Abdominal Imaging in Small Animals: New Insights

A special issue of Animals (ISSN 2076-2615). This special issue belongs to the section "Veterinary Clinical Studies".

Deadline for manuscript submissions: 30 June 2026 | Viewed by 1740

Special Issue Editor


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Guest Editor
Department of Clinical Sciences, Cummings School of Veterinary Medicine, Tufts University, North Grafton, MA, USA
Interests: small animal; ultrasound; radiology; CT; MRI; veterinary research

Special Issue Information

Dear Colleagues,

The abdomen houses numerous essential organ systems, such as the hepatobiliary, pancreatic, gastrointestinal, and genitourinary systems, which are often impacted by a diverse range of conditions. Imaging plays a crucial role in the diagnostic process, which can be particularly challenging due to the complexity of the anatomy and the diverse pathology that can occur. It is also essential for staging, treatment planning, and monitoring therapeutic response.

Advancements in imaging technologies, including state-of-the-art modalities and sophisticated post-processing techniques, continue to enhance diagnostic accuracy but also demand a high level of expertise from interpreting clinicians. Furthermore, the integration of artificial intelligence into abdominal imaging is revolutionizing the field, promising new insights and improved prognostication for patients.

This Special Issue aims to highlight the latest developments and innovations in abdominal imaging for small animals. We welcome original research and comprehensive reviews addressing conventional imaging, advanced modalities, cutting-edge post-processing techniques, artificial intelligence applications, and their impact on diagnosis and clinical outcomes.

In this Special Issue, original research articles and reviews are welcome. Research areas may include (but are not limited to) the following: articles, reviews, communication, commentary, and case reports.

I look forward to receiving your contributions.

Dr. Agustina Ansón
Guest Editor

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Keywords

  • radiology
  • ultrasound
  • computed tomography
  • magnetic resonance
  • dog
  • cat
  • gastrointestinal
  • hepatobiliary
  • pancreatic
  • genitourinary
  • adrenal
  • artificial intelligence

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Published Papers (2 papers)

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Research

22 pages, 1480 KB  
Article
Comparison of Virtual Non-Contrast Images Generated by Spectral Detector Computed Tomography and Conventional Computed Tomography Images of Histologically Confirmed Hepatic Pathologies in 28 Dogs
by Lydia K. Claußen, Alkje M. van Gemmeren, Philipp Lietz, Sebastian Meller, Adriano Wang-Leandro, Andreas Beineke, Verena Nerschbach, Holger A. Volk and Kristina Merhof
Animals 2025, 15(23), 3366; https://doi.org/10.3390/ani15233366 - 21 Nov 2025
Viewed by 286
Abstract
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 [...] Read more.
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. Full article
(This article belongs to the Special Issue Abdominal Imaging in Small Animals: New Insights)
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13 pages, 1351 KB  
Article
Measurements and Visibility of the Pancreatic Ducts on Computed Tomography in 78 Cats Without Clinical Evidence of Pancreatitis
by Abby Caine, Man-Hei Ma, Mike Herrtage, Tim Sparks and Marie Aude Genain
Animals 2025, 15(19), 2857; https://doi.org/10.3390/ani15192857 - 30 Sep 2025
Viewed by 1052
Abstract
Imaging is commonly used to help diagnose pancreatic disease in cats. In order to establish normal computed tomography (CT) measurements for the pancreatic ducts in cats, images of 78 cats without clinical evidence of pancreatic disease, and with normal DGGR (1,2-o-dilauryl-rac-glycero-3-glutaric acid-(6′-methylresorufin) ester [...] Read more.
Imaging is commonly used to help diagnose pancreatic disease in cats. In order to establish normal computed tomography (CT) measurements for the pancreatic ducts in cats, images of 78 cats without clinical evidence of pancreatic disease, and with normal DGGR (1,2-o-dilauryl-rac-glycero-3-glutaric acid-(6′-methylresorufin) ester lipase values, were evaluated retrospectively by two reviewers. The left pancreatic duct measured 1.4 ± 0.8 mm (mean ± standard deviation), the right pancreatic duct measured 1.1 ± 0.5 mm, and the common duct measured 1.6 ± 0.8 mm. All ducts were better visualised post-contrast, with the left pancreatic duct identified most frequently (not visualised on post-contrast images in only 3% of cases). There was visibility of the right and common hepatic ducts less frequently, not observed post-contrast in 22 and 20% of cases, respectively. The duodenal papilla measured 2.8 ± 0.7 mm in diameter. It had an HU of 43 ± 14 pre-contrast and 109 ± 32 post-contrast. It was identified in all but 6% of cases on post-contrast images. This study shows that the pancreatic ducts and duodenal papilla can be seen on post-contrast images and provides normal ranges of size for the pancreatic duct and duodenal papilla. Full article
(This article belongs to the Special Issue Abdominal Imaging in Small Animals: New Insights)
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