WO2024060018A1

WO2024060018A1 - Non-invasive method for detection, visualization and/or quantification of an endogenous fluorophore such as melanin in a biological tissue

Info

Publication number: WO2024060018A1
Application number: PCT/CN2022/119944
Authority: WO
Inventors: Juan Liu; Yinfeng FU; Emmanuel Malherbe; Ana-Maria PENA; Shanshan ZANG; Juanjuan Chen
Original assignee: Juan Liu; L'oreal
Priority date: 2022-09-20
Filing date: 2022-09-20
Publication date: 2024-03-28

Abstract

Method for detection, quantification and/or visualization of an endogenous fluorophore, such as melanin, in a biological tissue, the method comprising: acquiring a plurality of two-dimensional (2D) multiphoton images of fluorescence intensity, or combined multiphoton FLIM images, each image being acquired in a plane substantially perpendicular to a surface of the biological tissue, processing the images to detect a boundary of the surface of the biological tissue and to detect the endogenous fluorophore, and generating, on the basis of the processed images, information representative of a distribution of the endogenous fluorophore in said biological tissue with regard to the boundary, in particular as a function of the distance from the boundary.

Description

NON-INVASIVE METHOD FOR DETECTION, VISUALIZATION AND/OR QUANTIFICATION OF AN ENDOGENOUS FLUOROPHORE SUCH AS MELANIN IN A BIOLOGICAL TISSUE

Field of the invention

The present invention relates to the observation of biological tissues, in particular keratin materials such as the skin.

The invention relates more particularly but not exclusively to the methods aimed at determining the distribution of melanin in biological tissues, with a view in particular to evaluating the action of a cosmetic treatment thereon.

Background

The colour of some biological tissues is closely linked to the amount and the three-dimensional distribution of melanin. Today, the characterization of the amount and of the distribution of melanin can be carried out either ex vivo or in vivo using different methods.

Currently, the gold standard method for melanin quantification in skin is high-performance liquid chromatography (HPLC) chemical analysis of melanin degradation products. Although very specific, it requires ex vivo samples degradation and provides no information on melanin’s epidermal distribution. Fontana-Masson staining of transverse skin sections allows insights in 2D melanin distribution and content but has the drawback of non-specific stratum corneum (SC) staining, while Warthin-Starry stain may provide a more sensitive and specific melanin detection. Transmission electron microscopy enables melanosomes pattern analysis within epidermal cells and its variations according to skin phenotype.

Over the years, the possibility to provide a non-invasive melanin detection based on its optical properties, broad-band UV and visible absorption, fluorescence emission spectrum and lifetime, was investigated using different techniques. Spontaneous Raman spectroscopy found pheomelanin to have a specific peak within the “silent region” of the Raman spectrum, thus offering a straightforward route to specific non-invasive 3D pheomelanin detection in skin samples by CARS (Coherent anti-Stokes Raman Scattering) imaging. Recently, a combined analysis of specific Raman bands along with the NIR one-photon excited skin autofluorescence was used to estimate an xz depth-profile of melanin fraction in vivo, but this method lacks spatial localization of melanin within the cells and cannot image the entire epidermis. Pump-probe imaging has also been proven of value in analyzing melanin within 2D thin skin sections of pigmented lesions, namely for its eumelanin/pheomelanin discrimination.

Melanin imaging based on its endogenous fluorescence was evidenced in 1979 by conventional one-photon excited fluorescence microscopy on human skin sections and 20 years later in vivo on forearm skin using two photon excitation /multiphoton microscopy.

Multiphoton imaging enables three-dimensional characterization of biological tissues with sub-micrometer resolution. The imaging depth varies according to tissues, it may be approximately 200 μm for human skin. Using endogenous autofluorescence signals from keratin, NAD (P) H and FAD metabolic coenzymes and melanin, multiphoton microscopy provides non-invasive label free 3D visualization of epidermal layers and melanin’s epidermal distribution.

Upon multiphoton excitation at 760 nm, an intensity-based melanin detection method was proposed in vitro on reconstructed pigmented epidermis, for example as in FR 2 944 425 and in vivo on human skin, for example as in Ait El Madani, H. et al. “In vivo multiphoton imaging of human skin: assessment of topical corticosteroid-induced epidermis atrophy and depigmentation” J Biomed Opt 17, 026009 (2012) . This method was also applied to the quantitative assessment of melanin content in vitro on Chinese reconstructed pigmented epidermis (RPE) model, as explained in Qiu, J. et al. “The skin-depigmenting potential of Paeonia lactiflora root extract and paeoniflorin: In vitro evaluation using reconstructed pigmented human epidermis” Int J Cosmet Sci 38, 444-451, (2016) .

The intensity-based melanin detection method, disclosed in FR 2 944 425 is based on the fact that, in the skin, at the level of the basal layers of the epidermis, the highly concentrated melanin exhibits high fluorescence signal intensities, stronger than those of the other endogenous fluorophores. The pixels which have a strong intensity are attributed to melanin. This intensity-based approach works in the basal epidermal layers where melanin is highly concentrated and exhibits fluorescence signal intensities stronger than those of other endogenous fluorophores, but not in SC containing keratins with high fluorescence intensities. Moreover, pixels with low melanin concentration, low fluorescence intensity are not taken into account.

A more specific method consists in taking into account the fluorescence lifetime of melanin. Fluorescence lifetime is independent of the fluorophore concentration, but depends on the local microenvironment of the molecule, on variables such as pH, binding status, and molecular conformational changes. The skin’s autofluorescence lifetime spans from hundreds of picoseconds (e.g. melanin, free NAD (P) H, bound FAD) to nanoseconds (e.g. bound NAD (P) H, free FAD, keratin) . Multiphoton FLIM imaging of melanin samples such as synthetic, Dopa or Sepia melanins, skin and eye melanocytes, human hair and hair bulb, and human skin) indicate a specific bi-exponential decay behavior with a predominantly (> 90%relative contribution) short-fluorescence lifetime component around ～ 100–200 ps and a mixed species phasor plot with short phase lifetime distribution.

JP2009-142597 describes a method for visualizing melanin which combines multiphoton microscopy and Fluorescence lifetime imaging microscopy (FLIM) . However, image acquisition time needed for acquiring correct fluorescence decays for bi-exponential or phasor analysis is not compatible with 3D skin imaging in a clinical setup and in practice is limited to 2D imaging at selected epidermal depths, thereby limiting the possibilities of application of this technique, in particular in the context of three-dimensional imaging.

In order to specifically detect melanin from 3D multiphoton FLIM-like data, also compatible with 3D in vivo acquisitions on human subjects, another approach was proposed, combining (i) multiphoton FLIM, (ii) fast image acquisition times, and iii) a melanin detection method, called Pseudo-FLIM, which is based on slope analysis of the autofluorescence intensity decays from temporally binned data. WO2013/068943 discloses this method for specific 3D detection, visualization and/or quantification of an endogenous fluorophore such as melanin, in a biological tissue, the method being also described and compared to FLIM and phasor analyses in Pena, A. M. et al. “In vivo melanin 3D quantification and z-epidermal distribution by multiphoton FLIM, phasor and Pseudo-FLIM analyses” . Sci Rep 12, 1642 (2022) . Using parameters of melanin 3D global density and z-epidermal distribution, in vivo melanin modulations were assessed under different conditions: constitutive and acquired pigmentation, aging, natural UV exposure or application of topical retinoids known to having an effect on pigmentation.

However, 3D imaging is very time consuming and greatly limits its routine use for efficacy evaluation of melanin modulators. Multiphoton 2D vertical imaging (acquisition of images similar to a transverse histological section) , could be an alternative solution for a faster melanin assessment protocol. Although, multiphoton XZ imaging was already applied to the characterization of human skin dermal aging (e.g. Czekalla, C. et al. “Impact of Body Site, Age, and Gender on the Collagen/Elastin Index by Noninvasive in vivo Vertical Two-Photon Microscopy” , Skin Pharmacol Physiol 30, 260-267 (2017) ) , its interest and advantage over 3D imaging has not been investigated yet in the context of melanin assessment.

Summary

There remains a need to have the benefit of a sensitive, non-invasive method which is easy to implement, for three-dimensional visualization of the distribution of melanin in biological tissues, making it possible to obtain reliable, fast and relevant results.

The objective of the present invention is to develop a method which may be simpler and faster than the prior art methods, which makes it possible to detect melanin and to characterize its three-dimensional distribution in a biological tissue, in particular the epidermis.

There is also a need to make it possible to verify the efficacy or the innocuousness of a product, for example based on anti-pigmenting, depigmenting or pro-pigmenting active agents, used during treatment.

In addition, in the context of the search to develop new tissues in a reconstructed or synthetic manner, there is a need to objectify the differences in amount and distribution of melanin, according to the type of tissue model, in particular of skin model.

The invention aims to meet all or part of these needs.

Exemplary embodiments of the invention relate to a method for detection, quantification and/or visualization of an endogenous fluorophore, such as melanin, in a biological tissue, the method comprising

- acquiring a plurality of two-dimensional (2D) multiphoton images of fluorescence intensity, or combined multiphoton FLIM images, each image being acquired in a plane substantially perpendicular to a surface of the biological tissue, and

- processing the images to detect a boundary of the surface of the biological tissue and to detect the endogenous fluorophore, in particular melanin, and

- generating, on the basis of the processed images, information representative of a distribution of the endogenous fluorophore in said biological tissue with regard to the boundary, in particular as a function of the distance from the boundary.

By means of the present invention, a new faster method for melanin assessment, in particular in RPE model, can be obtained based on the acquisition of several transversal 2D XZ images. Each of the image is for example similar or equivalent to the ones provided by histology Fontana Masson staining.

Combined multiphoton FLIM, as known to one skilled in the art, is fluorescence lifetime imaging microscopy (FLIM) using multiphoton excitation. Combined multiphoton FLIM is for example described in Periasamy, A. &Clegg, R. M. FLIM Microscopy in Biology and Medicine. 1st edn, (Chapman and Hall/CRC, Taylor &Francis Group, 2009) .

Preferably, the endogenous fluorophore is detected using fluorescence intensity or Pseudo-FLIM analyses. As known to one skilled in the art, multiphoton images may be processed for melanin detection using fluorescence intensity analysis for example as described in FR 2 944 425. Multiphoton FLIM images may be processed for melanin detection and analyzed using any one of FLIM biexponential analysis, Phasor analysis and Pseudo-FLIM analysis, the later being described above in WO2013/068943 and Pena et al. Sci Rep 12, 1642 (2022) .

FLIM biexponential analysis is for example described in Dancik, Y., Favre, A., Loy, C.J., Zvyagin, A.V. &Roberts, M.S. 《Use of multiphoton tomography and fluorescence lifetime imaging to investigate skin pigmentation in vivo》 J. Biomed. Opt. 18, 26022; Ehlers, A., Riemann, I., Stark, M. &Konig, K. 《Multiphoton fluorescence lifetime imaging of human hair》 Microsc. Res. Tech. 70, 154–161; Dimitrow, E. et al. 《Spectral fluorescence lifetime detection and selective melanin imaging by multiphoton laser tomography for melanoma diagnosis. Exp. Dermatol 》 18, 509–515; Sugata, K. et al. 《Imaging of melanin distribution using multiphoton autofluorescence decay curves》 Skin Res. Technol. 16, 55–59.

Phasor analysis is for example described in Stringari, C. et al. 《Phasor approach to fluorescence lifetime microscopy distinguishes different metabolic states of germ cells in a live tissue》 Proc. Natl. Acad. Sci. U.S.A. 108, 13582–13587; Digman, M.A., Caiolfa, V.R., Zamai, M. &Gratton, E. 《The phasor approach to fluorescence lifetime imaging analysis》 Biophys. J. 94, L14-16; Vallmitjana, A. et al. 《Resolution of 4 components in the same pixel in FLIM images using the phasor approach》 Methods and Appl. Fluorescence 8, 035001.

In the following, the Z direction will designate a direction along a depth of the biological tissue, substantially perpendicular to said surface. X and Y direction will designate two directions defining a plane parallel to said surface of the biological tissue. For example, for a skin, the Z direction is a direction from stratum basale towards stratum corneum of the skin, or vice versa, and the X and Y direction designate the directions defining a plane parallel to the skin surface. An XZ image will thus designate an image substantially perpendicular to a surface of the biological issue.

The melanin density estimated by a subset of 2D XZ images according to the present invention is equivalent to the one estimated in 3D, while the present invention allows a faster evaluation protocol by acquiring a subset of 2D XZ images instead of a stack 3D XYZ images.

Each pixel of a 2D XZ image may be defined by spatial coordinates (x, z) , z being the depth in the sample. For a 2D XZ image, a line of pixels may be acquired at each z position corresponding to a given depth of the biological tissue. The number of pixels in X and Z directions and the pixel size in μm are parameters dependent on the imaging system (field of view and resolution) . The pixel size in Z is dependent on the imaging depth and sample thickness. For example, 2D XZ images of 1024×1024 pixels may be acquired within RPE model.

Preferably, for faster image acquisition times, each XZ image may be acquired through an objective capable of translating in the Z direction, for example by using a piezoelectric device.

Preferably, the method of the present invention comprises acquiring, within a sample such as the RPE model, between 20 and 80, better between 30 and 70, images having different y coordinates, for example approximately 50 2D XZ images every dy=100 μm. The number of images and the dy step value, i.e., the distance of acquisition between two XZ images along the Y direction, may be adjusted depending on melanin’ distribution homogeneity. The method may comprise acquiring at least fifty two-dimensional (2D) multiphoton or combined multiphoton FLIM images in different planes substantially perpendicular to the surface of the biological tissue. Preferably, to increase the imaging depth and ensure good fluorescence signal intensity within a biological sample such as the RPE model, its stratum basale is placed at the surface of the sample. In current histology Fontana Masson analysis, only a few 10 to 15 XZ images are acquired and investigated.

The acquired images may be further processed to detect melanin using methods such as the ones disclosed in FR 2 944 425 for intensity-based melanin detection or WO2013/068943 for lifetime-based melanin detection. Further information may be generated with associated melanin quantification tools, such as computer algorithms, to extract quantitative parameters of melanin in a biological issue, such as 2D melanin density and/or its z-distribution profile.

The determining of the boundary line between air and the surface of the biological tissue may be performed by finding signal points along the columns of each XZ image. The method may comprise detecting a boundary between air and stratum basale, for example by determining a median position of highest fluorescence intensity pixels in a surrounding interval in X direction. The length of the surrounding interval may depend on the size of the image in the X direction. For a 2D XZ images of 1024×1024 pixels, the surrounding interval may have a length of around 20 pixels along X direction.

Preferably, the method comprises applying a first intensity detection threshold to segment the sample surface for boundary detection. The method may comprise binarizing the 2D XZ image to denoise the image.

The boundary line may be displayed on the processed image.

The method may comprise applying, after the boundary detection, a second intensity detection threshold to binarize and Gaussian blur the 2D image for detection of melanin containing pixels, using the intensity-based melanin detection method described in FR 2 944 425. Within living epidermis, melanin pixels exhibiting strong fluorescence intensities above the fluorescence intensity level of other endogenous fluorophores (e.g. NAD (P) H in stratum granulosum) are selected by applying an intensity threshold. This second intensity detection threshold is preferably set at a higher value compared to the first boundary detection threshold. The application of a Gaussian blur allows to eliminate the noise pixels, before applying the second intensity threshold for melanin detection. The second intensity threshold may be the same as for 3D imaging, for example as taught in the FR 2 944 425 patent and in the article “The skin-depigmenting potential of Paeonia lactiflora root extract and paeoniflorin: In vitro evaluation using reconstructed pigmented human epidermis” mentioned above. The average number of melanin containing pixels with respect to their distance from the basal epidermal boundary may be used to estimate a melanin z-distribution profile from stratum basale up to for example 100 μm depth.

The association of the 2D XZ acquisition with the melanin quantification tools according to the present invention allows the distribution and quantity of melanin to be visualized and quantified in RPE epidermis model with an operational time for example at least 5 times faster compared to 3D imaging, thus providing a powerful method for routine efficacy evaluation of melanin modulators in cosmetic and dermatological investigations.

The method is non-invasive and may be used in a non-therapeutic, cosmetic context.

The method may make it possible to evaluate pigmentation.

The method according to the invention can be implemented in vivo, but also on ex vivo and in vitro samples.

The invention improves the rapidity of the melanin efficacy evaluation process, by decreasing the number of XZ images necessary to robustly estimate melanin density in RPE model compared to 3D imaging. The method also allows to improve the rapidity in processing the images for generating the information representative of distribution of the endogenous fluorophore component in said biological tissue. By virtue of the invention, 3D characterization of the tissue is possible and could be used for an in vivo application with a high throughput.

The biological tissue, in particular the keratin materials, according to the invention may be natural or artificial; the sample is, for example, human skin, or reconstructed or artificial skin.

The biological tissue may be melanized cells in culture.

The information may be generated in the form of at least one image, in particular a two-dimensional or three-dimensional image.

The information generated may provide information on the surface and/or the volume taken up by melanin in said tissue, and also on its 3D distribution compared with the other constituents of the tissue.

Exemplary embodiments of the invention also relate to a method (in particular non therapeutic method) for evaluating the action of a stimulus and/or of a treatment, which is in particular pro-pigmenting, depigmenting or anti-pigmenting, on a biological tissue, comprising:

- evaluating the pigmentation in a biological tissue by means of a method as previously described, exposing the sample to a stimulus (in particular a non-therapeutic one) chosen from: light radiation, in particular solar, ultraviolet (UVA and/or UVB) or infrared (IR) radiation, a stimulus causing an inflammatory response, and a mechanical action (tension, pressure, peeling, detachment, exfoliation, abrasion) , or to a treatment, in particular with at least one pro-pigmenting, depigmenting or anti-pigmenting product, for example lucinol or any other pigmentation-modulating chemical agent,

- performing a second evaluation of the pigmentation in the biological tissue by means of a method as previously described,

- comparing the information generated during the two evaluations, and evaluating the action of the stimulus or of the treatment on the pigmentation on the basis at least of this comparison.

The treatment may be non-therapeutic, in particular cosmetic.

The treatment may be chosen from: the application, injection, ingestion or inhalation of a product, in particular a cosmetic product.

The treatment may correspond to taking food supplements and/or medicaments. It may also comprise exposure of the biological tissues to a treatment chosen from: the application, injection, ingestion or inhalation of a product, in particular of a cosmetic product, or the taking of food supplements and/or of medicaments.

The term "cosmetic product" is intended to mean a product as defined in Directive 93/35/EEC of 14 June 1993, modifying Directive 76/768/EEC.

The product may have a depigmenting effect. Thus, the treatment may comprise the application of any pigmentation-modulating chemical agent.

The method according to the invention may be used for evaluating the efficacy or the innocuousness of depigmenting, anti-pigmenting or pro-pigmenting active agents. The active agents may be for therapeutic purposes, for instance hydroquinone or retinoids, and/or cosmetic purposes.

The method according to the invention may also be used for evaluating the side effects on pigmentation of certain products, for example dermocorticoids.

Exemplary embodiments of the invention also relate to a method for evaluating the action of a stimulus and/or of a treatment, which is in particular anti-pigmenting, pro-pigmenting or depigmenting, on a biological tissue, in which at least two regions of the tissue are exposed differently to the stimulus and/or treated differently, and in which the information on the presence and/or the amount of melanin in said regions, obtained by means of a method as previously described, before and after exposure to said stimulus or to said treatment, are compared.

To test the action of a product, an evaluation made after treatment with a placebo of the product and an evaluation made after treatment with this product may be compared.

The placebo is, for example, the same cosmetic medium as that of the product used for the treatment, but without the corresponding active agent (s) .

It is possible to carry out an evaluation of the distribution of melanin in the biological tissues of an individual or on samples of artificial or reconstructed skin which have been treated with a cosmetic compound, and to compare it with an evaluation of the distribution of melanin in the biological tissues of the same individual or the same samples of artificial or reconstructed skin which have been treated with a placebo of the cosmetic compound.

The treatment may correspond to the application of a product, in particular a cosmetic product. The product may, for example, be in the form of a cream, a lotion, an ointment, an oil, a powder, this list not being limiting.

The product may also be contained in a support to be applied to the biological tissues, in particular reconstructed or artificial human skin, for example a patch, a dressing, a bandage or a mask.

The product may not be a pigmenting or depigmenting product solely intended to act on the amount and/or the distribution of melanin in the biological tissues. The product may thus be intended, for example, for making up, for moisturizing or for protecting biological tissues, in particular protecting against the sun, or for repairing biological tissues, while at the same time having effects on the amount and/or the distribution of melanin in the biological tissues. The product may thus contain various compounds, in particular active agents other than active agents intended to act on the melanin of biological tissues.

Exemplary embodiments of the invention also relate to a method for promoting a treatment, in particular a non-therapeutic treatment, in which reference is made to an action of the treatment on melanin, demonstrated by means of a method as defined above.

Brief description of the drawings

The invention may be better understood from reading the following description of non-limiting examples of implementation thereof, and from examining the figures of the attached drawing, in which:

- Figure 1 illustrates various steps of a method in accordance with the invention,

- Figure 2 represents, diagrammatically and partially, an example of a multiphoton device which may be used in a method according to the invention,

- Figure 3 illustrates an example of a multiphoton 2D XZ fluorescence intensity image acquired according to the invention,

- Figures 4 illustrates the image of Figure 3 to which boundary detection is applied,

- Figure 5 corresponds to the image of Figure 4 obtained after fluorescence intensity-based melanin detection,

- Figure 6 illustrates the image of Figure 5 after alignment of the boundary in the Z direction,

- Figure 7 shows the melanin 2D z-distribution profile corresponding to the image in Figure 6.

Detailed description

As illustrated in Fig. 1, step 1 of a method according to the invention comprises acquiring, by multiphoton or multiphoton FLIM microscopy, a plurality of two-dimensional XZ images. Each image comprises a plurality of lines of pixels imaged at various depths of the biological tissue.

The use of a multiphoton microscopy device may allow automation of the biological tissue image acquisition steps.

The number of 2D XZ images to acquire and their dy step are parameters to be adjusted, as mentioned above, depending on the biological sample and imaging system. For RPE skin model, a stack of 50 images may be acquired every dy=100 μm. The acquired images may be stored in different formats, for example as single images or as a stack of images. Two or more stacks of 2D XZ images may also be acquired with different sample X, Y locations.

In a step 2, an algorithm is used to process the stack of images and read a single layer from an image stack. An example of a 2D XZ image obtained for skin by the method of the current invention is illustrated in Fig. 3. The image shows the epidermal fluorescence intensity of the RPE skin model, in a transversal plane substantially perpendicular to the surface of the skin. In the present case, the XZ image to be processed comprises a total number of 1024×1024 pixels.

Step 3 comprises the boundary determination or detection for the biological tissue. The step comprises applying a first intensity detection threshold to binarize the 2D XZ image extracted, i.e., denoise for boundary detection.

After denoising, an algorithm finds the signal points along the x-axis on the column where each pixel is located and determines the median position of the highest fluorescence intensity pixels in a surrounding interval. The algorithm may then concatenate signal points corresponding to the highest fluorescence intensity pixels. The concatenated signal points form the boundary line, i.e. the boundary between air and stratum basale. A boundary determined in this way is illustrated in Fig. 4.

Step 4 comprises melanin detection in the boundary detected 2D XZ image. This step comprising setting a second intensity detection threshold, which is also used for binarization to denoise. Then, Gaussian blur is applied to assist noise reduction to help detect the melanin signal points. As shown in Fig. 5, the bright part is the detected melanin signal points after noise reduction. A melanin mask is thus obtained after applying the second intensity detection threshold using fluorescence intensity-based melanin detection method.

In step 5, a curve representing the melanin distribution in the transversal plane corresponding to the single layer of 2D XZ image extracted in step 2 is computed. In the current example, an algorithm takes out 256 pixels from the starting point on the boundary line in each column of pixels, and aligns the starting points, forming the picture shown in Fig. 6. The algorithm thus detects the area of skin. The alignment of the starting points may facilitate the generation of curve representative of the melanin distribution, as will be illustrated in Fig. 7. The number of the pixels taken out can be varied, for example as a function of the melanin signal points detected in the step 4.

Those melanin pixels can be then counted with respect to their distance from the boundary line. The above steps can be applied to at least part of or each of the 2D XZ image acquired. Then, by averaging, for each depth corresponding to a distance of a line of pixels taken out in step 5 from the boundary line, this quantity in each 2D XZ image along the X direction and among the 2D XZ images, melanin distribution from the skin basal layer to the deep layer can be obtained as shown in Fig. 7, wherein the abscissa represents the distance from the stratum basale to the skin surface in micrometer and the ordinate represents the average of the count of melanin pixels in the 2D XZ image at a given depth z.Different XZ images may be acquired at different Y positions, in order to give information about melanin distribution at different sample’s locations. In this example, he melanin 2D z-distribution profile is presented from the sample surface up to a depth of 250 μm.

Any known multiphoton microscopy system, combined or not with a system for measuring fluorescence lifetime, may be used to implement the method above. In particular, the multiphoton microscopy system is for example of the type

A1RMP/FN1.

The excitation wavelength used may be between 700 and 1000 nm, preferably about 760 nm. This wavelength range makes it possible to image most of the endogenous fluorescent constituents of tissues.

Figure 2 represents, diagrammatically and partially, an example of a multiphoton device 100 which may be used in a method according to the invention.

The device 100 comprises a femtosecond laser 10, for example a Titanium-Sapphire (Ti : Sa) laser, which may be tuned into an infrared wavelength range and which may provide pulses of the order of 100 femtoseconds at a repetition rate of the order of 80 MHz. The laser 10 emits an infrared beam 11, which is directed towards a laser beam scanning device 12 in the form of an "XY scanner" .

The beam is then reflected by a first dichroic mirror 14 and it is focused on the keratin materials 13 by means of the objective 15. A scan of the laser beam may be obtained by angular movement of a first pair of two galvanometric mirrors 22 of the scanning device 12, which allows scanning of the focusing point in the plane (x, y) perpendicular to the Z direction. A piezoelectric device 26 makes it possible to translate the objective 15 and thus to change the plane of focusing at different depths in the keratin materials 13 during acquisition of a 2D XZ image. For each depth, a line of pixels is acquired by moving the focusing point in the X direction by the XY scanner.

The signals created at the focal point may then be detected, for example by epicollection through the excitation objective 15. The first dichroic mirror 14 makes it possible to select the multiphoton signals created, in particular the autofluorescence (AF) originating from the keratin materials 13. In particular, the first dichroic mirror 14 allows reflecting the laser light wavelengths (e.g. 700-1000 nm range) and transmitting the multiphoton signal (e.g. 350-650 nm) .

Then, a second dichroic mirror 16 makes it possible to separate the autofluorescence (AF) signals from the other multiphoton signals, corresponding for example to the second harmonic generation (SHG) .

A second pair of two galvanometric mirrors 23 may be positioned between the first 14 and the second dichroic mirror 16 for performing light alignment, to make sure that all the signals can be detected by the detector no matter at which XZ position.

In any event, the signals pass through spectral filters and reach at least one detector 18, thus making it possible to produce a fluorescence image. The data are further transferred onto another computer for image processing.

The method may thus be used for any type of tissue containing melanin.

Claims

Method for detection, quantification and/or visualization of an endogenous fluorophore, such as melanin, in a biological tissue, the method comprising

- acquiring a plurality of two-dimensional (2D) multiphoton images of fluorescence intensity, or combined multiphoton FLIM images, each image being acquired in a plane substantially perpendicular to a surface of the biological tissue,

- processing the images to detect a boundary of the surface of the biological tissue and to detect the endogenous fluorophore, and

- generating, on the basis of the processed images, information representative of a distribution of the endogenous fluorophore in said biological tissue with regard to the boundary, in particular as a function of the distance from the boundary.
Method according to Claim 1, the method comprising acquiring at least fifty two-dimensional (2D) multiphoton or combined multiphoton FLIM images in different planes substantially perpendicular to the surface of the biological tissue, preferably the endogenous fluorophore being detected using fluorescence intensity or Pseudo-FLIM analyses.
Method according to Claim 1 or 2, the information being generated in the form of at least one representation of 2D melanin density and/or its distribution profile along a depth of the biological tissue.
Method according to any one of the preceding claims, comprising applying a first intensity detection threshold to segment the sample surface for boundary detection.
Method according to any one of the preceding claims, comprising determining a boundary line between air and the surface of the biological tissue by finding signal points along the columns of the 2D images and determining the median position of the highest fluorescence intensity pixels in a surrounding interval.
Method according to any one of the preceding claims, comprising displaying the boundary line on the processed image.
Method according to any one of the preceding claims, comprising applying, after the boundary detection, a second intensity detection threshold to binarize and Gaussian blur the 2D image for detection of melanin containing pixels.
Method according to the preceding claim, comprising taking out pixels from starting points on the boundary line in each column of pixels of the 2D image, and aligning the starting points.
Method according to any one of the preceding claims, the biological issue being skin and the endogenous fluorophore component being melanin, the method comprising representing melanin distribution as a function of the distance from the skin basal layer.
Method according to any one of the preceding claims, comprising acquiring, for each 2D image, a plurality of lines of pixels at different depths of the biological issue, the method comprising translating an objective perpendicular to a surface of the biological tissue during acquisition of each 2D image, at each acquisition of a line of pixels, the objective being focused on a corresponding depth of the biological tissue.
Method according to any one of the preceding claims, the information generated providing information on the surface and/or the volume taken up by melanin in the tissue.
Method according to any one of the preceding claims, being implemented in vivo on a biological tissue.
Method according to any one of the preceding claims, the tissue being human skin, reconstructed or artificial skin, or melanized cells in culture.
Method for evaluating the action of a stimulus and/or of a treatment, which is in particular pro-pigmenting or depigmenting, on a biological tissue, comprising:

evaluating the pigmentation in the tissue by performing the method according to any one of the preceding claims,

performing a second evaluation of the pigmentation in the tissue with the method according to any one of the preceding claims, the tissue having been exposed to an action of a stimulus chosen from: light radiation, in particular solar, ultraviolet (UV) or infrared (IR) radiation, a stimulus causing an inflammatory response, and a mechanical action, or a treatment, in particular with at least one pro-pigmenting or depigmenting cosmetic product, comparing the information generated during the two evaluations, and evaluating the action of the stimulus or of the treatment on the pigmentation on the basis at least of this comparison.
Method for evaluating the action of a stimulus and/or of a treatment, which is in particular anti-pigmenting, pro -pigmenting or depigmenting, on a biological tissue, in which at least two regions of the tissue are exposed differently to the stimulus and/or treated differently, and in which the information on the presence and/or the amount of melanin in said regions, obtained by means of a method according to any one of claims 1 to 10, before and after exposure to said stimulus or to said treatment, are compared.