From Optical to Molecular Imaging on Human Skin: A Review

Abstract

Accurate diagnosis is of great importance in all medical fields, and dermatology is no exception. Among the various routes available to clinicians, medical tests based on imaging properties have become a cornerstone for the assessment of skin diseases. Advancements in dermatological imaging techniques, particularly those combining optical and molecular modalities, are revolutionizing our understanding of skin pathologies. These techniques offer a more comprehensive view of skin conditions, as they provide complementary insights at both macroscopic and molecular levels. This review explores the historical and current state of diverse imaging methodologies, both traditional and advanced, employed in dermatology for diagnostic, therapeutic, and research purposes. Key technological advancements in the field are discussed, including their integration with molecular profiling techniques, such as spatial omics. These hybrid approaches allow for the identification of biomarkers, molecular signatures, and deeper disease mechanisms, contributing to the development of precision medicine for skin conditions. The translational potential of these technologies is also highlighted, emphasizing their implementation into clinical workflows and the challenges of standardization and cost-effectiveness. Moreover, we address the current limitations, including access to specialized equipment, expertise, and data interpretation, and propose strategies to overcome these challenges. The paper finally discusses the potential future role of artificial Intelligence in streamlining image analysis and clinical decision-making support. By examining both the present and future perspectives of dermatological imaging, this review aims to provide a holistic overview of the full potential of the available advanced techniques and their applications.

1. Introduction

1.1. Importance of Skin Imaging in Dermatology

Skin conditions are a significant global health issue and evidently the most common reason for visits to general practitioners, with a prevalence of 1.9 billion people suffering worldwide. , There are more than 3000 distinct, documented skin diseases, varying in frequency and severity. Like most conditions, they can be classified as acute or chronic, with approximately 69% being chronic and 31% acute. The most common one is atopic dermatitis, often referred to as eczema, which affects approximately 15–20% of children and 1–3% of adults. It is followed by acne, which impacts about 9.4% of the population, with higher prevalence observed in industrialized regions, and psoriasis, affecting 2–3% of the global population, equivalent to about 125 million people, particularly living in Northern Europe and North America.. Furthermore, temporary conditions such as urticaria and fungal skin infections (athlete’s foot, jock itch, ringworm) affect up to 25% of the world’s population at least once during their lifetime. Finally, there are over 3 million cases of nonmelanoma skin cancer, and 132,000 cases of melanoma skin cancer reported annually.

These may pose a heavy burden on patients in terms of quality-of-life impairment and costs. They can lead to major physical discomfort and psychological distress, not to mention the social stigma of living with a visible condition. , More severe types can certainly cause emotional and mental health issues, including depression and anxiety. The types and statistics vary by region due to factors like climate, healthcare access, and genetic predispositions, nevertheless, men and women of all ages and social conditions can be affected. , Infectious skin diseases are more common in undeveloped countries, whereas chronic conditions are more prevalent in developed regions. Figure highlights global variations in the percentage change of skin disease prevalence from 1990 to 2017, emphasizing geographic disparities over nearly three decades. North America, Europe, and Australia are showing significant increases, as opposed to Africa and South Asia. The rest of the areas represent moderate or stable changes.

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Percentage change in prevalence rate of skin diseases per 100,000 population from 1990 to 2017. Reproduced with permission from ref . Copyright 2020 Elsevier.

These statistics underline the importance of effective public health strategies to reduce the burden of skin diseases worldwide, especially since research in dermatology is less prioritized due to the nonlife-threatening nature of these conditions. Against this backdrop, the primary objective of this paper is to investigate the multitude of imaging methodologies used for visualizing human skin with a key focus on molecular imaging modalities. This review aims to outline the applications, strengths, and limitations of these techniques while also examining their relevance to dermatological research and providing a historical overview of their development.

Skin imaging methodology is crucial in dermatology, both in biomedical research and clinical applications. The medical world needs techniques that can provide insights into any skin abnormality that can be used to study the phenotypes of a disease and aid in treatment decision-making. An experienced clinician can often diagnose a skin condition without the need for investigations. However, at times, skin swabs, scrapings, tape strips, nail clippings, biopsies, and blood samples are sent to the laboratory for further analysis, which frequently includes imaging of the samples as part of the diagnostic process. The images obtained initially used for diagnosis can also be collected in an archive to support research efforts. These efforts focus on studying the structural composition of the skin or understanding pathological changes to identify biomarkers and advance our understanding of how the skin behaves. , More advanced skin imaging can detect skin cancer at an early stage, leading to better outcomes. Noninvasive techniques, which are also widely available, allow for the examination of skin without the need for invasive procedures, resulting in a less stressful patient experience. Most available methods can also work dynamically to monitor skin lesions. By visualizing them over time, clinicians can better understand the progression of diseases and the effects of aging. Finally, imaging modalities give information regarding treatment responses, which in turn aid in the adjustment of therapy. The technology itself could be valuable in rural and underserved areas to facilitate remote diagnosis and consultation, since access to specialists can be limited in these regions.

1.2. Historical Context of Skin Imaging in Dermatology

One can argue that dermatological complaints have been documented throughout history due to their visible nature. The first ever documented skin disease in history is leprosy, also known as Hansen’s disease, with references dating back to 600 BCE in ancient medical texts. Archeological evidence, such as skeletal remains in India from 2000 BCE, further confirms its early presence.

Historically, skin imaging began with direct visual examination using only the naked eye or simple tools like magnifying glasses to assess characteristics such as color, texture, and shape of lesions to guide diagnoses. This practice, often referred to as visual inspection, is the most basic form of skin imaging and is currently considered the primary method for initial assessment in dermatology. It allows clinicians to examine the skin’s surface for rashes, lesions, discolorations, moles, infections, and changes in pigmentation. Based on this information, they can guide further investigations or interventions. Interestingly enough, early studies on tattoos in the late 1800s provided insight into pigment deposition and skin penetration, using rudimentary microscopy techniques.

The development of dermoscopy in the 1990s marked a significant advancement in dermatology, allowing for closer skin examination. In the 1920s, Johann Saphier, a German dermatologist, developed an early version of the dermatoscope by combining a magnifying lens with a light source. However, it was not used until the 1980s, when the technique gained popularity for its effectiveness in diagnosing melanoma. Dermoscopy has become a standard tool in dermatological practice, enabling doctors to visualize structures within the skin that are not visible to the naked eye with improved clarity and precision. Since its implementation in clinical settings in the late 20th century, it paved the way for the development of more advanced imaging techniques, such as reflectance confocal microscopy (RCM), optical coherence tomography (OCT), and multiphoton microscopy (MPM). ,

Skin imaging methods have evolved significantly over time, transitioning from traditional optical techniques, which primarily capture structural and anatomical details of the skin, to advanced molecular imaging approaches that provide insights into cellular and biochemical processes at the molecular level. The first step was to develop in vivo skin optical clearing techniques, which involve using chemical agents to make biological tissues, such as skin, more transparent by reducing light scattering and absorption and enhancing the penetration depth of light, both notable obstacles at the time. The transition from purely optical to molecular skin imaging techniques evolved gradually. Dermatologists had the necessity to visualize not only the structure of the skin but also its function and biochemical composition. Simultaneously, researchers needed to study the skin microstructure at the cellular level in vivo. Techniques such as confocal laser scanning microscopy (CLSM) enabled researchers to examine the skin microenvironment without requiring painful biopsies, providing information about cellular morphology. This initiated the path to understanding skin conditions beyond surface-level observations. CLSM and OCT further advanced the field when they introduced real-time imaging of abnormal skin morphology at high resolution, both in laboratory and clinical settings. The earliest integration of molecular imaging techniques could be fluorescence lifetime imaging microscopy (FLIM) and multiphoton tomography (MPT), which enabled the visualization of the skin at the molecular level, offering subcellular resolution. Another notable progress in the field was using two-photon imaging for the quantitative evaluation of skin disorders in animal models, offering insights into collagen morphology and skin health. Nowadays, advancements in imaging modalities also include the use of artificial intelligence (AI) and machine learning (ML) algorithms. These technologies are particularly effective in tasks such as segmentation, where they delineate the lesion from surrounding healthy skin with remarkable precision, and registration, which involves aligning images taken at different times or angles for consistent comparison. By automating these processes, AI enables clinicians to monitor changes in the lesion size, shape, and appearance over time with greater reliability. for accurate segmentation and registration of skin lesion images, facilitating the monitoring of how a lesion evolves over time. Smartphone-based multispectral imaging systems have recently been introduced, offering the potential for mobile skin diagnosis. Even after the development of these numerous techniques, there is still room for improvement, as with all fields. Currently, the focus is shifting toward more advanced molecular methods to gain deeper insights into the molecular pathways underlying the observed pathologies. This progress is expected to pave the way for the discovery of new therapeutic targets, ultimately leading to better treatment options (Figure ).

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Timeline of key milestones in skin imaging technology. Created in https://BioRender.com.

2. Optical Imaging Techniques for Skin Visualization

2.1. Overview of Noninvasive Optical Imaging Techniques and Their Applications

Noninvasive optical imaging techniques have significantly advanced the visualization of human skin, providing high-resolution imaging capabilities without the need for invasive procedures. Here are the most commonly used techniques. The technical information on each method that would influence the diagnostic approach can be found in Table while the summarized advantages, disadvantages, and applications of optical imaging techniques can be found in Table .

1. Technical Information on Optical Imaging Modalities.

Modality	Penetration Depth (μm)	Resolution (μm)	Speed	Cost
Dermoscopy	∼200–300	10–100	Fast (real-time)	Low
Reflectance Confocal Microscopy (RCM)	∼250	0.5–1	Fast (real-time)	High
Optical Coherence Tomography (OCT)	∼1000–1500	3–10	Fast (real-time)	Moderate to High
High-Frequency Ultrasound	∼15,000	30–100	Fast (real-time)	Moderate
Photoacoustic Imaging (PAI)	∼5000–6000	50–100	Moderate	High
Total Body Photography (TBP)	Surface only	Dependent on camera (∼500)	Slow (depends on workflow)	Moderate
Infrared Thermal Imaging	Surface only (∼500 max)	100–500	Fast (real-time)	Low to Moderate
Magnetic Resonance Imaging (MRI)	Several mm to cm (soft tissues)	100–500	Slow	High
Computed Tomography	Several cm (entire body)	∼500–1000	Fast	High
Fluorescence Microscopy	∼500	Submicron (∼0.1–1)	Moderate to Slow (image acquisition)	High (research mostly)
Confocal Microscopy	∼200–250	0.5–1	Fast (real-time)	High
Two-Photon Microscopy (TPM)	∼500–1000	Submicron (∼0.2–1)	Slow to Moderate	Very High (research only)
Dynamic Optical Coherence Elastography (OCE)	∼1000–1500	3–10	Moderate (depends on setup)	High (experimental)

2. Advantages, Disadvantages, and Applications of Optical Imaging Techniques.

Modality	Advantages	Disadvantages	Applications
Dermoscopy	- Noninvasive	- Requires experience and training to interpret	- Skin cancer (melanoma, BCC, SCC)
	- Quick and easy to use	- Limited to superficial skin structures	- Pigmented lesions and moles
Reflectance Confocal Microscopy (RCM)	- Noninvasive	- Expensive	- Skin cancer (melanoma, BCC)
	- High-resolution	- Limited depth penetration	- Inflammatory diseases
	- Cellular-level imaging
	- Real-time
Optical Coherence Tomography (OCT)	- Noninvasive	- Limited resolution compared to RCM	- Skin cancer (BCC, SCC)
	- Real-time imaging	- Costly	- Psoriasis
	- Detailed cross-sectional views	- Cannot resolve cellular-level details	- Wound healing
High-Frequency Ultrasound	- Noninvasive	- Lower resolution compared to other methods	- Tumor depth assessment (BCC, SCC)
	- Assesses deeper structures	- Limited ability to differentiate tissue types	- Inflammatory diseases
	- Easy to use
Photoacoustic Imaging (PAI)	- High resolution	- Limited availability	- Vascular tumors
	- Visualizes deeper layers	- Expensive	- Melanoma
	- Good for vasculature	- Limited clinical use	- Inflammation research
		- Complex setup
Total Body Photography (TBP)	- Comprehensive skin monitoring	- Time-consuming	- Early detection of new/changing moles
		- Requires standardized imaging	- Melanoma monitoring
Infrared Thermal Imaging	- Noninvasive	- Low specificity	- Inflammation
	- Detects inflammation and changes in blood flow	- Low resolution	- Infections
		- Requires a controlled environment	- Vascular conditions
			- Wound healing
Magnetic Resonance Imaging (MRI)	- High-resolution soft tissue imaging	- Expensive	- Large tumors
	- No ionizing radiation	- Time-consuming	- Soft tissue involvement
		- Limited accessibility in dermatology	- Skin cancer staging
Computed Tomography	- High-resolution	- Ionizing radiation	- Tumors
	- Fast	- Not ideal for superficial skin conditions	- Bone invasion
	- Complex anatomical imaging	- Limited use for surface skin diseases	- Deep tissue involvement
Fluorescence Microscopy	- High resolution	- Requires fluorescent dyes	- Skin cancer (melanoma)
	- Specific molecular targeting		- Protein and cell studies in skin
Confocal Microscopy	- Noninvasive	- Expensive	- Skin cancer (melanoma, BCC, SCC)
	- Cellular-level imaging	- Limited depth	- Noninvasive lesion evaluation
	- Real-time
	- 3D imaging
Two-Photon Microscopy (TPM)	- Deep tissue penetration	- Expensive	- Skin physiology research
	- Less photodamage	- Complex	- Collagen structure
	- 3D imaging	- Limited to research	- Live cell imaging
		- Long imaging times
Dynamic Optical Coherence Elastography (OCE)	- Noninvasive	- Expensive	- Skin cancer (stiffness)
	- Measures mechanical properties of skin	- Complex	- Fibrosis
		- Limited clinical availability	- Scarring

2.1.1. Dermoscopy

Dermoscopy, also known as dermatoscopy or epiluminescence microscopy, is a diagnostic technique that involves the use of a hand-held device called a dermatoscope. This device illuminates the skin and magnifies its surface structures, allowing dermatologists to visualize patterns, colors, and textures that are not visible to the naked eye. Figure shows examples of dermoscopy images, clearly illustrating the types of information that can be derived from them, including margins and morphologically heterogeneous lesions.

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Dermoscopy images. (a) Fuzzy and indistinct lesion boundaries; (b) Heterogeneous texture, color, and shape of the lesions; (c) Artifacts. Reproduced with permission from ref . Copyright 2021 Elsevier.

Dermatologists can differentiate between benign and malignant conditions through the examination of dermoscopic features of skin lesions, such as asymmetry, border irregularity, color variation, and specific structures (e.g., dots, globules, and streaks). It is widely used for the evaluation of melanoma, basal cell carcinoma (BCC), and squamous cell carcinoma (SCC), as well as for assessing pigmented lesions and moles. The technique enhances diagnostic accuracy and aids in monitoring changes over time, ultimately improving patient outcomes.

It is a noninvasive technique that is quick and easy to use. However, interpreting the results requires significant experience and training, and it is limited to examining superficial skin structures. Although dermoscopy is the most frequently used diagnostic tool in dermatology clinics, its application in research settings remains relatively limited.

2.1.2. Reflectance Confocal Microscopy

Reflectance Confocal Microscopy (RCM) is an advanced imaging technique that provides high-resolution, noninvasive images of skin structures at a cellular level. Using a focused laser beam, RCM captures images of the skin’s layers in real time, allowing dermatologists to visualize cellular morphology and architecture. This technique highlights features such as cell density, nuclear size, and the presence of abnormal cells, making it particularly valuable for diagnosing skin cancers such as melanoma and BCC, inflammatory conditions, and benign lesions.

RCM enhances diagnostic accuracy by enabling detailed assessment of skin lesions, facilitating better treatment decisions, and follow-up care. It is arguably one of the most used techniques since it provides high-resolution, real-time imaging of skin structures at a histopathologic level, allowing for a noninvasive examination while still offering the advantage of visualizing cellular and tissue structures in vivo. RCM is particularly valued for its ability to repeatedly image the same area over time without requiring a biopsy. However, the main limitation of RCM is its restricted imaging depth since the depth of penetration is limited to the superficial dermis. Furthermore, there is a steep learning curve in developing the ability to interpret RCM images.

Figure presents RCM images of normal skin, highlighting the distinct layers and microstructures that can be visualized by using this technique. It is a notable example of its value as it illustrates the level of cellular detail achievable with RCM, helping to contextualize its diagnostic potential and the types of morphological features clinicians can expect to observe.

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Reflectance confocal microscopy (RCM) images (500 × 500 μm) of the normal skinright forearm (a) cornified layer; (b) granular/spinous layer with regular honeycomb pattern; areas with cobblestone pattern (blue arrow) (c) dermal-epidermal junctionsmall basal cells and melanocytes arranged in a circular pattern (bright rings) (pink arrow) surrounding the dermal papillae (dark structures); small blood vessels inside the dermal papillae (green arrow); (d) dermis with elastic and collagen fibers visible as bright fibrillar or reticular structures (purple arrow). Reproduced from Bratu et al., ref ; licensed under CC-BY 4.0.

2.1.3. Optical Coherence Tomography

Optical Coherence Tomography (OCT) is a noninvasive, nondestructive, three-dimensional imaging technique that employs near-infrared light to capture high-resolution cross-sectional images of biological tissues, including the skin. By measuring the light reflected from different tissue layers, OCT provides detailed images that reveal the microanatomy of the skin in real time. ,

In dermatology, OCT is widely used and is particularly useful for assessing skin lesions, evaluating the depth of tumors, and monitoring conditions such as psoriasis and dermatitis. It is also valuable in diagnosing BCC and SCC, as well as for wound healing and assessment of the thickness and structure of the epidermis and dermis. It can also detect microstructural changes in stromal collagen distribution. ,

Despite its versatility, the OCT faces limitations in differentiating certain skin structures due to its imaging depth and resolution constraints. It has an axial resolution of approximately 7.5 μm and a penetration depth of less than 2 mm, which restrict its ability to differentiate finer skin structures. Compared to RCM, which offers a higher lateral resolution of about 1 μm, OCT is less effective at imaging specific cell types and features like melanin.

Figure displays OCT images from various skin regions with segmented outputs that highlight different structural layers and variations across anatomical sites. OCT’s capacity to noninvasively delineate skin architecture is demonstrated, offering insight into both healthy and pathological conditions with spatial context.

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Application of CNN-GS-skin to various skin lipid-free skin OCT images from five sample images. Original OCT image with segmented results of (a) forearm, (b) back of hand, (c) forehead, (d) neck, and (e) palm. Reproduced from Lin et al., ref ; licensed under CC-BY 4.0.

2.1.4. High-Frequency Ultrasound

High-frequency Ultrasound (HFUS) is a noninvasive and user-friendly imaging technique that uses sound waves to assess deeper skin structures and create detailed images of the skin and underlying tissues. Operating at frequencies typically above 10 MHz, HFUS provides high-resolution images that allow dermatologists to visualize structures such as the epidermis, dermis, and subcutaneous tissue in real time. ,

It is particularly useful for assessing skin lesions, measuring their depth, and evaluating the vascularity of tumors. HFUS can also evaluate the thickness, density, and composition of cysts in inflammatory processes. It aids in differentiating between benign and malignant conditions and assists in the monitoring of various skin diseases. This technique enhances diagnostic precision and helps guide treatment decisions while minimizing the need for invasive procedures. ,

Although HFUS is highly effective for examining tumor depth and inflammatory skin diseases, its resolution is lower compared to other imaging methods, and it has a limited ability to differentiate tissue types. ,

Figure illustrates one of the common uses of HFUS in the diagnosis of nodular basal cell carcinoma, highlighting its ability to delineate tumor boundaries, assess lesion depth, and visualize structural characteristics that support noninvasive tumor evaluation in clinical practice.

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Nodular basal cell carcinoma measuring 5 mm × 7 mm on the left lower cheek of a 66-year-old man. Note the pearly borders and central ulceration in the gross photograph (a), the polymorphous vessels and ulceration in the dermatoscopic photo (b), and the 5 mm hypoechoic lesion in the superficial dermis across the short axis of this biopsy-supported nodular basal cell carcinoma using a 50-MHz UHFUS probe. Reproduced from Levy et al., ref ; licensed under CC-BY 4.0.

2.1.5. Photoacoustic Imaging

Photoacoustic Imaging (PAI) is a novel imaging technique that combines light and sound to produce high-resolution images of biological tissues. It utilizes short pulses of laser light that are absorbed by tissues and subsequently converted into acoustic (sound) waves, which are then detected to construct detailed images.

PAI is particularly useful for visualizing vascular structures, skin lesions, and pigment distribution, providing valuable insights into the tissue composition. This makes it a promising tool for differentiating between benign and malignant conditions as well as for studying melanoma, vascular tumors, and inflammatory diseases such as psoriasis. One of the key strengths of PAI is its ability to noninvasively image deeper skin layers, particularly the vasculature, which supports improved diagnostic accuracy and enables more personalized treatment strategies.

Despite its potential, PAI is expensive, not widely available, and has limited clinical use due to its complex setup.

Figure presents photoacoustic imaging results in assessing psoriatic skin compared to healthy skin, together with treatment response. PAI has a clear ability to capture vascular changes and inflammatory patterns in vivo, illustrating its clinical and research potential in assessing skin diseases at a functional and structural level.

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(a) Histological cross-section of psoriatic skin showing acanthosis, hyperkeratosis, and elongated capillary loop. (b, c) Cross-sectional MIP images of psoriatic skin and adjacent healthy skin from a patient’s back. (d, e) Coronal RSOM images of the same psoriatic plaque on days 1 and 10 of conventional treatment with the PASI 7 and 2. All photoacoustic images are color-coded to represent the two reconstructed frequency bands (red: larger structures in the bandwidth of 10–40 MHz; green: smaller structures in the bandwidth of 40–120 MHz). Reproduced from Ying et al., ref ; licensed under CC-BY 4.0.

2.1.6. Total Body Photography

Total Body Photography (TBP) is a comprehensive imaging technique used to capture high-resolution images of the entire skin surface, typically in a standardized format. This method involves taking multiple photographs of the body from various angles and can be enhanced with digital imaging technology to create a complete photographic record of a patient’s skin.

This method is especially beneficial for the early detection and monitoring of skin cancers and is primarily used for melanoma surveillance since it allows dermatologists to identify new or changing lesions over time. It also aids in documenting the progression of skin diseases and facilitates patient education. By providing a visual baseline, TBP enhances the diagnostic accuracy and helps guide treatment decisions.

Despite its clinical benefits, TBP can be time-consuming and requires strict adherence to standardized imaging protocols to ensure consistency and reliability.

Figure presents images acquired with the prototype Dermagram imaging device for TBP, highlighting the device’s ability to achieve high-resolution imaging capable of detecting lesions as small as 1–2 mm in diameter. This illustrates the fine level of detail that TBP can capture, emphasizing its role in identifying subtle skin changes critical for early melanoma detection and ongoing surveillance.

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Images acquired with the prototype Dermagram imaging device with original image (left panel) and then zooming to 3× (center panel), and then (10×), demonstrating image resolution of lesions 1–2 mm in diameter (right panel). Reproduced with permission from ref . Copyright 2014 Wiley.

2.1.7. Infrared Thermal Imaging

Infrared Thermal Imaging is a noninvasive diagnostic technique that detects and visualizes infrared radiation, a type of electromagnetic radiation associated with heat, emitted from the skin’s surface, capturing temperature variations through specialized infrared cameras. This technology measures the infrared radiation produced by the body’s tissues, allowing dermatologists to identify areas of increased or decreased thermal activity, which can indicate underlying pathology.

Infrared thermal imaging is used to assess inflammatory conditions, monitor blood flow, and detect skin cancers by highlighting abnormal vascularization. This method enhances diagnostic capabilities by providing functional information about the skin and underlying tissues, facilitating early detection and treatment planning without the need for invasive procedures.

However, it has low specificity and resolution and requires a controlled environment for accurate results. It has been employed to measure and visualize skin hydration, detecting changes induced by skin care products.

In Figure , examples of visual and infrared thermal images of different kinds of benign and malignant skin lesions are shown. It is demonstrated even in untrained eyes how thermal imaging can reveal distinct thermal patterns associated with different lesion types, illustrating its potential role in distinguishing between benign and malignant processes based on functional skin activity.

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Examples of visual and IR images of different kinds of benign and malignant skin lesions. Reproduced from D’Alessandro et al. ref ; licensed under CC-BY 4.0.

2.1.8. Magnetic Resonance Imaging

Magnetic Resonance Imaging (MRI) is a noninvasive imaging technique that utilizes strong magnetic fields and radiofrequency waves to produce detailed cross-sectional images of soft tissues, including skin and underlying structures. MRI excels in differentiating various tissue types based on their water content and chemical composition, making it particularly useful for assessing complex skin conditions, tumors, and soft tissue pathologies. ,

In dermatology, MRI can help to evaluate the depth and extent of skin lesions, provide insights into inflammatory conditions, and guide treatment planning. Its high-resolution images offer valuable anatomical information, facilitating accurate diagnoses and avoiding ionizing radiation. However, MRI is expensive, time-consuming, and not widely accessible for either routine or research dermatological applications. ,

Figure illustrates trans-axial multispin–echo MRIs of control and tumor-bearing mice after inducing carcinogenesis. It is a specialized MRI technique, opted by researchers to visualize structural differences between normal and pathological tissues, and to exploit its potential for monitoring disease progression and assessing the effectiveness of therapeutic interventions.

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Trans-axial multispin–echo MRIs of control and tumor-bearing mice after inducing carcinogenesis with benzo­[a]­pyrene. (A) Control mice; (B) tumor-bearing mice at 4 weeks, (C) 8, (D) 12, (E) 16, and (F) 20 weeks. Tumors are indicated by arrows. Reproduced with permission from ref . Copyright 2003 Elsevier.

2.1.9. Computed Tomography

Computed Tomography is an advanced imaging modality that combines multiple X-ray images taken from different angles to create detailed cross-sectional images of the body. CT is renowned for its high-resolution and fast imaging capabilities, making it ideal for complex anatomical assessments.

In dermatology, CT is particularly useful for evaluating larger skin lesions and assessing their relationship with underlying structures such as muscles and bones. CT scans provide high-resolution images that can help identify tumors, infections, bone invasion, deep tissue involvement, and other skin abnormalities. While it involves exposure to ionizing radiation and it is unsuitable for superficial skin conditions, its speed, and ability to visualize complex anatomical details make it an essential tool for diagnosing skin conditions, especially in cases where rapid assessment is necessary, such as in the emergency setting.

Figure displays CT images of gunshot injuries, illustrating the modality’s capacity to assess the location and extent of injury. It is a bright example of CT’s effectiveness in visualizing both soft tissue and skeletal involvement, underscoring its critical role in managing severe and complex skin and subcutaneous injuries.

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A 23-year-old man with gunshot injuries to the anterior abdominal wall. (A) Axial CT scan of the abdomen with IV contrast shows a subcutaneous bullet (long arrow) and hematoma tract in the anterior abdominal wall (short arrows). (B) Axial CT scan at a slightly lower level shows the continuation of the tract of hematoma. Reproduced with permission from ref . Copyright 2012 Springer Nature.

Overall, noninvasive optical imaging techniques have been utilized for 3D and real-time imaging of human skin, providing valuable insights into skin pathology structures without the need for tissue biopsies. While these techniques are commonly employed in clinical care due to their noninvasive nature, their use in research is less prevalent as more advanced and efficient methods are available for investigative purposes.

2.2. Overview of Invasive Optical Imaging Techniques and Their Applications

Invasive optical imaging techniques used for human skin visualization encompass advanced methods that provide detailed insights into skin structures and conditions. Invasive optical imaging techniques for skin visualization often refer to methods that require physical penetration of the skin, through the introduction of contrast agents, tissue excision (biopsy), or direct probe insertion.

2.2.1. Fluorescence Microscopy

Fluorescence Microscopy is traditionally an optical imaging technique that uses fluorescent dyes or naturally fluorescent molecules to visualize structures within biological tissues. By illuminating the sample with specific wavelengths of light, the fluorescent molecules emit light at longer wavelengths, allowing detailed imaging of targeted skin structures or molecules.

In dermatology, fluorescence microscopy is used to study cellular and subcellular features of the skin, such as detecting cancerous cells, microbial presence, or specific proteins involved in skin diseases. This technique provides high-resolution, contrast-enhanced images, enabling dermatologists to investigate cellular dynamics, disease mechanisms, and treatment responses at the molecular level. Although it is generally used on ex vivo samples, advancements have enabled its use in conjunction with invasive procedures to obtain tissue samples.

Regardless of its advantages, it is prone to the photobleaching of fluorescent dyes and potential phototoxicity to skin tissues. It also provides less contextual information about the location of the molecules within the overall tissue tissues.

2.2.2. Confocal Microscopy

Confocal Microscopy is mainly used noninvasively, however, it can also be used on ex vivo skin samples. It is an advanced optical imaging technique that uses a focused laser beam to scan and produce high-resolution three-dimensional images of biological tissues. Eliminating out-of-focus light through a pinhole provides sharp, detailed images of skin layers at various depths. ,

In dermatology, confocal microscopy is used for real-time cellular-level visualization of skin structures, making it especially valuable for diagnosing skin cancers, such as melanoma, and other conditions like inflammatory diseases. The technique offers precise imaging of live cells, blood vessels, and skin architecture, enhancing diagnostic accuracy without the need for a biopsy or tissue damage. Its main drawbacks are its high cost and limited depth penetration. ,

Figure presents an in vivo confocal image and a horizontal histology section showing regions of cells from different layers. The image highlights key structures, including the stratum corneum, stratum granulosum, stratum spinosum, basal layer, dermis, and hair follicle. This level of detailed visualization of distinct cellular layers in vivo is invaluable, enhancing our understanding of skin architecture and facilitating precise diagnostics.

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This in vivo confocal image (a) and horizontal histology section (b) show regions of cells from different layers: C, stratum corneum; G, stratum granulosum; S, stratum spinosum; B, basal layer; D, dermis; F, hair follicle. A bright hair at the surface has caused a shadow in the layers beneath (a, double-headed white arrow). When imaging from superficial to deep, a thin, acellular layer was passed through at the level of deep stratum corneum, where neither topical fluorescein from above nor intradermal fluorescein from below had labeled and therefore appear darker. Bar, 25 μm. Reproduced with permission from ref . Copyright 2003 Elsevier.

2.2.3. Two-Photon Microscopy

Two-Photon Microscopy (TMP) uses two low-energy photons to excite fluorescent molecules within tissues, allowing deep imaging with minimal photodamage. This technique enables high-resolution, three-dimensional visualization of biological structures deep within the skin while reducing light scattering and preserving tissue integrity. ,

In dermatology, two-photon microscopy is particularly valuable for live-cell imaging, enabling the study of skin architecture, cellular interactions, and collagen structure as well as monitoring disease progression or treatment effects. It is frequently applied in research settings to monitor dynamic biological processes such as disease progression, tissue regeneration, and treatment response at both molecular and cellular levels. ,

While highly informative, the technique is currently limited by its high cost, technical complexity, and slower acquisition speeds. As a result, its use is primarily confined to advanced research applications, including studies of skin physiology, collagen remodeling, and noninvasive in vivo imaging of live tissue. ,

Figure presents in vivo two-photon composite images of human skin at various depths with topically applied sunscreen. All skin layers are visualized clearly in three dimensions, showing how sunscreen interacts with the skin’s surface and penetrates the layers, thus providing insights into the effectiveness and distribution of topical skin care products.

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In vivo two-photon composite images of human skin from different depths with topically applied sunscreen. SHG (red) and autofluorescence signals are overlaid in pseudocolors. The images represent horizontal en-face images with depth increasing in steps of 5 μm starting from the stratum corneum (a) up to the epidermal/dermal boundary (i–l). Scale bar: 20 μm. Reproduced with permission from ref . Copyright 2018 De Gruyter.

2.2.4. Dynamic Optical Coherence Elastography

Dynamic Optical Coherence Elastography (OCE) combines an OCT with mechanical stimulation to measure the biomechanical properties of tissues, such as stiffness. OCE provides detailed insights into tissue stiffness and elasticity by applying a controlled force and capturing real-time images of tissue deformation,.

Dynamic OCE is useful for assessing skin lesions, tumors, and conditions such as fibrosis or scarring, where tissue stiffness can be an important diagnostic marker. This technique allows noninvasive evaluation of the mechanical properties of the skin, aiding in the differentiation between benign and malignant lesions and enhancing the understanding of skin pathology. OCE has been utilized to assess the mechanical properties of skin lesions or evaluate skin pathologies such as cancerous tissue and burn scars.

Despite its potential, the use of OCE remains expensive, complex, and not widely available for clinical use. It is only applied in research on skin cancer, fibrosis, and scarring.

Figure displays the comparison between the OCT, the OCE, and overlaid images of in vivo skin on the middle finger. The added benefit of OCE in visualizing the mechanical properties of skin is highlighted, in contrast to OCT’s conventional imaging of structural details. The overlaid images demonstrate how these combined techniques can offer a more comprehensive understanding of both the structural and biomechanical aspects of skin lesions.

14.

(a) OCT; (b) OCE; and (c) overlaid images of in vivo skin on the middle finger. In (a), the stratum corneum (SC), living epidermis (LE), imaging plate, and a sweat gland are labeled. Image dimensions are 1.4 mm × 1.4 mm. Reproduced from Kennedy et al., ref ; licensed under CC-BY 4.0.

Overall, invasive optical imaging techniques provide valuable tools for studying human skin at the molecular, cellular, and biomechanical levels. Techniques such as dermoscopy, RCM, OCT, high-frequency ultrasound, TBP, immunofluorescence, MRI, and CT are widely used in clinical settings. Meanwhile, photoacoustic imaging, two-photon microscopy, and optical emission microscopy (OCE) are more commonly employed in research. Confocal and fluorescence microscopy serve as versatile techniques, bridging both clinical and research applications.

While each technique has advantages and limitations, its combined use can offer a comprehensive skin visualization and diagnosis approach. Scientists and clinicians value different imaging modalities, depending on the specific needs of their study or diagnostic purposes. For example, those studying the cellular response to certain treatments may favor RCM for its ability to repeatedly image the same area over time without a biopsy, while those interested in the biochemical changes within the skin may prefer the details provided by fluorescence microscopy. Opinions from researchers in the field often point to trade-offs among spatial resolution, depth of penetration, specificity, and the invasiveness of the technique.

Optical imaging techniques represent the backbone of clinical dermatology diagnostics due to their accessibility, patient comfort, and speed, offering noninvasive, high-resolution visualization of skin architecture across a spectrum of depths and diagnostic contexts. From widely adopted tools such as dermoscopy to advanced systems such as RCM and OCT, each modality contributes uniquely to both clinical practice and research.

In diagnostics, dermoscopy remains indispensable for rapid lesion assessment and melanoma triage due to its simplicity and cost-effectiveness, though it is limited in depth and reliant on user expertise. RCM offers cellular-level imaging, improving diagnostic accuracy in challenging or cosmetically sensitive cases. OCT adds depth penetration (∼1.5 mm), making it suitable for margin assessment and inflammatory disease monitoring. High-frequency ultrasound and photoacoustic imaging further extend the diagnostic range into deeper structures and vascular beds, although they are less commonly used in routine care. In research, optical imaging enables dynamic, in vivo investigation of skin physiology and pathology. Techniques like TPM and fluorescence microscopy allow real-time tracking of immune cells, collagen architecture, and drug delivery at subcellular resolution. , These methods are invaluable for mechanistic studies of skin disease and treatment response, especially in preclinical and translational settings.

Despite their strengths, advanced optical systems face challenges: high cost, time-intensive workflows, and limited accessibility outside specialist centers. Their added diagnostic value must be weighed against these factors. In many cases, traditional tools remain adequate, while advanced imaging is best reserved for ambiguous cases, lesion mapping, or longitudinal studies. − Ultimately, the greatest value of optical imaging lies in its complementary use.

While optical imaging techniques offer valuable structural and functional insights into the skin, they are often limited in their ability to capture biochemical and molecular information essential for understanding complex pathologies. As dermatological research moves toward precision diagnostics and personalized therapy, there is a growing need to visualize skin at the molecular level. Molecular imaging techniques bridge this gap by enabling the in situ detection of specific proteins, lipids, and metabolites, offering a deeper understanding of disease mechanisms and treatment response. The following section explores these advanced techniques and their expanding role in skin research and clinical care.

3. Molecular Imaging Methods in Skin Research

3.1. Molecular Imaging and Its Significance in Understanding Skin Biology

As previously described, molecular imaging enables the visualization, characterization, and quantification of biological processes in living systems at the molecular and cellular levels. In the context of skin biology, it can provide information about the structural and functional characteristics of the skin, including the assessment of skin lipids, hydration, protein expressions, and the skin’s response to various therapies. In a research setting, molecular imaging is valuable in studying the pathophysiology of skin disorders and can help shed light on the mechanisms of action for skin treatments, while in clinical care, it can help to personalize treatment strategies and monitor treatment efficacy in real-time. For instance, they are used to diagnose melanoma or psoriasis in an early stage by observing molecular changes before they become apparent at the macroscopic level. Another example would be using mass spectrometry imaging mapping the lipids in sebaceous glands and hair follicles, illuminating responses to end distributions of cosmetic products. ,

3.2. Overview of Molecular Imaging Techniques

The following molecular imaging techniques have significantly impacted the field of dermatology by providing insights into skin biology at the molecular and cellular levels. They were selected based on their frequent use and validation in scientific studies published in peer-reviewed research. Technical characteristics and parameters important enough to influence the choice of the optimal method can be seen in Table .

3. Technical Information on Molecular Imaging Techniques.

Modality	Penetration Depth (μm)	Resolution (μm)	Molecular Sensitivity	Speed	Cost
Raman Spectroscopy	200–300	1–10 μm lateral, 5–20 μm axial	High (specific chemical bonds, proteins, lipids, nucleic acids, DNA)	Slow (minutes for a single scan)	Moderate to high, depending on the equipment
Multiphoton and Nonlinear Microscopy (MPM)	200–300	0.2–0.5 μm lateral, 0.5–1 μm axial	Moderate (endogenous fluorophores NADH and FAD, proteins collagen and elastin)	Moderate	Very high (due to lasers and detection system)
Intravital Multiphoton Microscopy (MPM)	200–300	0.2–0.5 μm lateral, 0.5–1 μm axial	Moderate (endogenous fluorophores NADH and FAD, proteins collagen and elastin)	Moderate	Very high, requires live-animal imaging setups
Coherent Anti-Stokes Raman Scattering (CARS)	∼1000	0.3–1 μm lateral, 1–2 μm axial	High (vibrational contrast for lipids and DNA)	Fast (milliseconds per frame)	Very high (due to multilaser setup)
Immunofluorescence	∼300	0.2–1 μm lateral, 0.5–2 μm axial	Low to moderate (proteins with exogenous dyes, organelles, metabolic markers with autofluorescence)	Fast (real-time imaging possible) but slow sample preparation	Moderate (dyes are inexpensive, but lasers add to the cost)

3.2.1. Raman Spectroscopy

Raman Spectroscopy can be a noninvasive technique that provides molecular information based on vibrational spectroscopy. It functions by shining a laser onto a sample and measuring the scattered light. Most of the light scatters at the same energy as the incoming laser, but a small fraction undergoes a shift in energy due to interactions with the molecular vibrations of the sample. This energy shift provides a unique “fingerprint” of the molecules present by detecting these vibrations in response to light, allowing for the identification of chemical compositions within the tissue.

In dermatology, Raman spectroscopy can be used for identifying skin constituents and for diagnosing skin diseases based on their biochemical signatures, including skin cancer detection, inflammation, skin aging, and drug penetration studies. Raman spectroscopy provides molecular fingerprints of tissues nondestructively and without needing contrast agents.

Nevertheless, it is highly sensitive to tissue scattering, which may affect the accuracy of the molecular analysis. The signal strength is typically weak, leading to longer acquisition times and lower spatial resolution than similar methods. ,

Figure shows the Raman analysis of a porcine hair follicle, providing a detailed molecular profile of the follicle’s composition. This figure indicates the method’s ability to offer biochemical insights into the structure and function of skin appendages, which can aid in understanding various skin conditions and their molecular underpinnings.

15.

Raman analysis of a porcine hair follicle. (a) Light microscopy image of a histological hair follicle cross-section. (b) False-color Raman image of the area indicated in (a). Raman spectra of the individual sample components are depicted in the middle according to the color coding of the Raman image (sebumred, dermisgreen, epidermisyellow, hairblue). Reproduced with permission from ref . Copyright 2018 Springer Nature.

3.2.2. Multiphoton/Nonlinear Microscopy

Multiphoton/Nonlinear Microscopy (MPM) allows for high-resolution imaging of skin structures at a molecular level by using the nonlinear optical properties of tissues. They use high-intensity lasers to excite molecules in a sample by simultaneously absorbing two or more photons, typically in the infrared range. This enables deeper tissue penetration with less damage compared to single-photon methods.

In dermatology, these techniques allow the imaging of skin structures at the subcellular level. Multiphoton microscopy, for instance, can visualize collagen, elastin, and other components, providing insights into skin aging, wound healing, or cancer development. Nonlinear modes, like second harmonic generation (SHG), can operate label-free and reveal the organization of collagen fibers, offering valuable information on skin health and disease progression.

However, its application is limited by expensive equipment, the need for significant technical expertise, and slower imaging speeds. MPM also has depth limitations in highly scattering tissues and a relatively small field of view.

3.2.3. Intravital Multiphoton Microscopy

Intravital Multiphoton Microscopy is a specialized form of MPM that allows for real-time imaging of skin tissues with subcellular spatial resolution. Multiphoton excitation is employed by using infrared lasers for deep tissue penetration and minimal photodamage. It offers imaging within live organisms (in vivo), providing dynamic, high-resolution insights into biological processes as they happen, including immune responses, microbiota interactions, and molecular mechanisms. ,

Intravital MPM can be used to monitor cellular interactions, blood flow, and the skin’s extracellular matrix. It is especially valuable for studying disease progression, such as cancer metastasis, immune responses, and skin biomechanics like wound healing, offering a detailed view of skin function in its natural, living environment. ,

However, this method is complex, costly, and often invasive, requiring animal models for most applications. It is also limited to imaging small regions of tissue, which restricts its broader use in clinical settings. ,

Figure shows the gold standard alignment of intravital multiphoton tomography applied in atopic dermatitis. These images showcase the in vivo imaging of skin tissues in the context of a chronic inflammatory skin disease. They highlight how intravital MPM allows for dynamic monitoring of the immune response and tissue remodeling in real time, providing essential insights into disease progression and therapeutic efficacy.

16.

Gold standard alignment of intravital multiphoton tomography. (a) Standard vertical histological sections of the skin from healthy subjects (healthy), the ostensibly healthy skin of a patient affected by AD (AD nonlesional), and lesional atopic skin (AD lesional) examined via multiphoton tomography. Alignment of horizontal histological sections (“hist.”-column) with multiphoton tomographic sections (“MPT”-column) of the same regions of healthy, AD nonlesional and AD lesional areas of skin at distinct skin depths of 0 μm (Stratum corneum (b)), 10 μm (upper Stratum granulosum (c)), 30 μm (Stratum spinosum (d)), and 50 μm (e), representing the interface between the epidermal Stratum basale and the Stratum papillare of the dermis. Reproduced from Huck et al., ref ; licensed under CC-BY 4.0.

3.2.4. Coherent Anti-Stokes Raman Scattering Microscopy

Coherent Anti-Stokes Raman Scattering Microscopy (CARS) is a noninvasive, label-free imaging technique that uses infrared light in combination with visible lasers to excite molecular vibrations and signatures of chemical bonds and produce a signal at a higher energy (anti-Stokes shift) than the incident light. This allows for chemical-specific, three-dimensional imaging without the need for dyes or markers. ,

Its chemical specificity and high sensitivity to lipids make it especially useful for live imaging of the skin to observe lipids, proteins, and other biomolecules with a high spatial resolution, enabling the study of skin composition and dynamics. It is often used for analyzing lipid-rich structures like sebaceous glands or for monitoring changes in skin cancer, inflammation, or skin barrier function. ,

However, like Raman spectroscopy, it requires expensive equipment and expertise as well as careful tuning of laser frequencies. Despite its faster imaging speeds compared to traditional Raman techniques, its weak signal relative to fluorescence methods and the complexity of the setup present significant challenges. Nonetheless, CARS remains a promising tool for noninvasive dermatological research. ,

Figure shows the multimodal mapping of healthy human skin at depths from 0–66 μm. CARS was able to capture detailed chemical information at multiple depths of the skin. The imaging highlights the layer-specific distribution of lipids and other biomolecules, providing insights into the skin’s composition and functionality at various levels, which is crucial for understanding skin health and disease.

17.

Multimodal mapping of healthy human skin at depths from 0–66 μm: (a) coherent anti-Stokes Raman scattering and (b) corresponding autofluorescence/second harmonic generation signal distribution; scale bar 40 μm. Reproduced with permission from ref . Copyright 2015 IOP Publishing.

3.2.5. Fluorescence Imaging–Immunofluorescence

As previously described, fluorescence imaging is a primarily optical imaging technique that relies on fluorescent probes or intrinsic skin fluorescence to visualize cell types within the skin. However, at times, it can be used in molecular imaging when applied to visualize molecular processes in living cells and tissues. More specifically, it involves labeling molecules of interest with fluorescent dyes or proteins, which emit light when excited by specific wavelengths. This emitted light is then captured to visualize biological structures or processes. ,

In dermatology, fluorescence imaging is widely used to study skin cells, collagen, and other tissue components by tagging them with fluorescent markers. It allows for the detailed visualization of skin morphology, detection of abnormal cells, and monitoring of processes like wound healing or tumor growth and blood flow visualization. Additionally, it can be used to highlight specific molecular pathways in diseases like skin cancer, offering insights into cellular behavior and disease progression. ,

Fluorescence imaging is widely employed for its high sensitivity and ability to perform specific molecular labeling, providing insights into cellular and molecular processes in real time. However, fluorescence imaging often requires external labels, such as dyes or fluorophores, which can lead to issues such as photobleaching and phototoxicity during prolonged exposure. Its penetration depth is also limited, and the quality of the signal heavily depends on the efficiency of labeling. ,

Figure illustrates cryosections of ex vivo human skin observed by fluorescent microscopy. Fluorescence imaging was used to clearly differentiate between various skin structures and cell types. By using fluorescent markers, the image highlights specific tissue components such as collagen and keratinocytes, allowing for precise evaluation of skin morphology and the detection of abnormalities, which are crucial for monitoring skin conditions and disease progression.

18.

Cryosections of ex vivo human skin observed by fluorescent microscopy. (a, b) Application of a 1% w/v Carbopol hydrogel containing red fluorescent nanobeads to intact skin. Microneedle application removes the SC integrity and the hydrogel formulations (c, d) are able to reach the epidermis: (c) a 1% w/v Carbopol-940 and (d) a 23% w/w PLGA–PEG-PLGA hydrogel (bar = 100 mm in all cases). Reproduced with permission from ref . Copyright 2007 Springer Nature.

Building upon fluorescence microscopy, immunofluorescence enhances specificity using fluorescently labeled antibodies. Immunofluorescence combines fluorescence microscopy with antibodies to detect specific proteins and antigens within biological tissues. In this method, antibodies are labeled with fluorescent dyes and bind to their target molecules, which are then visualized under a fluorescence microscope. ,

In dermatology, immunofluorescence is commonly used to diagnose autoimmune skin diseases, such as lupus, pemphigus, and bullous pemphigoid, by highlighting abnormal immune deposits in the skin. This technique allows the precise localization of immune complexes and other proteins, providing crucial insights into the molecular mechanisms of skin diseases, aiding accurate diagnosis, and guiding treatment decisions. However, it requires a biopsy and the use of specialized antibodies, limiting its application to targeted investigations. ,

Figure shows skin confocal immunofluorescence analysis, where staining was performed using antibodies against K14 and K1 to specifically label and visualize particular keratins within the skin. The targeted staining highlights the expression patterns of K14 found in basal cells and K1 present in suprabasal layers, providing important insights into epidermal differentiation and aiding in the diagnosis of skin diseases, where these markers are altered.

19.

Skin confocal immunofluorescence analysis. Staining was performed using antibodies against K14 (red) and K1. (A) Control palmar skin. (B, C) Patient palmar skin (20× objective). (D) Normal palmar skin (40× objective). (E), Patient palmar skin with K1 and K14 staining merged with DAPI (40× objective), also for (F–I). (F) Capture only showing K1 distribution. (G) Patient skin with merged channels showing K14, K1, and DAPI. (H) Patient skin showing only K1 staining. (I) Patient skin showing only K14 staining. (A–F) Scale bar = 100 μm. (G–I) Scale bar = 50 μm. Reproduced from Caporali et al., ref ; licensed under CC-BY 4.0.

By combining advanced imaging technologies with molecular biology and genetics, researchers can unravel complex skin processes, identify novel therapeutic targets, and improve dermatology patient care. However, it is important to note that while fluorescence imaging has found some application in clinical dermatology for specific cases like tumor mapping and vascular studies, the other techniques, Raman spectroscopy, MPM, and CARSare still predominantly research tools. These techniques are invaluable for understanding skin biology at a molecular level, but they are rarely used in routine clinical settings due to their high cost, the need for specialized equipment, and the technical expertise required to operate them.

Experts believe that molecular imaging techniques play a crucial role in advancing dermatological research and clinical care. By leveraging the strengths of each imaging modality and addressing their limitations, researchers and clinicians can enhance their understanding of skin conditions and improve patient outcomes in dermatology. The collective strengths and weaknesses of the techniques mentioned can be summarized in the following tables (Table ).

4. Advantages, Disadvantages, and Applications of Molecular Imaging Techniques.

Modality	Advantages	Disadvantages	Applications
Raman Spectroscopy	- Label-free	- Weak signal limits real-time imaging	- Skin cancer detection (melanoma)
	- Noninvasive	- Long acquisition times	- Inflammation
	- Provides molecular fingerprinting	- Sensitive to background fluorescence	- Skin aging
	- Minimal sample preparation	- Limited penetration depth	- Drug penetration studies
Multiphoton and Nonlinear Microscopy (MPM)	- High resolution	- Expensive equipment	- Skin aging
	- Minimal photodamage	- Requires expertise	- Wound healing
	- Deep tissue imaging	- Relatively slow imaging speed	- Collagen/elastin disorders
	- Label-free in certain modes (SHG)	- Limited field of view	- Dermal structure/morphology
		- Depth limitations in highly scattering tissues
Intravital Multiphoton Microscopy (MPM)	- Real-time imaging in living tissues	- Complex and costly	- Skin cancer progression
	- High-resolution and deep-tissue penetration	- Requires animal models for most applications	- Immune response
	- Can visualize dynamic processes and cell interactions	- Limited to small regions of tissue	- Wound healing
		- Invasive	- Inflammation
Coherent Anti-Stokes Raman Scattering (CARS)	- Label-free	- Expensive lasers and equipment	- Lipid-related skin diseases (e.g., sebaceous gland disorders)
	- Chemical-specific imaging	- Requires tuning of laser frequencies	- Skin cancer
	- High sensitivity to lipids	- Weak signal compared to fluorescence methods
	- Fast imaging speeds compared to other Raman techniques	- Complex setup
Immunofluorescence	- High sensitivity	- Requires external labels (dyes or fluorophores)	- Skin cancer (melanoma)
	- Specific molecular labeling possible	- Photobleaching and phototoxicity with long exposures	- Wound healing
	- Widely used	- Limited penetration depth	- Tumor growth monitoring
	- Real-time imaging possible	- Signal depends on labeling efficiency	- Blood flow visualization
	- Specific targeting of immune complexes	- Requires biopsy	- Autoimmune diseases (pemphigus, lupus, bullous diseases)
		- Specialized antibodies

Molecular imaging techniques offer a layer of functional and biochemical information that complements optical imaging. Approaches like Raman spectroscopy, CARS, and mass spectrometry imaging enable label-free analysis of the skin’s chemical composition, delivering spatially resolved data on proteins, lipids, drugs, and metabolites. −

These technologies are especially valuable in fundamental research, where they support drug distribution studies, biomarker discovery, and spatial omics. MSI techniques achieve micrometer-scale resolution and can map hundreds of molecular species simultaneously, making them powerful tools for studying disease mechanisms and treatment responses. Raman-based methods, while limited in penetration depth, excel in analyzing surface chemistry and molecular changes in vivo with minimal sample preparation.

Despite their scientific value, molecular imaging methods face major barriers to clinical translation. They are typically ex vivo, expensive, and technically complex, requiring long acquisition times and expert data interpretation. However, emerging AI-driven algorithms promise to streamline image reconstruction, automate feature extraction, and reduce reliance on manual oversight, making high-throughput analysis more accessible. Furthermore, reproducibility across centers is limited by a lack of standardization in acquisition protocols, instrumentation, and data analysis workflows. MSI, in particular, produces large, multidimensional data sets that demand advanced computational tools for integration and interpretation. Currently, these methods are best suited to translational research rather than routine diagnostics. However, their potential is considerable, especially when integrated with imaging modalities like RCM or OCT and supported by artificial intelligence. As workflows become more automated and standardized, molecular imaging could play a central role in personalized dermatology, offering molecular-level diagnosis, prognosis, and treatment guidance.

3.3. Molecular Imaging: Mass Spectrometry Approaches

3.3.1. Overview of Mass Spectrometry-Based Imaging Methods in Dermatology

While mass spectrometry imaging (MSI) techniques also fall under the category of molecular imaging, they deserve special attention due to their unique ability to provide detailed spatial and chemical information about a sample. Unlike the previously discussed methods, which often rely on light-based or spectroscopic techniques to visualize molecular structures and functions in real time, MSI directly maps the spatial distribution of a wide range of biomolecules, such as lipids, proteins, and metabolites, without requiring external labels, and identifies the molecules in an untargeted fashion. This section explores MSI in more depth, highlighting its unique contributions to dermatology and its potential for advancing the molecular understanding of skin pathology.

Techniques such as matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS), desorption electrospray ionization mass spectrometry (DESI-MS), and secondary ion mass spectrometry (SIMS), are among the most relevant mass spectrometry imaging techniques for biomolecules in dermatology. These methods are ideal for studying skin lipids, metabolites, and topically applied compounds. , MALDI-MS works by applying a laser to a sample that has been coated with a matrix, causing the matrix to absorb the laser energy and desorb ions from the sample. This results in the generation of ionized molecules that are then analyzed by mass spectrometry, providing spatially resolved molecular maps. It allows for the visualization of the spatial distribution of proteins, lipids, and other biomolecules directly in tissue sections. It is used in dermatology to study skin cancer, wound healing, and drug permeation through the skin barrier (Figure ). However, it requires matrix application, which can lead to ion suppression or redistribution of molecules and typically requires fresh-frozen tissue samples, which may not always be available. DESI, on the other hand, uses an electrospray ionization technique, where a charged spray of solvent is directed onto the sample surface. This process desorbs ions from the sample without the need for a vacuum, making it particularly useful for imaging the surfaces of tissues in real time. It is used to investigate the distribution of drugs, metabolites, and lipids in the skin (Figure ). It does not require a matrix; hence, there might be less preparation time and artifact and it can be performed on tissue at ambient conditions. It does, however, offer a lower maximum spatial resolution (approximately 20–30 μm with the lowest at 10 μm) compared to MALDI (average 5–10 μm with the lowest at 1.4 μm). SIMS involves bombarding the sample with a focused primary ion beam, which causes the ejection of secondary ions that are analyzed to obtain detailed molecular and elemental compositions, offering high spatial resolution for imaging a sample’s uppermost layers at the microscopic level It is particularly useful for topographical studies of skin, such as the localization of small molecules and metal ions in the epidermis (85). It provides high spatial resolution and is ideal for surface analysis and depth profiling (Figure ). It is, nevertheless, generally limited to the very outer layers of the tissue, and the sample preparation can be complex and time-consuming.

20.

MALDI-IMS-MS images mapping the ions m/z 759.56, 757.54, 732.54, and 703.56 in skin equivalent tissue, at the different stages of a time course. These signals were identified from the PCA data as being significant contributors to the change in the spectra between the epidermis and dermis. Images are at a spatial resolution of 50 μm × 50 μm. Reproduced from Mitchell et al., ref ; licensed under CC-BY 4.0.

21.

Representative DESI-MSI ion images obtained from human lip tissue (subject #1) in positive ion mode. EV: Epithelium of the vermilion; PC: Phosphatidylcholine; PS: Phosphatidylserine. Reproduced with permission from ref . Copyright 2021 Elsevier.

22.

TOF-SIMS ion images from the epidermal region of skin tissue from lesional healthy and narrow-band ultraviolet B (NBUVB)-treated biopsies. (A) Optical microscopy images of epidermis regions from freeze-dried skin tissue sections in (i) lesional psoriasis tissue before treatment (sample 1), (ii) NBUVB-treated lesional tissue (sample 2), (iii) healthy tissue (sample 3), and (iv) NBUVB-treated lesional tissue (sample 4). Specific ion images of All individual ion images are in a 500 μm × 500 μm field of view and acquired at a pixel resolution of approximately 2 μm. Reproduced with permission from ref . Copyright 2019 Dove Medical Press.

Occasionally, less popular workflows, measured by their frequency of use and the number of laboratories adopting them, are followed. Laser microdissection followed by tandem mass spectrometry (LMD-MS) is rapidly gaining recognition when molecular subtyping is needed and has been used to classify amyloid deposits. In this method, a laser is used to precisely isolate specific areas of tissue, often on a microscope slide, before mass spectrometry is performed to analyze the molecular composition of the selected region. This technique allows for the extraction of specific biomolecules from small, localized regions of tissue, facilitating a deeper understanding of the molecular differences within heterogeneous tissue samples. Laser ablation inductively coupled plasma mass spectrometry (LA-ICP-MS) has also been used in creating qualitative and quantitative maps of elemental distribution in skin tissue sections. LA-ICP-MS involves focusing a laser beam on the tissue surface, which ablates a small volume of material that is then ionized in an inductively coupled plasma. The resulting ions are analyzed by mass spectrometry to generate maps of elemental composition, which can be used to study the distribution of metals and other trace elements in skin samples, providing valuable insights into skin health and disease.

The advantages of MSI techniques include high chemical sensitivity and specificity, combined with a high spatial resolution and the capability to analyze a wide range of molecules in skin tissues. The visualization of molecular distributions in skin samples is therefore possible, leading to the identification of biomarkers, drug penetration studies, and an understanding of disease pathogenesis. MSI has been effectively utilized to investigate skin hydration, lipid composition, and the distribution of small molecules in skin tissues. − Nevertheless, some techniques may necessitate complex sample preparation procedures and the need for extensive optimized protocols. Interpreting mass spectrometry imaging data can be intricate and often requires expertise in both mass spectrometry and bioinformatics. Additionally, currently, the cost and availability of specialized instrumentation may hinder the widespread adoption of these techniques in clinical settings. However, technology is advancing quickly, and it is likely that these techniques will become more affordable and widely used in clinics over the next decade.

3.3.2. Applications of Mass Spectrometry Imaging in Studying Skin Diseases

Mass spectrometry-based imaging techniques have several applications in studying skin diseases. They are used to characterize skin composition and pathology, together with omics. Analyzing the lipid profiles can provide insights into the skin’s barrier function, which is valuable information on atopic dermatitis and psoriasis, among others. Additionally, the biochemical environment of skin wounds can be studied to understand the healing process and potentially guide interventions to improve healing. MSI can also identify and localize specific proteins and peptides associated with cancerous changes. It aids particularly in visualizing the molecular distribution within tumor tissues, which paints a better picture of the complexity and heterogeneity of melanoma. Moreover, detecting small-molecule metabolites helps to understand metabolic changes that occur in skin disorders. It can also help to identify the presence of chemical elements or compounds associated with drug resistance within tumor microenvironments. There are also studies using MSI to investigate drug penetration through various layers of the skin (Figure ). , On top of that, understanding the distribution of a drug within the skin can help to infer its pharmacokinetic and pharmacodynamic properties. Those applications are targeted toward the design and development of novel medications (Figure ).

23.

Distribution of Ruxolitinib, Tofacitinib, LEO 29102, and Tacrolimus in skin treated with an ointment or solution containing cassette dosing of the four drugs. A sebaceous gland was observed and is marked with an arrow. Images were acquired in positive ion mode with a spatial resolution of 18 × 18 μm. Reproduced with permission from ref . Copyright 2017 Springer Nature.

24.

Hierarchical Classification of Imaging Modalities in Dermatology.

4. Multimodal Imaging Integration and Spatial Omics

Mass spectrometry spatial omics is an emerging field that combines MSI techniques with omics analyses to unravel the spatial distribution of molecules within the skin. It is able to provide spatially resolved molecular analyses of tissue biopsies with a resolution high enough to reach the single-cell level. The application of spatial omics in skin research and clinical care includes disease diagnosis and prognosis, drug penetration and efficacy, personalized medicine, and biomarker discovery.

Ma et al. (2020) used LC-MS-based proteomics and bioinformatics analyses to look for alterations in the expression of epidermal proteins among different ages and were able to identify differentially expressed proteins involved in skin aging. Forensic science is another field highly impacted by MSI, as well. MS-based proteomics is being used by forensic pathologists in the examination and characterization of wounds, especially in cases of violent death. Zhu et al. (2021) reported a novel analytical chemical methodology to be used in the real-time monitoring of skin conditions and early detection of abnormalities. They subsequently employed MS-based quantitative proteomics to validate their results.

Besides proteomics, metabolomics is a useful addition to the field since human skin contains multiple low-molecular-weight compounds. For instance, there are studies carried out to show differences in metabolites within psoriatic skin lesions by comparing them to healthy controls and, therefore, identifying metabolites such as glutamic acid, lactic acid, and urocanic acid as biomarkers of psoriatic disease. In the case of atopic dermatitis, LC-MS-based metabolomics helped in revealing dysbiosis of the skin microbiota, with increased Staphylococcus abundance and decreased Propionibacterium. This microbial imbalance was associated with altered metabolites involved in purine and phenylalanine metabolism, highlighting potential metabolic pathways driving eczema pathology. In the context of environmental pollution research, the metabolomics approach (UPLC-MS/MS method with electrospray ionization) was able to identify, among others, 350 metabolites that were associated with molecular signatures of pollution-induced skin dysfunction, highlighting the link between environmental factors and early skin aging. Metabolomics has also shown promise in the investigation of skin care products whose effects on the molecular distribution of the skin are unknown.

In comparison to the other spatial omics technologies, lipidomics is an increasingly important area of research due to the diverse lipid compositions in skin regions and layers that play crucial roles in disease mechanisms and treatment efficacy. The field of lipidomics, which has rapidly advanced since its inception in 2003, is aided by MSI-based strategies primarily categorized into direct infusion-based shotgun lipidomics, liquid chromatography–mass spectrometry platforms, and matrix-assisted laser desorption/ionization methods. A study by Yu et al. (2022) employed spatial lipidomics to map the distribution of lipids in healthy and psoriatic skin, revealing significant alterations in ceramide levels, which contribute to skin barrier dysfunction and inflammation. In a study by t’Kindt et al. (2012), focusing on ceramide profiling, an LC-MS method was developed for the characterization of ceramide species in the upper layer of human skin, revealing the presence of over 1000 unique known and previously undiscovered ceramides, demonstrating significant complexity in ceramide composition that could influence skin barrier function and health. Furthermore, van Smeden et al. (2014) developed a robust LC/MS method for the (semi)­quantitative analysis of ceramides, cholesterol, and free fatty acids in human stratum corneum showing that human skin equivalents closely mimic human lipid composition, with notable differences from porcine skin. A recent study of atopic dermatitis systematically investigated the composition of the stratum corneum lipidome, skin microbiome, and physiological parameters to reveal significant differences in lipid composition between body sites and among patients and healthy individuals.

While many studies focus on individual molecular classes, there is a growing recognition of the importance of integrating omics approaches to capture the complexity of skin biology. The skin is a complex ecosystem inhabited by diverse microorganisms, collectively known as the skin microbiota, which exhibit high microbial colonization with low diversity at the phylum level and high diversity at the species level. This complexity is further amplified by the interactions among host genetics, resident microbes, and their communities. To truly understand the skin’s ecosystem, a multiomics approach is essential. This includes analyzing the gene expression (genomics and metagenomics), transcription (transcriptomics and meta-transcriptomics), protein production (proteomics and meta-proteomics), and metabolite formation (metabolomics and lipidomics). The review by Dessi et al. (2024) emphasizes the value of this integrated omics approach in studying skin issues, with a particular focus on metabolomics as a key tool for understanding how the genome interacts with the environment.

5. Clinical Applications and Translational Potential

5.1. Current State of Clinical Studies in Dermatology Imaging

Over the past years, there has been a growing use of combined optical and molecular imaging techniques in clinical studies focused on diagnosing skin conditions and monitoring treatment outcomes. This integration provides complementary data that enhances the understanding of skin diseases at both the macroscopic and molecular levels. For instance, a combination of RCM and MSI has been used to map the distribution of skin cancer biomarkers, providing a detailed look at both cellular morphology and the molecular environment within the same lesion. In the field of psoriasis and other inflammatory skin diseases, studies combining OCT with molecular techniques have resulted in longitudinally monitoring disease progression and treatment response. OCT offers detailed images of the epidermis and dermis, while the MSI can detect the presence of specific inflammatory mediators within the skin layers, making it possible to correlate structural changes with molecular profiles. Furthermore, fluorescence in vivo imaging, together with MSI provides a way to visualize the efficacy of drug delivery systems. For example, by tracking a fluorescently labeled drug with optical imaging, researchers can determine its location and concentration, whereas MSI can offer a broader analysis of the drug and its metabolites within the skin. The applications of advanced imaging techniques in dermatology, covering personalized diagnostics, drug development, treatment monitoring, predictive biomarker identification, and understanding skin biology for various skin diseases, are summarized in Table .

5. Summary of imaging Applications in Clinical Research.

Application	Skin Disease	Imaging Techniques
Personalized Diagnostics -Differences among benign/malignant lesions and identification of cellular features	Melanoma	Dermoscopy, CLSM
	Basal Cell Carcinoma	Dermoscopy, RCM
	Squamous Cell Carcinoma	Dermoscopy, RCM
	Acne Vulgaris	High-Frequency US, OCT
	Rosacea	Dermoscopy, RCM
	Seborrheic Keratosis	Dermoscopy, CLSM
	Nevi (Moles)	Dermoscopy, RCM
Drug DevelopmentMeasuring of epidermal thickness/inflammation and evaluation of changes in collagen/elastin	Psoriasis	OCT, MPM, MSI
	Atopic Dermatitis	OCT, High-Frequency US, MSI
	Vitiligo	MPM, Hyperspectral Imaging
	Eczema	OCT, High-Frequency US, MSI
	Acne Vulgaris	OCT, MPM
	Alopecia Areata	High-Frequency US, OCT
Treatment MonitoringMonitoring of skin thickness/subcutaneous changes and evaluation of treatment efficacy	Atopic Dermatitis	US, Hyperspectral Imaging, MSI
	Psoriasis	OCT, US, MSI
	Acne Vulgaris	High-Frequency US, OCT
	Vitiligo	MPM, Hyperspectral Imaging
	Melanoma	Dermoscopy, CLSM
	Rosacea	Dermoscopy, RCM
	Basal Cell Carcinoma	RCM, OCT
Identifying Predictive BiomarkersIdentification of cellular features and use of AI for predictive patterns for disease progression	Basal Cell Carcinoma	CLSM
	Melanoma	Dermoscopy
	Psoriasis	OCT
	Atopic Dermatitis	High-Frequency US
	Acne Vulgaris	OCT
Understanding Skin BiologyEvaluation of melanin distribution/collagen structure and assessment of pigmentation/vascular changes	Vitiligo	MPM, MSI
	Psoriasis	MPM, MSI
	Atopic Dermatitis	MPM, MSI
	Eczema	MPM, MSI
	Rosacea	MPM, Hyperspectral Imaging
	Acne Vulgaris	MPM, Hyperspectral Imaging

One study by Gao et al. (2017) highlighted the use of fluorescent chemical probes for accurate tumor diagnosis and targeted therapy. The study emphasized the importance of optical imaging techniques in visualizing tumor lesions that contribute significantly to surgical resection. Another review by Csuka et al. (2021) evaluated the use of RCM and OCT in diagnosing and prognosticating inflammatory skin diseases (Figure ). In a study by Grajdeanu et al. (2019), various noninvasive imaging techniques, including dermoscopy, ultrasound, and OCT, were reviewed for their applications in diagnosing and monitoring psoriasis (Figure ). Additionally, Ianoşi et al. (2018) supported the role of dermoscopy and RCM in the in vivo diagnosis of lichen planus (Figure ). Ring et al. (2019) reviewed the potential of contrast agents to enhance in vivo confocal microscopy and OCT and then used them to monitor treatment efficacy over time (Figure ). These studies collectively highlight the significance of optical and molecular imaging techniques in advancing dermatological research, which aims to improve clinical care.

25.

Sample images of (a) reflectance confocal microscopy (RCM), (b) optical coherence tomography (OCT), and (c) multiphoton microscopy (MPM) in normal skin. Reproduced with permission from ref . Copyright 2021 Wiley.

26.

HFUS analysis with Dermascan C USB (20 MHz B-mode) of a psoriasis plaque showing thickening of epidermis with a hyperechogenic band, which represents hyperkeratosis and parakeratosis accompanied by hypoechogenic band, corresponding to the elongation of the dermal papillae (A) in comparison with adjacent healthy tissue (B). Reproduced with permission from ref . Copyright 2019 Spandidos Publications.

27.

RCM image (500 × 500 μm) at the level of the papillary dermis showing numerous bright roundish or polygonal cells (white arrows) corresponding to the dermal inflammatory infiltrate. Reproduced with permission from ref . Copyright 2019 Spandidos Publications.

28.

Fluorescence confocal microscopy of sodium fluorescein in the laser and microneedle channels in normal skin. FCM images of sodium fluorescein in laser and microneedle channels obtained by Vivascope in 488 nm mode. The laser grit following the fractional CO₂ laser at 25 mJ, 5% density is recognized in the upper row. The skin channels after microneedling are randomly distributed as a 1 mm microneedle device was rolled over the same skin area twice. Sodium fluorescein (1% Minims, Bausch & Lomb, U.K.) was applied on top of laser channels immediately after laser and needle exposure. It is evident that fluorescence highlights the epidermal ridges and intercellular tissue in both methods.

Recent multicenter studies have further validated the clinical utility and reproducibility of advanced skin imaging modalities in real-world settings. A randomized clinical trial conducted across three dermatology referral centers in Italy evaluated the impact of reflectance confocal microscopy RCM on the diagnostic management of over 3000 clinically suspicious skin lesions. The study demonstrated that integrating RCM into the diagnostic pathway reduced unnecessary surgical excisions by over 30%, without compromising diagnostic accuracy for melanomas thicker than 0.5 mm. These findings underscore the role of RCM in improving diagnostic precision, minimizing patient burden, and optimizing resource use in dermatology clinics.

Similarly, a multicenter study assessed the robustness of MALDI-MSI across laboratories with varying instrumentation and workflows. The study showed that when standardized preprocessing protocols were followed, tissue classification models trained at one site could be reliably applied at others, achieving cross-site classification accuracies as high as 94%. This level of reproducibility highlights MSI’s potential for broader clinical adoption and supports its value in biomarker discovery, drug distribution analysis, and diagnostic research in dermatological diseases.

At the same time, in clinical reality, dermoscopy remains the most widely used noninvasive imaging tool, with skin punch biopsies serving as the standard for definitive diagnosis when needed. Although advanced techniques included in this review are gradually entering clinical use, especially in specialized centers and complex cases, their application is still relatively limited due to factors such as cost, equipment availability, and required expertise.

5.2. Translational Potential of Advanced Imaging Techniques for Dermatology

The translational potential of advanced imaging techniques in dermatology is substantial as these innovations have the end goal of enabling clinicians to visualize skin pathologies with the highest precision. Any newly developed technique aims not only to enhance diagnostic accuracy but also to facilitate personalized treatment strategies by providing insights into the molecular composition of skin lesions. Translating new imaging modalities for skin from research to clinical care involves several key steps. First, rigorous validation and standardization are necessary to ensure accuracy and reliability in clinical settings. Regulatory approval from bodies such as the FDA is essential for safety and efficacy. The following step would be the integration with existing clinical workflows, including compatibility with electronic health records, to make the transition easier. In the same context of evolving the clinical environment, healthcare providers need to be trained in these new technologies to enhance their implementation. Moreover, demonstrating the cost-effectiveness of new modalities and protocols is vital for their acceptance by both clinicians and patients. Robust clinical evidence showing improved patient outcomes would be highly beneficial for this cause and for gaining traction in the medical community. Finally, interdisciplinary collaboration and continuous feedback from users will help refine these technologies, ensuring that they effectively meet the clinical needs of the population.

5.3. Role of Artificial Intelligence in Dermatological Imaging

Artificial intelligence (AI), particularly deep learning, is increasingly advancing dermatological imaging by enabling automated lesion detection, segmentation, and disease monitoring. Algorithms trained on large dermoscopic data sets now achieve dermatologist-level performance in melanoma classification, especially when combined with clinical metadata or ensemble models. Recent multicenter studies have shown that AI tools can outperform human specialists in certain tasks, including the detection of challenging melanomas. Beyond skin cancer, AI has been applied to chronic inflammatory diseases such as psoriasis and atopic dermatitis. It assists in quantifying lesion area, erythema, and scaling with high reproducibility, supporting both clinical trials and personalized care. , Mobile imaging apps increasingly embed AI-powered scoring systems for self-monitoring, although clinical validation varies.

Despite these advances, significant challenges remain. Data set bias, particularly underrepresentation of darker skin types, can compromise model generalizability. Privacy concerns also limit access to high-quality annotated data, though federated learning approaches now enable collaborative model training without data sharing. Another key concern is explainability; black-box AI models often lack transparent rationale, raising trust and regulatory issues. Techniques such as saliency maps, class activation maps, and concept bottlenecks are being explored to address this. The regulatory landscape is evolving, with emerging standards promoting transparency and reproducibility. Clinical adoption will require prospective validation, interoperability with existing imaging systems, and continuous performance monitoring. Nonetheless, AI holds strong potential to complement human expertise, improve diagnostic consistency, and streamline dermatological workflows, particularly when integrated with optical and molecular imaging platforms.

In conclusion, the future role of AI is poised to be transformative; AI algorithms can streamline data processing, enhance image interpretation, and support real-time decision-making, ultimately leading to improved patient outcomes. As interdisciplinary collaborations expand and data analysis tools become more accessible, the full translational potential of advanced imaging techniques in dermatology will be established, paving the way for a new era of precision medicine.

6. Challenges and Future Perspectives

6.1. Identification of Current Limitations and Challenges in Dermatological Imaging

The field of dermatology encounters limitations concerning imaging approaches, protocols, and workflows for both research and clinical care. These challenges impact the accessibility and efficiency of dermatological imaging practices, ultimately influencing patient outcomes and the quality of care provided.

Access to dermatologic care is obstructed by factors such as the shortage of dermatologists, geographic barriers, and lack of health insurance, which results from the fact that the majority of skin conditions are not life-threatening and therefore are less prioritized. This limited access can result in delays in diagnosis, inadequate treatment, and disparities in healthcare delivery. , As previously stated, molecular imaging leads to the most efficient medical insights. However, the need for specialized equipment and expertise in advanced imaging techniques, such as MSI, poses a challenge. Integrating these technologies with existing clinical laboratory and information systems can be costly and complex. Another limitation is the recurring absence of standardization and interoperability. The lack of standardized protocols in dermatological imaging makes the exchange of imaging data challenging. Unlike other specialties relying on imaging techniques like radiology, dermatology lacks uniform standards for imaging, which can impede collaboration and data sharing. Furthermore, while tele-dermatology shows promise in expanding access to care and reducing patient wait times, it has been proven difficult to implement. Major issues lie in funding and resource constraints. The cost of implementing and maintaining advanced imaging technologies, not to exclude AI imaging models and digital pathology systems, can be prohibitive for healthcare facilities. Limited resources hinder the adoption of cutting-edge imaging solutions in dermatology. In this context, monitoring the effects of skin treatments “on the fly” emerges as a crucial aspect of improving patient outcomes. Utilizing advanced technologies like wearable sensors and mobile imaging devices allows for real-time assessment of treatment efficacy, enabling timely adjustments to therapy. This immediate feedback can enhance personalized care, ensuring that patients receive optimal treatment based on their unique responses, ultimately bridging some gaps in dermatological care access.

The advent of advanced imaging techniques in dermatology represents a significant leap forward in our ability to visualize and understand skin pathologies. While these techniques offer unparalleled insights into skin health and disease, many are still relatively new and not yet fully integrated into clinical practice. As researchers and clinicians work to optimize these methodologies, a notable challenge lies in harnessing their full potential. Automation and standardization of imaging protocols are essential to streamline their application in routine dermatological assessments. This ongoing evolution requires extensive collaboration between scientists and clinicians to develop robust workflows that can consistently deliver reliable and clinically relevant information.

The importance of data and image analysis cannot be overstated; while anyone can run a sample on an instrument, extracting meaningful conclusions from the resulting data is where the true expertise lies. Currently, many researchers and clinicians face challenges such as the overwhelming volume of imaging data, the complexity of interpreting high-dimensional data sets, and a lack of standardized analytical methods. These issues can obstruct the effective translation of imaging results into clinical practice. Solutions include enhanced training programs that focus not only on instrument operation but also on advanced data analysis techniques as well as the development of user-friendly software that can assist in data interpretation. The current state of imaging data analysis indicates a need for interdisciplinary collaboration, where data scientists work alongside dermatologists to improve analysis outcomes. By fostering these skills and resources and recognizing the importance of interdisciplinary science, practitioners can maximize the insights derived from advanced imaging technologies, ensuring that their potential is fully realized in clinical practice and patient care.

6.2. Integrating Imaging Modalities and Omics for Comprehensive Skin Analysis

The further integration of imaging modalities such as OCT, multiphoton microscopy, and fluorescence microscopy with omics data (genomics, proteomics, metabolomics) can provide a more holistic characterization of skin conditions at the molecular, cellular, and tissue levels. , By combining imaging modalities that offer different contrast mechanisms and resolutions, researchers can improve diagnostic accuracy and identify disease-specific biomarkers. For example, coupling reflectance confocal microscopy or OCT with spatial transcriptomics or mass spectrometry imaging enables the in situ mapping of gene or protein expression patterns within morphologically defined lesions. Such fusion supports early detection and differential diagnosis, as well as the stratification of disease subtypes based on spatially resolved molecular signatures. Another benefit would be the development of personalized treatment strategies since doctors can tailor treatment plans based on individual patient characteristics. , The identification of patient-specific biomarkers, not necessarily suited for all patients at once, can also enable guiding targeted therapies. , Finally, novel disease mechanisms can be uncovered, accelerating the development of new treatment modalities for skin visualization. , As image resolution improves and molecular panels expand, multimodal workflows may become indispensable in both precision dermatology and translational research.

Looking ahead, the integration of AI is expected to play a central role in operationalizing multimodal imaging. AI algorithms can now perform coregistration of heterogeneous data sets, segment anatomical structures, and interpret complex spatial relationships between histological and molecular features. For instance, AI has been successfully used to align MSI chemical maps with structural OCT images to localize drug penetration relative to lesion borders and to analyze Raman spectra alongside confocal images for enhanced classification of pigmented lesions. Deep learning also offers solutions for harmonizing data across platforms and institutions, addressing the variability in acquisition and interpretation. Foundation models trained on multimodal dermatological data represent an emerging trend that could enable real-time AI-guided diagnostic support across imaging types. However, for these innovations to reach clinical application, challenges in data standardization, regulatory validation, and explainability must be addressed.

As technological advancements continue to refine imaging techniques and omics integration, the future of dermatological imaging holds immense promise. The synergy between optical and molecular imaging, powered by AI, could revolutionize the way that skin diseases are diagnosed, monitored, and treated. Future research should focus on optimizing multimodal imaging systems, improving accessibility, and addressing challenges related to data interpretation and standardization.

6.3. Future Directions in Dermatological Imaging

Looking forward, the future of dermatological imaging will likely center around multimodal platforms that integrate optical and molecular data in real time. Technologies such as ultrahigh-resolution OCT, advanced Raman spectroscopy (e.g., SRS, CARS), and high-resolution MSI are poised to move from research to clinical environments as hardware becomes faster, more compact, and more affordable. Integration into clinical workflows will require automation of data interpretation, improved coregistration between modalities, and regulatory frameworks to validate novel biomarkers. AI will be central in driving this transition, supporting tasks such as rapid tissue classification, drug monitoring, and predictive modeling. Future systems may combine bedside-compatible imaging with molecular insight, enabling personalized treatment decisions within minutes of image acquisition.

Beyond the currently established methods, several advanced imaging techniques from other fields hold potential in dermatology. Terahertz imaging can noninvasively assess hydration levels, structural integrity, and detect nonmelanoma skin cancers, making it promising for burn evaluation and tumor margin mapping. Fluorescence lifetime imaging microscopy (FLIM) and second harmonic generation (SHG) offer label-free visualization of metabolic activity and structural proteins like collagen and elastin, with applications in fibrosis, photoaging, and wound healing. , Multiplexed imaging platforms, such as MIBI or MALDI-IHC, allow targeted spatially resolved protein profiling and immune cell phenotyping, potentially enhancing the understanding of inflammatory and neoplastic skin disorders. , Incorporating these emerging technologies, especially when combined with omics and AI, could significantly broaden the diagnostic and research capabilities of dermatological imaging.

Glossary

Vocabulary Section

Optical Imaging

A group of imaging techniques that use light in the ultraviolet, visible, and infrared regions of the electromagnetic spectrum, and special properties of photons to acquire detailed images of tissues, organs, and cells.

Dermoscopy

A noninvasive technique used to examine skin lesions by magnifying and illuminating the skin surface with a dermatoscope.

Molecular Imaging

The visualization, characterization, and measurement of biological processes at the molecular and cellular levels in humans and other living systems.

Mass Spectrometry Imaging

A label-free analytical technique that can visualize the spatial distribution of molecules on the sample surface.

Spatial Omics

A group of approaches that combine molecular omics data, such as genomics, transcriptomics, proteomics, or metabolomics, with spatial information.

A.B. contributed to the investigation, formal analysis, conceptualization, and writingreview, and editing; R.M.A.H. contributed to conceptualization, supervision, writingreview and editing, and funding acquisition; E.C. contributed to conceptualization, supervision, writingreview and editing, and funding acquisition; and R.J.V. contributed to conceptualization, supervision, writingreview and editing, and funding acquisition.

This study was supported by the NWA-ORC project NWA.1389.20.182 entitled Next Generation ImmunoDermatology (NGID).

The authors declare no competing financial interest.