Near infrared spectroscopy as a tool for in vivo analysis of human muscles

Bonifazi, Giuseppe; Cardillo, Alessandra; Currà, Antonio; Gasbarrone, Riccardo; Serranti, Silvia

doi:10.1117/12.2304311

Cited by 7 publications

(8 citation statements)

References 49 publications

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“…The percentage reflectance spectrum shown in Figure 11 agrees with previously reported works where reflectance profiles were taken both experimentally 25,48,49 and with Monte Carlo simulation, 32,44 in the given spectral range. The spatial surface reflectance variation for a given set of tissue optical properties is shown in Figure 12.…”

Section: Discussionsupporting

confidence: 88%

Quantification of soft tissue parameters from spatially resolved diffuse reflectance finite element models

Vasudevan

Sujatha

2021

Numer Methods Biomed Eng

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Spatially resolved diffuse reflectance spectroscopy (SRDRS) is a non-invasive optical technique that helps in clinical diagnosis of various tissue microcirculation and skin pigmentation disorders based on collected backscattered light from multi-layered tissue. The extraction of the optical properties from the reflectance spectrum using analytical solutions is laborious. Model-based light tissue interaction studies help in quantifying the optical properties. This work presents the use of finite element models of light tissue interaction for this purpose. A bilayer model mimicking human skin was considered and the diffused reflectance spectra at multiple detector points were generated using finite element modelling for varying melanin concentration, epidermal thickness, blood volume fraction, oxygen saturation and scattering components. The reflectance value based on varying optical parameters from multiple detection points lead to the generation of a look-up table (LUT), which is further used for finding the tissue parameters that contribute to the spatially resolved reflectance values. The tissue parameters estimated after inverse modelling showed a high degree of agreement with the expected tissue parameters for a test dataset different from the training dataset.

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Section: Discussionsupporting

confidence: 88%

Quantification of soft tissue parameters from spatially resolved diffuse reflectance finite element models

Vasudevan

Sujatha

2021

Numer Methods Biomed Eng

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“…Near-infrared spectroscopy (NIRS) is an in-vivo technique that has undergone considerable testing in human subjects [305][306][307][308][309][310][311] . It utilises wavelengths between 700 nm and 1000 nm, which can penetrate the skull and several millimetres into brain tissue, to monitor brain cortical perfusion and oxygenation.…”

Section: Near-infrared Spectroscopymentioning

confidence: 99%

Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury

Harris

Rickard

Butt

et al. 2023

IEEE Rev. Biomed. Eng.

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The study of ocular manifestations of neurodegenerative disorders, Oculomics, is a growing field of investigation for early diagnostics, enabling structural and chemical biomarkers to be monitored overtime to predict prognosis. Traumatic brain injury (TBI) triggers a cascade of events harmful to the brain, which can lead to neurodegeneration. TBI, termed the "silent epidemic" is becoming a leading cause of death and disability worldwide. There is currently no effective diagnostic tool for TBI, and yet, earlyintervention is known to considerably shorten hospital stays, improve outcomes, fasten neurological recovery and lower mortality rates, highlighting the unmet need for techniques capable of rapid and accurate point-of-care diagnostics, implemented in the earliest stages. This review focuses on the latest advances in the main neuropathophysiological responses and the achievements and shortfalls of TBI diagnostic methods. Validated and emerging TBI-indicative biomarkers are outlined and linked to ocular neuro-disorders. Methods detecting structural and chemical ocular responses to TBI are categorised along with prospective chemical and physical sensing techniques. Particular attention is drawn to the potential of Raman spectroscopy as a non-invasive sensing of neurological molecular signatures in the ocular projections of the brain, laying the platform for the first tangible path towards alternative point-of-care diagnostic technologies for TBI.

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“…The Contiguous Block (with a number of data splits equal to 10) cross-validation method was chosen (Figure 2) (Ballabio and Consonni 2013), in order to evaluate the complexity of models and to select the appropriate number of latent variables (LVs). Moreover, the optimal number of 3 LVs was decided by the smaller difference between RMSEC and RMSECV (Balage et al, 2018;Currà et al, 2019;Suhandy and Yulia, 2019).…”

Section: Hyperspectral Data Analysismentioning

confidence: 99%

Recycling-oriented characterization of PET waste stream by SWIR hyperspectral imaging and variable selection methods

Bonifazi

Capobianco

Cucuzza

et al. 2022

Volume 18 - March 2022

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The proposed study was carried out to develop a fast and efficient strategy for plastic waste sensor-based sorting in recycling plants, based on hyperspectral imaging (HSI), combined with variable selection methods, to produce a high-quality recycled polyethylene terephthalate (PET) flakes stream. Variable selection techniques were applied in order to identify a limited number of spectral bands useful to recognize the presence of other plastic materials, considered as contaminant, inside a stream of recycled PET flakes, reducing processing time as requested by sorting online applications. Post-consumer plastic samples were acquired by HSI device working in the short-wave infrared (SWIR) range (1000 - 2500 nm). As a first step, the hypercubes were processed applying chemometric logics to build a partial least squares discriminant analysis (PLSDA) classification model using the full investigated spectral range, able to identify PET and contaminant classes. As a second step, two different variable selection methods were then applied, i.e., interval PLSDA (I-PLSDA) and variable importance in projection (VIP) scores, in order to identify a limited number of spectral bands useful to recognize the two classes and to evaluate the best method, showing efficiency values close to those obtained by the full spectrum model. The best result was achieved by the VIP score method with an average efficiency value of 0.98. The obtained results suggested that the variables selection method can represent a powerful approach for the sensor-based sorting-online, decreasing the amount of data to be processed and thus enabling faster recognition compared to the full spectrum model.

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Near infrared spectroscopy as a tool for in vivo analysis of human muscles

Cited by 7 publications

References 49 publications

Quantification of soft tissue parameters from spatially resolved diffuse reflectance finite element models

Quantification of soft tissue parameters from spatially resolved diffuse reflectance finite element models

Review: Emerging Eye-Based Diagnostic Technologies for Traumatic Brain Injury

Recycling-oriented characterization of PET waste stream by SWIR hyperspectral imaging and variable selection methods

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