Virtual non-contrast images of detector-based spectral computed tomography in dogs: a promising alternative to true non-contrast images in veterinary medicine

Philipp Lietz Manon Brüntgens Adriano Wang-Leandro Holger Andreas Volk Sebastian Meller Kristina Merhof

Background: The authors aim to evaluate the reliability of virtual non-contrast (VNC) images derived from spectral detector CT (SDCT) for abdominal organs in dogs without abdominal pathologies, by comparing them with true non-contrast (TUE) images.

Study: Retrospectively review of 313 CT examinations of the abdomen of dogs using SDCT and selected 44 dogs with normal abdominal organs for the study. They performed quantitative and qualitative analyses of the attenuation values, signal-to-noise ratio, image quality, and iodine subtraction of VNC and TUE images.

Methods: The authors used a Philips IQon Spectral CT scanner with 120–140 kV maximum tube potential, a pitch of 0.6, a slice thickness of 2 mm, and a 512 image matrix. They acquired TUE images followed by contrast-enhanced CT images with a 60-s delay after bolus tracking. They reconstructed VNC images from the post-contrast data using the system-associated software. They placed multiple regions of interest (ROIs) in the TUE images and transferred them to the VNC images. They calculated the difference in Hounsfield units (HUs) between the ROIs and classified them into four categories based on human medical studies. They also calculated the signal-to-noise ratio (SNR) for each ROI. They performed a two one-sided t-test (TOST) to test the equivalence between VNC and TUE images. They also performed a subjective assessment of image quality and iodine subtraction using a 5-point Likert scale.

Results: The difference in HUs between VNC and TUE images was ≤5 HU in 50.87%, ≤10 HU in 78.67%, and ≤15 HU in 91.61% of all compared ROIs. The TOST showed equivalence for the liver, spleen, pancreas, and musculature with a limit of ≤10 HU. The Bland–Altman plots showed a very good agreement between the two modalities. The SNR of SDCT images was better than conventional CT images. The subjective assessment of image quality showed that SDCT images were equal or superior to conventional CT images. The subjective assessment of iodine subtraction showed that VNC images achieved an average score of at least 4 points or higher on the Likert scale for most of the abdominal organs and vessels, except for the kidneys, caudal vena cava, and gastrointestinal tract.

Limitations: The authors acknowledged that their study population was limited and not representative of the overall canine population. They also noted that they only included dogs with normal abdominal organs and that they only applied the iodine subtraction algorithm to the venous phase of the post-contrast scan. They suggested that future studies should investigate the influence of breed, age, sex, body condition, and pathology on the VNC images, and also evaluate the performance of VNC images in other contrast phases.

Conclusions: VNC images derived from SDCT data proved to be a valid alternative to conventional TUE images in the abdominal organs of canine patients without abdominal pathology. They stated that VNC images could reduce the time under general anesthesia and minimize the radiation exposure for the patients. They also highlighted the potential of SDCT to provide additional information and improve image quality compared to conventional CT.

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