventional...

Spectral detector computed tomography (SDCT) is an innovative imaging technique in veterinary medicine that utilises simultaneous data acquisition at different energy levels using two rows of detectors. This technique provides several interesting applications which improve insights into tissue composition. One implementation is the generation of virtual non-contrast (VNC) images from post-contrast spectral CT data by identifying and subtracting iodine pixels. Preliminary studies suggest that VNC images may offer diagnostic quality comparable to true unenhanced (TUE) images in healthy dogs; however, this technique has yet to be evaluated in clinical patients. This study compared the Hounsfield units (HUs) measured in VNC to those in TUE images of canine hepatic pathologies, taking into account specific types of pathologies based on their imaging characteristics. The attenuation values of the VNC and TUE series were analysed using two one-sided t-tests (TOST), and the signal-to-noise ratio (SNR) was calculated for each region of interest (ROI). A 5-point Likert scale was utilised to assess image noise, quality, and iodine subtraction in the VNC images. A total of 287 ROIs were analysed in the liver, gallbladder, paravertebral muscle, and pancreatic body of 28 dogs with histopathologically confirmed hepatic pathologies. 92.61% of the hepatic ROIs displayed a "negligible" difference of ≤10 HUs between VNC and TUE images, with significant p-values of <0.05 maintained for all ROIs within the limit of ≤10 HUs in the TOST, confirming equivalence between the two imaging modalities. The image quality assessment indicated that SDCT-derived images provided equal or superior quality compared to conventional CT. Therefore, it can be concluded that VNC images calculated from SDCT data could be an alternative to conventional TUE images for hepatic pathologies.