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Title: | Near-infrared spectroscopy for structural bone assessment. | Austin Authors: | Sharma, Varun J;Adegoke, John A;Afara, Isaac O;Stok, Kathryn;Poon, Eric;Gordon, Claire L ;Wood, Bayden R;Raman, Jaishankar | Affiliation: | Thoracic Surgery Department of Surgery, Melbourne Medical School, University of Melbourne, Melbourne, Australia. Spectromix Laboratory, Melbourne, Australia.;Centre for Biospectroscopy, Monash University, Melbourne, Australia.;Biomedical Spectroscopy Laboratory, Department of Applied Physics, University of Eastern Finland, Kuopio, Finland.;School of Information Technology and Electrical Engineering Faculty of Engineering, Architecture and Information Technology, Melbourne, Australia. Department of Biomedical Engineering, University of Melbourne, Melbourne, Australia. Cardiac Surgery Department of Medicine, Melbourne Medical School, University of Melbourne, Melbourne, Australia.;Department of Infectious Diseases, Austin Hospital, Melbourne, Australia. Spectromix Laboratory, Melbourne, Australia.;Centre for Biospectroscopy, Monash University, Melbourne, Australia. Department of Surgery, Melbourne Medical School, University of Melbourne, Melbourne, Australia.;Brian F. Buxton Department of Cardiac and Thoracic Aortic Surgery, Austin Hospital, Melbourne, Australia.;Spectromix Laboratory, Melbourne, Australia. |
Issue Date: | 7-Apr-2023 | Date: | 2023 | Publication information: | Bone & Joint Open 2023; 4(4) | 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. | URI: | https://ahro.austin.org.au/austinjspui/handle/1/32711 | DOI: | 10.1302/2633-1462.44.BJO-2023-0014.R1 | ORCID: | 0000-0002-5008-4113 |
Journal: | Bone & Joint Open | Start page: | 250 | End page: | 261 | PubMed URL: | 37051828 | ISSN: | 2633-1462 | Type: | Journal Article |
Appears in Collections: | Journal articles |
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