Glushkov Evgeny V, Glushkova Natalia V, Ermolenko Olga A, Tatarinov Alexey M
Institute for Mathematics, Mechanics and Informatics, Kuban State University, Krasnodar 350040, Russia.
Institute of Electronics and Computer Sciences, LV-1006 Riga, Latvia.
Materials (Basel). 2023 Sep 12;16(18):6179. doi: 10.3390/ma16186179.
Tubular bones are layered waveguide structures composed of soft tissue, cortical and porous bone tissue, and bone marrow. Ultrasound diagnostics of such biocomposites are based on the guided wave excitation and registration by piezoelectric transducers applied to the waveguide surface. Meanwhile, the upper sublayers shield the diseased interior, creating difficulties in extracting information about its weakening from the surface signals. To overcome these difficulties, we exploit the advantages of the Green's matrix-based approach and adopt the methods and algorithms developed for the guided wave structural health monitoring of industrial composites. Based on the computer models implementing this approach and experimental measurements performed on bone phantoms, we analyze the feasibility of using different wave characteristics to detect hidden diagnostic signs of developing osteoporosis. It is shown that, despite the poor excitability of the most useful modes associated with the diseased inner layers, the use of the improved matrix pencil method combined with objective functions based on the Green's matrix allows for effective monitoring of changes in the elastic moduli of the deeper sublayers. We also note the sensitivity and monotonic dependence of the resonance response frequencies on the degradation of elastic properties, making them a promising indicator for osteoporosis diagnostics.
管状骨是由软组织、皮质骨和多孔骨组织以及骨髓组成的层状波导结构。对此类生物复合材料的超声诊断基于应用于波导表面的压电换能器对导波的激发和记录。同时,上层子层会屏蔽患病的内部结构,这给从表面信号中提取有关其弱化的信息带来了困难。为克服这些困难,我们利用基于格林矩阵方法的优势,并采用为工业复合材料的导波结构健康监测所开发的方法和算法。基于实现此方法的计算机模型以及在骨模型上进行的实验测量,我们分析了使用不同波特征来检测骨质疏松症发展的隐藏诊断迹象的可行性。结果表明,尽管与患病内层相关的最有用模式的激发性较差,但结合基于格林矩阵的目标函数使用改进的矩阵束方法可以有效地监测较深子层弹性模量的变化。我们还注意到共振响应频率对弹性特性退化的敏感性和单调依赖性,使其成为骨质疏松症诊断的一个有前景的指标。