Multimodal system and related method for non-invasive in VIVO characterization of the tissue microenvironment

Abstract

The present invention relates to a multimodal non-invasive in vivo system and related method for the characterization of the tissue microenvironment. The system comprises: a multispectral imaging (MSI) camera for superficial spectral screening; a multispectral optoacoustic tomography (MSOT) module for dynamic vascular and perfusion analysis; a Mueller Matrix Polarimetry (MMP) module for extracellular matrix anisotropy assessment; a Raman spectroscopy module for molecular fingerprinting of fibroblast-associated proteins; an optical coherence tomography (OCT) module for morphological and stratigraphic evaluation; an optional Elastic Scattering Spectroscopy (ESS) module for subcellular scattering biomarkers; and a diachronic analysis module for longitudinal monitoring. Data are integrated by an artificial intelligence processing unit to generate quantitative biomarkers of vascularization, extracellular matrix features, immune activity (Langerhans cells) and fibroblast phenotype, distinguishing physiological myofibroblasts from CAF. The invention enables non-nvasive, biopsy-free evaluation of scars, melanocytic lesions, tumor stroma, wound healing and surgical site monitoring.

Description

[0001] MULTIMODAL SYSTEM AND RELATED METHOD FOR NON-INVASIVE IN VIVO

[0002] CHARACTERIZATION OF THE TISSUE MICROENVIRONMENT

[0003] The present invention relates to a multimodal system and related method for the non-invasi ve , in vivo characterization of the tissue microenvironment .

[0004] More specifically, the invention concerns a modular platform integrating complementary optical and optoacoustic modalities with advanced data analytics and artificial intelligence, configured to provide quantitative and reproducible biomarkers of tissue structure, vascularization, cellular composition, and immune activity.

[0005] The disclosed system was originally conceived for the instrumental, non-invasive diagnosis of scar tissue, through quantitative and qualitative analysis of its optical properties; however, its scope extends beyond scars to include skin oncological lesions, wound healing processes, and peri- / post-operative surgical site monitoring.

[0006] The primary objective is to enable an in vivo assessment of the tissue microenvironment that is as objective and reproducible as possible, thereby supporting early diagnosis, personalized treatment planning, and longitudinal follow-up.

[0007] The invention provides a modular and platform-based diagnostic system, designed to characterize the tissue microenvironment beyond scar assessment. The system integrates complementary optical and optoacoustic modalities and Al-driven analytics to produce quantitative biomarkers that combine structural, vascular, cellular and immune parameters. This allows prediction of scar hypertrophy, malignant transformation in melanocytic lesions and pathological fibrotic evolution in surgical sites and chronic wounds .

[0008] This method finds application not only in the medical and clinical fields, but also in research and technological innovation. It involves numerous scientific disciplines, including tissue and electromedical bioengineering, physics, chemistry, biology, computer engineering, artificial intelligence, and materials science.

[0009] In the medical field, the proposed method not only allows for accurate scar diagnosis, but also allows for monitoring their progression and the effectiveness of applied treatments. Furthermore, it can significantly contribute to expanding knowledge of wound healing processes, fibrotic-related pathologies, and various dermatological issues.

[0010] The invention concerns a system and method for the advanced diagnosis of scars, applicable in the fields of dermatology, plastic surgery, regenerative medicine and in all clinical contexts where it is necessary to monitor the evolution of scars.

[0011] In the field of scar diagnostics, several technologies and methods are currently used to evaluate and treat scars, including hypertrophic and keloid scars. These approaches range from advanced imaging techniques to standardized clinical assessments.

[0012] Regarding clinical assessments and measurement scales, scars are commonly assessed using standardized clinical scales, such as the Vancouver Scar Scale (VSS) , which considers parameters such as vascularity, pigmentation, flexibility, and scar height. Although widely used, these methods are subject to subjectivity as they rely on visual observation and the clinician experience.

[0013] Optical imaging techniques primarily focus on the non-invasive assessment of scar tissue properties, such as structure, vascularization, and optical properties. However, each of these techniques, taken individually, provides limited information and is not always sufficient to fully characterize the three-dimensional structure of scars or their physical properties, particularly optical properties .

[0014] Among the main technologies available there are:

[0015] 1. Optical Coherence Tomography (OCT) : OCT is widely used for scar assessment due to its ability to provide high-resolution images of superficial skin structures. However, its limited ability to penetrate deeply makes it difficult to assess deeper scars.

[0016] 2. High-frequency ultrasound: This technique offers good spatial resolution and allows for the visualization of deeper structures than OCT. It is particularly useful for measuring dermal thickness and identifying structural abnormalities in scar tissue, but image quality depends heavily on the operator skill.

[0017] 3. Photoacoustic Imaging (PAI) : Photoacoustic imaging is an emerging technique that combines the advantages of optical and acoustic imaging. It allows for detailed information on the vascularization and structure of scar tissue, penetrating deeper than pure optical imaging. However, its large-scale clinical application is still limited.

[0018] 4. Fibroscan: Originally developed to evaluate liver fibrosis, Fibroscan is sometimes used to assess the hardness of scar tissue. This technology is less common in dermatological practice and more suitable for thicker, internal tissue.

[0019] 5. Confocal Dermatoscopy: This technology provides high- resolution images of superficial cellular structures, similar to those obtained with a biopsy but non-invasively . However, its ability to analyse deeper structures is limited.

[0020] Laser-based treatments and diagnostics, such as pulsed dye laser (PDL) and fractional laser, are widely used for both the treatment and evaluation of scars. Despite their effectiveness in reducing the visibility of scars, these techniques have limitations in their ability to diagnose complex scar changes and assess individual response to treatment.

[0021] Recently, computational models and artificial intelligence (Al) algorithms have been developed to analyse scar images, aiming to improve diagnostic accuracy and reduce subjectivity. Although promising, these approaches are still in the experimental stage, and their effectiveness depends on the quality and quantity of data used to train the algorithms.

[0022] The limitations of existing solutions and technologies are:

[0023] - sub ectivity: many current methods, such as clinical rating scales, are highly dependent on the operator subjectivity, leading to variability in results; limited penetration: Optical technologies, such as OCT and confocal dermoscopy, are limited in their ability to penetrate deep into tissue, making comprehensive assessment of more extensive scars difficult; operator-dependent variability: Technologies such as ultrasound require significant technical expertise, which can lead to variability in results based on operator experience; incomplete tissue characterization: existing technologies often fail to fully characterize the physical properties of scar tissue, which are critical for accurate diagnosis; imaging limitations: available imaging techniques may not provide a sufficiently detailed or three-dimensional view of scars, limiting the ability to fully understand tissue structure and its evolution over time;

[0024] - limited clinical implementation: although technologies such as photo-acoustics show great promise, their clinical adoption is still limited and further studies are needed to evaluate their efficacy on a large scale; variable effectiveness of treatments: despite advances in laser treatments and other therapies, response to treatments can vary significantly between patients, and not all types of scars respond satisfactorily.

[0025] These limitations highlight the need for further technological developments to improve the accuracy and objectivity of scar diagnosis, especially regarding the assessment of the physical and structural properties of deep tissues.

[0026] Unmet need at the knowledge of the tissue microenvironment level: Beyond structural and superficial assessments, clinically actionable decision-making requires quantitative, multimodal characterization of the tissue microenvironment, including (i) epidermal immune activity with emphasis on Langerhans cells, (ii) fibroblast phenotypes, distinguishing physiological myofibroblasts from cancer-associated fibroblasts (CAF) , and (iii) vascular pattern and perfusion dynamics. No existing non-invasive system provides an integrated, in vivo, quantitative view across these axes with longitudinal follow-up suitable for clinical workflows in scars, oncology, wound healing, and surgery. Prior solutions (e.g. , photoacoustics alone) do not integrate structural, immune, cellular, and functional biomarkers within a single platform.

[0027] The proposed invention fits into this context, aiming to overcome many of the existing limitations through a non-invasive approach based on the evaluation of the physical and optical properties of the tissue, supported by advanced image and data analysis via artificial intelligence algorithms.

[0028] Scars are the result of complex tissue repair processes; however, in some cases they progress adversely, resulting in hypertrophic or keloid scars. Currently, there are no standardized diagnostic methods that accurately predict adverse progression, making early intervention difficult. More broadly, similar challenges apply to other conditions involving tissue remodeling, such as oncological lesions, chronic wounds, and post-surgical sites, where the evolution of the tissue microenvironment— including vascular pattern, fibroblast activity, extracellular matrix remodelling, and immune response— critically determines the outcome. Existing diagnostic tools typically provide only partial or superficial information (e.g. , morphological imaging) and lack quantitative, longitudinal, and multimodal assessment of these parameters in vivo. As a result, clinicians often rely on subjective evaluation or invasive biopsies, which are not always feasible or repeatable. The proposed invention addresses this unmet need by providing a non- invasive, integrated platform capable of quantitatively characterizing the tissue microenvironment, enabling early detection of adverse trajectories (such as pathological scarring, malignant transformation, impaired wound healing, or excessive fibrosis) and supporting timely, personalized intervention.

[0029] The invention provides a multimodal, modular platform integrating: (a) Mui tispectral Imaging (MSI) for superficial spectral screening and mapping of pigmentation and vascularization; (b) Mui tispectral Optoacoustic Tomography (MSOT) for dynamic vascular and perfusion analysis; (c) Mueller Matrix Polarimetry (MMP) for ECM anisotropy and structural assessment; (d) Raman spectroscopy for molecular fingerprinting of ECM components and fibroblast-associated proteins; (e) Optical Coherence Tomography (OCT) for depth-resolved morphology; (f) a Diachronic analysis module for longitudinal monitoring; and(g) optionally, an Elastic Scattering Spectroscopy (ESS) module for subcellular and nuclear / cytoplasmic scattering biomarkers, complementing Raman and MSI to enhance early detection of morphological alterations and dysplastic changes. A central Al processing unit integrates multimodal inputs to generate quantitative biomarkers of the microenvironment, including: vascular metrics (perfusion, oxygenation) , ECM metrics (anisotropy, orientation, birefringence) , epidermal immune metrics (indirect proxies of Langerhans cell activity) , and fibroblast phenotype metrics distinguishing myofibroblasts vs CAE. The system operates without biopsy and without exogenous markers, enabling non-invasive , reproducible characterization across scars, melanocytic lesions, oncological stroma, wound healing, and surgical sites.

[0030] In some embodiments, the modular architecture allows deployment as a basic configuration (e.g. MSI) or a fully integrated researchgrade platform.

[0031] To date, there is no integrated diagnostic system capable of combining complementary optical and optoacoustic technologies to provide a comprehensive, quantitative, and longitudinal characterization of the tissue microenvironment. Existing solutions are either limited to single modalities (e.g. , OCT, photoacoustics, Raman) or provide only partial, qualitative information, lacking the integration required to correlate structural, vascular, cellular, and immune parameters in vivo. The proposed invention represents a unique multimodal platform that integrates several advanced technologies— MSI, MSOT, MMP, Raman, OCT, ESS (optional) , and diachronic monitoring— combined with artificial intelligence analytics, creating a truly multidimensional approach to diagnosis. This enables not only precise identification of tissue and cellular components in scar tissue, but also comprehensive characterization of the vascular pattern, fibroblast phenotypes (physiological vs. cancer-associated) , ECM anisotropy, and epidermal immune activity. As a result, the system can distinguish scars with potential for unfavourable evolution from those that pose no risk and extend its application to oncological lesions, wound healing, and surgical site monitoring, offering essential support for early intervention and personalized clinical management.

[0032] A crucial aspect of the invention is the ability to characterize key cellular players of the tissue microenvironment. In scar tissue, this includes the ability to identify myofibroblasts, contractile cells driving wound closure and fibrosis, through detection of proteins such as alpha-SMA ( alpha- smooth muscle actin) and EDA fibronectin. Alpha-SMA is a marker of tissue contraction, while EDA fibronectin is associated with extracellular matrix deposition and modulation of the fibrotic response. Beyond scars, the system further enables assessment of fibroblast phenotypes, distinguishing physiological myofibroblasts from CAE in oncological lesions, which are key mediators of tumor stroma remodeling, angiogenesis, and immune modulation. In addition, the system can provide indirect quantification of epidermal immune activity, including Langerhans cell density and activation status, and correlate these with local vascular patterns and perfusion dynamics. The ability to detect and integrate these biomarkers allows for a precise and predictive assessment of the tissue microenvironment, providing essential diagnostic clues for early intervention and personalized therapy.

[0033] The diagnostic system is non-invasive, eliminating the need for interventions that could damage tissue or cause discomfort and / or harm to the patient. Furthermore, it does not require the use of invasive biomarkers, operating entirely in vivo. This approach ensures accurate and safe assessment, significantly improving clinical management.

[0034] Pathological scars, such as hypertrophic scars and keloids, entail significant economic and social costs, as well as serious psychological and physical consequences for patients. The proposed invention has the potential to significantly reduce these costs.

[0035] Direct costs associated with scar management include medical expenses related to treatments, which may include laser therapy, corticosteroid injections, surgery, and medications. Scar treatment is estimated to represent a significant expense for healthcare systems, with costs reaching billions of dollars annually, especially when considering the repeated therapies required to manage problematic scars and their complications. These costs can further increase when considering treatments for scars resistant to standard therapies, which require more advanced and expensive interventions. Indirect costs include lost productivity due to reduced work capacity and absenteeism caused by treatments or scar-related disabilities. Scars, especially those that limit mobility or cause chronic pain, can significantly reduce productivity, generating a negative economic impact for both individuals and society as a whole. Furthermore, psychological and physical discomfort and functional difficulties can prolong recovery times and increase the need for ongoing care.

[0036] Visible scars can profoundly impact quality of life, causing problems with self-esteem, anxiety, depression, and social isolation. The psychological impact is particularly significant in populations who have experienced trauma or surgery, where scars not only serve as reminders of the traumatic event but can also hinder social and occupational reintegration. These problems may require additional psychological and psychiatric interventions, further increasing costs for healthcare systems.

[0037] In addition to the underlying causes, scarring can cause significant symptoms such as chronic pain, itching, and physical discomfort, significantly impairing quality of life. These symptoms can lead to further complications, such as sleep disturbances and chronic fatigue, which may require additional medical care. The physical and psychological distress associated with scarring can reduce the ability to perform daily activities, increasing dependence on ongoing therapies. Beyond scars, similar clinical, economic, and psychosocial burdens are observed in other conditions characterized by pathological tissue remodelling, such as chronic wounds, oncological lesions with stromal activation, and fibrotic complications at surgical sites. By extending the analysis to the tissue microenvironment — including vascular dynamics, extracellular matrix remodelling, immune activation, and fibroblast phenotypes — the proposed invention provides a broader solution that can reduce costs, improve patient outcomes, and support earlier therapeutic decisionmaking across multiple clinical domains.

[0038] The proposed invention integrates advanced technologies such as MSI, OCT, polarimetry, diachrony analysis, Raman spectroscopy, photoacoustic analysis, and ESS (optional) , offering an innovative solution: this integrated diagnostic system allows for the early identification of scars with an unfavourable evolutionary potential, improving diagnostic accuracy and personalizing treatments. The ability to detect myofibroblasts using biomolecular markers such as alpha-SMA and EDA fibronectin is crucial for predicting scar progression and enabling timely intervention. These markers are essential for assessing scar status and predicting its progression, reducing the need for costly and invasive subsequent interventions. Furthermore, the system non-invasive , in vivo approach eliminates the need for external biomarkers or surgery, reducing patient risks and improving the quality of diagnosis and treatment. Beyond scar evaluation, the same multimodal approach can be applied to characterize the tissue microenvironment in oncological lesions, chronic wounds, and surgical sites, providing composite biomarkers of vascular, immune, and fibroblast activity that support early intervention and optimized patient management across multiple clinical domains.

[0039] In summary, the invention not only improves the diagnosis and treatment of scars, but also has the potential to significantly reduce associated costs and improve the psychophysical well-being of patients .

[0040] The invention, as claimed in the respective independent claims, consists of a non-invasive diagnostic system designed for the comprehensive assessment of the components characterizing skin scars. This system combines several innovative technologies to analyse the tissue, cellular, and molecular properties of scars, with a particular focus on the detection and monitoring of myofibroblasts, cells crucial to the healing process and the formation of pathological scars such as hypertrophic scars and keloids. This system integrates several advanced technologies: MSI, which enables superficial spectral screening and mapping of pigmentation and vascularization, providing an initial overview of tissue morphology and perfusion; OCT, which provides high-resolution images of the internal structure of scars; Muller matrix polarimetry, which measures tissue birefringence to identify structural alterations; diachronic analysis, which allows for the temporal monitoring of scar evolution by observing how cellular and tissue components, particularly myofibroblasts, change over time; Raman spectroscopy, which analyses the chemical composition of scar tissue to identify biomarkers such as a-SMA and EDA fibronectin, indicators of myofibroblast activation; opto-acous tic technology, which measures the elasticity and density of scar tissue; and, optionally, ESS, which extracts scattering-based biomarkers of subcellular and extracellular structures, providing complementary information on early tissue remodeling.

[0041] The combination of these modalities allows for early detection of potential pathological changes in scar tissue and provides a comprehensive, multimodal assessment that supports timely and targeted therapeutic interventions.

[0042] The system works by collecting optical, spectroscopic, and optoacoustic data from scar tissue and the surrounding tissue microenvironment in vivo, using a combined interface that facilitates simultaneous acquisition from all integrated modules, including MSI for superficial spectral mapping and, optionally, ESS for subcellular scattering analysis. This multimodal data is processed by a central unit equipped with artificial intelligence algorithms trained on large datasets of images and clinical data, enabling the generation of quantitative biomarkers across structural, vascular, cellular, and immune axes. The algorithms analyse and classify tissue remodelling based on the likelihood of adverse evolution — including hypertrophic scarring, pathological fibrosis, or malignant transformation — providing physicians with clear and timely guidance for targeted interventions. The system enables early identification of scars at risk of unfavourable progression, personalizes treatments based on biomarker-driven analysis, and continuously monitors tissue evolution with a focus on myofibroblast dynamics, vascular pattern changes, and immune activation signals. This comprehensive approach allows for more effective and personalized clinical management, reduces the risk of complications, and improves therapeutic outcomes.

[0043] In some embodiments, the system is implemented as a modular platform, where each imaging modality (MSI, MSOT, MMP, Raman, OCT, ESS) can be combined according to clinical requirements. This architecture allows scalable deployment (e.g. , a basic MSI + MSOT configuration for vascular screening, or a full multimodal platform for research and complex diagnostics) .

[0044] The system of the invention represents a significant innovation in the diagnostics of skin scars and in the characterization of the surrounding tissue microenvironment, providing a non-invasive and comprehensive assessment of the tissue, cellular, and molecular characteristics of scars. This system is designed to address the limitations of existing diagnostic technologies, by offering a multidimensional and quantitative evaluation through the integration of complementary optical, spectroscopic, and optoacoustic modalities. Optical and spectroscopic data are collected in vivo from scar tissue through a combined interface that integrates multiple, including MSI for superficial mapping and, in some embodiments, optional ESS, to ensure a comprehensive assessment.

[0045] 1. Tissue Analysis of the Scar

[0046] Technologies Used:

[0047] MSI : used for spectral mapping of pigmentation, vascularization, and superficial chromophore distribution, providing an initial screening layer and guiding targeted acquisition with the other modalities .

[0048] OCT: Allows us to obtain high-resolution images of the internal structures of the scar, analysing the architecture of the collagen fibres and the integrity of the various tissue components.

[0049] Muller Matrix Polarimetry: Used to evaluate the anisotropic optical properties of scar tissue, providing detailed information on the orientation of collagen fibres and the presence of structural disorganizations that could indicate unfavourable evolution.

[0050] 2. Cellular Analysis of the Scar

[0051] Technologies Used:

[0052] Diachronic Analysis: This method involves monitoring the scar over time, using images and data collected at regular intervals to assess the dynamics of myofibroblasts. Diachronic analysis allows us to observe how the myofibroblast population evolves, providing insights into the risk of pathological scar formation.

[0053] Raman spectroscopy: This non-invasive technique allows for the molecular analysis of the cellular components of the scar, with particular attention to myofibroblasts and other fibroblast phenotypes relevant to scar remodeling. Through Raman spectroscopy, it is possible to identify the presence of a-smooth muscle actin (a- SMA) , a characteristic marker of myofibroblasts, without the need for additional stains or markers. The technique allows for the detection of variations in a-SMA concentration, providing information on the density and activity of myofibroblasts.

[0054] 3. Molecular analysis of the scar

[0055] Technologies Used:

[0056] MSOT : used to visualize and quantify vascular and functional biomarkers in scar tissue, such as microperfusion, hemoglobin concentration and oxygenation. These parameters indirectly reflect tissue metabolic activity and mechanical state, providing insight into the biological processes influencing scar evolution. In relation to myofibroblasts, MSOT can monitor oxygenation levels and tissue tension gradients, factors that influence myofibroblast activity and their contribution to pathological healing. This technology allows for three-dimensional imaging, providing a detailed picture of the distribution and functional status of cells within the scar. The proposed technologies were carefully selected based on their unique ability to provide detailed, non-invasive information on the structural, cellular, vascular, and molecular characteristics of the tissue microenvironment. While the system was originally conceived to address the unmet need for objective scar assessment, its multimodal and modular nature allows extension to other contexts where precise tissue characterization is essential, including oncological lesions, wound healing, and surgical site monitoring. Each selected technology contributes complementary information, enabling a comprehensive and quantitative assessment of tissue remodeling processes, with predictive value for scar evolution and other pathological outcomes.

[0057] The following are the rationales for each selected technology:

[0058] MSI : This is used for superficial spectral screening and mapping of tissue pigmentation, vascular patterns, and chromophore distribution. This technology acquires images in multiple narrow spectral bands, allowing the extraction of quantitative parameters such as melanin concentration, hemoglobin content, and spatial distribution of vascular structures. MSI provides a rapid, non- invasive overview of the tissue surface and offers essential input features for multimodal data fusion. In preferred embodiments, MSI is employed as a first-line screening tool to guide the positioning of other modules (e.g. , Raman, OCT) and to optimize the diagnostic workflow by pre-classifying regions of interest for higher-resolution analysis . OCT: This is a high-resolution optical imaging technology that allows for detailed images of internal tissue structures, similar to a non-invasive "optical biopsy." It is particularly useful for scar analysis because it can reveal the organization of collagen fibres, tissue architecture, and overall scar integrity. This capability is essential for identifying structural features that may indicate unfavourable development, such as the formation of hypertrophic scars or keloids .

[0059] Muller Matrix Polarimetry: allows analysis of anisotropic tissue properties, such as collagen fibre orientation and the structural heterogeneity of scar tissue. This technology is crucial for identifying fibre disorganizations that could be indicative of problematic scar tissue. The ability to assess the arrangement of collagen fibres provides key information on how the scar is remodelling, which is essential for predicting whether the scar will evolve in an unfavourable way.

[0060] Diachronic Analysis: This approach is based on the temporal monitoring of scar characteristics through imaging and other data collection techniques. This approach allows us to follow the evolution of the scar over time, observing dynamic changes in cellular and tissue components. It is particularly useful for monitoring myofibroblast activity over time and detecting any changes that may indicate a risk of adverse development. This ability to continuously and longitudinally monitor scar tissue is essential for prompt intervention if signs of pathological scarring are observed.

[0061] Raman spectroscopy: This non-invasive technique allows for precise molecular information to be obtained directly from tissue, without the need for markers or contrast agents. It is particularly useful for identifying and quantifying specific molecules, such as a- smooth muscle actin (a-SMA) , a distinctive marker of myofibroblasts. Myofibroblasts are crucial for wound healing, and their activity can significantly influence scarring. Raman spectroscopy provides a non- invasive means of monitoring myofibroblast activity, allowing for early diagnosis of the risk of pathological scarring.

[0062] MSOT: combines the spatial resolution of ultrasound with optical sensitivity, allowing for three-dimensional visualization and quantification of specific biomarkers in scar tissue, such as blood oxygenation and the distribution of specific proteins. This is particularly relevant for understanding the scar microenvironment, which can influence myofibroblast activity and the healing process. MSOT provides crucial information on the functional status of the scar, which, combined with tissue and cellular data, allows for a comprehensive assessment of the risk of adverse outcome. In preferred embodiments, MSOT quantifies hemoglobin concentration, oxygen saturation (S02) , and perfusion kinetics, supporting angiogenesis mapping and functional heterogeneity assessment to inform microenvironmental risk indices.

[0063] ESS [Optional] : ESS is an optical modality that acquires scattering spectra from the tissue at multiple wavelengths, providing information on subcellular structures such as nuclear size, chromatin condensation, and cytoplasmic refractive index. These scatteringbased biomarkers offer an additional contrast mechanism, complementary to MSI and Raman, enabling early detection of dysplastic or malignant transformations and refined characterization of extracellular matrix remodelling. In preferred embodiments, ESS enhances the sensitivity and specificity of melanocytic lesion screening and may also improve the discrimination between physiological myofibroblasts and CAE by capturing subtle morphological changes not visible with imaging alone.

[0064] The technologies integrated in the invention work together to provide an accurate, multidimensional characterization of the tissue microenvironment Each modality contributes complementary, non- invasive, high-resolution information on structural organization, vascular dynamics, fibroblast phenotypes, and immune activity This integration enables not only a precise assessment of scar remodelling but also a comprehensive understanding of other tissue remodelling contexts, including oncological stroma, chronic wounds, and surgical sites. The synergy among the modules allows simultaneous analysis of structural, cellular, vascular, and molecular parameters, generating quantitative biomarkers and composite indices. For example, combining birefringence analysis from MMP with Raman-derived molecular fingerprints and MSOT-derived vascular metrics yields a detailed profile of myofibroblast persistence or CAF activation, crucial for predicting pathological outcomes and guiding timely intervention.

[0065] Quantitative Biomarkers of the Tissue Microenvironment:

[0066] - Vascular biomarkers: microvascular density, vessel caliber, hemoglobin concentration, oxygen saturation (S02) , time-to-peak, wash-in / wash-out kinetics .

[0067] - ECM biomarkers: anisotropy index, fibrillar orientation, bire f ringence / depolari zation / diattenuation, Raman peaks of collagen I / III, fibronectin ED-A, periostin, tenascin-C.

[0068] - Epidermal immune biomarkers (Langerhans-related) : indirect estimates derived from combined MSOT functional features, multispectral chromophore mapping, and polarimetric epidermal signals .

[0069] - Fibroblast phenotype biomarkers: discrimination of myofibroblasts vs CAF integrating Raman signatures, ECM disorganization, angiogenic persistence, and longitudinal dynamics.

[0070] 4. Data Processing Unit (DPU)

[0071] Integrated processor with artificial intelligence algorithms for analysing data collected from various sensors. The data is then processed by a central processing unit equipped with Al algorithms trained on a large dataset of images and clinical data. The Al-based algorithm integrates data obtained from tissue, cellular, and molecular analyses, processed using the technologies described above. These algorithms are designed to identify complex, multimodal patterns within the tissue microenvironment that may indicate pathological evolution. Particular attention is given to the persistence and activity of myofibroblasts, but the models also integrate vascular perfusion metrics, extracellular matrix structural features, and indirect biomarkers of epidermal immune activation (Langerhans cell-related) .

[0072] The Al engine classifies the analysed tissue according to its risk profile, generating composite biomarkers and a quantitative risk score. This output can be used not only for scar assessment (predicting hypertrophic or keloid evolution) , but also for oncological stroma profiling, wound healing prognosis, and surgical site monitoring. The system provides physicians with clear, reproducible, and timely recommendations to guide personalized interventions .

[0073] The Al pipeline may include feature-engineering, convolutional neural networks, ensemble classifiers, and temporal neural networks for longitudinal modelling, trained on expert-annotated datasets and, where available, optional histological correlation not forming part of the claimed method. Outputs include composite biomarker indices and a unified risk score.

[0074] Regarding the operation of the diagnostic system and its method of use, the system is applied directly to the patient' s skin, without the need to take tissue samples or perform invasive procedures. During analysis, the device's various modules — including MSI for superficial spectral mapping, MSOT for vascular and functional imaging, MMP for ECM anisotropy, Raman spectroscopy for molecular fingerprinting, OCT for depth-resolved morphology, ESS (optional) for subcellular scattering biomarkers, and the diachronic analysis module for longitudinal monitoring — acquire multimodal optical and spectroscopic data, which are automatically synchronized and processed by the central processing unit. The output consists of a composite, quantitative map of the tissue microenvironment, integrating structural, vascular, cellular, and immune parameters, and generating a predictive assessment of tissue evolution. This enables early and accurate identification not only of scars at risk of unfavourable progression, but also of melanocytic lesions with malignant potential, oncological stroma activation, and pathological fibrotic activity in wounds or surgical sites.

[0075] Operational Workflow: Step 1: Multimodal data collection through MSI screening and subsequent targeted imaging using MSOT, MMP, Raman, OCT, ESS (optional) , and diachronic analysis.

[0076] Step 2: Data fusion and processing using Al-driven predictive algorithms to extract quantitative biomarkers (vascular, ECM, fibroblast phenotype, immune activity) .

[0077] Step 3: Generation of a composite risk index and visualization of a spatially resolved heatmap or report, supporting clinical decision-making and guiding intervention strategies.

[0078] The advantages of the system of the invention are as follows:

[0079] Accurate characterization of the tissue microenvironment: Early identification of pathological signatures such as persistent myofibroblast activity, CAE-related ECM remodeling, aberrant vascular patterns, or immune dysregulation .

[0080] Personalized care: Enables risk-stratified and targeted interventions, from scar prevention to melanoma biopsy triage and surgical site management.

[0081] Continuous monitoring: Longitudinal follow-up over weeks or months to assess treatment response and dynamically adapt therapy. Practical examples of implementation

[0082] Structure of the Machine Ergonomic and portable design: The device has a compact and portable shape, similar to an advanced medical cart, but with a stable base and lockable wheels for ease of movement. The machine can be easily positioned close to the patient, allowing for non-invasive testing .

[0083] Adjustable mechanical arms: The device features one or more lightweight, flexible, fully articulated mechanical arms. These arms are designed to gently position themselves over the scar area to be analysed, such as the face, arm, or leg.

[0084] Integrated Technologies

[0085] MSI : One arm of the system is equipped with a mul tispectral imaging camera configured to acquire images in multiple spectral bands. This module enables rapid superficial screening of the tissue, providing chromophore maps, pigmentation distribution, and superficial vascular pattern visualization. MSI serves as the first step of the multimodal acquisition workflow, guiding subsequent deeper analyses and allowing early detection of abnormal patterns, such as irregular vascularization in scars or melanocytic lesions.

[0086] OCT: One arm is dedicated to OCT, with an optical module that emits and collects low-coherence light to create detailed images of subcutaneous structures. Muller Matrix Polarimeter: Another arm is equipped with a polarimeter that analyses the polarization properties of light reflected from the skin, helping to characterize scars.

[0087] Diachronic Analysis: This module is designed to study temporal variations in scar characteristics, monitoring subtle changes over time .

[0088] Raman Spectroscopy: A third arm integrates a Raman spectroscopy system, used for non-invasive chemical analysis of tissues.

[0089] Opto-acoustics : The optoacoustic system is integrated to generate high-resolution images based on light-induced acoustic waves, adding an additional level of detail to the analysis.

[0090] ESS (optional) : An optional module integrates elastic scattering spectroscopy, acquiring scattering spectra across multiple wavelengths to extract subcellular and extracellular biomarkers. ESS provides information about nuclear size, chromatin condensation, and cytoplasmic refractive index, offering an additional layer of contrast to distinguish normal from dysplastic or malignant tissue. When combined with MSI and Raman spectroscopy data, ESS enhances the ability to detect early morphological and biochemical changes, refining risk stratification in scar remodelling and melanocytic lesion screening.

[0091] User Interface Advanced Touchscreen: The device features a large touchscreen that allows the physician to control and monitor all integrated technologies. The interface displays images and collected data in real time, with the ability to overlay and compare results from different technologies.

[0092] Integrated Al: Data analysis is assisted by an artificial intelligence system that processes the collected information, providing a preliminary diagnosis and suggesting further analysis if necessary .

[0093] Analysis Area

[0094] Scanning Area: The scanning area is designed to be flexible, adapting to different areas of the body. It may include safety sensors that ensure the patient is positioned correctly and that the device does not come into direct contact with the skin, keeping the analysis completely non-invasive .

[0095] Patient comfort: The examination area is surrounded by soft, padded materials to ensure maximum comfort during the examination, with LED lights indicating the status of each technological module.

[0096] Aesthetics and general design

[0097] High-tech and clean look: The machine has a modern and minimalist look, with smooth white and grey surfaces and metallic accents. Coloured LED lights indicate the operating status of the various modules, adding a futuristic touch to the design. The invention system is composed of the following Modules:

[0098] Module 0: Multispectral Imaging (MSI) . A multispectral camera configured to acquire images in multiple spectral bands for surfacelevel mapping of pigmentation, vascular pattern, and chromophore distribution, providing rapid screening features and inputs for multimodal integration.

[0099] Module 1: Optical Coherence Tomography (OCT) , this module captures high-resolution images of the internal structures of scars, using light reflection to generate a tomographic image of the tissue. Schematic: comprising the broadband light source, beam splitter, sample (scar tissue) , reflection detector, and image processor. The system reflects light from the tissue and reconstructs the internal image of the scar.

[0100] Module 2: Muller Matrix Polarimetry, this module measures the birefringence of scar tissue by detecting changes in the polarization of light through the tissue. Schematic: includes the polarized light source, the initial polarizer, the sample (scar tissue) , the polarization analyser, and the detector. The module measures the tissue birefringence, indicating the presence of structural abnormalities .

[0101] Module 3: Diachronic Analysis, this module measures temporal changes in the optical and mechanical properties of scar tissue, providing insights into the dynamics of healing. Schematic: includes the temporal data acquisition system, the sample (scar tissue) , and the data processor. The module compares measurements at different times to detect changes in the scar over time.

[0102] Module 4: Raman Spectroscopy, this module analyses the chemical composition of scar tissue by detecting the specific molecular vibrations of collagen, a-SMA, and fibronectin EDA. Schematic diagram: including the laser source, the sample (scar tissue) , the Raman scatterer, and the spectroscopic detector. The system collects the Raman spectrum of the tissue, providing information on the chemical composition and activation of myofibroblasts.

[0103] Optional Module: Elastic Scattering Spectroscopy (ESS) . Configured to acquire scattering spectra at multiple wavelengths to extract subcellular and extracellular scattering biomarkers (e.g. , nuclear size, chromatin condensation, cytoplasmic refractive index) . ESS complements MSI / OCT / Raman by detecting early morphological changes relevant to scar remodeling and melanocytic lesion screening, enabling early detection of dysplastic or malignant transformation and refining fibroblast phenotype analysis.

[0104] Optoacoustic System, this module measures the elasticity and density of scar tissue using laser pulses to generate acoustic waves that are detected by the transducer. Schematic: comprising the pulsed laser source, the sample (scar tissue) , and the acoustic transducer. The system detects the generated acoustic waves, providing a measurement of the tissue elasticity and density.

[0105] Final Module: Complete Diagnostic System, combines all previous modules into a single integrated system that processes data and images through an artificial intelligence unit, simplifying the user interface and providing accurate diagnoses. Complete diagram of the Novainsight non-invasive diagnostic system, integrating all modules: OCT, Muller Matrix Polarimetry, Raman Spectroscopy, Opto-acous tics , and Diachronic Analysis, connected to the central Al unit. The system analyses scars in vivo, providing a comprehensive and predictive assessment .

[0106] Examples of Realization

[0107] The following preferred embodiments illustrate the versatility of the invention across multiple clinical contexts, including scar assessment, oncological lesion characterization, wound healing prediction clinically actionable, quantitative biomarkers equivalent to histopathological information without the need for biopsy.

[0108] Example 1: Pre-operative evaluation of a hypertrophic scar

[0109] A patient presents to the doctor with a hypertrophic scar on his arm, formed after an accidental trauma. The doctor decides to use the non-invasive diagnostic system described above to evaluate the scar and determine the most appropriate treatment strategy. System preparation and positioning: The diagnostic device of the invention is placed over the scar. The physician applies a conductive gel to facilitate the transmission of optoacoustic signals.

[0110] Image and Data Acquisition:

[0111] - MSI : The multispectral imaging camera is used as a first step to acquire surface-level maps of pigmentation, chromophore distribution, and superficial vascular patterns. MSI highlights areas of abnormal vascularity and helps define the most representative regions for deeper multimodal analysis.

[0112] - OCT: Acquires high-resolution images of the internal structure of the scar, revealing the organization and density of collagen fibres .

[0113] Polarimetry: Measures the birefringence of the tissue, highlighting misalignments of collagen fibres that could indicate pathological scarring.

[0114] - Diachronic Analysis: Monitors the scar over time, acquiring images and data at regular intervals to assess the evolution of scar tissue, observing cellular dynamics— particularly changes in the population and activity of myofibroblasts— and identifying early signs of pathological scar development.

[0115] - Raman Spectroscopy: Analyses the chemical composition of scar tissue, identifying the presence of activated myofibroblasts through a-SMA and fibronectin EDA detection. Opto-acoustics : Measures tissue elasticity and density, providing additional information on scar stiffness.

[0116] ESS (optional) : If activated, the elastic scattering spectroscopy module acquires scattering spectra to assess subcellular changes such as nuclear size and chromatin condensation, providing additional contrast for detecting early dysplastic or abnormal fibroblast phenotypes.

[0117] Data processing and Al analysis: All acquired data are sent to the central processing unit, where they are analysed by artificial intelligence algorithms. The Al compares the data with a database of previously analysed and classified scars, generating a composite risk index .

[0118] Result and diagnosis: The system outputs a comprehensive assessment indicating that the scar shows structural, vascular, and molecular characteristics consistent with an unfavourable progression toward hypertrophic scarring. The doctor decides to proceed with early treatment, including corticosteroid injections and fractional laser therapy, to prevent further thickening of the scar.

[0119] Example 2 (Revised) : Post-operative monitoring of a surgical scar

[0120] A patient undergoing plastic surgery presents for a postoperative check-up. The surgeon uses the multimodal diagnostic system to monitor scar healing and prevent potential complications. Initial data acquisition: One week after surgery, the diagnostic system is used to acquire a baseline dataset on the developing scar. MSI : Multispectral imaging is performed first to generate superficial vascular and pigmentation maps, defining the most representative regions for deeper acquisition. OCT: Reveals good organization of collagen fibres and normal dermal thickness. Polarimetry: Confirms well-aligned collagen fibres, suggesting physiological healing. Raman Spectroscopy: Indicates an absence of activated myofibroblasts (a-SMA negative) . ESS (optional) : When performed, confirms normal nuclear size and chromatin pattern, consistent with non-prolif erative fibroblastic activity.

[0121] Mid-term monitoring: One month after surgery, the system is used again to monitor the scar. MSI: Detects a slight increase in superficial vascularity around the scar margins, considered part of the normal maturation process. Optoacoustics: Measures a moderate but stable tissue stiffness without pathological perfusion deficits. Al analysis compares these new data with baseline, confirming no adverse evolution .

[0122] Final evaluation: Three months after surgery, the system detects no signs of myofibroblast activation, ECM disorganization, or abnormal increase in tissue density. ESS and MSI confirm normalization of vascular and nuclear parameters. The surgeon confirms that the scar is healing properly, and no further intervention is required. Example 3: Identification of scars at risk of unfavourable evolution

[0123] A patient with a history of keloid scars presents with a new scar formed after a burn. The doctor decides to use the diagnostic system to assess the risk of developing a keloid scar.

[0124] Data acquisition and Al analysis: The invention is used to analyse the new scar. Raman spectroscopy detects the presence of EDA fibronectin and elevated levels of a-SMA, key indicators of myofibroblast activation. OCT shows increased tissue density, and polarimetry highlights significant misalignment of collagen fibres.

[0125] Diagnosis and treatment plan: Al analysis classifies the scar as high risk of developing into a keloid. The doctor decides to initiate aggressive treatment with silicone and corticosteroid injections, combined with laser therapy, to prevent keloid formation.

[0126] Follow-up: Diagnostics are used during follow-up visits to monitor treatment response. With early diagnosis and ongoing monitoring, the scar is successfully managed, preventing the development of a keloid scar.

[0127] Example 4 : Melanocytic lesion screening (biopsy reduction)

[0128] Multimodal acquisition (MSI + MSOT + Raman + MMP) yields a composite risk biomarker that stratifies lesions (low vs high risk) . In a pilot cohort, the system enables safe deferral of biopsy for low-risk lesions, reducing unnecessary excisions while preserving sensitivity for melanoma triage.

[0129] Outcome: fewer unnecessary biopsies, accelerated workflows, improved patient comfort.

[0130] Example 5: Chronic wound healing prediction

[0131] Serial acquisitions generate a healing probability index (e.g. , 4-6 weeks closure prediction) by integrating perfusion / oxygenation (MSOT) , ECM remodeling (MMP / Raman) , and immune-related signals (Langerhans proxies) .

[0132] Outcome: earlier therapy optimization, lower amputation risk.

[0133] Example 6: Surgical site monitoring.

[0134] Peri- and post-operative monitoring tracks flap perfusion, immune activation, and fibroblast activity; early detection of ischemia or excessive fibrosis triggers timely intervention (e.g. , flap revision, pharmacologic modulation) .

[0135] Outcome: reduced dehiscence / necrosis, fewer readmissions.

[0136] Example 7 : Oncological stroma profiling

[0137] CAE-related signatures (Raman + MMP) and oxygenation heterogeneity (MSOT) support grading and margin assessment, potentially lowering local recurrence.

[0138] Outcome: quantifiable stromal activation biomarker to guide management . Implementation for best results

[0139] To achieve optimal results, the invention should be integrated into the standard care protocol for patients at risk of developing pathological scarring, fibrotic diseases, or abnormal tissue remodeling, as well as for those undergoing oncological screening or surgical site monitoring. Below are some options to address and improve the critical issues related to the specificity, sensitivity, and reproducibility of the technologies involved:

[0140] 1. MSI optimization for superficial mapping

[0141] MSI can be optimized by selecting narrow-band filters tailored to key chromophores (oxy- / deoxy-hemoglobin, melanin) to improve sensitivity to vascular and pigment alterations. Advanced registration algorithms can ensure precise co-localization with other modalities (OCT, MSOT) .

[0142] 2. OCT optimization for higher resolution and contrast

[0143] OCT can sometimes suffer from limitations in image resolution and contrast, which can affect the ability to distinguish between different types of tissue microenvironment alterations. Implementing optimized wavelength light sources and advanced post-processing algorithms improves image resolution. The use of speckle reduction techniques and Al-based automatic segmentation can increase contrast and specificity in tissue visualization.

[0144] 3. Increased sensitivity in Muller Matrix Polarimetry The sensitivity of polarimetry may be limited when birefringence changes are subtle. Use polarizers with higher angular resolution and optical amplifiers to improve detection of minimal polarization variations. The integration of Al-based filtering algorithms can help eliminate noise and improve measurement accuracy.

[0145] 4. Diachronic analysis for greater temporal precision

[0146] The accuracy of detecting temporal changes can be compromised by fluctuations in acquisition conditions. Implement environmental control systems to ensure stable conditions during repeated acquisitions. Integrating deep learning-based temporal analysis algorithms can improve the ability to detect subtle changes and provide more accurate predictions of tissue microenvironment evolution .

[0147] 5. Improving the specificity of Raman Spectroscopy

[0148] The specificity of Raman spectroscopy can be reduced by the presence of background signals or interference from other tissue components . Apply background subtraction techniques to remove background signals and use multiwavelength lasers to achieve greater penetration depth and molecular specificity. Multivariate analysis of spectroscopic data can improve the identification of specific biomarkers such as a-SMA, fibronectin EDA, periostin, and tenascin-C.

[0149] 6. Increased accuracy in optoacoustic analysis (MSOT) The accuracy of measuring tissue perfusion and elasticity can be affected by variations in acoustic response. Implement broadband transducers with greater acoustic sensitivity and develop acoustic compensation algorithms that correct for variations in tissue response. Optoacoustic tomography techniques can provide detailed three-dimensional vascular and metabolic maps, enabling microenvironmental risk stratification.

[0150] 7. ESS optimization for subcellular contrast (optional)

[0151] ESS can be optimized by calibrating reference phantoms to distinguish nuclear size distributions, chromatin condensation, and cytoplasmic refractive indices. This enhances early detection of dysplasia in melanocytic lesions and improves discrimination of proliferative vs. quiescent fibroblasts in scar tissue.

[0152] The implementation of these technological solutions will improve the overall specificity, sensitivity, and reproducibility of the system of the invention, making it an even more powerful and reliable tool for the characterization of the tissue microenvironment in scars, oncology, chronic wounds, and surgical sites.

[0153] Adaptation for Telemedicine

[0154] To adapt the device to this new demand, we can imagine a system where artificial intelligence (Al) analyses the collected data and returns a simplified result that is immediately understandable even to a non-healthcare professional. This could include the use of simple symbols and colour codes, avoiding complex images. In certain embodiments, the system supports secure cloud connectivity for remote review and longitudinal follow-up, with anonymized data, audit trails, and interoperability with healthcare IT systems. In some embodiments, the system comprises a secure connectivity and telemedicine module enabling remote data transfer, cloud-based Al inference, and longitudinal follow-up by specialists. This feature supports teledermatology, wound care at home and decentralized clinical trials.

[0155] 1. Interface with Al

[0156] No complex images. The device does not display detailed images of the results. Instead, the collected data is sent to an integrated artificial intelligence system that processes and analyses the information .

[0157] Simplified result. The Al returns a very simple output, such as a three-color traffic light (green, yellow, red) to indicate "normal," "caution," and "problem," respectively, accompanied by an intuitive symbol, such as a green checkmark, a yellow exclamation point, or a red cross.

[0158] Specific diagnosis. In addition to colours and symbols, the Al provides a specific diagnosis in the form of short text, such as "Scar stable," "Monitor scar," or "Intervention recommended."

[0159] 2. Simple and clear display Minimal interface. The display on the device shows only symbols and colours, with clear and understandable text diagnosis.

[0160] No interpretation required. The output is designed to be understandable without the need for medical expertise, ideal for use by non-healthcare professionals.

[0161] 3. Use on patient

[0162] Direct skin contact. The operator places the device directly on the patient skin, such as on the arm or face, and the device automatically begins scanning and analysing.

[0163] Instant feedback. After a few seconds, the device displays the simplified result.

[0164] 4. Cloud / IT

[0165] In certain embodiments, the system supports secure cloud connectivity for remote review and longitudinal follow-up, with anonymized data, audit trails, and interoperability with healthcare IT systems.

[0166] Conclusions

[0167] The invention represents a significant advance in the field of non-invasive diagnostics, offering an integrated and multimodal solution for the characterization of the tissue microenvironment, including but not limited to scar tissue assessment. Through the innovative combination of optical and optoacoustic technologies — including Optical Coherence Tomography (OCT) , Muller Matrix Polarimetry (MMP) , Raman Spectroscopy, Multispectral Imaging (MSI) , Multispectral Optoacoustic Tomography (MSOT) , Elastic Scattering Spectroscopy (ESS, optional) , and Diachronic Analysis — the invention enables predictive, quantitative, and highly specific assessment of structural, vascular, cellular, and immunological parameters.

[0168] This integration allows not only accurate diagnosis of pathological scars but also early prediction of hypertrophic or keloid evolution, stratification of melanocytic lesions, profiling of tumor associated stroma (CAE activity) , and longitudinal monitoring of wound healing and surgical sites.

[0169] The use of advanced artificial intelligence algorithms to analyse the collected data not only improves the accuracy and specificity of diagnoses but also enables dynamic and personalized patient monitoring. The invention is particularly useful not only in the clinical management of scars but also in the study of diseases characterized by irregular fibrosis, offering a powerful tool for research and early diagnosis of complex conditions.

[0170] The use of advanced artificial intelligence algorithms to integrate multimodal data generates quantitative biomarkers of the tissue microenvironment, including vascular pattern, extracellular matrix anisotropy, fibroblast phenotype, and epidermal immune activity related to Langerhans cells. These biomarkers provide actionable and reproducible indices for clinical decision-making, enabling early intervention and personalized therapeutic strategies. This not only improves the accuracy and reproducibility of the results but also enables longitudinal and personalized monitoring of the tissue microenvironment. By integrating structural, vascular, cellular, and immune biomarkers, the system generates clinically actionable indices that support early decision-making, reduce unnecessary biopsies, and improve patient outcomes.

[0171] Due to its ability to integrate multiple diagnostic modalities into a single system, the invention has the potential to become a fundamental tool in dermatology, plastic surgery, and burn treatment units. Furthermore, with its applicability in studying fibrosis in various body tissues, this technology opens new frontiers in biomedical research.

[0172] In summary, the invention not only innovates the approach to the diagnosis and management of scars, but extends its potential to a wide range of clinical and research applications, significantly contributing to the improvement of treatments and understanding of fibrotic diseases.

[0173] In summary, the system comprises an ergonomic handpiece connected to a modular mobile unit, integrating Optical Coherence Tomography (OCT) , Muller Matrix Polarimetry, Raman Spectroscopy, Opto-acous tics and Diachronic Analysis technologies, where the data collected by each module is analysed by a central processing unit equipped with artificial intelligence algorithms to provide a predictive diagnosis of scar evolution.

[0174] This integrated system enables a comprehensive, multidimensional assessment of scars, combining multiple diagnostic modalities to obtain detailed information on the structure, composition, and optical properties of scar tissue.

[0175] The use of artificial intelligence algorithms for data analysis significantly improves the accuracy and objectivity of diagnosis, overcoming the limitations of traditional assessment techniques.

[0176] The central processing unit can be configured to run deep learning algorithms and convolutional neural networks to analyse the data and images collected by the modules, improving the accuracy and specificity of diagnosis.

[0177] The implementation of advanced machine learning techniques allows the system to identify complex patterns and subtle variations in scar characteristics that may otherwise escape the human eye, leading to greater accuracy in predicting scar progression and planning treatment.

[0178] The Raman Spectroscopy module can be configured to detect scarspecific biomarkers, including a-SMA and EDA fibronectin, providing insights into myofibroblast activation and other molecular indicators of scar evolution. This ability to detect specific biomarkers at the molecular level offers a significant advantage in understanding the biological processes underlying scar formation and evolution, allowing for a more precise assessment of the risk of developing pathological scars and more effective personalization of treatments.

[0179] The integration of multimodal technologies can enable the monitoring and study of wound healing processes and diseases characterized by dysregulated fibrosis, such as pulmonary fibrosis, liver cirrhosis, and chronic kidney disease.

[0180] This feature significantly extends the system scope, making it a valuable tool not only for dermatology but also for other medical specialties dealing with fibrotic diseases, opening up new research possibilities and improving our understanding of these complex conditions .

[0181] The central processing unit can be configured to analyse temporal changes in scar tissue properties through diachrony analysis, providing a dynamic and predictive assessment of wound healing and scar evolution.

[0182] The ability to monitor and analyse changes over time represents a significant advancement in scar management, allowing for timely intervention and ongoing customization of treatment based on observed evolution . The diagnostic device can be configured for use in clinical settings, particularly in dermatology, plastic surgery, and burn treatment units, for pre-operative and post-operative scar assessment .

[0183] This versatility in clinical application makes the system a valuable tool for various medical specialties, improving patient management in various contexts and stages of scar treatment.

[0184] The diagnostic system of the invention may comprise an ergonomic handpiece connected to a modular mobile unit.

[0185] This ergonomic handpiece can be designed to be easily handled by the operator, allowing for precise and comfortable positioning on the patient scar tissue.

[0186] The modular mobile unit can be designed to accommodate and integrate the various diagnostic technologies used by the system, including Optical Coherence Tomography (OCT) , Muller Matrix Polarimetry, Raman Spectroscopy, Opto-acoustics and Diachronic Analysis .

[0187] Each module can be designed to function independently, but can also be coordinated with other modules to provide a comprehensive, multidimensional scar assessment.

[0188] This unit can be easily moved and positioned near the patient, allowing quick and convenient access during the examination. In some cases, the modular mobile unit may be equipped with lockable wheels to ensure stability during use.

[0189] Advantageously, the ergonomic handpiece can be designed to be placed directly on the patient skin, such as on the arm or face, and automatically begins scanning and analysis once positioned.

[0190] This can eliminate the need for invasive procedures or tissue sampling, making the entire diagnostic process more comfortable and less stressful for the patient.

[0191] Furthermore, the ergonomic design of the handpiece can facilitate the operator use, allowing precise positioning and accurate control during the examination.

[0192] Additionally, the modular mobile unit can be equipped with a centralized control system that manages data acquisition and processing, ensuring efficient and synchronized operation of the diagnostic system.

[0193] The diagnostic system of the invention integrates Optical Coherence Tomography (OCT) technology.

[0194] OCT is a high-resolution optical imaging technology that allows for detailed images of internal tissue structures, similar to a non- invasive "optical biopsy". This technology is particularly useful for scar analysis because it can reveal the organization of collagen fibres, tissue architecture, and overall scar integrity.

[0195] This ability is essential for identifying structural features that may be indicative of an unfavourable evolution, such as the formation of hypertrophic scars or keloids .

[0196] In the system of the invention, the OCT can be optimized to improve the resolution and contrast of the images.

[0197] Advantageously, OCT-optimized light sources can be used, which emit light at specific wavelengths to improve image resolution.

[0198] These light sources can be selected to maximize light penetration into the scar tissue, allowing for more detailed images of the internal structures of the scar.

[0199] Furthermore, in the system of the invention, advanced postprocessing algorithms can be implemented to further improve the quality of OCT images.

[0200] These algorithms can include "speckle reduction" techniques to reduce image noise and improve contrast, and Al-based automatic segmentation techniques to precisely identify and delineate tissue structures in OCT images. These optimizations can significantly improve the system ability to detect and characterize scars, providing a more accurate and detailed diagnosis.

[0201] Muller Matrix Polarimetry is used to analyse the anisotropic optical properties of scar tissue, providing detailed information on the orientation of collagen fibres and the presence of structural disorganizations that could indicate unfavourable scar evolution.

[0202] According to the present invention, the Muller Matrix Polarimetry module can be equipped with a polarizer with increased angular resolution capability and optical amplifiers to improve the detection of minute changes in light polarization, which can allow for more precise and reliable measurements of the birefringence properties of scar tissue.

[0203] Furthermore, in the system of the invention, artificial intelligence-based filtering algorithms can be implemented to eliminate noise and improve the accuracy of Muller Matrix Polarimetry measurements .

[0204] These algorithms can be trained on a large dataset of scar images and clinical data, allowing them to identify complex patterns associated with scars with potential adverse evolution.

[0205] In the diagnostic system of the invention according to the present invention, Raman Spectroscopy technology is integrated. This technology is used for the non-invasive chemical analysis of tissues, allowing the detection and quantification of specific molecular biomarkers.

[0206] In particular, Raman spectroscopy can be used to identify the presence of activated myofibroblasts in scar tissue, through the detection of specific biomarkers such as a-SMA (alpha-smooth muscle actin) and EDA fibronectin.

[0207] These biomarkers are key indicators of the activation of myofibroblasts, cells crucial in the healing process and in the formation of pathological scars such as hypertrophic scars and keloids .

[0208] Furthermore, Raman Spectroscopy includes the laser source, the sample (scar tissue) , the Raman scatterer, and the spectroscopic detector .

[0209] The system collects the Raman spectrum of the tissue, providing information on the chemical composition and activation of myofibroblasts .

[0210] Advantageously, the diagnostic system of the invention can use "background subtraction" techniques to improve the specificity and sensitivity of Raman spectroscopy.

[0211] These techniques can be used to remove nonspecific background signals, improving the ability to detect and quantify specific biomarkers such as a-SMA and EDA fibronectin. Furthermore, multivariate analysis of spectroscopic data can be used to further improve the identification of specific biomarkers.

[0212] The diagnostic system of the invention integrates opto-acoustic technology, which uses the interaction between light and sound to generate opto-acoustic signals, which can be used to obtain high- resolution images of tissues.

[0213] In particular, opto-acous tics can be used to measure the elasticity and density of scar tissue, providing detailed information about the tissue stiffness and structure.

[0214] The Opto-acous tics module may include a laser illumination system, an acoustic transducer and a signal processing system.

[0215] The laser illumination system can be designed to emit pulses of light at a specific wavelength, optimized to generate acoustic waves in the scar tissue.

[0216] The acoustic transducer can be designed to detect acoustic waves generated by light and convert them into electrical signals, the signal processing system can be designed to analyse the electrical signals and generate opto-acoustic images of the scar tissue.

[0217] Advantageously, the diagnostic system of the invention can utilize broadband transducers to improve the sensitivity and resolution of opto-acoustic images. These transducers can be designed to detect a wide range of acoustic frequencies, allowing for high- resolution imaging of scar tissue. Additionally acoustic compensation algorithms can be implemented to correct for variations in tissue response, further improving measurement accuracy.

[0218] According to the present invention, the Diachronic Analysis technology is integrated into the diagnostic system of the invention.

[0219] This technology is used to monitor temporal changes in scar tissue properties, providing a dynamic and predictive assessment of wound healing and scar evolution.

[0220] The Diachronic Analysis module can be configured to acquire images and data at regular intervals, allowing to observe how cellular and tissue components, particularly myofibroblasts, change over time.

[0221] This module may include a time-based data acquisition system, which can be designed to collect data continuously or at predefined interval s .

[0222] Additionally, a data processing system can be implemented to analyse temporal changes and provide a dynamic assessment of scar evolution .

[0223] In particular, the diagnostic system of the invention can use artificial intelligence-based temporal analysis algorithms. These algorithms can be trained on a large dataset of images and clinical data of scars, allowing the identification of complex patterns associated with scars with potential unfavourable evolution. The central processing unit of the diagnostic system of the invention can be designed to run advanced artificial intelligence algorithms for analysing the data and images collected by the various modules. This unit can be equipped with a high-performance processor and large-capacity memory, designed to handle large amounts of data and perform complex calculations in real time.

[0224] Artificial intelligence algorithms used in the central processing unit may include deep learning algorithms and convolutional neural networks. Such algorithms can be trained on large datasets of images and clinical scar data, allowing them to identify complex patterns associated with scars with potential for adverse evolution.

[0225] Additionally, deep learning algorithms can be used to analyse images collected by MSI, OCT, Muller Matrix Polarimetry, Raman Spectroscopy, Opto-acous tics modules, and ESS (optional) .

[0226] These algorithms can be designed to recognize specific features in images, such as collagen fibre structure, fibre orientation, the presence of activated myofibroblasts, and the optical and mechanical properties of scar tissue.

[0227] Additionally, artificial intelligence algorithms can be used to analyse the data collected by the Diachronic Analysis module. These algorithms can be designed to detect temporal changes in scar tissue properties, providing a dynamic and predictive assessment of scar evolution .

[0228] In summary, the central processing unit and artificial intelligence algorithms of the diagnostic system of the invention can provide more comprehensive and accurate diagnosis of scars, significantly improving the clinical management of scars and fibrotic diseases .

[0229] The diagnostic system of the invention integrates a simplified interface with Al analysis that returns a simplified result that is understandable even for non-healthcare professionals. This interface is designed to be intuitive and easy to use, allowing the operator to start and monitor the analysis in just a few simple steps.

[0230] The interface includes:

[0231] - a visual display showing the analysis results in real time, using simple symbols and colour codes to indicate the state of the scar and the risk of adverse evolution;

[0232] - a touch-screen input system, designed to be robust and reliable, that allows the operator to select analysis options and view results.

[0233] The simplified output provided by Al analysis may include the use of simple symbols and colour codes. For example, a green check mark may indicate that the scar is stable and shows no signs of adverse development, while a yellow exclamation point may indicate that the scar requires closer monitoring; a red cross may indicate that the scar shows signs of adverse development and may require therapeutic intervention.

[0234] Advantageously, the simplified Al analysis interface of the inventive diagnostic system can provide immediate and understandable feedback to operators, improving the efficiency and effectiveness of scar diagnosis.

[0235] In some aspects, the diagnostic system of the invention can be configured for use in a clinical setting, particularly in dermatology, plastic surgery, and burn treatment units.

[0236] In the dermatology department, the system of the invention can be used for the diagnosis and monitoring of skin scars caused by various dermatological conditions, such as acne, dermatitis, skin infections and autoimmune diseases.

[0237] Additionally, the system can be used to evaluate the effectiveness of dermatological treatments, such as laser therapies, topical medications, and systemic treatments, by monitoring changes in the optical, mechanical, and chemical properties of scar tissue over time.

[0238] In plastic surgery departments and burn treatment units, the system of the invention can be used to assess patient scars before and after surgery to predict the risk of pathological scar formation, and to monitor the evolution of scars over time. This can allow surgeons to plan surgical procedures more effectively, intervene promptly in the event of unfavourable scar evolution, and monitor the effectiveness of post-operative treatments.

[0239] In summary, the diagnostic system of the invention can provide an effective means for the assessment and monitoring of scars in various clinical settings, significantly improving the clinical management of scars and fibrotic diseases.

[0240] The diagnostic system of the invention, according to the present invention, offers numerous advantages over existing diagnostic technologies for the evaluation of skin scars.

[0241] One of the main advantages is its diagnostic accuracy. Due to the integration of several advanced technologies, such as OCT, Muller Matrix Polarimetry, Raman Spectroscopy, Opto-acoustics , and Diachronic Analysis, the system of the invention can provide an extremely precise quantitative and qualitative assessment of the optical, mechanical, and chemical properties of scar tissue. This allows for the precise identification of the tissue and cellular components of scars, providing a more accurate and detailed diagnosis than traditional diagnostic methods.

[0242] Another significant advantage of the inventive system is its non-invasiveness . The system is designed to operate entirely in vivo, eliminating the need for tissue sampling or the use of exogenous biomarkers. This makes the entire diagnostic process more comfortable and less stressful for the patient, reducing the risk of complications associated with invasive procedures.

[0243] Furthermore, the non-invasive nature of the system of the invention allows for repeated analyses to be performed over time, providing a dynamic assessment of the evolution of scars.

[0244] Finally, the system of the invention offers advanced predictive capabilities due to the use of artificial intelligence algorithms for the analysis of the collected data; the system can identify complex patterns associated with scars with potential unfavourable evolution.

[0245] In summary, the diagnostic system of the invention offers superior diagnostic accuracy, non-invasiveness , and advanced predictive capacity compared to existing diagnostic technologies for assessing skin scars. These advantages can significantly improve the clinical management of scars and fibrotic diseases, helping to improve the quality of care and reduce healthcare costs associated with these conditions.

[0246] Some preferred embodiments of the present invention have been illustrated and described above: obviously, numerous variants and modifications, functionally equivalent to the previous ones, will be immediately evident to those skilled in the art, which fall within the scope of the invention as highlighted in the appended claims. The multimodal system can be manufactured using established optical / optoacoustic components in a compact, portable medical device. The modular design enables scalable production and incremental validation. Clinically, the platform serves as a non- invasive alternative to biopsy for microenvironment characterization across dermatology, oncology, wound care, and surgery, improving outcomes, reducing costs, and accelerating decisions. Thanks to its modular design and regulatory compliance readiness (EU MDR, FDA) , the system is suitable for scalable production, clinical translation and integration into hospital workflows, enabling its adoption as a standard tool for tissue microenvironment assessment.

[0247] The system is configurable to comply with medical device regulations (EU MDR; FDA) . The modular architecture allows stepwise validation of each imaging component. Generating quantitative biomarkers rather than direct diagnostic outcomes supports classification as clinical decision-support, facilitating CE marking and FDA clearance pathways.

Claims

1. CLAIMS1. Non-invasive diagnostic system for the assessment of scars, comprising at least one ergonomic handpiece operatively connected to at least one modular mobile unit; wherein said ergonomic handpiece and said modular mobile unit comprise :- at least one integrated Optical Coherence Tomography (OCT) module ;- at least one Muller Matrix Polarimetry module;- at least one Raman Spectroscopy module;- at least one Opto-acoustics module;- at least one module of Diachronic Analysis;- a Mui ti spectral Optical Tomography (MSOT) module; and- at least one central processing unit equipped with artificial intelligence algorithms configured to analyse the data collected by said modules.

2. System according to claim 1, wherein the Optical Coherence Tomography (OCT) module is designed to capture high-resolution images of the internal structures of scars, using the reflection of light to generate a tomographic image of the tissue, said OCT module comprising a broadband light source, a beam splitter, a reflectiondetector and an image processor, the system reflecting light from the tissue and reconstructing the internal image of the scar.

3. System according to claim 1 or 2, wherein the Muller Matrix Polarimetry module is designed to measure the birefringence of scar tissue by detecting changes in the polarization of light through the tissue, said module comprising a polarized light source, an initial polarizer, a polarization analyser, and a detector, said module measuring the birefringence of the tissue, indicating the presence of structural abnormalities.

4. System according to claim 1, 2, or 3, wherein the Diachronic Analysis module is designed to measure temporal changes in the optical and mechanical properties of scar tissue, providing information on the dynamics of healing, said module comprising a temporal data acquisition system, and a data processor, said module comparing measurements at different times to detect changes in the scar over time.

5. System according to any preceding claim, wherein the Raman Spectroscopy module is designed to analyse the chemical composition of scar tissue by detecting the specific molecular vibrations of collagen, a-SMA, and fibronectin EDA, said module comprising a laser source, a Raman scatterer, and a spectroscopic detector, the module collecting the Raman spectrum of the tissue, providing information on the chemical composition and activation of myofibroblasts.

6. System according to any preceding claim, wherein the OptoAcoustic system module is designed to measure the elasticity and density of scar tissue using laser pulses to generate acoustic waves which are detected by the transducer, said module comprising a pulsed laser source, and an acoustic transducer, said module detecting the generated acoustic waves, providing a measure of the elasticity and density of the tissue.

7. System according to any preceding claim, wherein the Multispectrum Optical Tomography (MSOT) module is designed to combine the spatial resolution of ultrasound with optical sensitivity, allowing for three-dimensional visualization and quantification of specific biomarkers in scar tissue, such as blood oxygenation and the distribution of specific proteins, the MSOT module providing crucial information on the functional status of the scar, which, combined with tissue and cellular data, allows for a comprehensive assessment of the risk of adverse evolution.

8. System according to any preceding claim, wherein the central processing unit is designed to unite all the preceding modules into a single integrated system that processes data and images via an artificial intelligence unit, simplifying the user interface and providing accurate diagnoses, said central processing unit analysing scars in vivo, providing a comprehensive and predictive assessment.

9. System according to any preceding claim, wherein the central processing unit is configured to execute deep learning algorithms and convolutional neural networks for analysing the data and images collected by the modules.

10. System according to any of the preceding claims, configured for use in a clinical setting, in particular in dermatology, plastic surgery, and burn treatment units, for the pre-operati ve and postoperative assessment of scars.

11. System according to any of the preceding claims, wherein a mul tispectral imaging (MSI) camera is further provided and configured to acquire multi-band images for superficial mapping of pigmentation, vascular pattern, and chromophore distribution, whose features are integrated into the Al pipeline.

12. System according to any of the preceding claims, wherein an Elastic Scattering Spectroscopy (ESS) module is further provided as an optional adjunct configured to extract scattering-based quantitative biomarkers of subcellular and extracellular structures, complementary to MSI / OCT / Raman .

13. System according to any of the preceding claims, wherein the Al processing unit is configured to compute quantitative biomarkers of the tissue microenvironment, including vascular (per fusion / oxygenation) , ECM ( anisotropy / orientation / biref ringence ) , epidermal immune (Langerhans-related proxies) , and fibroblastphenotype (myofibroblasts vs CAF) biomarkers, and to output a composite risk score.

14. System according to any of the preceding claims, wherein the diachronic analysis module generates longitudinal trajectories of said quantitative biomarkers over hours, days, weeks, or months.

15. System according to any of the preceding claims, wherein the system is applied to scar tissue to predict hypertrophic / keloid evolution through persistence of myofibroblast-related biomarkers and aberrant vascular patterns.

16. System according to any of the preceding claims, wherein the system is applied to melanocytic lesion screening / triage, enabling reduction of unnecessary biopsies by providing a non-invasive risk score .

17. System according to any of the preceding claims, wherein the system is applied to oncological stroma profiling, quantifying CAF- related signatures and functional oxygenation heterogeneity.

18. System according to any of the preceding claims, wherein the system is applied to wound healing to compute a healing probability index .

19. System according to any of the preceding claims, wherein the system is applied to peri- and post-operative surgical site monitoring to detect early ischemia or excessive fibrotic activation.

20. Method for the non-invasive assessment of skin scars, comprising acquiring data from a scar using the non-invasive diagnostic system according to any of the preceding claims, the method comprising analysing the acquired data using artificial intelligence algorithms to provide a predictive diagnosis of the evolution of the scar.

21. Method according to claim 20, wherein the data acquisition comprises the use of Optical Coherence Tomography (OCT) , Muller Matrix Polarimetry, Raman Spectroscopy, Opto-acous tics and Diachrony Analysis technologies.

22. Method according to claim 20 or 21, wherein the data analysis using artificial intelligence algorithms comprises running deep learning algorithms and convolutional neural networks.

23. Method according to any of claims 20 to 22, wherein the data acquisition comprises the detection of scar-specific biomarkers, including a-SMA and EDA fibronectin, by Raman Spectroscopy.

24. Method according to any of claims 20 to 23, further comprising analysing temporal changes in scar tissue properties through Diachronic Analysis to provide a dynamic assessment of scar evolution .

25. Method according to any of claims 20 to 24, wherein a mul tispectral imaging (MSI) camera is further provided and configured to acquire multi-band images for superficial mapping of pigmentation,vascular pattern, and chromophore distribution, whose features are integrated into the Al pipeline.

26. Method according to any of claims 20 to 25, wherein an Elastic Scattering Spectroscopy (ESS) module is further provided as an optional adjunct configured to extract scattering-based quantitative biomarkers of subcellular and extracellular structures, complementary to MSI / OCT / Raman.

27. Method according to any of claims 20 to 26, wherein the Al processing unit is configured to compute quantitative biomarkers of the tissue microenvironment, including vascular (per fusion / oxygenation) , ECM ( anisotropy / orientation / biref ringence ) , epidermal immune (Langerhans-related proxies) , and fibroblast phenotype (myofibroblasts vs CAE) biomarkers, and to output a composite risk score.

28. Method according to any of claims 20 to 27, wherein the diachronic analysis module generates longitudinal trajectories of said quantitative biomarkers over hours, days, weeks, or months.

29. Method according to any of claims 20 to 28, wherein the system is applied to scar tissue to predict hypertrophic / keloid evolution through persistence of myofibroblast-related biomarkers and aberrant vascular patterns.

30. Method according to any of claims 20 to 29, wherein the system is applied to melanocytic lesion screening / triage, enabling reduction of unnecessary biopsies by providing a non-invasive risk score.

31. Method according to any of claims 20 to 30, wherein the system is applied to oncological stroma profiling, quantifying CAF-related signatures and functional oxygenation heterogeneity.

32. Method according to any of claims 20 to 31, wherein the system is applied to wound healing to compute a healing probability index.

33. Method according to any of claims 20 to 32, wherein the system is applied to peri- and post-operative surgical site monitoring to detect early ischemia or excessive fibrotic activation.