Initial Study of A-mode Ultrasound Spectroscopy Through Mechanical Wave Scattering Phenomenon for Measuring 3D-printed Bone Model Density

Author:

Susanti Hesty1,Mukhtar Husneni1,Suprijanto Suprijanto2,Cahyadi Willy Anugrah1

Affiliation:

1. School of Electrical Engineering, Telkom University, Jalan Telekomunikasi No. 1, Bandung 40257 Republic of Indonesia

2. Instrumentation and Control Research Group, Faculty of Industrial Technology, Institut Teknologi Bandung, Jalan Ganesha No. 10, Bandung 40132 Republic of Indonesia

Abstract

In Indonesia, the prevalence of osteoporosis is high. Given the economic burden it may impose on the population, this condition must be taken seriously. Dual-energy X-ray absorptiometry is the gold standard for diagnosing osteoporosis (DEXA). However, due to its high cost, non-portability, and radiation risk, DEXA cannot be applied to large populations. An alternative method for evaluating bone quality is ultrasound. It is more affordable, portable, and has no radiation risk. In this preliminary study, an A-mode ultrasound spectroscopy prototype for assessing the density of a 3D-printed bone model is designed. A single-element transducer (Transmit-Tx/Receive-Rx), a reconfigurable and modular FPGA-based ultrasound beamformer system, and a Raspberry Pi 3 are the system's control units. The raw radio frequency (RF) signal is acquired from three variations of density of the 3D-printed bone model, i.e., 100%, 60%, and 40%, to represent normal bone, osteopenia, and osteoporosis. The designed prototype can adequately characterize the mechanical wave scattering pattern of the 3D-printed bone model indicated by the increased tendency in the maximum amplitude when the density of the bone model is increasing. The tendency is the opposite for delay time and Power Spectral Density (PSD). These three signal parameters are potential candidate parameters to represent bone density. For future work, the selected candidate parameters can later be used as reference values while adding a significant data so that a machine learning method can be employed to extract representative features of bone density level, i.e., normal bone, osteopenia, and osteoporosis.

Publisher

North Atlantic University Union (NAUN)

Subject

Electrical and Electronic Engineering,General Physics and Astronomy

Reference19 articles.

1. C. Komar, et al, “Advancing method of assessing bone quality to expand screening for osteoporosis,” The Journal of Osteopathic Association, vol. 119, no. 3, pp. 147-154, 2019.

2. (text in Indonesian) N. Sani, P. Yuniastini, Yuliyana, “Tingkat pengetahuan osteoporosis sekunder dan perilaku pencegahan mahasiswa Universitas Malahayati,” Jurnal Ilmiah Kesehatan Sari Husada, vol. 11, no. 1, pp. 159-163, 2020.

3. (text in Indonesian) World Health Organization, “Pedoman Pengendalian Osteoporosis,” Technical Notes, 2019.

4. (text in Indonesian) Kementerian Kesehatan Republik Indonesia, “Data dan Kondisi Penyakit Osteoporosis di Indonesia,” Technical Notes, 2015.

5. M. Krugh & M.D. Langaker, “Dual energy x-ray absorptiometry,” Florida: StatPearls Publishing, 2022.

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