Selection of density standard and X–ray tube settings for computed digital absorptiometry in horses using the k–means clustering algorithm.
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| Title: | Selection of density standard and X–ray tube settings for computed digital absorptiometry in horses using the k–means clustering algorithm. |
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| Authors: | Turek, Bernard1 (AUTHOR), Pawlikowski, Marek2 (AUTHOR), Jankowski, Krzysztof2 (AUTHOR), Borowska, Marta3 (AUTHOR), Skierbiszewska, Katarzyna1 (AUTHOR), Jasiński, Tomasz1 (AUTHOR), Domino, Małgorzata1 (AUTHOR) malgorzata_domino@sggw.edu.pl |
| Source: | BMC Veterinary Research. 3/13/2025, Vol. 21 Issue 1, p1-19. 19p. |
| Document Type: | Article |
| Subjects: | Clustering algorithms, Phalanges, Bone density, Cancellous bone, Compact bone |
| Author-Supplied Keywords: | Bone mineral density Computed digital absorptiometry Distal limbs Horse Medical and Health Sciences Clinical Sciences Information and Computing Sciences Artificial Intelligence and Image Processing Radiological signs |
| Abstract: | Background: In 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 results: Five 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. Conclusion: Density 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. [ABSTRACT FROM AUTHOR] |
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| Author Affiliations: | 1https://ror.org/05srvzs48 Department of Large Animal Diseases and Clinic, Institute of Veterinary Medicine, Warsaw University of Life Sciences (WULS – SGGW), Nowoursynowska 100, 02-797, Warsaw, Poland 2https://ror.org/00y0xnp53 Institute of Mechanics and Printing, Warsaw University of Technology, Narbutta 85, 02-524, Warsaw, Poland 3https://ror.org/02bzfsy61 Institute of Biomedical Engineering, Faculty of Mechanical Engineering, Białystok University of Technology, Wiejska 45C, 15-351, Bialystok, Poland |
| Full Text Word Count: | 12907 |
| ISSN: | 1746-6148 |
| DOI: | 10.1186/s12917-025-04591-5 |
| Accession Number: | 183750211 |
| Database: | Veterinary Source |
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| Abstract: | Background: In 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 results: Five 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. Conclusion: Density 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. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 17466148 |
| DOI: | 10.1186/s12917-025-04591-5 |