Evidence map›Paper›PMID 40082938›Full record

ArticleBMC veterinary research2025

Selection of density standard and X-ray tube settings for computed digital absorptiometry in horses using the k-means clustering algorithm.

Bernard Turek, Marek Pawlikowski, Krzysztof Jankowski, Marta Borowska, Katarzyna Skierbiszewska, Tomasz Jasiński, Małgorzata Domino

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Article in BMC veterinary research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

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3 · Its place in the literature

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1 citing paper in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Bernard TurekDepartment of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, Warsaw, 02-797, Poland.
Marek PawlikowskiInstitute of Mechanics and Printing, Warsaw University of Technology, Narbutta 85, Warsaw, 02-524, Poland.
Krzysztof JankowskiInstitute of Mechanics and Printing, Warsaw University of Technology, Narbutta 85, Warsaw, 02-524, Poland.
Marta BorowskaInstitute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, Bialystok, 15-351, Poland.
Katarzyna SkierbiszewskaDepartment of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, Warsaw, 02-797, Poland.
Tomasz JasińskiDepartment of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, Warsaw, 02-797, Poland.
Małgorzata DominoDepartment of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS - SGGW), Nowoursynowska 100, Warsaw, 02-797, Poland. malgorzata_domino@sggw.edu.pl.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIn veterinary medicine, conventional radiography is the first-choice method for most diagnostic imaging applications in both small animal and equine practice. One direction in its development is the integration of bone density evaluation and artificial intelligence-assisted clinical decision-making, which is expected to enhance and streamline veterinarians' daily practices. One such decision-support method is k-means clustering, a machine learning and data mining technique that can be used clinically to classify radiographic signs into healthy or affected clusters. The study aims to investigate whether the k-means clustering algorithm can differentiate cortical and trabecular bone in both healthy and affected horse limbs. Therefore, identifying the optimal computed digital absorptiometry parameters was necessary. METHODS AND

resultsFive metal-made density standards, made of pure aluminum, aluminum alloy (duralumin), cuprum alloy, iron-nickel alloy, and iron-silicon alloy, and ten X-ray tube settings were evaluated for the radiographic imaging of equine distal limbs, including six healthy limbs and six with radiographic signs of osteoarthritis. Density standards were imaged using ten combinations of X-ray tube settings, ranging from 50 to 90 kV and 1.2 to 4.0 mAs. The relative density in Hounsfield units was firstly returned for both bone types and density standards, then compared, and finally used for clustering. In both healthy and osteoarthritis-affected limbs, the relative density of the long pastern bone (the proximal phalanx) differed between bone types, allowing the k-means clustering algorithm to successful differentiate cortical and trabecular bone.

conclusionDensity standard made of duralumin, along with the 60 kV, 4.0 mAs X-ray tube settings, yielded the highest clustering metric values and was therefore considered optimal for further research. We believe that the identified optimal computed digital absorptiometry parameters may be recommended for further researches on the relative quantification of conventional radiographs and for distal limb examination in equine veterinary practice.

Indexed as

Absorptiometry, PhotonBone DensityHorse DiseasesAlgorithmsAnimalsCluster AnalysisClustering AlgorithmsHorsesBone mineral densityComputed digital absorptiometryDistal limbsHorseRadiological signs

Identifiers

PMID40082938
PMCPMC11905476

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