Near-infrared spectroscopy for structural bone assessment

Varun J Sharma; John A Adegoke; Isaac O Afara; Kathryn Stok; Eric Poon; Claire L Gordon; Bayden R Wood; Jaishankar Raman

doi:10.1302/2633-1462.44.BJO-2023-0014.R1

Near-infrared spectroscopy for structural bone assessment

Bone Jt Open. 2023 Apr 7;4(4):250-261. doi: 10.1302/2633-1462.44.BJO-2023-0014.R1.

Authors

Varun J Sharma^{1

2

3}, John A Adegoke^{3

4}, Isaac O Afara^{3

4

5

6}, Kathryn Stok⁷, Eric Poon^{3

8}, Claire L Gordon^{8

9}, Bayden R Wood^{3

4}, Jaishankar Raman^{1

2

3}

Affiliations

¹ Department of Surgery, Melbourne Medical School, University of Melbourne, Melbourne, Australia.
² Brian F. Buxton Department of Cardiac and Thoracic Aortic Surgery, Austin Hospital, Melbourne, Australia.
³ Spectromix Laboratory, Melbourne, Australia.
⁴ Centre for Biospectroscopy, Monash University, Melbourne, Australia.
⁵ Biomedical Spectroscopy Laboratory, Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.
⁶ School of Information Technology and Electrical Engineering Faculty of Engineering, Architecture and Information Technology, Melbourne, Australia.
⁷ Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia.
⁸ Department of Medicine, Melbourne Medical School, University of Melbourne, Melbourne, Australia.
⁹ Department of Infectious Diseases, Austin Hospital, Melbourne, Australia.

PMID: 37051828
PMCID: PMC10079377
DOI: 10.1302/2633-1462.44.BJO-2023-0014.R1

Abstract

Disorders of bone integrity carry a high global disease burden, frequently requiring intervention, but there is a paucity of methods capable of noninvasive real-time assessment. Here we show that miniaturized handheld near-infrared spectroscopy (NIRS) scans, operated via a smartphone, can assess structural human bone properties in under three seconds. A hand-held NIR spectrometer was used to scan bone samples from 20 patients and predict: bone volume fraction (BV/TV); and trabecular (Tb) and cortical (Ct) thickness (Th), porosity (Po), and spacing (Sp). NIRS scans on both the inner (trabecular) surface or outer (cortical) surface accurately identified variations in bone collagen, water, mineral, and fat content, which then accurately predicted bone volume fraction (BV/TV, inner R² = 0.91, outer R² = 0.83), thickness (Tb.Th, inner R² = 0.9, outer R² = 0.79), and cortical thickness (Ct.Th, inner and outer both R² = 0.90). NIRS scans also had 100% classification accuracy in grading the quartile of bone thickness and quality. We believe this is a fundamental step forward in creating an instrument capable of intraoperative real-time use.