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2018 Fiscal Year Final Research Report

Improvement of the diagnosis of osteoporosis base on the high-accuracy ultrasound simulation with the relaxation mechanism of the material

Research Project

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Project/Area Number 16K01431
Research Category

Grant-in-Aid for Scientific Research (C)

Allocation TypeMulti-year Fund
Section一般
Research Field Medical systems
Research InstitutionKobe City College of Technology

Principal Investigator

NAGATANI Yoshiki  神戸市立工業高等専門学校, その他部局等, 准教授 (60448769)

Research Collaborator MATSUKAWA Mami  
CHIBA Ko  
TAKI Hirofumi  
OKUMURA Shigeaki  
WU Shuqiong  
AIBA Eriko  
SAEKI Takashi  
Haïat Guillaume  
Nguyen Vu-Hieu  
Naili Salah  
Wear Keith A.  
Project Period (FY) 2016-04-01 – 2019-03-31
Keywords超音波 / 骨粗鬆症 / 骨密度 / 骨質 / 橈骨 / FDTD / シミュレーション / 機械学習
Outline of Final Research Achievements

A numerical simulation system of a real-size 3-D model of the human radius including the cancellous bone part inside for calculating the propagation of ultrasound was created by using a high-resolution CT device for deriving the X-ray image of human bone. As a result, it was realized to investigate the behavior of the ultrasound when the bone density or the physical parameters of the bone were changed.
The investigation using the visco-elastic FDTD method was also performed. Here, some interesting effects of the viscosity of bone material on the parameters of the received waveforms were found.
In addition, a machine learning system was developed to directly estimate not only the bone density but also the geometry of the wave reflectors allocated in the propagation field by using the received waveform that propagates inside the bone-mimicking model.

Free Research Field

医工学

Academic Significance and Societal Importance of the Research Achievements

研究計画立案当初は,手首内部の超音波伝搬の挙動の理解や得られたパラメータの検討をおこない,それらから骨粗鬆症診断装置の改良につなげることのみを目的としていた。この目的は充分に達成され,超高齢社会のQOL維持・向上のための貢献ができたと考えているが,これに加えて,機械学習を用いて骨密度を推定する手法や,伝搬経路内部の反射体の形状推定までがおこなえる可能性を示すことができた。これは新たな研究領域が生まれたことを意味しており,将来の超音波利用方法の拡大に大きく貢献するものであると考えている。以上のように,本研究課題の成果は当初の予定を超えた領域にまで広がっており,非常に意義深い多数の知見が得られた。

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Published: 2020-03-30  

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