Optical Bone Densitometry

Osteoporosis is a common skeletal disease that increases the risk of fractures, making early detection and regular assessment important. We are developing optical bone densitometry as a simple, safe, and accessible method for evaluating bone health using near-infrared light.

Our approach estimates bone density from light transmitted and scattered through the wrist. By combining optical measurements with computational modeling and machine learning, we aim to improve the accuracy and robustness of bone density estimation. Recent studies have extended this approach to multidirectional optical measurements, providing richer information about the internal bone structure.

Ultimately, our goal is to develop a compact and radiation-free technology that could complement conventional bone density measurements and facilitate routine screening for osteoporosis.

Publications
Kaname Miura, Hidenori Matsubara, Shigeo M. Tanaka, Development of optical bone densitometry using near-infrared light, Journal of Mechanical Engineering, vol 5-4, 60-67, 2018.
Kaname Miura, Anak Khantachawana, and Shigeo M. Tanaka, Optical bone densitometry robust to variation of soft tissue using machine learning techniques: validation by Monte Carlo simulation, Journal of Biomedical Optics, Vol.27, No.5, Paper Number: 056004 (16 pages), 2022, doi: 10.1117/1.JBO.27.5.056004
Kaname Miura, Anak Khantachawana, Tsuyoshi Wakamori, Hidenori Matsubara, and Shigeo M. Tanaka, Optical Bone Densitometry Insensitive to Skin Thickness, Biomedical Engineering / Biomedizinische Technik, Vol. 67, No. 6, pp. 503-512. 2022, doi: 10.1515/bmt-2021-0314
Kaname Miura, Shigeo M. Tanaka, Chanisa Chotipanich, Thanapon Chobpenthai, Attapon Jantarato, Anak Khantachawana, Osteoporosis prediction using machine‑learned optical bone densitometry data, Annals of Biomedical Engineering, Vol. 52, No. 2, pp. 396-405, 2024, doi: 10.1007/s10439-023-03387-8
Shigeo M. Tanaka, Kaito Yoshikawa, Multidirectional Optical bone densitometry using a simulation-based machine learning model: Experimental validation with bone phantoms, Annals of Biomedical Engineering, 2026, doi: 10.1007/s10439-026-04258-8

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