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Background: Raman spectroscopy is a non-invasive optical technique that can probe the molecular structure and conformation of biochemical constituents. The probability of Raman scattering is exceedingly low (∼10−10), and consequently up to now the practical application of Raman spectroscopy to clinical medicine has been limited by either the weak spectral signal or by the long data acquisition times. Recent advances in Raman hardware and probe design have reduced spectral acquisition times, paving the way for clinical applications. Methods: We present an integrated real-time Raman spectroscopy system for skin evaluation and characterization, which combines customized hardware features and software implementation. Real-time data acquisition and processing includes CCD dark-noise subtraction, wavelength calibration, spectral response calibration, intensity calibration, signal saturation detection, cosmic ray rejection, fluorescence background removal, and composition modeling. Real-time in vivo Raman measurement of volar forearm skin is presented to illustrate the methods and modeling. Results: The system design implemented full-chip vertical hardware binning to improve the signal-to-noise ratio by 16-fold. The total time for a single in vivo measurement with analysis can be reduced to 100 ms with this implementation. Human skin was well modeled using the base Raman spectra. Conclusion: In vivo real-time Raman can be a very promising research and practical technique for skin evaluation. [ABSTRACT FROM AUTHOR]

Background: Although many hair disorders can be readily diagnosed based on their clinical appearance, their progression and response to treatment are often difficult to monitor, particularly in quantitative terms. We introduce an innovative technique utilizing a smartphone and computerized image analysis to expeditiously and automatically measure and compute hair density and diameter in patients in real time. Methods: A smartphone equipped with a dermatoscope lens wirelessly transmits trichoscopy images to a computer for image processing. A black‐and‐white binary mask image representing hair and skin is produced, and the hairs are thinned into single‐pixel‐thick fiber skeletons. Further analysis based on these fibers allows morphometric characteristics such as hair shaft number and diameters to be computed rapidly. The hair‐bearing scalps of fifty participants were imaged to assess the precision of our automated smartphone‐based device in comparison with a specialized trichometry device for hair shaft density and diameter measurement. The precision and operation time of our technique relative to manual trichometry, which is commonly used by hair disorder specialists, is determined. Results: An equivalence test, based on two 1‐sided t tests, demonstrates statistical equivalence in hair density and diameter values between this automated technique and manual trichometry within a 20% margin. On average, this technique actively required 24 seconds of the clinician's time whereas manual trichometry necessitated 9.2 minutes. Conclusion: Automated smartphone‐based trichometry is a rapid, precise, and clinically feasible technique which can significantly facilitate the assessment and monitoring of hair loss. Its use could be easily integrated into clinical practice to improve standard trichoscopy. [ABSTRACT FROM AUTHOR]

Background/purposes Fluorescence emission from in vivo cutaneous melanin was recently detected under near-infrared ( NIR) excitation by our group. We then built a prototype NIR autofluorescence imaging system to observe and characterize the melanin distribution in human skin. In this article, we reported a new setup of NIR fluorescence imaging system and calibration methods to optimize the system for better clinical feasibility and clearer image. Methods The imaging system was designed to perform both fluorescence and reflectance imaging with a 785-nm fiber-coupled laser source. The illumination light was purified by a 785-nm bandpass filter for fluorescence excitation; while the spontaneous components were selected by a longpass filter for NIR reflectance imaging. A hand-controlled filter wheel was used to switch these two filters for different imaging modes. A dichroic filter was used to guide the illuminating light onto the skin surface for excitation. Reflectance and fluorescence signals were collected sequentially by a NIR optimized CCD camera. The captured images were calibrated by the reflectance images of a standard reflectance disk for non-uniform illuminations and light collection efficiencies. Results The clinical results demonstrated that NIR fluorescence intensities and distribution patterns vary among lesion types. It was also confirmed that pigmented skin lesions emitted higher NIR fluorescence than the surrounding normal skin due to the presentation of higher concentrations of cutaneous melanin within the lesions. Conclusion NIR autofluorescence imaging system could be utilized as a powerful tool for visualizing melanin distribution in pigmented skin lesions and as a potential method for aiding melanoma detection. [ABSTRACT FROM AUTHOR]