Proceedings Article | 14 May 2018
KEYWORDS: Reflectivity, Principal component analysis, Calibration, Near infrared, In vivo imaging, Sensors, Near infrared spectroscopy, Analytical research, Tissues, Chemometrics
Human skeletal muscles may undergo qualitative and quantitative, physiological and pathological changes during life. Some of these changes may be detected with imaging techniques, others with immunohystochemical and molecular analysis. Both these types of investigation are expensive, time consuming, and not readily available. Therefore, at present, a cheap, reliable, and widely applicable technique for non-invasive in vivo analysis of human muscles is lacking. Here we propose optical spectroscopy as a tool that can be added to clinical investigation without significant cost and time penalties. Recent advances in materials and fabrication techniques provided portable, performant, sensing optical spectrometers readily operated by user-friendly cabled or wireless systems. Such systems allow rapid, non-invasive and not destructive quantitative analysis of human tissues. In this investigation, we tested whether infrared spectroscopy techniques, currently utilized in many areas as primary/secondary raw materials sector, cultural heritage, agricultural/food industry, environmental remote and proximal sensing, pharmaceutical industry, etc., could be applied in living humans to categorize muscles. We acquired muscles reflectance spectra in the Vis-SWIR regions (350-2500 nm), utilizing an ASD FieldSpec 4™ Standard-Res Spectroradiometer with a spectral sampling capability of 1.4 nm at 350- 1000 nm and 1.1 nm at 1001-2500 nm. Spectra were collected from the upper limb muscles (i.e. biceps, a forearm flexor, and triceps, a forearm extensor) placed in fixed limb postures (elbow angle approximately 90°) of 22 healthy subjects (age 25-89 years, 11 females). Spectra off-line analysis included preliminary pre-processing for signal scattering reduction, Principal Component Analysis (PCA) aimed to spectral grouping and Partial Least-Squares Discriminant Analysis (PLS-DA) for implementing discrimination/prediction models. Spectral data were correlated with anthropometric variables. Optical spectroscopy proved effective for studying human muscles in vivo. Vis-SWIR spectra acquired from the arm detect muscles from other tissues, and distinguished flexors from extensors.
