Histopathological analysis and in vivo optical spectroscopy were used to discriminate several histological stages of UV-irradiated mouse skin. At different times throughout the $30-week$ irradiation, autofluorescence (AF) and diffuse reflectance (DR) spectra were acquired in a bimodal approach. Then skin was sampled and processed to be classified, according to morphological criteria, into four histological categories: normal, and three types of hyperplasia (compensatory, atypical, and dysplastic). After extracting spectral characteristics, principal component analysis (data reduction) and the $k$-nearest neighbor classifying method were applied to compare diagnostic performances of monoexcitation AF (based on each of the seven excitation wavelengths: 360, 368, 390, 400, 410, 420, and $430nm$), multiexcitation AF (combining the seven excitation wavelengths), DR, and bimodal spectroscopies. Visible wavelengths are the most sensitive ones to discriminate compensatory from precancerous (atypical and dysplastic) states. Multiexcitation AF provides an average 6-percentage-point increased sensitivity compared to the best scores obtained with monoexcitation AF for all pairs of tissue categories. Bimodality results in a 4-percentage-point increase of specificity when discriminating the three types of hyperplasia. Thus, bimodal spectroscopy appears to be a promising tool to discriminate benign from precancerous stages; clinical investigations should be carried out to confirm these results.

This paper deals with multi-class classification of skin pre-cancerous stages based on bimodal spectroscopic features combining spatially resolved AutoFluorescence (AF) and Diffuse Reflectance (DR) measurements. A new hybrid method to extract and select features is presented. It is based on Discrete Cosine Transform (DCT) applied to AF spectra and on Mutual Information (MI) applied to DR spectra. The classification is performed by means of a multi-class SVM: the M-SVM². Its performance is compared with the one of the One-Versus-All (OVA) decomposition method involving bi-class SVMs as base classifiers. The results of this study show that bimodality and the choice of an adequate spatial resolution allow for a significant increase in diagnostic accuracy. This accuracy can get as high as 81.7% when combining different distances in the case of bimodality.

This contribution presents the development of an optical spectroscopy device, called SpectroLive, that allows spatially-resolved multiply-excited autofluorescence and diffuse reflectance measurements. Besides describing the device, this study aims at presenting the metrological and safety regulation validations performed towards its aimed application to skin carcinoma in vivo diagnosis. This device is made of six light sources and four spectrometers for detection of the back-scattered intensity spectra collected through an optical probe (made of several optical fibers) featuring four source-to-detector separations (from 400 to 1000 µm). In order to be allowed by the French authorities to be evaluated in clinics, the SpectroLive device was successfully checked for electromagnetic compatibility and electrical and photobiological safety. In order to process spectra, spectral correction and metrological calibration were implemented in the post-processing software. Finally, we characterized the device’s sensitivity to autofluorescence detection: excitation light irradiance at the optical probe tip in contact with skin surface ranges from 2 to 11 W/m², depending on the light source. Such irradiances combined to sensitive detectors allow the device to acquire a full spectroscopic sequence within 6 s which is a short enough duration to be compatible with optical-guided surgery. All these results about sensitivity and safety make the SpectroLive device mature enough to be evaluated through a clinical trial that aims at evaluating its diagnostic accuracy for skin carcinoma diagnosis.

SignificanceThe clinical use of optical methods for in vivo skin imaging is limited by skin strong scattering properties, which reduce image contrast and probing depth. The efficiency of optical methods can be improved by optical clearing (OC). However, for the use of OC agents (OCAs) in a clinical setting, compliance with acceptable non-toxic concentrations is required.AimOC of in vivo human skin, combined with physical and chemical methods to enhance skin permeability to OCAs, was performed to determine the clearing-effectiveness of biocompatible OCAs using line-field confocal optical coherence tomography (LC-OCT) imaging.ApproachNine types of OCAs mixtures were used in association with dermabrasion and sonophoresis for OC protocol on three volunteers hand skin. From 3D images obtained every 5 min for 40 min, the intensity and contrast parameters were extracted to assess their changes during the clearing process and evaluate each OCAs mixture’s clearing efficacy.ResultsThe LC-OCT images average intensity and contrast increased over the entire skin depth with all OCAs. The best image contrast and intensity improvement was observed using the polyethylene glycol, oleic acid, and propylene glycol mixture.ConclusionsComplex OCAs featuring reduced component concentrations that meet drug regulation-established biocompatibility requirements were developed and proved to induce significant skin tissues clearing. By allowing deeper observations and higher contrast, such OCAs in combination with physical and chemical permeation enhancers may improve LC-OCT diagnostic efficacy.

This work is first a description of a statistical simulation algorithm developed for simulating the spectral absorption and emission of several fluorophores in an absorbing and diffusing multilayer model. Second, a detailed experimental validation of the simulation program is conducted on two sets of liquid and solid multilayer phantoms, containing one, two, or three fluorophores, within absorbing and scattering media. Experimental spatially resolved reflectance spectra are acquired in the wavelength band $400to800nm$ and compared to corresponding simulated spectra. The degree of similarity between experimentation and simulation data is quantified. The results obtained underline good correlations with mean errors varying from 2 to 10%, depending on the number of layers and on the complexity of the phantom’s composition.

In the context of cutaneous carcinoma diagnosis based on in vivo optical biopsy, Diffuse Reflectance (DR) spectra, acquired using a Spatially Resolved (SR) sensor configuration, can be analyzed to distinguish healthy from pathological tissues. The present contribution aims at studying the depth distribution of SR-DR-detected photons in skin from the perspective of analyzing how these photons contribute to acquired spectra carrying local physiological and morphological information. Simulations based on modified Cuda Monte Carlo Modeling of Light transport were performed on a five-layer human skin optical model with epidermal thickness, phototype and dermal blood content as variable parameters using (i) wavelength-resolved scattering and absorption properties and (ii) the geometrical configuration of a multi-optical fiber probe implemented on an SR-DR spectroscopic device currently used in clinics. Through histograms of the maximum probed depth and their exploitation, we provide numerical evidence linking the characteristic penetration depth of the detected photons to their wavelengths and four source–sensor distances, which made it possible to propose a decomposition of the DR signals related to skin layer contributions.