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. 2025 Dec 29;6(2):100446. doi: 10.1016/j.xjidi.2025.100446

Dermoscopy-guided high-frequency ultrasound: Principles and applications in dermatology

Mehdi Boostani 1, Ximena Wortsman 2,3, Giovanni Pellacani 4, Krisztián Füzesi 5, Mariano Suppa 6,7,8, Veronique Del Marmol 6,7, Florencia Vera Morandini 9, Javiera Perez-Anker 9, Priscila Giavedoni 9, Carmen Cantisani 4, Lucas Boussingault 6,7, Miklós Gyöngy 5, Gyorgy Paragh 1, Kamran Avanaki 10,∗,12, Norbert Kiss 11,∗,12
PMCID: PMC12874293  PMID: 41658266

Abstract

Conventional skin imaging modalities are often bulky, expensive, and impractical for routine dermatology practice. There is a need for a portable, multimodal imaging tool that integrates high-resolution surface and subsurface visualization at the point of care. The aim of this study was to describe the design, technical capabilities, and clinical application of dermoscopy-guided high-frequency ultrasound and to evaluate its performance across a range of dermatologic conditions. Dermoscopy-guided high-frequency ultrasound was applied to a total of 130 lesions from 122 patients at the Department of Dermatology, Semmelweis University (Budapest, Hungary); Université Libre de Bruxelles (Brussels, Belgium); and Hospital Clínic, Universidad de Barcelona (Barcelona, Spain). The examined cases included malignant skin cancers and inflammatory disorders. Dermoscopy-guided high-frequency ultrasound enabled simultaneous visualization and correlation of surface dermoscopic patterns with underlying structural alterations in real time. The device identified disease-specific imaging features for both malignant and inflammatory lesions. Artificial intelligence-based segmentation improved image interpretability. Dermoscopy-guided high-frequency ultrasound bridges a critical gap between surface and subsurface dermatologic imaging, offering a practical, portable, and cost-effective solution that could enhance noninvasive diagnosis and management in dermatologic care.

Keywords: Dermoscopy-assisted high-frequency ultrasound, Dermoscopy-guided high-frequency ultrasound, High-frequency ultrasound, Imaging, Skin cancer

Introduction

High-frequency ultrasound (HFUS) is a valuable imaging technique for analyzing morphological changes in the skin, offering detailed visualization of subsurface structures (Vergilio et al, 2021). Dermoscopy, on the other hand, is widely used and well-established for surface-level skin analysis, making it a cornerstone in dermatologic diagnostics. Correlating dermoscopy findings with HFUS imaging remains a significant challenge owing to the difficulty in aligning surface localization with subsurface visualization (Campos-do-Carmo and Ramos-e-Silva, 2008). Although portable HFUS devices for skin imaging exist (Boostani et al, 2024), they lack the capability to coregister dermoscopy localization, limiting their ability to integrate clinical and subclinical diagnostic information at the same time.

Several other advanced imaging techniques, such as optical coherence tomography (OCT) (Huang et al, 1991; Welzel, 2001), line-field confocal OCT (Dubois et al, 2018), and reflectance confocal microscopy (RCM) (Rajadhyaksha et al, 1999, 1995), are also used for skin analysis and have automated coregistration with dermoscopy images. However, these imaging modalities have certain drawbacks that limit their practicality in routine dermatological practice. Many of these devices are large, require a dedicated setup, and are often confined to specific clinical environments. Moreover, they are not designed for rapid image acquisition, making them time intensive for use during standard outpatient dermatology patient appointments. Their high cost further exacerbates these limitations. As a result, even though these technologies demonstrate diagnostic efficacy, they often fall short of being effective in real-life clinical settings where cost efficiency and limited time per patient are critical considerations (Zucker and Price, 2001).

The dermoscopy-guided HFUS (DG-HFUS) system, also known as dermoscopy-assisted HFUS, is a multimodal imaging platform that unites detailed surface visualization with deep tissue penetration in a compact, cost-effective design. Unlike conventional imaging technologies that are often bulky, expensive, and time consuming, DG-HFUS enables rapid image acquisition and real-time assessment at the point of care. By coregistering dermoscopic and HFUS data, it bridges the diagnostic gap between clinical superficial and subsurface skin analysis. This allows clinicians to capture comprehensive views of both surface features and underlying structures without the logistical and financial constraints of larger, stationary systems. In this paper, we present the design and capabilities of the DG-HFUS system and evaluate its performance in imaging a range of dermatologic conditions.

Results

DG-HFUS clinical performance

Healthy skin imaging in vivo

The DG-HFUS system was evaluated on healthy skin that was subsequently excised as part of the safety margin during lesion resections, following standard resection protocols. Imaging this skin enabled us to assess the system’s ability to differentiate normal skin structures. DG-HFUS imaging delineated key anatomical layers and features, including the epidermis, dermis, and hypodermis; hair follicles; and lesions, which were similar in morphology to the reported patterns in the literature (Argalia et al, 2025; Wortsman, 2023).

On ultrasound, the epidermis appeared as a thin, hyperechoic (bright) layer; the dermis appeared as a thicker, heterogeneous hyperechoic layer owing to its dense connective tissue; and the hypodermis appeared as a hypoechoic (darker) region containing subcutaneous fat. Notably, the DG-HFUS images of these subsurface structures could be correlated with corresponding surface features observed in dermoscopic panels (Figure 1a and b). Image processing enables the automatic labeling of the epidermis, dermis, and subcutis in different colors (Figure 1d). Hair follicles were visualized as small, tubular hypoechoic structures extending from the epidermis into the dermis or hypodermis (Figure 2).

Figure 1.

Figure 1

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DG-HFUS imaging of healthy skin. The figure shows representative images from the right temporal region of a male patient aged 56 years with Fitzpatrick III skin phototype who underwent standard surgical excision of basal cell carcinoma. Healthy skin was imaged from the safety margin to evaluate the ability of the DG-HFUS system to delineate normal skin layers. (a) Dermoscopy image. The central red line indicates the plane along which the corresponding HFUS scan (panel b) was acquired. (b) HFUS image prior to segmentation, displaying key anatomical landmarks. (c) HFUS image postautomated segmentation, with different skin layers distinctly color coded to enhance anatomical interpretation. (d) Corresponding histological section of the same skin region stained with H&E, validating the structural assignment of skin layers. In b, the blue arrow indicates the silicone membrane of the DG-HFUS probe, and the asterisk (∗) denotes the coupling gel. Bar (d) = 500 μm. The epidermis (denoted as E), dermis (denoted as D), and subcutis (denoted as S) are visible in b, c, and d. The subject provided written, informed consent for publication of this image. DG-HFUS, dermoscopy-guided high-frequency ultrasound; HFUS, high-frequency ultrasound.

Figure 2.

Figure 2

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DG-HFUS visualization of hair follicles in healthy skin. DG-HFUS images from the right cheek of a healthy male aged 27 years with Fitzpatrick III skin phototype are shown. The dermoscopic panel (a) shows multiple terminal hairs emerging from follicular ostia; the red vertical line indicates the plane of the corresponding ultrasound scan. (b) In the coregistered HFUS image, the colored arrows highlight the same hair follicles seen on dermoscopy, which appear as small, tubular hypoechoic structures extending from the epidermis into the dermis. The subject provided written, informed consent for publication of this image. DG-HFUS, dermoscopy-guided high-frequency ultrasound; HFUS, high-frequency ultrasound.

Skin cancers

Among melanomas, 27 of 40 lesions (67.5%) appeared as hypoechoic lesions that could extend into the surrounding tissue. Irregular thickness of the lesion was noted in 25 of 40 melanomas (62.5%). Representative DG-HFUS findings for melanoma are displayed in Figure 3.

Figure 3.

Figure 3

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DG-HFUS imaging of skin cancers. (a–e) An infiltrative basal cell carcinoma on the left temple of a male patient aged 68 years with Fitzpatrick II skin phototype: (a) a macroscopic image of the lesion, (b) a dermoscopic image taken using a commercial dermoscope, (c) a dermoscopic image obtained using the DG-HFUS system, (d) the coregistered HFUS image corresponding to the red line, and (e) an HFUS image enhanced with AI-based segmentation generated using the DG-HFUS system. (f–j) A squamous cell carcinoma on the left forehead of a female patient aged 60 years with Fitzpatrick III skin phototype: (f) a macroscopic image of the lesion; (g) a dermoscopic image taken using a commercial dermoscope; (h) a dermoscopic image obtained using the DG-HFUS system; (i) the coregistered HFUS image corresponding to the red line, showing acoustic shadowing from the tumor that conceals the dermis and subcutis; and (j) an HFUS image enhanced with AI-based segmentation generated using the DG-HFUS system. (k–o) Present a melanoma on the right deltoid area of a male patient aged 78 years with Fitzpatrick III skin phototype: (k) a macroscopic image of the lesion, (l) a dermoscopic image taken using a commercial dermoscope corresponding to the area marked with a white circle on the macroscopic image, (m) a dermoscopic image obtained using the DG-HFUS system corresponding to the area marked with a black circle on the commercial dermoscopic image, (n) the coregistered HFUS image corresponding to the red line, and (o) an HFUS image enhanced with AI-based segmentation generated using the DG-HFUS system. In the HFUS images (d, i, and n), the epidermis (denoted as E), dermis (denoted as D), subcutis (denoted as S), and tumor (marked with an asterisk) are visualized. In the AI-enhanced segmented HFUS images (e, j, and o), purple represents the epidermis, pink represents the tumor, green represents the dermis, and yellow represents the subcutis. The subject provided written, informed consent for publication of this image. AI, artificial intelligence; DG-HFUS, dermoscopy-guided high-frequency ultrasound; HFUS, high-frequency ultrasound.

In squamous cell carcinoma, 13 of 15 lesions (86.7%) appeared as hypoechoic areas on DG-HFUS. Acoustic shadowing, in which the lesion attenuates the ultrasound beam and obscures visualization of deeper structures, was present in 11 of 15 lesions (73.3%). In these cases, the dermis and hypodermis beneath the tumor could not be clearly visualized. DG-HFUS imaging features of squamous cell carcinoma are illustrated in Figure 3.

Using the DG-HFUS system, 37 of 40 basal cell carcinomas (BCCs) (92.5%) appeared as well-defined hypoechoic (darker) lesions in contrast to the surrounding healthy dermis, which was hyperechoic (brighter). In addition, the HFUS region of BCC lesions frequently showed internal heterogeneity, with hyperechoic spots observed in 32 of 40 lesions (80.0%) and variable echogenicity. Representative DG-HFUS images of BCC are shown in Figure 3.

Inflammatory skin disease

Psoriasis typically appears as an area of thickened epidermis with increased echogenicity. DG-HFUS also identified the inflammatory hypoechoic upper dermal band in 100% of the lesional areas (Figure 4) but not in healthy regions. The subsurface structures of psoriasis could be correlated with surface features observed in the dermoscopic panel.

Figure 4.

Figure 4

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DG-HFUS imaging of psoriasis. This figure demonstrates imaging of a lesion from a male patient aged 56 years with Fitzpatrick III skin phototype with plaque psoriasis on the left flank. (a) In the macroscopic image, the black circle indicates the psoriasis-affected region scanned with the DG-HFUS system, whereas the white circle represents an unaffected section of the skin. (b–d) Correspond to the psoriasis-affected region: (b) a dermoscopic image obtained using the DG-HFUS system corresponding to the area marked with a black circle on the macroscopic image; (c) the coregistered HFUS image corresponding to the red line, showing the presence of a hypoechoic upper dermal band; and (d) an HFUS image enhanced with AI-based segmentation generated using the DG-HFUS system, showing the hypoechoic upper dermal band in pink. (e–g) Images correspond to the unaffected skin region: (e) a dermoscopic image obtained using the DG-HFUS system corresponding to the area marked with a white circle on the macroscopic image; (f) the coregistered HFUS image corresponding to the red line, showing the absence of the hypoechoic upper dermal band; and (g) an HFUS image enhanced with AI-based segmentation generated using the DG-HFUS system. In the HFUS images (c and f), the epidermis (denoted as E), dermis (denoted as D), subcutis (denoted as S), and the hypoechoic upper dermal band (marked with an asterisk only in panel c) are visualized. In the AI-enhanced segmented HFUS images (d and g), purple represents the epidermis, pink represents the upper dermal hypoechoic band (only in panel d), green represents the dermis, and yellow represents the subcutis. The HFUS images are displayed with a pseudo-color scale indicating relative echo intensity. The multicolored appearance at the dermal–epidermal junction and in the dermis, including perilesional areas, reflects variations in echogenicity and speckle. The subject provided written, informed consent for publication of this image. DG-HFUS, dermoscopy-guided high-frequency ultrasound; HFUS, high-frequency ultrasound.

On DG-HFUS, hidradenitis suppurativa (HS) typically appears as a complex, heterogeneous lesion with hypoechoic (darker) areas representing pseudocysts, fluid collections, or tunnels, often with irregular borders and a substantial average of 4- to 5-fold increase in epidermal and dermal thickness in 100% of the HS-affected lesions. The subsurface structures of HS can be correlated with surface features observed in the dermoscopic panel. Figure 5 shows images from a patient with HS and the corresponding area in a healthy person. The HFUS image and the artificial intelligence–based segmentation images show significant differences in dermal thickness.

Figure 5.

Figure 5

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DG-HFUS imaging of hidradenitis suppurativa. (a–c) Pertain to the left axilla of a female patient aged 48 years with Fitzpatrick II skin phototype with HS Hurley stage 3. (a) Shows a dermoscopic image of an HS-affected lesion. (b) Presents the coregistered HFUS image corresponding to the red line. (c) Displays an HFUS image enhanced with AI-based segmentation generated using the DG-HFUS system, highlighting the thickened dermis. (d–f) Pertain to the left axilla of a healthy male volunteer aged 63 years with Fitzpatrick III skin phototype without any skin disease. (d) A dermoscopic image taken using the DG-HFUS system. (e) The coregistered HFUS image corresponding to the red line. (f) An HFUS image enhanced with AI-based segmentation generated using the DG-HFUS system. In the HFUS images (b and e), the epidermis (denoted as E), dermis (denoted as D), and subcutis (denoted as S) are visualized, and the asterisk (∗) denotes a hypoechoic inflammatory area, presumably part of a pseudocystic structure. In the AI-enhanced segmented HFUS images (c and f), purple represents the epidermis, green represents the dermis, and yellow represents the subcutis. The HFUS images are shown using a pseudo-color scale, where different colors indicate different echo intensities. The multicolored bands at the dermal–epidermal junction and within the dermis reflect gradual transitions in echogenicity and speckle pattern. The subject provided written, informed consent for publication of this image. DG-HFUS, dermoscopy-guided high-frequency ultrasound; HFUS, high-frequency ultrasound; HS, hidradenitis suppurativa.

Discussion

This study introduces DG-HFUS as a practical and innovative alternative to conventional imaging technologies in dermatology, addressing major limitations in current modalities. Although advanced tools such as RCM and multiphoton microscopy offer exceptional axial resolution (1–2 μm), they are limited by shallow penetration depths (∼0.2 mm), rendering them unsuitable for imaging deeper skin layers (Calzavara-Pinton et al, 2008; Hofmann-Wellenhof et al, 2009; Kiss et al, 2019; Nehal et al, 2008; Rajadhyaksha et al, 1999, 1995; Stachs et al, 2019; Zipfel et al, 2003). In contrast, DG-HFUS offers a balanced approach with an axial resolution of ∼100 μm, lateral resolution of 300 μm, and a penetration depth of up to 10 mm. Although this resolution is insufficient for visualizing cellular structures, it provides sufficient detail to assess the morphology and depth of skin lesions. Unlike conventional HFUS, which lacks surface-level orientation, DG-HFUS delivers real-time, coregistered images of surface and subsurface structures, offering a more intuitive and diagnostically useful workflow. Its portability and ease of use further distinguish it from bulky, high-cost systems such as RCM, line-field confocal OCT, and nonlinear microscopy that require dedicated space and trained personnel for operation (Aguirre et al, 2003; Alarcon et al, 2014; Beaurepaire et al, 1998; Calzavara-Pinton et al, 2008; Chen et al, 2012, 2007; Cortex, 2025; Dalimier and Salomon, 2012; Drexler and Fujimoto, 2008; Dubois et al, 2018, 2004; Fujimoto et al, 2000; Guitera et al, 2010; Hofmann-Wellenhof et al, 2009; Holmes and Hattersley, 2009; Izatt et al, 1994; Izzetti, 2021; Konig and Riemann, 2003; Kollias and Stamatas, 2002; Lee et al, 2013; Levine et al, 2017; Minhaz et al, 2024; Nehal et al, 2008; Ogien and Dubois, 2019; Pellacani et al, 2007; Phillips et al, 2020; Podoleanu, 2012; Rajadhyaksha et al, 1999, 1995; Schuh et al, 2016; Srinivasan et al, 2012; Stachs et al, 2019; Welzel et al, 1997; Zipfel et al, 2003) (Table 1).

Table 1.

Comparison of Imaging Modalities for Dermatological Assessment

Example Device View Axial Resolution Lateral Resolution Lateral Field Optical Guidance Handheld (Portable) Penetration Depth Cost
RCM by Vivascope En face 5 μm 1 μm 1.0a mm No No 0.2 mm >$100,000
NLO by DermaInspect En face 2 μm 1 μm 0.35 mm No No 0.2 mm >$100,000
OCM (FF-OCM) (SkinTell) by Agfa Healthcare En face, B mode, 3-D 3 μm 3 μm 1.5 mm No No 0.3 mm >$100,000
LC-OCT (deeplive) by Damae B mode 1 μm 1 μm 1.2 mm Yes No 0.5 mm >$100,000
OCT (multibeam FD-OCT) by Vivosight En face, B mode, 3-D 5 μm 7.5 μm 6 mm No No 1 mm >$100,000
DG-HFUS (Skinscanner) by Dermus B mode 100 μm 300 μm 12 mm Yes Yes 10 mm $5000-10 000
Fujifilm Visualsonics (70 MHz probe) B mode 30 μm 65 μm 9.7 mm No No 10 mm >$200,000-500-000
HFUS (DermaScan 20 MHz transducer) by Cortex B mode 60 μm 150 μm 12.1 mm No No 13 mm $25,000-$50,000
HFUS (L20 HD3) by Clarius B mode 377 μm 550 μm 25 mm No Yes 40 mm $<15,000
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Abbreviations: DG-HFUS, dermoscopy-guided high-frequency ultrasound; FD-OCT, Fourier-domain optical coherence tomography; FF-OCM, full-field optical coherence tomography; HFUS, high-frequency ultrasound; LC-OCT, line-field confocal optical coherence tomography; NLO, nonlinear microscopy; OCM, optical coherence microscopy; OCT, optical coherence tomography; RCM, reflectance confocal microscopy.

The diagnostic potential of DG-HFUS was evaluated through multiple clinical studies on skin cancers and inflammatory dermatoses. For melanoma, where Breslow thickness is a critical prognostic marker (Breslow, 1970), DG-HFUS achieved a sensitivity of 91.8% and specificity of 96.0% in estimating tumor depth, with a Pearson correlation coefficient of r = 0.943 (P < .0001), outperforming conventional 20 MHz HFUS (r = 0.390) and even OCT (r = 0.734) (Hinz et al, 2011; Varga et al, 2023). In BCC, DG-HFUS demonstrated the ability to distinguish between low- and high-risk subtypes on the basis of lesion morphology. In a cohort of 60 patients with 63 BCCs, DG-HFUS achieved 83.33% sensitivity and 91.66% specificity in classifying high-risk lesions, rivaling RCM, which shows 88.9% sensitivity for nonsuperficial subtypes but only 33.3% for aggressive forms (Boostani et al, 2025e; Bozsányi et al, 2023; Di Stefani et al, 2023; Woliner-van der Weg et al, 2021). Furthermore, in a recent pilot study on preoperative lateral margin mapping of BCC, DG-HFUS demonstrated 94.4% sensitivity and 93.0% specificity, with a diagnostic accuracy of 93.4% for detecting tumor presence within 2 mm of the surgical margin, showing strong agreement with histopathology and highlighting its potential role in surgical planning (Boostani et al, 2025f, 2024).

In inflammatory skin diseases, DG-HFUS provides promising noninvasive metrics for disease assessment and monitoring. In HS, DG-HFUS detected 3–5× increases in epidermal and dermal thickness in affected areas, a result consistent with Doppler OCT findings that reported significant epidermal thickening at HS borders (203 vs 128 μm in healthy skin) (Manfredini et al, 2022). However, the device is limited to detecting larger lesions or early lesions as well as for staging the patients.

For psoriasis, dermoscopic guidance enabled precise and repeatable tracking of inflammatory hypoechoic upper dermal bands and epidermal thickness, yielding strong correlations with disease activity (PASI-inflammatory hypoechoic upper dermal band correlations of 0.90 and 0.93, P < .05). In contrast, OCT-based studies, although effective at tracking epidermal thickness (r2 = 0.41, P = .001), failed to show consistent alignment with PASI scores (Morsy et al, 2010). By enabling surface-to-depth correlation and consistent probe placement across visits, DG-HFUS supports reproducible and longitudinal imaging, making it especially useful for treatment response evaluation in inflammatory conditions.

Despite its versatility, DG-HFUS has limitations that must be acknowledged. It lacks the ultra-high resolution of dermoscopes with super-resolution optics (up to ×400 magnification) and cannot resolve cellular-level structures as RCM or line-field confocal OCT can. Dedicated 70–100 MHz ultra-high ultrasound systems also offer finer resolution for subepidermal detail and can detect earlier alterations at the resolution of the lower magnification of histology. Therefore, DG-HFUS should not be viewed as a replacement for these high-end modalities in applications where microscopic precision is essential. Another point is the limitation of DG-HFUS in lesions that are larger than the field of view, which requires panoramic software available in high-end ultrasound machines. Furthermore, the system’s axial and lateral resolution restricts reliable visualization of only thicker hair follicles, whereas finer hairs often remain below the detectable threshold. Finally, the present work is primarily descriptive and was not designed or powered for robust statistical comparisons, which we acknowledge as an important limitation to be addressed in future, hypothesis-driven studies.

Rather, its strength lies in providing an optimal balance between diagnostic capability, usability, and cost-effectiveness. Its handheld design, real-time coregistration, and ability to bridge surface and subsurface imaging make it an invaluable tool in clinical dermatology, particularly in settings where space, cost, or time constraints preclude the use of larger imaging systems.

Moreover, with the rapid growth of image recognition with artificial intelligence (Boostani et al, 2025a, 2025b, 2025c, 2025d), artificial intelligence–based automated diagnosis could further enhance the potential utility in primary care settings for general practitioners. Multicenter prospective trials and longitudinal monitoring studies are also essential to further validate its accuracy in tumor margin delineation, treatment response evaluation, and real-time clinical decision making.

DG-HFUS offers a practical, portable, and cost-effective solution for simultaneous surface and subsurface in vivo dermatologic imaging. Although not a substitute for ultra-high-resolution modalities, DG-HFUS bridges a critical diagnostic gap, supporting improved clinical decision making and expanding access to advanced imaging in routine dermatology.

Materials and Methods

Technical overview of the DG-HFUS system

The DG-HFUS system is a commercially available device (Skinscanner, Dermus, Budapest, Hungary). The system was developed as a portable multimodal imaging tool capable of integrating clinical surface and subsurface skin assessment in real time. The device weighs approximately 220 g, has an ergonomic handheld design, and can be used in outpatient or bedside settings without specialized training (Figure 6). Its size allows scanning across various anatomical regions, including sites with complex contours such as behind the ears or around the nose. The configuration enables relatively rapid image acquisition and requires minimal patient preparation.

Figure 6.

Figure 6

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Overview of the DG-HFUS design. This figure illustrates the design of the DG-HFUS (measurement values in mm). (a) A lateral view, showcasing the openable and closable silicon membrane, positioned in front of the water chamber. The magnetic attachment site for the smartphone is visible as well as the control panel. (b) The top view, where the magnetic phone attachment site is oriented towards the user, with the control panel and buttons positioned in front of them. (c) Bottom view, highlighting the silicon membrane covering the device and the examination window, which is placed on the lesion of interest for imaging. (d) Another bottom view, focusing on the USB-C ports of the device, one located at the bottom and the other at the side. DG-HFUS, dermoscopy-guided high-frequency ultrasound.

The DG-HFUS system is an integrated imaging unit that combines a dermoscopic optical module with a HFUS transducer (20–40 MHz). A smartphone attached to the top of the device serves as the control and display interface, with the option to connect to a desktop computer for extended viewing and analysis. The optical module includes a complementary metal-oxide-semiconductor sensor, magnifying lens, and light-emitting diode illumination, capturing high-resolution 2-dimensional surface images at approximately 75 pixels/mm over a 15-mm field of view. Simultaneously, a piezoelectric transducer mounted on a motorized linear stage acquires cross-sectional ultrasound images (12 × 12 mm) by moving in a controlled X–Z plane trajectory, as shown in Figure 7. An optically transparent 45° beam splitter directs both light and acoustic waves for coregistered imaging, with their imaging planes arranged orthogonally. A water-filled chamber sealed with a silicon membrane enables efficient ultrasound coupling. The system operates within a frequency range of 20–40 MHz, achieving an axial resolution of 100 μm, a lateral resolution of 300 μm, and a maximum imaging depth of 10 mm. This balance of resolution and penetration allows detailed visualization of both superficial and deep skin structures. Real-time coregistration of dermoscopic and ultrasound data is achieved through synchronized acquisition using millisecond-level timestamping, ensuring spatial alignment between modalities. The imaging frame rate of 4–5 frames per second supports dynamic scanning during patient evaluations. Users can adjust optical shutter times and ultrasound colormapping parameters through the interface to optimize visualization for different skin tones and lesion types.

Figure 7.

Figure 7

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Schematic of the DG-HFUS system. (a) External view of the handheld imaging probe, highlighting the position of the imaging window. (b) Cross-sectional schematic of the internal components. The optical path (blue) transmits light from the LED source in the optical module through a beam splitter to the optical camera sensor for surface imaging. The acoustic path (red) originates from the single-element transducer and passes perpendicularly through the beam splitter and a water tank, which is sealed by a silicon membrane to maintain contact with the skin without the need for gel. The integrated design enables simultaneous coregistered optical and acoustic imaging. Field of view: 12 × 12 mm for HFUS and 13 × 14 mm for optical imaging. (c) Rendered model of the finalized DG-HFUS probe, illustrating its ergonomic and compact form factor for point-of-care use. DG-HFUS, dermoscopy-guided high-frequency ultrasound; FOV, field of view; HFUS, high-frequency ultrasound.

To enhance image quality, the DG-HFUS system incorporates advanced signal processing algorithms, including finite impulse response filtering and selective averaging of signal envelopes. These techniques reduce high-frequency noise and imaging artifacts while preserving anatomical detail and maintaining system stability. An integrated artificial intelligence–based segmentation module supports real-time delineation of anatomical layers and pathological features. Trained convolutional neural networks automatically identify and color code the epidermis; dermis; subcutis; and common abnormalities such as nodules, tumors, or fluid-filled cavities. This feature improves diagnostic consistency by reducing interobserver variability and streamlining clinical interpretation.

Clinical study subjects

To evaluate the clinical utility of the DG-HFUS system across a range of dermatologic conditions, a total of 130 skin lesions from 122 patients were imaged in vivo between November 2, 2021 and January 21, 2025 at the Department of Dermatology, Venereology, and Dermatooncology at Semmelweis University, Université Libre de Bruxelles, and Universidad de Barcelona. The study population had a mean age of 56 ± 16.2 years and consisted of 54% female and 46% male participants. DG-HFUS imaging was performed on 40 histopathologically confirmed BCCs from 40 patients, 15 squamous cell carcinomas from 15 patients, and 40 melanomas from 40 patients. Inflammatory skin conditions were also included, with 15 affected regions scanned from 8 patients diagnosed with HS and 10 areas from 9 patients diagnosed with psoriasis. To establish baseline references for normal skin anatomy, adjacent healthy skin from 1 patient, imaged within the surgical safety margins during BCC resection, was also scanned in vivo and later analyzed ex vivo. This allowed validation of the DG-HFUS system’s ability to detect and coregister normal anatomical features.

All participants provided informed consent, and inclusion criteria mandated the availability of a standardized diagnostic reference. Histopathologic biopsy served as the gold standard for skin cancer diagnoses, whereas performance in inflammatory conditions was assessed using dermatologic clinical examinations and validated clinical scoring systems (Zouboulis et al, 2017, 2015). Lesions in anatomically challenging regions, such as the eyelids, eyebrows, ears, or near the nasal folds, were excluded if their curvature hindered appropriate probe placement. In addition, lesions on bleeding, purulent, or otherwise compromised skin surfaces were excluded to ensure imaging accuracy and patient safety.

Ethics Statement

This study was reviewed and approved by Semmelweis University Regional and Institutional Committee of Science and Research Ethics (SE RKEB) (approval number 16/2022). All procedures were conducted in accordance with applicable guidelines and regulations and the principles of the Declaration of Helsinki. Written, informed consent was obtained from all participants prior to imaging. Written, informed consent for publication of clinical photographs/dermoscopic images and associated clinical information (in print and online) was obtained from all participants (or from a parent/legal guardian when applicable), with the understanding that the published material may be publicly accessible.

Data Availability Statement

No public dataset is available. Data and analyses are available on reasonable request to the corresponding author.

ORCIDs

Mehdi Boostani: http://orcid.org/0000-0001-9728-1117

Ximena Wortsman: http://orcid.org/0000-0003-3359-5023

Giovanni Pellacani: http://orcid.org/0000-0002-7222-2951

Krisztián Füzesi: http://orcid.org/0009-0002-3838-3396

Mariano Suppa: http://orcid.org/0000-0002-9266-0342

Veronique Del Marmol: http://orcid.org/0000-0002-4359-0667

Florencia Vera Morandini: http://orcid.org/0009-0009-0672-0010

Javiera Pérez-Anker: http://orcid.org/0000-0002-6959-7250

Priscila Giavedoni: http://orcid.org/0000-0002-1474-9261

Carmen Cantisani: http://orcid.org/0000-0003-2181-951X

Lucas Boussingault: http://orcid.org/0009-0003-3582-7681

Miklós Gyöngy: http://orcid.org/0000-0003-1356-2697

Gyorgy Paragh: http://orcid.org/0000-0002-6612-9267

Kamran Avanaki: http://orcid.org/0000-0002-1437-8456

Norbert Kiss: http://orcid.org/0000-0002-9947-1755

Conflict of Interest

XW reports royalties from Springer Books, medical writing support from Novartis (unpaid to her); honoraria for lectures from Novartis and UCB; consulting fees from Galderma; and unpaid participation in the editorial board of the Journal of Ultrasound in Medicine, Journal of the American Academy of Dermatology International, and Skin Research and Technology. MG (chief executive officer) and KF (hardware lead) are employees of Dermus, the manufacturer of the dermoscopy-guided high-frequency ultrasound device used in this study. Their involvement in this work was strictly limited to providing technical information about the dermoscopy-guided high-frequency ultrasound system and verifying the accuracy of its technical details. They had no role whatsoever in the design of the study, the analysis or interpretation of data, or the writing of the manuscript. Importantly, they did not offer suggestions or influence the content in any way. Their only engagement with the manuscript was reviewing the final version solely to confirm the accuracy of technical descriptions related to the dermoscopy-guided high-frequency ultrasound device. The remaining authors state no conflict of interest.

Acknowledgments

This work was supported by the 2024-2.1.2-EKÖP-KDP-2024-00002 and EKÖP-2024-174 New National Excellence Program of the Ministry for Culture and Innovation from the source of the National Research, Development and Innovation Fund and the Roswell Park Alliance Foundation. Project number 2020-1.1.5-GYORSÍTÓSÁV-2021-00015 has been implemented with the support provided by the Ministry of Culture and Innovation of Hungary from the National Research, Development and Innovation Fund, financed under the 2020-1.1.5-GYORSÍTÓSÁV funding scheme. NK is the guarantor for this work.

Author Contributions

Conceptualization: MB, NK; Data Curation: MB, LB, FVM; Formal Analysis: MB; Investigation: MB, KA, NK; Methodology: MB, KA, NK; Supervision: KA, NK; Writing - Original Draft Preparation: MB, KA; Writing - Review and Editing: MB, XW, GPe, KF, MS, VDM, FVM, JP-A, PG, CC, LB, MG, GPa, KA, NK

Declaration Of Generative Artificial Intelligence (AI) or Large Language Models (LLMs)

The author(s) did not use AI/LLM in any part of the research process and/or manuscript preparation.

accepted manuscript published online XXX; corrected proof published online XXX

Footnotes

Cite this article as: JID Innovations 2025.100446

Contributor Information

Kamran Avanaki, Email: avanaki@uic.edu.

Norbert Kiss, Email: kiss.norbert@semmelweis.hu.

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Data Availability Statement

No public dataset is available. Data and analyses are available on reasonable request to the corresponding author.

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