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

Abstract

NON-INVASIVE METHOD FOR THE DETECTION, VISUALIZATION AND / OR QUANTIFICATION OF AN ENDOGENOUS FLUOROPHORE SUCH AS MELANIN IN BIOLOGICAL TISSUE. Method for the detection, quantification and / or visualization of an endogenous fluorophore, such as melanin, in biological tissue, the method comprising: - the acquisition of a plurality of two-dimensional (2D) multiphoton fluorescence intensity images, or combined multiphoton FLIM images, each image being acquired in a plane substantially perpendicular to a surface of the biological tissue, - the processing of the images to detect a boundary of the surface of the biological tissue and to detect the endogenous fluorophore, and - the generation, based on the processed images, of information representative of a distribution of the endogenous fluorophore in said biological tissue with respect to the boundary, in particular as a function of the distance from the boundary. Figure for the abstract: Fig. 1

Description

Title of the invention: NON-INVASIVE METHOD FOR DETECTION, VISUALIZATION AND / OR QUANTIFICATION OF AN ENDOGENOUS FLUOROPHORE SUCH AS MELANIN IN BIOLOGICAL TISSUE

[0001] The present invention relates to the observation of biological tissues, in particular keratinous materials such as skin.

[0002] The invention relates more particularly, but not exclusively, to methods for determining the distribution of melanin in biological tissues, in particular for the purpose of evaluating the action of a cosmetic treatment on them. CONTEXT

[0003] The color of certain biological tissues is closely related to the quantity and three-dimensional distribution of melanin. Today, the characterization of the quantity and distribution of melanin can be carried out either ex vivo or in vivo using different methods.

[0004] Currently, the reference method for quantifying melanin in the skin is chemical analysis by high-performance liquid chromatography (HPLC) of melanin degradation products. Although highly specific, it requires ex vivo degradation of the samples and provides no information on the epidermal distribution of melanin. Fontana-Masson staining of cross-sectional skin sections provides information on the 2D distribution and melanin content, but has the disadvantage of non-specific staining of the stratum corneum (SC), whereas Warthin-Starry staining can provide more sensitive and specific melanin detection. Transmission electron microscopy allows analysis of the melanosome profile in epidermal cells and its variations according to skin phenotype.

[0005] Over the years, the possibility of providing non-invasive detection of melanin based on its optical properties, broadband UV-visible absorption, fluorescence emission spectrum, and lifetime has been investigated using various techniques. Spontaneous Raman spectroscopy revealed that pheomelanin exhibited a specific peak in the "silent region" of the Raman spectrum, thus offering a direct route to specific non-invasive 3D detection of pheomelanin in skin samples by CARS (Coherent anti-Stokes Raman Scattering) imaging. Recently, a combined analysis of specific Raman bands with single-photon excitation NIR autofluorescence of skin has been used to estimate an xz depth profile of the melanin fraction in vivo, but this This method does not allow for the spatial localization of melanin within cells and cannot represent the entire epidermis. Pump-probe imaging has also proven useful for 2D analysis of melanin in thin skin sections of pigmented lesions, particularly for its eumelanin / pheomelanin discrimination.

[0006] Imaging of melanin based on its endogenous fluorescence was demonstrated in 1979 by conventional single-photon excitation fluorescence microscopy on sections of human skin and 20 years later in vivo on forearm skin using two-photon / multiphoton microscopy.

[0007] Multiphoton imaging allows for the three-dimensional characterization of biological tissues with sub-micrometer resolution. The imaging depth varies depending on the tissue; it can be approximately 200 µm for human skin. Using endogenous autofluorescence signals from keratin, the metabolic coenzymes NAD(P)H and FAD, and melanin, multiphoton microscopy provides non-invasive, label-free 3D visualization of epidermal layers and melanin distribution within the epidermis.

[0008] During multiphoton excitation at 760 nm, an intensity-based melanin detection method has been proposed in vitro on pigmented reconstructed epidermis, for example in FR 2 944 425, and in vivo on human skin, for example 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 has also been applied to the quantitative in vitro assessment of melanin content on the Chinese pigmented reconstructed epidermis (PRE) model, as explained in Qiu, J. et al. “The skin-depigmenting potential of Paeonia lactiflora root extract and paeoniflorin: In vitro evaluation using reconstructedpigmented human epidermis” Int J Cosmet Sci 38, 444-451, (2016).

[0009] 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, highly concentrated melanin exhibits high fluorescence signal intensities, stronger than those of other endogenous fluorophores. Pixels with high intensity are attributed to melanin. This intensity-based approach works in the basal layers of the epidermis where melanin is highly concentrated and exhibits higher fluorescence signal intensities than other endogenous fluorophores, but not in the stratum corneum containing keratins exhibiting high fluorescence intensities. Furthermore, pixels with low melanin concentration and low fluorescence intensity are not taken into account.

[0010] A more specific method consists of taking into account the fluorescence lifetime of melanin. The fluorescence lifetime is independent of The fluorophore concentration, but depends on the local microenvironment of the molecule, variables such as pH, binding state, and changes in molecular conformation. The autofluorescence lifetime of skin ranges 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 melanins, Dopa or Sepia, skin and eye melanocytes, human hair and hair bulbs, and human skin) indicates a specific bi-exponential decay behavior with a predominantly short-lived fluorescence component (>90% relative contribution) of approximately 100–200 ps and a mixed-species phasor plot with a short-lived phase distribution.

[0011] JP2009-142597 describes a method for visualizing melanin that combines Multiphoton microscopy and time-resolved fluorescence microscopy (FLIM) are used. However, the image acquisition time required to acquire adequate fluorescence decays for bi-exponential or phaser analysis is not compatible with 3D skin imaging in a clinical setting and is practically limited to 2D imaging at selected epidermal depths, thus limiting the possibilities of applying this technique, particularly in the context of three-dimensional imaging.

[0012] In order to specifically detect melanin from 3D multiphoton FLIM data, also compatible with in vivo 3D acquisitions on human subjects, another approach has been proposed, combining (i) multiphoton FLIM, (ii) fast image acquisition times, and (iii) a melanin detection method, called pseudo-FLIM, which is based on analyzing the slope of autofluorescence intensity declines from time-grouped data. WO2013 / 068943 discloses this method for the specific 3D detection, visualization, and / or quantification of an endogenous fluorophore such as melanin in biological tissue. The method is also described and compared to FLIM and phasor analyses in Pena, AM 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 global density parameters and 3D z-epidermal distribution of melanin, in vivo modulations of melanin were evaluated under different conditions: constitutive and acquired pigmentation, aging, natural UV exposure, or application of topical retinoids known to have an effect on pigmentation.

[0013] However, 3D imaging is time-consuming and significantly limits its routine use for evaluating the efficacy of melanin modulators. 2D vertical multiphoton imaging (acquisition of images similar to a cross-section) (cross-sectional histological) could be an alternative solution for a faster melanin assessment protocol. Although multiphoton XZ imaging has already been applied to the characterization of dermal aging in human skin (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 relevance and advantage over 3D imaging have not yet been studied in the context of melanin assessment. SUMMARY

[0014] It remains necessary to have a sensitive and non-invasive method that is easy to implement for the three-dimensional visualization of melanin distribution in biological tissues, allowing reliable, rapid and relevant results to be obtained.

[0015] The objective of the present invention is to develop a method that can be simpler and faster than prior art methods, which allows the detection of melanin and the characterization of its three-dimensional distribution in a biological tissue, in particular the epidermis.

[0016] It is also necessary to allow verification of the efficacy or safety of a product, for example from anti-pigmenting, depigmenting or pro-pigmenting active agents, used during treatment.

[0017] Furthermore, in the context of research to develop new reconstructed or synthetic tissues, it is necessary to objectify the differences in quantity and distribution of melanin, according to the type of tissue model, in particular the skin model.

[0018] The invention aims to meet all or part of these needs.

[0019] Examples of embodiments of the invention relate to a method for detecting, quantifying and / or visualizing an endogenous fluorophore, such as melanin, in a biological tissue, the method comprising: - the acquisition of a plurality of two-dimensional (2D) fluorescence intensity multiphoton images, or combined multiphoton FLIM images, each image being acquired in a plane substantially perpendicular to a surface of the biological tissue, and - image processing to detect a boundary of the biological tissue surface and to detect the endogenous fluorophore, in particular melanin, and - the generation, based on the processed images, of information representative of the distribution of the endogenous fluorophore in said biological tissue by relation to the limit, in particular as a function of the distance from the limit.

[0020] By means of the present invention, a new, faster method for evaluating melanin, particularly in the ERP model, can be obtained on the basis of acquiring several 2D XZ cross-sectional images. Each of the images is, for example, similar or equivalent to those provided by Fontana-Mas son histological staining.

[0021] Combined multiphoton FLIM, as known to those skilled in the art, is time-resolved fluorescence microscopy (FLIM) using multiphoton excitation. Combined multiphoton FLIM is described, for example, in Periasamy, A. & Clegg, RM FLIM Microscopy in Biology and Medicine. Ist edn, (Chapman and Hall / CRC, Taylor & Francis Group, 2009).

[0022] Preferably, the endogenous fluorophore is detected using fluorescence intensity analysis or pseudo-FLIM. As those skilled in the art know, multiphoton images can be processed for melanin detection using fluorescence intensity analysis, for example, as described in FR 2 944 425. Multiphoton FLIM images can be processed for melanin detection and analyzed using any bi-exponential FLIM analysis, phasor analysis, and pseudo-FLIM analysis, the latter being described above in WO2013 / 068943 and in Pena et al. Sci Rep 12, 1642 (2022).

[0023] L’analyse bi-exponentielle par FLIM est par exemple décrite 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 détection and sélective 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.

[0024] Phaser 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. USA 108, 13582-13587; Digman, MA, Caiolfa, VR, 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.

[0025] In what follows, the Z direction denotes a direction along a depth of the biological tissue, substantially perpendicular to said surface. The X and directions The letters Y denote two directions defining a plane parallel to the surface of the biological tissue. For example, for skin, the Z direction is a direction from the basal layer (stratum basale) to the stratum corneum (stratum corneum) of the skin, or vice versa, and the X and Y directions denote the directions defining a plane parallel to the skin surface. An XZ image therefore designates an image that is approximately perpendicular to a surface of the biological tissue.

[0026] The melanin density estimated by a subset of 2D XZ images according to the present invention is equivalent to that estimated in 3D, while the present invention allows a faster evaluation protocol by acquiring a subset of 2D XZ images instead of stacked 3D XYZ images.

[0027] Each pixel of a 2D XZ image can be defined by spatial coordinates (x, z), where z is the depth in the sample. For a 2D XZ image, a line of pixels can be acquired at each z position corresponding to a given depth of the biological tissue. The number of pixels in the X and Z directions and the pixel size in pm are parameters dependent on the imaging system (field of view and resolution). The pixel size in the Z direction depends on the imaging depth and the sample thickness. For example, 2D XZ images of 1024 x 1024 pixels can be acquired in the ERP model.

[0028] Preferably, for faster image acquisition times, each XZ image can be acquired via a lens capable of performing a translation in the Z direction, for example using a piezoelectric device.

[0029] Preferably, the method of the present invention comprises acquiring, within a sample such as the ERP model, between 20 and 80, more preferably between 30 and 70, images having different y-coordinates, for example, approximately 50 2D XZ images every dy = 100 pm. The number of images and the dy step value, i.e., the acquisition distance between two XZ images along the Y direction, can be adjusted according to the homogeneity of the melanin distribution. The method may comprise acquiring at least fifty two-dimensional (2D) multiphoton images 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 ERP model, its basal layer is placed on the surface of the sample.In the current Fontana-Masson histological analysis, only 10 to 15 XZ images are acquired and studied.

[0030] The acquired images can be further processed to detect melanin using methods such as those disclosed in FR 2 944 425 for intensity-based melanin detection or in WO2013 / 068943 for lifetime-based melanin detection. Other information can be generated with tools associated melanin quantification, such as computer algorithms, to extract quantitative parameters of melanin in a biological tissue, such as 2D melanin density and / or its z distribution profile.

[0031] Determining the boundary between the air and the surface of the biological tissue can be done by finding signal points along the columns of each XZ image. The method may include detecting a boundary between the air and the basal layer, for example, by determining a median position of the pixels with the strongest fluorescence intensity within a surrounding interval in the X direction. The length of the surrounding interval may depend on the image size in the X direction. For 2D XZ images of 1024 x 1024 pixels, the surrounding interval may have a length of approximately 20 pixels along the X direction.

[0032] Preferably, the method includes applying a first intensity detection threshold to segment the sample surface for boundary detection. The method may include binarizing the 2D XZ image to denoise it.

[0033] The boundary line can be displayed on the processed image.

[0034] The method may include applying, after boundary detection, a second intensity detection threshold to binarize and apply Gaussian blur to the 2D image for the detection of melanin-containing pixels, using the intensity-based melanin detection method described in FR 2 944 425. Within the living epidermis, melanin pixels exhibiting high fluorescence intensities exceeding the fluorescence intensity level of other endogenous fluorophores (e.g., NAD(P)H in the stratum granulosum) are selected by applying an intensity threshold. This second intensity detection threshold is preferably set at a higher value than the first boundary detection threshold. Applying Gaussian blur eliminates noise pixels before applying the second intensity threshold for melanin detection.The second intensity threshold can be the same as for 3D imaging, for example as taught in French patent FR 2 944 425 and in the aforementioned article "The skin-depigmenting potential of Paeonia lactiflora root extract and paeoniflorin: In vitro evaluation using reconstructed pigmented human epidermis". The average number of pixels containing melanin relative to their distance from the basal boundary of the epidermis can be used to estimate a z-distribution profile of melanin from the basal layer down to, for example, 100 pm depth.

[0035] The combination of 2D XZ acquisition and melanin quantification tools according to the present invention makes it possible to visualize and quantify the distribution and quantity of melanin in the ERP epidermis model with an operational time, for example, at least 5 times faster compared to 3D imaging, thus providing a powerful method for routine evaluation of the efficacy of melanin modulators in cosmetic and dermatological studies.

[0036] The method is non-invasive and can be used in a non-therapeutic cosmetic context.

[0037] The method can be used to evaluate pigmentation.

[0038] The method according to the invention can be implemented in vivo, but also on ex vivo and in vitro samples.

[0039] The invention improves the speed of the melanin efficiency assessment process by reducing the number of XZ images required to robustly estimate melanin density in the ERP model compared to 3D imaging. The method also improves the speed of image processing to generate representative information on the distribution of the endogenous fluorophore component in said biological tissue. According to the invention, 3D tissue characterization is possible and could be used for high-throughput in vivo applications.

[0040] The biological tissue, in particular keratinous materials, according to the invention may be natural or artificial; the sample is, for example, human skin, reconstructed or artificial skin.

[0041] The biological tissue may be melanized cells in culture.

[0042] The information can be generated in the form of at least one image, in particular a two-dimensional or three-dimensional image.

[0043] The information generated can provide information on the surface area and / or volume occupied by melanin in said tissue, as well as on its 3D distribution relative to the other constituents of the tissue.

[0044] Examples of embodiments of the invention also relate to a method (in particular a non-therapeutic method) for evaluating the action of a stimulus and / or a treatment, which is in particular pro-pigmenting, depigmenting or anti-pigmenting, on a biological tissue, comprising:

[0045] - the evaluation of pigmentation in a biological tissue using a method as described above, exposure of the sample to a stimulus (in particular a non-therapeutic stimulus) selected from: light radiation, in particular solar, ultraviolet (UVA and / or UVB) or infrared (IR) radiation, a stimulus causing an inflammatory response and 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 chemical pigmentation modulator,

[0046] - carrying out a second evaluation of pigmentation in the biological tissue using a method described previously,

[0047] - the comparison of the information generated during the two evaluations, and the evaluation of the action of the stimulus or treatment on pigmentation at least on the basis of this comparison.

[0048] The treatment may be non-therapeutic, in particular cosmetic.

[0049] The treatment can be chosen from: the application, injection, ingestion or inhalation of a product, in particular a cosmetic product.

[0050] The treatment may consist of taking food supplements and / or medication. It may also include exposing biological tissues to a treatment chosen from: the application, injection, ingestion or inhalation of a product, in particular a cosmetic product, or taking food supplements and / or medication.

[0051] The term “cosmetic product” means a product as defined in Directive 93 / 35 / EEC of 14 June 1993 amending Directive 76 / 768 / EEC.

[0052] The product may have a depigmenting effect. Thus, the treatment may include the application of any chemical pigmentation-modulating agent.

[0053] The method according to the invention can be used to evaluate the efficacy or safety of depigmenting, anti-pigmenting, or pro-pigmenting active agents. The active agents may be for therapeutic purposes, for example, hydroquinone or retinoids, and / or for cosmetic purposes.

[0054] The method according to the invention can also be used to evaluate the side effects of certain products on pigmentation, for example dermocorticoids.

[0055] Embodiments of the invention given by way of example also relate to a method for evaluating the action of a stimulus and / or a treatment, which is in particular anti-pigmentation, pro-pigmentation or depigmentation, 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 information on the presence and / or quantity of melanin in said regions, obtained by means of a method as described above, is compared before and after exposure to said stimulus or said treatment.

[0056] To test the action of a product, an evaluation carried out after treatment with a placebo of the product and an evaluation carried out after treatment with this product can be compared.

[0057] The placebo is, for example, the same cosmetic agent as that of the product used for the treatment, but without the corresponding active agent(s).

[0058] 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 that have been treated with a cosmetic compound, and to compare it to an evaluation of the distribution of melanin in the biological tissues of the same individual or of the same samples of artificial or reconstructed skin that were treated with a placebo of the cosmetic compound.

[0059] The treatment may involve the application of a product, in particular a cosmetic product. The product may, for example, be in the form of a cream, lotion, ointment, oil, or powder, this list being non-exhaustive.

[0060] The product may also be contained in a carrier to be applied to biological tissues, in particular reconstructed or artificial human skin, for example a patch, a dressing, a bandage or a mask.

[0061] The product may not be a pigmenting or depigmenting product solely intended to act on the quantity and / or distribution of melanin in biological tissues. The product may thus be intended, for example, for makeup, hydration, or protection of biological tissues, particularly sun protection, or for the repair of biological tissues, while also having effects on the quantity and / or distribution of melanin in biological tissues. The product may therefore contain various compounds, in particular active agents other than those intended to act on melanin in biological tissues.

[0062] Illustrative embodiments of the invention also relate to a method of 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.

[0063] The invention can be better understood by reading the following description of non-restrictive examples of its implementation, and by examining the figures in the accompanying drawing, in which:

[0064] [Fig-1] - Fig. 1 illustrates the different steps of a method in accordance with the invention,

[0065] [Fig.2] - Fig.2 represents, schematically and partially, an example of multiphoton device that can be used in a method according to the invention,

[0066] [Fig.3] - [Fig.3] illustrates an example of a 2D XZ fluorescence intensity image multiphoton acquisition according to the invention

[0067] [Fig.4] - [Fig.4] illustrates the image of [Fig.3] on which the boundary detection is applied,

[0068] [Fig.5] - Fig.5 corresponds to the image of Fig.4 obtained after detection of melanin by fluorescence intensity,

[0069] [Fig.6] - Fig.6 illustrates the image of Fig.5 after alignment of the boundary in the direction Z,

[0070] [Fig.7] - Fig.7 shows the 2D z distribution profile of melanin corresponding to the image in [Fig.6].

[0071] As illustrated in [Fig. 1], step 1 of a method according to the invention comprises the acquisition, by multiphoton FLIM microscopy or multiphoton microscopy, of a plurality of two-dimensional XZ images. Each image comprises a plurality of pixel lines represented at different depths of the biological tissue.

[0072] The use of a multiphoton microscopy device can enable the automation of the image acquisition steps of biological tissue.

[0073] The number of 2D XZ images to be acquired and their dy intervals are parameters to be adjusted, as mentioned above, according to the biological sample and the imaging system. For the ERP skin model, a stack of 50 images can be acquired every dy = 100 µm. The acquired images can be stored in different formats, for example as individual images or image stacks. At least two 2D XZ image stacks can also be acquired with different X,Y sample locations.

[0074] In step 2, an algorithm is used to process the image stack and read a single layer from an image stack. An example of a 2D XZ image obtained for skin by the method of the present invention is illustrated in [Fig. 3]. The image shows the epidermal fluorescence intensity of the ERP skin model, in a transverse plane substantially perpendicular to the skin surface. In this case, the XZ image to be processed comprises a total of 1024 x 1024 pixels.

[0075] Step 3 includes boundary determination or detection for the biological tissue. The step consists of applying a first intensity detection threshold to binarize the extracted 2D XZ image, i.e., to denoise for boundary detection purposes.

[0076] After denoising, an algorithm finds the signal points along the x-axis in the column where each pixel is located and determines the median position of the pixels with maximum fluorescence intensity within a surrounding interval. The algorithm can then concatenate the signal points corresponding to the pixels with maximum fluorescence intensity. The concatenated signal points form the boundary line, i.e., the boundary between air and the basal layer. A boundary thus determined is illustrated in [Fig. 4].

[0077] Step 4 involves detecting melanin within the boundary of the detected 2D XZ image. This step includes setting a second intensity detection threshold, which is also used for binarization for denoising purposes. Next, a Gaussian blur is applied to facilitate noise reduction and help detect the melanin signal points. As shown in [Fig. 5], the bright area corresponds to the melanin signal points detected after noise reduction. A melanin mask is thus obtained after applying the second detection threshold. intensity using the fluorescence intensity-based melanin detection method.

[0078] In step 5, a curve representing the melanin distribution in the transverse plane corresponding to the single layer of the 2D XZ image extracted in step 2 is calculated. In the present example, an algorithm removes 256 pixels from the starting point on the boundary line in each pixel column and aligns the starting points, forming the image shown in [Fig. 6]. The algorithm thus detects the skin area. Aligning the starting points can facilitate the generation of a curve representing the melanin distribution, as shown in [Fig. 7]. The number of pixels removed can vary, for example, depending on the melanin signal points detected in step 4.

[0079] These melanin pixels can then be counted with respect to their distance from the boundary line. The above steps can be applied to at least some or all of the acquired 2D XZ images. Then, by calculating the average, for each depth corresponding to a distance of one line of pixels removed in step 5 from the boundary line, this quantity in each 2D XZ image along the X direction and among the 2D XZ images, the distribution of melanin from the basal layer of the skin to the deep layer can be obtained as shown in [Fig. 7], in which the abscissa represents the distance between the basal layer and the skin surface in micrometers and the ordinate represents the average number of melanin pixels in the 2D XZ image at a given depth z.Different XZ images can be acquired at different Y positions to provide information on the distribution of melanin at different locations within the sample. In this example, the 2D z-distribution profile of melanin is shown from the sample surface down to a depth of 250 sq m.

[0080] Any known multiphoton microscopy system, whether or not combined with a fluorescence lifetime measurement system, can be used to implement the above method. In particular, the multiphoton microscopy system is, for example, the Nikon® A1RMP / FN1 type.

[0081] The excitation wavelength used can be between 700 and 1000 nm, preferably around 760 nm. This wavelength range allows for the reflection of most of the endogenous fluorescent constituents of tissues.

[0082] Fig. 2 represents, schematically and partially, an example of a multiphoton device 100 that can be used in a method according to the invention.

[0083] The device 100 comprises a femtosecond laser 10, for example a sapphire-titanium (Ti:Sa) laser, which can be tuned in a range of infrared wavelengths and which can provide pulses on 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".

[0084] The beam is then reflected by a first dichroic mirror 14 and focused onto the keratin materials 13 by means of the objective lens 15. A scan of the laser beam can be obtained by angular movement of a first pair of galvanometric mirrors 22 of the scanning device 12, which allows the focal point to be scanned in the (x, y) plane perpendicular to the Z direction. A piezoelectric device 26 allows the translation of the objective lens 15 and thus changes the plane of focus at different depths in the keratin materials 13 during the acquisition of a 2D XZ image. For each depth, a line of pixels is acquired by moving the focal point in the X direction by the XY scanner.

[0085] The signals created at the focal point can then be detected, for example by epicollection via the excitation objective 15. The first dichroic mirror 14 allows selection of the multiphoton signals created, in particular autofluorescence (AF) from keratinous materials 13. The first dichroic mirror 14 allows in particular to reflect the wavelengths of laser light (for example, in a range of 700 to 1000 nm) and the transmission of the multiphoton signal (for example, from 350 to 650 nm).

[0086] Next, a second dichroic mirror 16 allows the autofluorescence (AF) signals to be separated from other multiphoton signals, which corresponds for example to the generation of the second harmonic (GSH).

[0087] A second pair of galvanometric mirrors 23 can be positioned between the first dichroic mirror 14 and the second dichroic mirror 16 to perform light alignment, in order to ensure that all signals can be detected by the detector, regardless of the XZ position.

[0088] In all cases, the signals pass through spectral filters and reach at least one detector 18, which produces a fluorescent image. The data is then transferred to another computer for image processing.

[0089] The method can therefore be used for any type of tissue containing melanin.

Claims

Demands

1. A method for detecting, quantifying, and / or visualizing an endogenous fluorophore, such as melanin, in a biological tissue, the method comprising: - acquiring a plurality of two-dimensional (2D) multiphoton fluorescence intensity images 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 biological tissue surface by applying a first boundary detection threshold; - applying a second intensity detection threshold to binarize and perform Gaussian blurring on the 2D image for the detection of melanin-containing pixels, the second intensity detection threshold being set at a higher value than the first boundary detection threshold; and - generating, based on the processed images,representative information of the distribution of the endogenous fluorophore in said biological tissue relative to the boundary, particularly as a function of the distance from the boundary.

2. Method according to claim 1, the method comprising at least fifty two-dimensional (2D) multiphoton images or combined multiphoton FLIMs in different planes substantially perpendicular to the surface of the biological tissue, preferably the endogenous fluorophore being detected using fluorescence intensity analyses or by pseudo-FLIM.

3. Method according to claim 1 or 2, the information being generated in the form of at least one 2D representation of the melanin density and / or its distribution profile along a depth of biological tissue.

4. Method according to any one of the preceding claims, the biological tissue being skin and the endogenous fluorophore component being melanin, the method comprising the representation of the distribution of melanin as a function of distance from the cutaneous basal layer.

5. A method according to any one of the preceding claims, comprising the acquisition, for each 2D image, of a plurality of pixel lines at different depths of the biological tissue, the method comprising the translation of a lens perpendicular to a surface of the biological tissue during the acquisition of each 2D image, at each acquisition of a pixel line, the lens being focused on a corresponding depth of the biological tissue.

6. Method according to any one of the preceding claims, the information generated providing information on the surface area and / or volume occupied by melanin in the tissue.

7. Method according to any one of the preceding claims, the tissue being human skin, reconstructed or artificial skin, or melanized cells in culture.

Images