FREE SHIPPING over $40
OVER 9000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Home / Equine Research Bank / Animals (Basel) / Computed Tomographic Assessment of Normal Ocular Dimensions ...
Animals : an open access journal from MDPI2025; 15(21); 3165; doi: 10.3390/ani15213165

Computed Tomographic Assessment of Normal Ocular Dimensions and Densities in Cadaveric Horses (Equus ferus caballus).

Abstract: This study aimed to characterize the computed tomographic (CT) dimensions and contrast attenuation properties of the equine eye. CT scans from 21 horses without ocular abnormalities were analyzed to obtain detailed ocular measurements and attenuation values. In addition, cranial measurements, such as nasal-occipital length and zygomatic width, were incorporated to explore potential anatomical relationships between the skull and intraocular structures. Although most correlations between cranial and ocular parameters were weak, statistically significant associations-particularly those involving lens dimensions and anterior chamber measurements-suggest that skull morphology may exert a subtle influence on ocular anatomy.
Get Full Text
Publication Date: 2025-10-31 PubMed ID: 41227495PubMed Central: PMC12607728DOI: 10.3390/ani15213165Google Scholar: Lookup
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

Overview

  • This study used computed tomography (CT) scans to measure the normal eye sizes and tissue densities in horses to better understand equine ocular anatomy in relation to skull structure.
  • Researchers analyzed CT images of 21 horses without eye problems to assess eye dimensions and contrast attenuation values, and compared these with skull measurements to identify any anatomical correlations.

Study Objective

  • To characterize normal ocular dimensions and tissue density properties of the horse eye using CT imaging.
  • To explore potential relationships between the size and shape of the skull and internal eye structures, which could inform veterinary diagnostics and treatment planning.

Methodology

  • CT scans were collected from 21 cadaveric horses with no known ocular abnormalities to ensure normal anatomy was studied.
  • Detailed intraocular measurements were taken, covering key eye structures such as lens size and the anterior chamber, which is the fluid-filled space between the cornea and iris.
  • Contrast attenuation values from CT scans were recorded to characterize tissue density differences within the eye, aiding in the differentiation of ocular components.
  • Cranial parameters—specifically nasal-occipital length (distance from nose to back of the skull) and zygomatic width (width of the cheekbone)—were measured to assess their relationship with eye dimensions.

Key Findings

  • Most correlations between skull measurements and eye parameters were weak, suggesting that gross skull size does not strongly predict eye size or density.
  • However, some statistically significant associations were found, especially concerning lens dimensions and measurements of the anterior chamber, indicating subtle influences of skull morphology on certain intraocular structures.
  • The findings imply that while the overall shape and size of the skull may have limited impact on the general eye anatomy, specific features like the lens and anterior chamber are somewhat linked to cranial anatomy.

Significance and Implications

  • This quantitative data on normal equine ocular dimensions and densities provides a useful reference baseline for veterinary ophthalmologists and radiologists.
  • Understanding normal variability and its subtle relationship with skull structure may improve the accuracy of diagnosing ocular diseases or abnormalities using CT imaging.
  • The study supports the idea that skull morphology should be considered as a potential factor when assessing eye anatomy and planning surgical or medical interventions in horses.

Limitations and Future Research

  • The study used a relatively small sample size (21 horses), so broader studies could help confirm these relationships and generalize findings.
  • As the scans were from cadavers, physiological changes in live horses might affect measurements, suggesting future work could incorporate live animal imaging techniques.
  • Further research might investigate additional cranial parameters or include more diverse equine populations to explore breed or age-related variations in ocular-skull relationships.

Cite This Article

APA
Díaz-Bertrana ML, Pitti L, Ramírez AS, Encinoso M, Fumero-Hernández M, Morales I, Arencibia A, Jaber JR. (2025). Computed Tomographic Assessment of Normal Ocular Dimensions and Densities in Cadaveric Horses (Equus ferus caballus). Animals (Basel), 15(21), 3165. https://doi.org/10.3390/ani15213165

Publication

Animals : an open access journal from MDPI
ISSN: 2076-2615
NlmUniqueID: 101635614
Country: Switzerland
Language: English
Volume: 15
Issue: 21
PII: 3165

Researcher Affiliations

Díaz-Bertrana, Maria Luisa
  • Hospital Clínico Veterinario, Facultad de Veterinaria, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.
Pitti, Lidia
  • Hospital Clínico Veterinario, Facultad de Veterinaria, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.
Ramírez, Ana Sofia
  • Department of Pathology and Food Technology, Faculty of Veterinary Medicine, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.
Encinoso, Mario
  • Hospital Clínico Veterinario, Facultad de Veterinaria, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.
Fumero-Hernández, Marcos
  • Hospital Clínico Veterinario, Facultad de Veterinaria, Universidad Autónoma de Barcelona, Carrer de l'Hospital, 08193 Bellaterra, Spain.
Morales, Inmaculada
  • Hospital Clínico Veterinario, Facultad de Veterinaria, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.
Arencibia, Alberto
  • Departamento de Morfología, Facultad de Veterinaria, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.
  • Grupo de Investigación en Anatomía Aplicada y Herpetopatología, Departamento de Morfología, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.
Jaber, José Raduan
  • Departamento de Morfología, Facultad de Veterinaria, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.
  • Grupo de Investigación en Anatomía Aplicada y Herpetopatología, Departamento de Morfología, Universidad de Las Palmas de Gran Canaria, Trasmontaña, 35413 Las Palmas, Spain.

Conflict of Interest Statement

The authors declare no conflicts of interest.

References

This article includes 32 references
  1. Stoppini R, Gilger BC. Equine ocular examination basic techniques. In: Gilger B.C., editor. Equine Ophthalmology. Wiley and Sons, Inc.; New York, NY, USA: 2017. pp. 1–39.
  2. McMullen RJ. Advancements in equine ophthalmic imaging enhance understanding of ocular and orbital anatomy and disease in standing sedated horses. J. Am. Vet. Med. Assoc. 2024;262:S47–S56.
    doi: 10.2460/javma.24.06.0376pubmed: 39454619google scholar: lookup
  3. Gallhoefer NS, Bentley E, Ruetten M, Grest P, Haessig M, Kircher PR, Dubielzig RR, Spiess BM, Pot SA. Comparison of ultrasonography and histologic examination for identification of ocular diseases of animals: 113 cases (2000–2010). J. Am. Vet. Med. Assoc. 2013;243:376–388.
    doi: 10.2460/javma.243.3.376pubmed: 23865880google scholar: lookup
  4. Dennis R. Use of magnetic resonance imaging for the investigation of orbital disease in small animals. J. Small Anim. Pract. 2000;41:145–155.
    doi: 10.1111/j.1748-5827.2000.tb03184.xpubmed: 10812543google scholar: lookup
  5. Hollis AR, Dixon JJ, Berlato D, Murray R, Weller R. Computed tomographic dimensions of the normal adult equine eye. Vet. Ophthalmol. 2019;22:651–659.
    doi: 10.1111/vop.12636pubmed: 30716192google scholar: lookup
  6. Grinninger P, Skalicky M, Nell B. Evaluation of healthy equine eyes by use of retinoscopy, keratometry, and ultrasonographic biometry. Am. J. Vet. Res. 2010;71:677–681.
    doi: 10.2460/ajvr.71.6.677pubmed: 20513184google scholar: lookup
  7. Salgüero R, Johnson V, Williams D, Hartley C, Holmes M, Dennis R, Herrtage M. CT dimensions, volumes and densities of normal canine eyes. Vet. Rec. 2015;176:386.
    doi: 10.1136/vr.102940pubmed: 25690914google scholar: lookup
  8. Chandrakumar S, Linden AZ, Owen M, Pemberton S, Pinard CL, Matsuyama A, Poirier VJ. Computed tomography measurements of intraocular structures of the feline eye. Vet. Rec. 2019;184:651.
    doi: 10.1136/vr.105136pubmed: 31040219google scholar: lookup
  9. Fumero-Hernández M, Encinoso M, Ramírez AS, Fariña IM, Calabuig P, Jaber JR. Morphometric Study of the Eyeball of the Loggerhead Turtle (Caretta caretta) Using Computed Tomography (CT). Animals 2023;13:1016.
    doi: 10.3390/ani13061016pmc: PMC10044611pubmed: 36978556google scholar: lookup
  10. Fumero-Hernández M, Encinoso M, Ramírez AS, Morales I, Pérez AS, Jaber JR. A Cadaveric Study Using Computed Tomography for Measuring the Eyeball and Scleral Skeleton of the Atlantic Puffin (Aves, Alcidae, Fratercula arctica). Animals 2023;13:2418.
    doi: 10.3390/ani13152418pmc: PMC10417006pubmed: 37570227google scholar: lookup
  11. Hall MI. The anatomical relationships between the avian eye, orbit and sclerotic ring: Implications for inferring activity patterns in extinct birds. J. Anat. 2008;212:781–794.
    doi: 10.1111/j.1469-7580.2008.00897.xpmc: PMC2423400pubmed: 18510506google scholar: lookup
  12. Evans KE, McGreevy PD. Conformation of the Equine Skull: A Morphometric Study. Anat. Histol. Embryol. 2006;35:221–227.
    doi: 10.1111/j.1439-0264.2005.00663.xpubmed: 16836585google scholar: lookup
  13. Yoo H, Lee S, Shin K, Seo J. Computed tomographic dimensions and densities of the normal eye in Jeju horses. J. Vet. Med. Sci. 2024;86:308–311.
    doi: 10.1292/jvms.23-0382pmc: PMC10963092pubmed: 38171740google scholar: lookup
  14. Pérez S, Encinoso M, Corbera JA, Morales M, Arencibia A, González-rodríguez E, Déniz S, Melián C, Suárez-bonnet A, Jaber JR. Cranial Structure of Varanus Komodoensis as Revealed by Computed-tomographic Imaging. Animals 2021;11:1078.
    doi: 10.3390/ani11041078pmc: PMC8070356pubmed: 33918974google scholar: lookup
  15. Pérez S, Encinoso M, Morales M, Arencibia A, Suárez-Bonnet A, González-Rodríguez E, Jaber JR. Comparative evaluation of the Komodo dragon (Varanus komodoensis) and the Green iguana (Iguana iguana) skull by three dimensional computed tomographic reconstruction. Slov. Vet. Res. 2021;58:111–116.
    doi: 10.26873/SVR-1330-2021google scholar: lookup
  16. Banzato T, Selleri P, Veladiano IA, Martin A, Zanetti E, Zotti A. Comparative evaluation of the cadaveric, radiographic and computed tomographic anatomy of the heads of green iguana (Iguana iguana), common tegu (Tupinambis merianae) and bearded dragon (Pogona vitticeps). BMC Vet. Res. 2012;11:53.
    doi: 10.1186/1746-6148-8-53pmc: PMC3439268pubmed: 22578088google scholar: lookup
  17. González Rodríguez E, Encinoso Quintana M, Morales Bordon D, Garcés JG, Artiles Nuez H, Jaber JR. Anatomical Description of Rhinoceros Iguana (Cyclura cornuta cornuta) Head by Computed Tomography, Magnetic Resonance Imaging and Gross-Sections. Animals 2023;13:955.
    doi: 10.3390/ani13060955pmc: PMC10044561pubmed: 36978497google scholar: lookup
  18. Andrade SBD, Araujo NLLCD, Raposo ACS, Muramoto C, Oriá AP. Morphometric descriptive report of scleral ossicle rings, by ultrasound and computed tomography, in three Testudines specimens. Ciênc Rural 2023;53:e20210423.
    doi: 10.1590/0103-8478cr20210423google scholar: lookup
  19. Harman AM, Moore S, Hoskins R, Keller P. Horse vision and an explanation for the visual behaviour originally explained by the ‘ramp retina’. Equine Vet. J. 1999;31:384–390.
    doi: 10.1111/j.2042-3306.1999.tb03837.xpubmed: 10505953google scholar: lookup
  20. Hanggi EB, Ingersoll JF. Lateral vision in horses: A behavioral investigation. Behav. Process. 2012;91:70–76.
    doi: 10.1016/j.beproc.2012.05.009pubmed: 22698758google scholar: lookup
  21. Timney B, Keil K. Visual acuity in the horse. Vision. Res. 1992;32:2289–2293.
    doi: 10.1016/0042-6989(92)90092-Wpubmed: 1288005google scholar: lookup
  22. Guo X, Sugita S. Topography of ganglion cells in the retina of the horse. J. Vet. Med. Sci. 2000;62:1145–1150.
    doi: 10.1292/jvms.62.1145pubmed: 11129856google scholar: lookup
  23. Bartol SM, Musick JA, Ochs AL. Visual acuity thresholds of juvenile loggerhead sea turtles (Caretta caretta): An electrophysiological approach. J. Comp. Physiol. A Neuroethol. Sens. Neural Behav. Physiol. 2002;187:953–960.
    doi: 10.1007/s00359-001-0262-xpubmed: 11913813google scholar: lookup
  24. Timney B, Macuda T. Vision and hearing in horses. J. Am. Vet. Med. Assoc. 2001;218:1567–1574.
    doi: 10.2460/javma.2001.218.1567pubmed: 11393366google scholar: lookup
  25. Cappellato A, Miletto Petrazzini ME, Bisazza A, Dadda M, Agrillo C. Susceptibility to Size Visual Illusions in a Non-Primate Mammal (Equus caballus). Animals 2020;10:1673.
    doi: 10.3390/ani10091673pmc: PMC7552233pubmed: 32957449google scholar: lookup
  26. Hall CA, Cassaday HJ, Derrington AM. The effect of stimulus height on visual discrimination in horses. J. Anim. Sci. 2003;81:1715–1720.
    doi: 10.2527/2003.8171715xpubmed: 12854807google scholar: lookup
  27. Yoshimiya M, Noriki S, Shimbashi S, Uesaka H, Hyodoh H. Postmortem changes in porcine eyes on computed tomography images. Leg. Med. 2025;73:102568.
    doi: 10.1016/j.legalmed.2025.102568pubmed: 39827728google scholar: lookup
  28. Stoeck C, Deuster C, Fleischmann T, Lipiski M, Cesarovic N, Kozerke S. Direct comparison of in vivo versus postmortem second-order motion-compensated cardiac diffusion tensor imaging. Magn. Reson. Med. 2018;79:2265–2276.
    doi: 10.1002/mrm.26871pubmed: 28833410google scholar: lookup
  29. Mckenna MF, Goldbogen JA, Leger J, Hildebrand JA, Cranford TW. Evaluation of postmortem changes in tissue structure in the bottlenose dolphin (Tursiops truncatus). Anat. Rec. 2007;290:1023–1032.
    doi: 10.1002/ar.20565pubmed: 17654676google scholar: lookup
  30. Crespigny A, Bou-Reslan H, Nishimura M, Phillips H, Carano R, D’Arceuil H. 3D micro-CT imaging of the Postmortem Brain. J. Neurosci. Methods. 2008;171:207–213.
    doi: 10.1016/j.jneumeth.2008.03.006pmc: PMC2693019pubmed: 18462802google scholar: lookup
  31. Bryce AJ, Dandrieux JR, Tyrrell D, Milne ME. The evolving use of post-mortem veterinary imaging in a university specialist hospital. Forensic Imaging 2021;26:200475.
    doi: 10.1016/j.fri.2021.200475google scholar: lookup
  32. Germonpré J, Vandekerckhove LMJ, Raes E, Chiers K, Jans L, Vanderperren K. Post-mortem feasibility of dual-energy computed tomography in the detection of bone edema-like lesions in the equine foot: A proof of concept. Front. Vet. Sci. 2024;10:1201017.
    doi: 10.3389/fvets.2023.1201017pmc: PMC10797750pubmed: 38249561google scholar: lookup

Citations

This article has been cited 0 times.
Subscribe to our newsletter
Join 99,030 horse owners like you who receive our email updates on horse health and nutrition.