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Shehata E, Nippolainen E, Shaikh R, Ronkainen AP, Töyräs J, Sarin JK, Afara IO. Raman Spectroscopy and Machine Learning Enables Estimation of Articular Cartilage Structural, Compositional, and Functional Properties. Ann Biomed Eng 2023; 51:2301-2312. [PMID: 37328704 PMCID: PMC10518284 DOI: 10.1007/s10439-023-03271-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 06/01/2023] [Indexed: 06/18/2023]
Abstract
OBJECTIVE To differentiate healthy from artificially degraded articular cartilage and estimate its structural, compositional, and functional properties using Raman spectroscopy (RS). DESIGN Visually normal bovine patellae (n = 12) were used in this study. Osteochondral plugs (n = 60) were prepared and artificially degraded either enzymatically (via Collagenase D or Trypsin) or mechanically (via impact loading or surface abrasion) to induce mild to severe cartilage damage; additionally, control plugs were prepared (n = 12). Raman spectra were acquired from the samples before and after artificial degradation. Afterwards, reference biomechanical properties, proteoglycan (PG) content, collagen orientation, and zonal (%) thickness of the samples were measured. Machine learning models (classifiers and regressors) were then developed to discriminate healthy from degraded cartilage based on their Raman spectra and to predict the aforementioned reference properties. RESULTS The classifiers accurately categorized healthy and degraded samples (accuracy = 86%), and successfully discerned moderate from severely degraded samples (accuracy = 90%). On the other hand, the regression models estimated cartilage biomechanical properties with reasonable error (≤ 24%), with the lowest error observed in the prediction of instantaneous modulus (12%). With zonal properties, the lowest prediction errors were observed in the deep zone, i.e., PG content (14%), collagen orientation (29%), and zonal thickness (9%). CONCLUSION RS is capable of discriminating between healthy and damaged cartilage, and can estimate tissue properties with reasonable errors. These findings demonstrate the clinical potential of RS.
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Affiliation(s)
- Eslam Shehata
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- Diagnostic Imaging Center, Kuopio University Hospital, Kuopio, Finland
| | - Ervin Nippolainen
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | - Rubina Shaikh
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
| | | | - Juha Töyräs
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- Science Service Center, Kuopio University Hospital, Kuopio, Finland
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
| | - Jaakko K. Sarin
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- Department of Medical Physics, Medical Imaging Center, Pirkanmaa Hospital District, Tampere, Finland
| | - Isaac O. Afara
- Department of Technical Physics, University of Eastern Finland, Kuopio, Finland
- School of Information Technology and Electrical Engineering, The University of Queensland, Brisbane, Australia
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Afara IO, Oloyede A. Resolving the Near-Infrared Spectrum of Articular Cartilage. Cartilage 2021; 13:729S-737S. [PMID: 34643470 PMCID: PMC8808936 DOI: 10.1177/19476035211035417] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/15/2022] Open
Abstract
OBJECTIVE Spectroscopic techniques, such as near-infrared (NIR) spectroscopy, are gaining significant research interest for characterizing connective tissues, particularly articular cartilage, because there is still a largely unmet need for rapid, accurate and objective methods for assessing tissue integrity in real-time during arthroscopic surgery. This study aims to identify the NIR spectral range that is optimal for characterizing cartilage integrity by (a) identifying the contribution of its major constituents (collagen and proteoglycans) to its overall spectrum using proxy constituent models and (b) determining constituent-specific spectral contributions that can be used for assessment of cartilage in its physiological state. DESIGN The NIR spectra of cartilage matrix constituent models were measured and compared with specific molecular components of organic compounds in the NIR spectral range in order to identify their bands and molecular assignments. To verify the identified bands, spectra of the model compounds were compared with those of native cartilage. Since water obscures some bands in the NIR range, spectral measurements of the native cartilage were conducted under conditions of decreasing water content to amplify features of the solid matrix components. The identified spectral bands were then compared and examined in the resulting spectra of the intact cartilage samples. RESULTS As water was progressively eliminated from cartilage, the specific contribution of the different matrix components was observed to correspond with those identified from the proxy cartilage component models. CONCLUSION Spectral peaks in the regions 5500 to 6250 cm-1 and 8100 to 8600 cm-1 were identified to be effective for characterizing cartilage proteoglycan and collagen contents, respectively.
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Affiliation(s)
- Isaac O. Afara
- Department of Applied Physics,
University of Eastern Finland, Kuopio, Finland
- School of Information Technology and
Electrical Engineering, The University of Queensland, Brisbane, Queensland,
Australia
| | - Adekunle Oloyede
- School of Chemistry, Physics, and
Mechanical Engineering, Science and Engineering Faculty, Queensland University of
Technology, Brisbane, Queensland, Australia
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Khan B, Kafian-Attari I, Nippolainen E, Shaikh R, Semenov D, Hauta-Kasari M, Töyräs J, Afara IO. Articular cartilage optical properties in the near-infrared (NIR) spectral range vary with depth and tissue integrity. BIOMEDICAL OPTICS EXPRESS 2021; 12:6066-6080. [PMID: 34745722 PMCID: PMC8548021 DOI: 10.1364/boe.430053] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/28/2021] [Revised: 07/27/2021] [Accepted: 08/09/2021] [Indexed: 05/02/2023]
Abstract
Optical properties of biological tissues in the NIR spectral range have demonstrated significant potential for in vivo diagnostic applications and are critical parameters for modelling light interaction in biological tissues. This study aims to investigate the optical properties of articular cartilage as a function of tissue depth and integrity. The results suggest consistent wavelength-dependent variation in optical properties between cartilage depth-wise zones, as well as between healthy and degenerated tissue. Also, statistically significant differences (p<0.05) in both optical properties were observed between the different cartilage depth-wise zones and as a result of tissue degeneration. When taken into account, the outcome of this study could enable accurate modelling of light interaction in cartilage matrix and could provide useful diagnostic information on cartilage integrity.
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Affiliation(s)
- Bilour Khan
- University of Eastern Finland, Department of Applied Physics, Yliopistonranta 1, Kuopio, Finland, 70120, Finland
| | - Iman Kafian-Attari
- University of Eastern Finland, Department of Applied Physics, Yliopistonranta 1, Kuopio, Finland, 70120, Finland
| | - Ervin Nippolainen
- University of Eastern Finland, Department of Applied Physics, Yliopistonranta 1, Kuopio, Finland, 70120, Finland
| | - Rubina Shaikh
- University of Eastern Finland, Department of Applied Physics, Yliopistonranta 1, Kuopio, Finland, 70120, Finland
| | - Dmitry Semenov
- University of Eastern Finland, School of Computing, Lämsikatu 15, Joensuu, Finland, 80110, Finland
| | - Markku Hauta-Kasari
- University of Eastern Finland, School of Computing, Lämsikatu 15, Joensuu, Finland, 80110, Finland
| | - Juha Töyräs
- University of Eastern Finland, Department of Applied Physics, Yliopistonranta 1, Kuopio, Finland, 70120, Finland
- The University of Queensland, School of Information Technology, and Electrical Engineering, St. Lucia, Australia, QLD 4072, Australia
| | - Isaac O. Afara
- University of Eastern Finland, Department of Applied Physics, Yliopistonranta 1, Kuopio, Finland, 70120, Finland
- The University of Queensland, School of Information Technology, and Electrical Engineering, St. Lucia, Australia, QLD 4072, Australia
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Kushida Y, Ozeki N, Mizuno M, Katano H, Otabe K, Tsuji K, Koga H, Kishima K, Soma Y, Sekiya I. Two- and three-dimensional optical coherence tomography to differentiate degenerative changes in a rat meniscectomy model. J Orthop Res 2020; 38:2592-2600. [PMID: 32697398 DOI: 10.1002/jor.24808] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 05/18/2020] [Accepted: 06/12/2020] [Indexed: 02/04/2023]
Abstract
Optical coherence tomography (OCT) is an attractive tool for evaluating cartilage. We developed an OCT system that reconstructs and analyzes a three-dimensional (3D) OCT image by determining the cartilage surface and cartilage-bone boundary from the image taken with currently available OCT devices. We examined the usefulness of 3D renderings of OCT images. In a rat meniscectomized model, the tibia was harvested after 0, 2, 4, or 8 weeks (n = 6). We scanned 300 slices in the y-plane to cover a 4 × 3 × 6-mm section (x-plane; 10 µm × 400 pixels, y-plane; 10 µm × 300 pixels, z-plane; 12.66 µm × 500 pixels) of the medial tibial cartilage. The cartilage surface line and the cartilage-bone boundary were plotted semi-automatically. Slices from 300 two-dimensional (2D) sequential images were systematically and visually checked and corrected, as necessary. We set a region of interest in the cartilage and quantified the cartilage volume in the 3D image. The Osteoarthritis Research Society International (OARSI) histological score was also obtained. The cartilage volume determined using 3D OCT images was 0.291 ± 0.022 mm3 in the normal, 0.264 ± 0.009 mm3 at 2 weeks, 0.210 ± 0.012 mm3 at 4 weeks, and 0.205 ± 0.011 mm3 at 8 weeks. The cartilage volume significantly decreased at 4 and 8 weeks and was significantly correlated with the OARSI histological score (r = -0.674; P = .002). Although the 3D image information could be obtained from the 2D images, the 3D OCT images provided easier-to-understand information because the 3D reconstructed cartilage provided information about the smoothness of the surface, the area, and depth of the defect at a glance.
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Affiliation(s)
- Yoshihisa Kushida
- Center for Stem Cell and Regenerative Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Nobutake Ozeki
- Center for Stem Cell and Regenerative Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Mitsuru Mizuno
- Center for Stem Cell and Regenerative Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hisako Katano
- Center for Stem Cell and Regenerative Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Koji Otabe
- Center for Stem Cell and Regenerative Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | - Kunikazu Tsuji
- Department of Cartilage Regeneration, Graduate School, Tokyo Medical and Dental University, Tokyo, Japan
| | - Hideyuki Koga
- Department of Joint Surgery and Sports Medicine, Tokyo Medical and Dental University, Tokyo, Japan
| | | | - Yoshio Soma
- Sony Imaging Products & Solutions Inc, Tokyo, Japan
| | - Ichiro Sekiya
- Center for Stem Cell and Regenerative Medicine, Tokyo Medical and Dental University, Tokyo, Japan
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Otsuka Y, Ito A, Takeuchi M, Pal S, Tanaka H. Predictive evaluation of powder X-ray diffractograms of pharmaceutical formulation powders based on infrared spectroscopy. Biomed Mater Eng 2020; 31:307-317. [PMID: 32894235 DOI: 10.3233/bme-206003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/15/2022]
Abstract
BACKGROUND To ensure quality and stability, monitoring systems are recommended to analyze pharmaceutical manufacturing processes. OBJECTIVE This study was performed to predict powder X-ray diffraction (PXRD) patterns of formulation powders through attenuated total reflectance (ATR)-infrared (IR) spectroscopy in a nondestructive manner along with chemometrics. RESULTS Caffeine anhydrate, acetaminophen, and lactose monohydrate were grinded at six weight ratios. The six sample groups were evaluated using ATR-IR spectroscopy and PXRD analysis. Partial least squares models were constructed to predict the PXRD intensities of the samples from the ATR-IR spectra. The prediction accuracy on the prepared PLS regression models was as high as R2 = 0.993. CONCLUSIONS Linear relationships were obtained between the prediction data set and reference PXRD intensity at each degree. 2D PLS regression coefficient analysis enabled the analysis of the correlation between PXRD patterns and IR spectra.
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Affiliation(s)
- Yuta Otsuka
- Faculty of Pharmaceutical Sciences, Tokyo University of Science, 2641 Yamazaki, Noda, Chiba, Japan
| | - Akira Ito
- Graduate School of Pharmaceutical Sciences, Tokushima University, 1-78-1 Shomachi, Tokushima, Japan
| | - Masaki Takeuchi
- Institute of Biomedical Sciences, Tokushima University, 1-78-1 Shomachi, Tokushima, Japan
| | - Suvra Pal
- Department of Mathematics, University of Texas at Arlington, Arlington, Texas 76019, USA
| | - Hideji Tanaka
- Institute of Biomedical Sciences, Tokushima University, 1-78-1 Shomachi, Tokushima, Japan
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6
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Ala-Myllymäki J, Danso EK, Honkanen JTJ, Korhonen RK, Töyräs J, Afara IO. Optical spectroscopic characterization of human meniscus biomechanical properties. JOURNAL OF BIOMEDICAL OPTICS 2017; 22:1-10. [PMID: 29275548 DOI: 10.1117/1.jbo.22.12.125008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2017] [Accepted: 11/27/2017] [Indexed: 06/07/2023]
Abstract
This study investigates the capacity of optical spectroscopy in the visible (VIS) and near-infrared (NIR) spectral ranges for estimating the biomechanical properties of human meniscus. Seventy-two samples obtained from the anterior, central, and posterior locations of the medial and lateral menisci of 12 human cadaver joints were used. The samples were subjected to mechanical indentation, then traditional biomechanical parameters (equilibrium and dynamic moduli) were calculated. In addition, strain-dependent fibril network modulus and permeability strain-dependency coefficient were determined via finite-element modeling. Subsequently, absorption spectra were acquired from each location in the VIS (400 to 750 nm) and NIR (750 to 1100 nm) spectral ranges. Partial least squares regression, combined with spectral preprocessing and transformation, was then used to investigate the relationship between the biomechanical properties and spectral response. The NIR spectral region was observed to be optimal for model development (83.0%≤R2≤90.8%). The percentage error of the models are: Eeq (7.1%), Edyn (9.6%), Eϵ (8.4%), and Mk (8.9%). Thus, we conclude that optical spectroscopy in the NIR range is a potential method for rapid and nondestructive evaluation of human meniscus functional integrity and health in real time during arthroscopic surgery.
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Affiliation(s)
- Juho Ala-Myllymäki
- University of Eastern Finland, Department of Applied Physics, Kuopio, Finland
- Kuopio University Hospital, Diagnostic Imaging Center, Kuopio, Finland
| | - Elvis K Danso
- Colorado State University, Department of Mechanical Engineering, Fort Collins, Colorado, United States
| | | | - Rami K Korhonen
- University of Eastern Finland, Department of Applied Physics, Kuopio, Finland
- Kuopio University Hospital, Diagnostic Imaging Center, Kuopio, Finland
| | - Juha Töyräs
- University of Eastern Finland, Department of Applied Physics, Kuopio, Finland
- Kuopio University Hospital, Diagnostic Imaging Center, Kuopio, Finland
| | - Isaac O Afara
- University of Eastern Finland, Department of Applied Physics, Kuopio, Finland
- Kuopio University Hospital, Diagnostic Imaging Center, Kuopio, Finland
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Monitoring osteoarthritis progression using near infrared (NIR) spectroscopy. Sci Rep 2017; 7:11463. [PMID: 28904358 PMCID: PMC5597588 DOI: 10.1038/s41598-017-11844-3] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2017] [Accepted: 08/29/2017] [Indexed: 02/07/2023] Open
Abstract
We demonstrate in this study the potential of near infrared (NIR) spectroscopy as a tool for monitoring progression of cartilage degeneration in an animal model. Osteoarthritic degeneration was artificially induced in one joint in laboratory rats, and the animals were sacrificed at four time points: 1, 2, 4, and 6 weeks (3 animals/week). NIR spectra were acquired from both (injured and intact) knees. Subsequently, the joint samples were subjected to histological evaluation and glycosaminoglycan (GAG) content analysis, to assess disease severity based on the Mankin scoring system and to determine proteoglycan loss, respectively. Multivariate spectral techniques were then employed for classification (principal component analysis and support vector machines) and prediction (partial least squares regression) of the samples’ Mankin scores and GAG content from their NIR spectra. Our results demonstrate that NIR spectroscopy is sensitive to degenerative changes in articular cartilage, and is capable of distinguishing between mild (weeks 1&2; Mankin <=2) and advanced (weeks 4&6; Mankin =>3) cartilage degeneration. In addition, the spectral data contains information that enables estimation of the tissue’s Mankin score (error = 12.6%, R2 = 86.2%) and GAG content (error = 7.6%, R2 = 95%). We conclude that NIR spectroscopy is a viable tool for assessing cartilage degeneration post-injury, such as, post-traumatic osteoarthritis.
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8
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Afara IO, Singh S, Moody H, Zhang L, Oloyede A. Characterization of Articular Cartilage Recovery and Its Correlation with Optical Response in the Near-Infrared Spectral Range. Cartilage 2017; 8:307-316. [PMID: 28618866 PMCID: PMC5625859 DOI: 10.1177/1947603516662502] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 12/11/2022] Open
Abstract
OBJECTIVES In this study, we examine the capacity of a new parameter, based on the recovery response of articular cartilage, to distinguish between healthy and damaged tissues. We also investigate whether or not this new parameter correlates with the near-infrared (NIR) optical response of articular cartilage. DESIGN Normal and artificially degenerated (proteoglycan-depleted) bovine cartilage samples were nondestructively probed using NIR spectroscopy. Subsequently they were subjected to a load and unloading protocol, and the recovery response was logged during unloading. The recovery parameter, elastic rebound ( ER), is based on the strain energy released as the samples underwent instantaneous elastic recovery. RESULTS Our results reveal positive relationship between the rebound parameter and cartilage proteoglycan content (normal samples: 2.20 ± 0.10 N mm; proteoglycan-depleted samples: 0.50 ± 0.04 N mm for 1 hour of enzymatic treatment and 0.13 ± 0.02 N mm for 4 hours of enzymatic treatment). In addition, multivariate analysis using partial least squares regression was employed to investigate the relationship between ER and NIR spectral data. The results reveal significantly high correlation ( R2cal = 98.35% and R2val = 79.87%; P < 0.0001), with relatively low error (14%), between the recovery and optical response of cartilage in the combined NIR regions 5,450 to 6,100 cm-1 and 7,500 to 12,500 cm-1. CONCLUSION We conclude that ER can indicate the mechanical condition and state of health of articular cartilage. The correlation of ER with cartilage optical response in the NIR range could facilitate real-time evaluation of the tissue's integrity during arthroscopic surgery and could also provide an important tool for cartilage assessment in tissue engineering and regeneration research.
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Affiliation(s)
- Isaac Oluwaseun Afara
- Department of Electrical and Computer Engineering, Faculty of Engineering, Elizade University, Ilara-Mokin, Ondo, Nigeria,School of Chemistry, Physics, and Mechanical Engineering, Institute of Health and Biomedical Innovation, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia,Research and Innovation Centre, Elizade University, Ilara-Mokin, Ondo State, Nigeria,Isaac Oluwaseun Afara, Department of Electrical and Computer Engineering, Elizade University, Ilara-Mokin, Ondo, Nigeria.
| | - Sanjleena Singh
- Central Analytical Research Facility, Institute of Future Environment, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Hayley Moody
- School of Chemistry, Physics, and Mechanical Engineering, Institute of Health and Biomedical Innovation, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia
| | - Lihai Zhang
- Department of Infrastructure Engineering, University of Melbourne, Melbourne, Victoria, Australia
| | - Adekunle Oloyede
- School of Chemistry, Physics, and Mechanical Engineering, Institute of Health and Biomedical Innovation, Science and Engineering Faculty, Queensland University of Technology, Brisbane, Queensland, Australia,Research and Innovation Centre, Elizade University, Ilara-Mokin, Ondo State, Nigeria
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Lakin BA, Snyder BD, Grinstaff MW. Assessing Cartilage Biomechanical Properties: Techniques for Evaluating the Functional Performance of Cartilage in Health and Disease. Annu Rev Biomed Eng 2017; 19:27-55. [DOI: 10.1146/annurev-bioeng-071516-044525] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Affiliation(s)
- Benjamin A. Lakin
- Center for Advanced Orthopedic Studies, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215
| | - Brian D. Snyder
- Center for Advanced Orthopedic Studies, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts 02215
- Orthopedic Center, Children's Hospital, Boston, Massachusetts 02115
| | - Mark W. Grinstaff
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215
- Department of Chemistry, Boston University, Boston, Massachusetts 02215
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Eneh CTM, Afara IO, Malo MKH, Jurvelin JS, Töyräs J. Porosity predicted from ultrasound backscatter using multivariate analysis can improve accuracy of cortical bone thickness assessment. THE JOURNAL OF THE ACOUSTICAL SOCIETY OF AMERICA 2017; 141:575. [PMID: 28147588 DOI: 10.1121/1.4973572] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/23/2023]
Abstract
A rapidly growing area of interest in quantitative ultrasound assessment of bone is to determine cortical bone porosity from ultrasound backscatter. Current backscatter analyses are based on numerical simulations, while there are no published reports of successful experimental measurements. In this study, multivariate analysis is applied to ultrasound reflections and backscatter to predict cortical bone porosity. The porosity is then applied to estimate cortical bone radial speed of sound (SOS) and thickness using ultrasound backscatter signals obtained at 2.25 and 5 MHz center frequencies from cortical bone samples (n = 43) extracted from femoral diaphyses. The study shows that the partial least squares regression technique could be employed to successfully predict (R2 = 0.71-0.73) cortical porosity. It is found that this multivariate approach can reduce uncertainty in pulse-echo assessment of cortical bone thickness from 0.220 to 0.045 mm when porosity based radial SOS was applied, instead of a constant value from literature. Upon further validation, accurate estimation of cortical bone porosity and thickness may be applied as a financially viable option for fracture risk assessment of individuals.
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Affiliation(s)
- Chibuzor T M Eneh
- Diagnostic Imaging Center, Kuopio University Hospital, P.O. Box 100, FI-70029, Kuopio, Finland
| | - Isaac O Afara
- Diagnostic Imaging Center, Kuopio University Hospital, P.O. Box 100, FI-70029, Kuopio, Finland
| | - Markus K H Malo
- Department of Applied Physics, University of Eastern Finland, P.O. Box 1627, FI-70211, Kuopio, Finland
| | - Jukka S Jurvelin
- Department of Applied Physics, University of Eastern Finland, P.O. Box 1627, FI-70211, Kuopio, Finland
| | - Juha Töyräs
- Department of Applied Physics, University of Eastern Finland, P.O. Box 1627, FI-70211, Kuopio, Finland
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te Moller NCR, Pitkänen M, Sarin JK, Väänänen S, Liukkonen J, Afara IO, Puhakka PH, Brommer H, Niemelä T, Tulamo RM, Argüelles Capilla D, Töyräs J. Semi-automated International Cartilage Repair Society scoring of equine articular cartilage lesions in optical coherence tomography images. Equine Vet J 2016; 49:552-555. [DOI: 10.1111/evj.12637] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/07/2016] [Accepted: 08/25/2016] [Indexed: 11/27/2022]
Affiliation(s)
- N. C. R. te Moller
- Department of Equine Sciences; Utrecht University; Utrecht the Netherlands
| | - M. Pitkänen
- Department of Applied Physics; University of Eastern Finland; Kuopio Finland
| | - J. K. Sarin
- Department of Applied Physics; University of Eastern Finland; Kuopio Finland
- Diagnostic Imaging Centre; Kuopio University Hospital; Kuopio Finland
| | - S. Väänänen
- Department of Applied Physics; University of Eastern Finland; Kuopio Finland
- Diagnostic Imaging Centre; Kuopio University Hospital; Kuopio Finland
| | - J. Liukkonen
- Department of Applied Physics; University of Eastern Finland; Kuopio Finland
| | - I. O. Afara
- Department of Electrical and Computer Engineering; Elizade University; Ondo Nigeria
| | - P. H. Puhakka
- Department of Applied Physics; University of Eastern Finland; Kuopio Finland
- Diagnostic Imaging Centre; Kuopio University Hospital; Kuopio Finland
| | - H. Brommer
- Department of Equine Sciences; Utrecht University; Utrecht the Netherlands
| | - T. Niemelä
- Department of Equine and Small Animal Medicine; University of Helsinki; Helsinki Finland
| | - R.-M. Tulamo
- Department of Equine and Small Animal Medicine; University of Helsinki; Helsinki Finland
| | - D. Argüelles Capilla
- Department of Equine and Small Animal Medicine; University of Helsinki; Helsinki Finland
| | - J. Töyräs
- Department of Applied Physics; University of Eastern Finland; Kuopio Finland
- Diagnostic Imaging Centre; Kuopio University Hospital; Kuopio Finland
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12
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Tuchin VV. Polarized light interaction with tissues. JOURNAL OF BIOMEDICAL OPTICS 2016; 21:71114. [PMID: 27121763 DOI: 10.1117/1.jbo.21.7.071114] [Citation(s) in RCA: 128] [Impact Index Per Article: 16.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/04/2016] [Accepted: 03/22/2016] [Indexed: 05/02/2023]
Abstract
This tutorial-review introduces the fundamentals of polarized light interaction with biological tissues and presents some of the recent key polarization optical methods that have made possible the quantitative studies essential for biomedical diagnostics. Tissue structures and the corresponding models showing linear and circular birefringence, dichroism, and chirality are analyzed. As the basis for a quantitative description of the interaction of polarized light with tissues, the theory of polarization transfer in a random medium is used. This theory employs the modified transfer equation for Stokes parameters to predict the polarization properties of single- and multiple-scattered optical fields. The near-order of scatterers in tissues is accounted for to provide an adequate description of tissue polarization properties. Biomedical diagnostic techniques based on polarized light detection, including polarization imaging and spectroscopy, amplitude and intensity light scattering matrix measurements, and polarization-sensitive optical coherence tomography are described. Examples of biomedical applications of these techniques for early diagnostics of cataracts, detection of precancer, and prediction of skin disease are presented. The substantial reduction of light scattering multiplicity at tissue optical clearing that leads to a lesser influence of scattering on the measured intrinsic polarization properties of the tissue and allows for more precise quantification of these properties is demonstrated.
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Affiliation(s)
- Valery V Tuchin
- Saratov National Research State University, Research-Educational Institute of Optics and Biophotonics, 83 Astrakhanskaya street, Saratov 410012, RussiabInstitute of Precision Mechanics and Control of Russian Academy of Sciences, 24 Rabochaya street, Sarat
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