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

IF 2.3 2区 农林科学 Q1 VETERINARY SCIENCES
Bernard Turek, Marek Pawlikowski, Krzysztof Jankowski, Marta Borowska, Katarzyna Skierbiszewska, Tomasz Jasiński, Małgorzata Domino
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引用次数: 0

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.

使用k-均值聚类算法选择马匹计算数字吸收测量的密度标准和x射线管设置。
背景:在兽医学中,常规x线摄影是大多数小动物和马的诊断成像应用的首选方法。其发展的一个方向是骨密度评估和人工智能辅助临床决策的整合,这有望提高和简化兽医的日常实践。其中一种决策支持方法是k-means聚类,这是一种机器学习和数据挖掘技术,可在临床上用于将放射学征象分为健康或受影响的群集。本研究旨在探讨k-means聚类算法是否可以区分健康和患病马肢体的皮质骨和小梁骨。因此,确定最佳的计算数字吸收测定参数是必要的。方法与结果:采用纯铝、铝合金(硬铝)、铜合金、铁镍合金、铁硅合金5种金属制密度标准和10种x射线管设置对马远端肢体进行影像学评价,其中包括6条健康肢体和6条有骨关节炎影像学表现的肢体。使用10种x射线管设置组合对密度标准进行成像,范围为50至90 kV, 1.2至4.0 ma。首先返回骨骼类型和密度标准的Hounsfield单元的相对密度,然后进行比较,最后用于聚类。在健康和患骨关节炎的肢体中,不同骨类型的长粘骨(近端指骨)的相对密度不同,这使得k-means聚类算法能够成功区分皮质骨和小梁骨。结论:硬铝制成的密度标准,以及60 kV, 4.0 ma的x射线管设置,产生了最高的聚类度量值,因此被认为是进一步研究的最佳选择。我们认为,所确定的最佳计算数字吸收测量参数可以推荐用于进一步研究传统x线片的相对量化和马兽医实践中的远端肢体检查。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
BMC Veterinary Research
BMC Veterinary Research VETERINARY SCIENCES-
CiteScore
4.80
自引率
3.80%
发文量
420
审稿时长
3-6 weeks
期刊介绍: BMC Veterinary Research is an open access, peer-reviewed journal that considers articles on all aspects of veterinary science and medicine, including the epidemiology, diagnosis, prevention and treatment of medical conditions of domestic, companion, farm and wild animals, as well as the biomedical processes that underlie their health.
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