Comprehensive assessment of the condition of bone and muscle tissues using quantitative ultrasound (BoMUS)

Project No. Izp-2021/1-0290

The goal of the project is to explore the scientific basis of a new ultrasound technology (BoMUS) in order to comprehensively characterize the condition of bones and muscles in terms of tissue composition and structure.

Project collaboration partner: Riga Technical University.

The BoMUS technology is based on enhanced ultrasound signal processing obtained by scanning the human extremities using various acoustic modes and employing image recognition methods. Decision-making rules or multiple informative ultrasound indicators help assess the relevant factors of interest (FOIs) that determine the quality of bone and muscle tissues. FOIs include cortical thickness, porosity, and degree of mineralization for bone tissue, as well as lean muscle content, subcutaneous and intramuscular fat, and muscle edema. The key innovation lies in the multidimensional analysis of digital signal matrices at different ultrasound frequencies using elements of artificial intelligence. The integration of bone and muscle components into a comprehensive diagnostic system is particularly advantageous, considering the concept of bone-muscle relationships and their shared monitoring in aspects of aging, physical activity, immobilization, osteoporosis, and sarcopenia. BoMUS will overcome existing limitations of quantitative ultrasound and expand diagnostic capabilities. Project activities include experimental design, laboratory research, development of data processing, technology testing, and result dissemination. The outcomes will open up prospects for further research and development to achieve higher Technology Readiness Levels (TRL) and for commercialization efforts.

Publications

V. Glushkov, N. V. Glushkova, O. A. Ermolenko and A. M. Tatarinov.. Extracting guided wave characteristics of bone phantoms from ultrasonometric data for osteoporosis diagnosis. 2022 Days on Diffraction (DD), IEEE, 2022. : https://doi.org/10.1109/DD55230.2022.9961013 (https://www.edi.lv/en/publications/extracting-guided-wave-characteristics-of-bone-phantoms-from-ultrasonometric-data-for-osteoporosis-diagnosis-2/)

Sisojevs, A.; Tatarinov, A. and Chaplinska, A. (2023). Evaluation of Factors-of-Interest in Bone Mimicking Models Based on DFT Analysis of Ultrasonic Signals. In Proceedings of the 12th International Conference on Pattern Recognition Applications and Methods – ICPRAM; ISBN 978-989-758-626-2; ISSN 2184-4313, SciTePress, pages 914-919. DOI: 10.5220/0011742800003411 (https://www.scitepress.org/PublishedPapers/2023/117428/)

Aleksejs Tatarinov*, Aleksandrs Sisojevs and Anastasija Chaplinska (2023). Pattern recognition based approach for extraction of factors of interest from ultrasonic data. In: International Workshop on Embedded Digital Intelligence (IWoEDI’2023), (https://events.edi.lv/iwoedi2023/wp-content/uploads/sites/2/2023/06/IWoEDI-2023-Pattern-recognition-algorithms-for-extraction-of-factors-of-interest-from-ultrasonic-data.pdf)

Chuchalina, M.; Sisojevs, A. and Tatarinov, A. (2024). Determination of Factors of Interest in Bone Models Based on Ultrasonic Data. In Proceedings of the 13th International Conference on Pattern Recognition Applications and Methods – ICPRAM; ISBN 978-989-758-684-2; ISSN 2184-4313, SciTePress, pages 281-287. DOI: 10.5220/0012358500003654 (https://www.scitepress.org/PublicationsDetail.aspx?ID=z3HhxwvVLoI=&t=1)

Presentations at international conferences:

Alexey Tatarinov, Aleksandrs Sisojevs, Anastasia Chaplinska “Identification of Osteoporosis Diagnostic Signs in Cortical Bone Models Examined by Axial Transmission Ultrasound” QMSKI  13.06.2022. – 17.06. 2022. Noordwijk, Netherlands. https://qmski.org/.

Participating scientists

    Mg.sc.ing. Dans Laksis
    Mg.sc.ing. Dans Laksis

    Research assistant

    [protected]
    Mg. math. Tamāra Laimiņa

    Research assistant

    +371 67558202; +371 67558207
    [protected]