A novel multi-task learning network for skin lesion classification based on multi-modal clues and label-level fusion.

In this paper, we propose a multi-task learning (MTL) network based on the label-level fusion of metadata and hand-crafted features by unsupervised clustering to generate new clustering labels as an optimization goal. We propose a MTL module (MTLM) that incorporates an attention mechanism to enable the model to learn more integrated, variable information. We propose a dynamic strategy to adjust the loss weights of different tasks, and trade off the contributions of multiple branches. Instead of feature-level fusion, we propose label-level fusion and combine the results of our proposed MTLM with the results of the image classification network to achieve better lesion prediction on multiple dermatological datasets. We verify the effectiveness of the proposed model by quantitative and qualitative measures. The MTL network using multi-modal clues and label-level fusion can yield the significant performance improvement for skin lesion classification.

Quantifying Bone and Skin Movement in the Residual Limb-Socket Interface of Individuals With Transtibial Limb Loss Using Dynamic Stereo X-Ray: Protocol for a Lower Limb Loss Cadaver and Clinical Study.

BACKGROUND: Relative motion between the residual limb and socket in individuals with transtibial limb loss can lead to substantial consequences that limit mobility. Although assessments of the relative motion between the residual limb and socket have been performed, there remains a substantial gap in understanding the complex mechanics of the residual limb-socket interface during dynamic activities that limits the ability to improve socket design. However, dynamic stereo x-ray (DSX) is an advanced imaging technology that can quantify 3D bone movement and skin deformation inside a socket during dynamic activities. OBJECTIVE: This study aims to develop analytical tools using DSX to quantify the dynamic, in vivo kinematics between the residual limb and socket and the mechanism of residual tissue deformation. METHODS: A lower limb cadaver study will first be performed to optimize the placement of an array of radiopaque beads and markers on the socket, liner, and skin to simultaneously assess dynamic tibial movement and residual tissue and liner deformation. Five cadaver limbs will be used in an iterative process to develop an optimal marker setup. Stance phase gait will be simulated during each session to induce bone movement and skin and liner deformation. The number, shape, size, and placement of each marker will be evaluated after each session to refine the marker set. Once an optimal marker setup is identified, 21 participants with transtibial limb loss will be fitted with a socket capable of being suspended via both elevated vacuum and traditional suction. Participants will undergo a 4-week acclimation period and then be tested in the DSX system to track tibial, skin, and liner motion under both suspension techniques during 3 activities: treadmill walking at a self-selected speed, at a walking speed 10% faster, and during a step-down movement. The performance of the 2 suspension techniques will be evaluated by quantifying the 3D bone movement of the residual tibia with respect to the socket and quantifying liner and skin deformation at the socket-residuum interface. RESULTS: This study was funded in October 2021. Cadaver testing began in January 2023. Enrollment began in February 2024. Data collection is expected to conclude in December 2025. The initial dissemination of results is expected in November 2026. CONCLUSIONS: The successful completion of this study will help develop analytical methods for the accurate assessment of residual limb-socket motion. The results will significantly advance the understanding of the complex biomechanical interactions between the residual limb and the socket, which can aid in evidence-based clinical practice and socket prescription guidelines. This critical foundational information can aid in the development of future socket technology that has the potential to reduce secondary comorbidities that result from complications of poor prosthesis load transmission. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID): DERR1-10.2196/57329.

An evaluation of the effectiveness of 'ULTRACOL 200' in enhancing nasolabial fold wrinkles through cutaneous repair.

BACKGROUND: Injectable filler, a nonsurgical beauty method, has gained popularity in rejuvenating sagging skin. In this study, polydioxanone (PDO) was utilized as the main component of the ULTRACOL200 filler that helps stimulate collagenesis and provide skin radiant effects. The study aimed to evaluate and compare the effectiveness of ULTRACOL200 with other commercialized products in visually improving dermatological problems. METHODS: Herein, 31 participants aged between 20 and 59 years were enrolled in the study. 1 mL of the testing product, as well as the quantity for the compared groups was injected into each participants face side individually. Subsequently, skin texture and sunken volume of skin were measured using ANTERA 3D CS imaging technology at three periods: before the application, 4 weeks after the initial application, and 4 weeks after the 2nd application of ULTRACOL200. RESULTS: The final results of skin texture and wrinkle volume evaluation consistently demonstrated significant enhancement. Consequently, subjective questionnaires were provided to the participants to evaluate the efficacy of the testing product, illustrating satisfactory responses after the twice applications. CONCLUSION: The investigation has contributed substantially to the comprehension of a PDO-based filler (ULTRACOL200) for skin enhancement and provided profound insight for future clinical trials.

A novel SpaSA based hyper-parameter optimized FCEDN with adaptive CNN classification for skin cancer detection.

Skin cancer is the most prevalent kind of cancer in people. It is estimated that more than 1 million people get skin cancer every year in the world. The effectiveness of the disease's therapy is significantly impacted by early identification of this illness. Preprocessing is the initial detecting stage in enhancing the quality of skin images by removing undesired background noise and objects. This study aims is to compile preprocessing techniques for skin cancer imaging that are currently accessible. Researchers looking into automated skin cancer diagnosis might use this article as an excellent place to start. The fully convolutional encoder-decoder network and Sparrow search algorithm (FCEDN-SpaSA) are proposed in this study for the segmentation of dermoscopic images. The individual wolf method and the ensemble ghosting technique are integrated to generate a neighbour-based search strategy in SpaSA for stressing the correct balance between navigation and exploitation. The classification procedure is accomplished by using an adaptive CNN technique to discriminate between normal skin and malignant skin lesions suggestive of disease. Our method provides classification accuracies comparable to commonly used incremental learning techniques while using less energy, storage space, memory access, and training time (only network updates with new training samples, no network sharing). In a simulation, the segmentation performance of the proposed technique on the ISBI 2017, ISIC 2018, and PH2 datasets reached accuracies of 95.28%, 95.89%, 92.70%, and 98.78%, respectively, on the same dataset and assessed the classification performance. It is accurate 91.67% of the time. The efficiency of the suggested strategy is demonstrated through comparisons with cutting-edge methodologies.

Mapping cutaneous field carcinogenesis of nonmelanoma skin cancer using mesoscopic imaging of pro-inflammation cues.

Nonmelanoma skin cancers remain the most widely diagnosed types of cancers globally. Thus, for optimal patient management, it has become imperative that we focus our efforts on the detection and monitoring of cutaneous field carcinogenesis. The concept of field cancerization (or field carcinogenesis), introduced by Slaughter in 1953 in the context of oral cancer, suggests that invasive cancer may emerge from a molecularly and genetically altered field affecting a substantial area of underlying tissue including the skin. A carcinogenic field alteration, present in precancerous tissue over a relatively large area, is not easily detected by routine visualization. Conventional dermoscopy and microscopy imaging are often limited in assessing the entire carcinogenic landscape. Recent efforts have suggested the use of noninvasive mesoscopic (between microscopic and macroscopic) optical imaging methods that can detect chronic inflammatory features to identify pre-cancerous and cancerous angiogenic changes in tissue microenvironments. This concise review covers major types of mesoscopic optical imaging modalities capable of assessing pro-inflammatory cues by quantifying blood haemoglobin parameters and hemodynamics. Importantly, these imaging modalities demonstrate the ability to detect angiogenesis and inflammation associated with actinically damaged skin. Representative experimental preclinical and human clinical studies using these imaging methods provide biological and clinical relevance to cutaneous field carcinogenesis in altered tissue microenvironments in the apparently normal epidermis and dermis. Overall, mesoscopic optical imaging modalities assessing chronic inflammatory hyperemia can enhance the understanding of cutaneous field carcinogenesis, offer a window of intervention and monitoring for actinic keratoses and nonmelanoma skin cancers and maximise currently available treatment options.

Parameter-based transfer learning for severity classification of atopic dermatitis using hyperspectral imaging.

BACKGROUND/PURPOSE: Because atopic dermatitis (AD) is a chronic inflammatory skin condition that causes structural changes, there is a growing need for noninvasive research methods to evaluate this condition. Hyperspectral imaging (HSI) captures skin structure features by exploiting light wavelength variations in penetration depth. In this study, parameter-based transfer learning was deployed to classify the severity of AD using HSI. Therefore, we aimed to obtain an optimal combination of classification results from the four models after constructing different source- and target-domain datasets. METHODS: We designated psoriasis, skin cancer, eczema, and AD datasets as the source datasets, and the set of images acquired via hyperspectral camera as the target dataset for wavelength-specific AD classification. We compared the severity classification performances of 96 combinations of sources, models, and targets. RESULTS: The highest classification performance of 83% was achieved when ResNet50 was trained on the augmented psoriasis dataset as the source, with the resulting parameters used to train the model on the target Near-infrared radiation (NIR) dataset. The second highest classification accuracy of 81% was achieved when ResNet50 was trained on the unaugmented psoriasis dataset as the source, with the resulting parameters used to train the model on the target R dataset. ResNet50 demonstrated potential as a generalized model for both the source and target data, also confirming that the psoriasis dataset is an effective training resource. CONCLUSION: The present study not only demonstrates the feasibility of the severity classification of AD based on hyperspectral images, but also showcases combinations and research scalability for domain exploration.

Hydradermabrasion through the lens of Line-Field Confocal Optical Coherence Tomography.

BACKGROUND: Hydradermabrasion, also known as "HydraFacial," is an exfoliative cosmetic procedure for skin rejuvenation that has gained popularity. Despite its increasing popularity, clinical studies validating its efficacy with non-invasive assessment of histological changes to the skin, are scarce. In this study, we used Line-Field Confocal Optical Coherence Tomography (LC-OCT), an optical imaging device, to non-invasively visualize microscopic changes to skin anatomy after hydradermabrasion treatment. MATERIALS/METHODS: Eight volunteers (Fitzpatrick skin types II-V) were recruited for this study. Images, using LC-OCT (DeepLive, DAMAE medical) were obtained before and after hydradermabrasion and at 2 weeks post-treatment. A commercially available hydradermabrasion device was utilized to perform the dermabrasion. RESULTS: In the epidermis, initially, a decrease in the average thickness of the stratum corneum, from 9.42 to 6.67 µm was visualized in LC-OCT images after hydradermabrasion. However, at 2 weeks of follow-up, the average stratum corneum thickness was 9.75 µm, resulting in an overall increase in the average thickness after treatment. Improved homogenization of the stratum corneum and decreased number of undulations in the epidermis post-treatment were also visualized. In all the subjects, the superficial dermis appeared stretched, which returned to baseline by the 2-week follow-up. At the 2-week follow-up, there were no visible differences in the quality and quantity of collagen fibers in the dermis. CONCLUSION: In our study, LC-OCT images of the epidermis and dermis demonstrated microscopic features of skin rejuvenation when treated with hydradermabrasion. Thus, not only highlighting the efficacy of hydradermabrasion but also the potential of LC-OCT to serve as a tool for visualizing the microscopic effects of cosmetic procedures on skin anatomy.

Multi-frequency spatial frequency domain imaging: a depth-resolved optical scattering model to isolate scattering contrast in thin layers of skin.

Significance: Current methods for wound healing assessment rely on visual inspection, which gives qualitative information. Optical methods allow for quantitative non-invasive measurements of optical properties relevant to wound healing. Aim: Spatial frequency domain imaging (SFDI) measures the absorption and reduced scattering coefficients of tissue. Typically, SFDI assumes homogeneous tissue; however, layered structures are present in skin. We evaluate a multi-frequency approach to process SFDI data that estimates depth-specific scattering over differing penetration depths. Approach: Multi-layer phantoms were manufactured to mimic wound healing scattering contrast in depth. An SFDI device imaged these phantoms and data were processed according to our multi-frequency approach. The depth sensitive data were then compared with a two-layer scattering model based on light fluence. Results: The measured scattering from the phantoms changed with spatial frequency as our two-layer model predicted. The performance of two δ-P1 models solutions for SFDI was consistently better than the standard diffusion approximation. Conclusions: We presented an approach to process SFDI data that returns depth-resolved scattering contrast. This method allows for the implementation of layered optical models that more accurately represent physiologic parameters in thin tissue structures as in wound healing.

Customizable Presentation Attack Detection for Improved Resilience of Biometric Applications Using Near-Infrared Skin Detection.

Due to their user-friendliness and reliability, biometric systems have taken a central role in everyday digital identity management for all kinds of private, financial and governmental applications with increasing security requirements. A central security aspect of unsupervised biometric authentication systems is the presentation attack detection (PAD) mechanism, which defines the robustness to fake or altered biometric features. Artifacts like photos, artificial fingers, face masks and fake iris contact lenses are a general security threat for all biometric modalities. The Biometric Evaluation Center of the Institute of Safety and Security Research (ISF) at the University of Applied Sciences Bonn-Rhein-Sieg has specialized in the development of a near-infrared (NIR)-based contact-less detection technology that can distinguish between human skin and most artifact materials. This technology is highly adaptable and has already been successfully integrated into fingerprint scanners, face recognition devices and hand vein scanners. In this work, we introduce a cutting-edge, miniaturized near-infrared presentation attack detection (NIR-PAD) device. It includes an innovative signal processing chain and an integrated distance measurement feature to boost both reliability and resilience. We detail the device's modular configuration and conceptual decisions, highlighting its suitability as a versatile platform for sensor fusion and seamless integration into future biometric systems. This paper elucidates the technological foundations and conceptual framework of the NIR-PAD reference platform, alongside an exploration of its potential applications and prospective enhancements.

A Protocol for the Automated Assessment of Cutaneous Pathology in a Mouse Model of Hemichannel Dysfunction.

In this chapter, we provide detailed instructions to perform quantitative reflectance imaging in a mouse model of a rare epidermal disorder caused by hyperactive connexin 26 hemichannels. Reflectance imaging is a versatile and powerful tool in dermatology, offering noninvasive, high-resolution insights into skin pathology, which is essential for both clinical practice and research. This approach offers several advantages and applications. Unlike traditional biopsy, reflectance imaging is noninvasive, allowing for real-time, in vivo examination of the skin. This is particularly valuable for monitoring chronic conditions or assessing the efficacy of treatments over time, enabling the detailed examination of skin morphology. This is crucial for identifying features of skin diseases such as cancers, inflammatory conditions, and infections. In therapeutic applications, reflectance imaging can be used to monitor the response of skin lesions to treatments. It can help in identifying the most representative area of a lesion for biopsy, thereby increasing the diagnostic accuracy. Reflectance imaging can also be used to diagnose and monitor inflammatory skin diseases, like psoriasis and eczema, by visualizing changes in skin structure and cellular infiltration. As the technology becomes more accessible, it has potential in telemedicine, allowing for remote diagnosis and monitoring of skin conditions. In academic settings, reflectance imaging can be a powerful research tool, enabling the study of skin pathology and the effects of novel treatments, including the development of monoclonal antibodies for therapeutic applications.

An overview of current assessment techniques for evaluating cutaneous perfusion in reconstructive surgery.

This article provides a comprehensive analysis of modern techniques used in the assessment of cutaneous flaps in reconstructive surgery. It emphasizes the importance of preoperative planning and intra- and perioperative assessment of flap perfusion to ensure successful outcomes. Despite technological advancements, direct clinical assessment remains the gold standard. We categorized assessment techniques into non-invasive and invasive modalities, discussing their strengths and weaknesses. Non-invasive methods, such as acoustic Doppler sonography, near-infrared spectroscopy, hyperspectral imaging thermal imaging, and remote-photoplethysmography, offer accessibility and safety but may sacrifice specificity. Invasive techniques, including contrast-enhanced ultrasound, computed tomography angiography, near-infrared fluorescence angiography with indocyanine green, and implantable Doppler probe, provide high accuracy but introduce additional risks. We emphasize the need for a tailored decision-making process based on specific clinical scenarios, patient characteristics, procedural requirements, and surgeon expertise. It also discusses potential future advancements in flap assessment, including the integration of artificial intelligence and emerging technologies.

Correlation analysis between texture features and elasticity of skin hyperspectral images in the near-infrared band.

BACKGROUND/PURPOSE: Skin elasticity was used to evaluate healthy and diseased skin. Correlation analysis between image texture characteristics and skin elasticity was performed to study the feasibility of assessing skin elasticity using a non-contact method. MATERIALS AND METHODS: Skin images in the near-infrared band were acquired using a hyperspectral camera, and skin elasticity was obtained using a skin elastimeter. Texture features of the mean, standard deviation, entropy, contrast, correlation, homogeneity, and energy were extracted from the acquired skin images, and a correlation analysis with skin elasticity was performed. RESULTS: The texture features, and skin elasticity of skin images in the near-infrared band had the highest correlation on the side of eye and under of arm, and the mean and correlation were features of texture suitable for distinguishing skin elasticity according to the body part. CONCLUSION: In this study, we performed elasticity and correlation analyses for various body parts using the texture characteristics of skin hyperspectral images in the near-infrared band, confirming a significant correlation in some body parts. It is expected that this will be used as a cornerstone of skin elasticity evaluation research using non-contact methods.

HDS-Net: Achieving fine-grained skin lesion segmentation using hybrid encoding and dynamic sparse attention.

Skin cancer is one of the most common malignant tumors worldwide, and early detection is crucial for improving its cure rate. In the field of medical imaging, accurate segmentation of lesion areas within skin images is essential for precise diagnosis and effective treatment. Due to the capacity of deep learning models to conduct adaptive feature learning through end-to-end training, they have been widely applied in medical image segmentation tasks. However, challenges such as boundary ambiguity between normal skin and lesion areas, significant variations in the size and shape of lesion areas, and different types of lesions in different samples pose significant obstacles to skin lesion segmentation. Therefore, this study introduces a novel network model called HDS-Net (Hybrid Dynamic Sparse Network), aiming to address the challenges of boundary ambiguity and variations in lesion areas in skin image segmentation. Specifically, the proposed hybrid encoder can effectively extract local feature information and integrate it with global features. Additionally, a dynamic sparse attention mechanism is introduced, mitigating the impact of irrelevant redundancies on segmentation performance by precisely controlling the sparsity ratio. Experimental results on multiple public datasets demonstrate a significant improvement in Dice coefficients, reaching 0.914, 0.857, and 0.898, respectively.

Variations of skin thermal diffusivity on different skin regions.

BACKGROUND AND OBJECTIVE: Skin thermal diffusivity plays a crucial role in various applications, including laser therapy and cryogenic skin cooling.This study investigates the correlation between skin thermal diffusivity and two important skin parameters, melanin content and erythema, in a cohort of 102 participants. METHODS: An in-house developed device based on transient temperature measurement was used to assess thermal diffusivity at different body locations. Melanin content and erythema were measured using a colorimeter. Statistical analysis was performed to examine potential correlations. RESULTS: The results showed that the measured thermal diffusivity values were consistent with previous reports, with variations observed among subjects. No significant correlation was found between thermal diffusivity and melanin content or erythema. This suggests that other factors, such as skin hydration or epidermis thickness, may have a more dominant influence on skin thermal properties. CONLCUSION: This research provides valuable insights into the complex interplay between skin thermal properties and physiological parameters, with potential implications for cosmetic and clinical dermatology applications.

The impact of skin color and tone on histamine iontophoresis and Doppler flowmetry measurements as a pharmacodynamic biomarker.

The phenotypical manifestations of asthma among children are diverse and exhibit varying responses to therapeutic interventions. There is a need to develop objective biomarkers to improve the characterization of allergic and inflammatory responses relevant to asthma to predict therapeutic treatment responses. We have previously investigated histamine iontophoresis with laser Doppler flowmetry (HILD) as a potential surrogate biomarker that characterizes histamine response and may be utilized to guide the treatment of allergic and inflammatory disease. We have identified intra-individual variability of HILD response type among children and adults with asthma and that HILD response type varied in association with racial classification. As laser Doppler flowimetry may be impacted by skin color, we aimed to further validate the HILD method by determining if skin color or tone is associated with observed HILD response type differences. We conducted an observational study utilizing quantification of skin color and tone obtained from photographs of the skin among participants during HILD assessments via the RGB color model. We compared RGB values across racial, ethnic, and HILD response type via the Kruskal-Wallis test and calculated Kendall rank correlation coefficient to evaluate the relationship between RGB composite scores and HILD pharmacodynamic measures. We observed that RGB scores differed among racial groups and histamine response phenotypes (p < 0.05). However, there was a lack of correlation between the RGB composite score and HILD pharmacodynamic measures (r values 0.1, p > 0.05). These findings suggest that skin color may not impact HILD response variations, necessitating further research to understand previously observed differences across identified racial groups.

Characterization of the collagen network of human cheek skin using ultrasonic microscopy.

Dermal collagen is the most abundant component of human skin and has a network structure that regulates the mechanical properties of the skin. Therefore, non-invasive characterization of the collagen network would be beneficial for the evaluation of skin conditions. The microscopic substructures of the network, which are individual bundles and fibers, have been optically investigated. However, the macroscopic structure of the collagen network has not been assessed. To evaluate the dermal collagen network, we developed two new indicators, volume filling factor (VFF) and collagen fiber texture (CFT), to analyze three-dimensional echo intensity maps of high-frequency ultrasonic microscopy. By identifying the difference in the elastic modulus components of the dermal layer of facial skin, the density and texture of the collagen network were characterized using VFF and CFT, respectively. These new indicators revealed that the density decreased and the texture became fine with facial age. This study demonstrates that ultrasonic microscopy is useful for investigating skin conditions, paving the way for diagnostic applications in dermatology and aesthetic medicine.

Microneedles: A novel clinical technology for evaluating skin characteristics.

BACKGROUND: Current methods for evaluating efficacy of cosmetics have limitations because they cannot accurately measure changes in the dermis. Skin sampling using microneedles allows identification of skin-type biomarkers, monitoring treatment for skin inflammatory diseases, and evaluating efficacy of anti-aging and anti-pigmentation products. MATERIALS AND METHODS: Two studies were conducted: First, 20 participants received anti-aging treatment; second, 20 participants received anti-pigmentation treatment. Non-invasive devices measured skin aging (using high-resolution 3D-imaging in the anti-aging study) or pigmentation (using spectrophotometry in the anti-pigmentation study) at weeks 0 and 4, and adverse skin reactions were monitored. Skin samples were collected with biocompatible microneedle patches. Changes in expression of biomarkers for skin aging and pigmentation were analyzed using qRT-PCR. RESULTS: No adverse events were reported. In the anti-aging study, after 4 weeks, skin roughness significantly improved in 17 out of 20 participants. qRT-PCR showed significantly increased expression of skin-aging related biomarkers: PINK1 in 16/20 participants, COL1A1 in 17/20 participants, and MSN in 16/20 participants. In the anti-pigmentation study, after 4 weeks, skin lightness significantly improved in 16/20 participants. qRT-PCR showed significantly increased expression of skin-pigmentation-related biomarkers: SOD1 in 15/20 participants and Vitamin D Receptor (VDR) in 15/20 participants. No significant change in TFAP2A was observed. CONCLUSION: Skin sampling and mRNA analysis for biomarkers provides a novel, objective, quantitative method for measuring changes in the dermis and evaluating the efficacy of cosmetics. This approach complements existing evaluation methods and has potential application in assessing the effectiveness of medical devices, medications, cosmeceuticals, healthy foods, and beauty devices.

A model that predicts a real-time tumour surface using intra-treatment skin surface and end-of-expiration and end-of-inhalation planning CT images.

OBJECTIVES: To develop a mapping model between skin surface motion and internal tumour motion and deformation using end-of-exhalation (EOE) and end-of-inhalation (EOI) 3D CT images for tracking lung tumours during respiration. METHODS: Before treatment, skin and tumour surfaces were segmented and reconstructed from the EOE and the EOI 3D CT images. A non-rigid registration algorithm was used to register the EOE skin and tumour surfaces to the EOI, resulting in a displacement vector field that was then used to construct a mapping model. During treatment, the EOE skin surface was registered to the real-time, yielding a real-time skin surface displacement vector field. Using the mapping model generated, the input of a real-time skin surface can be used to calculate the real-time tumour surface. The proposed method was validated with and without simulated noise on 4D CT images from 15 patients at Léon Bérard Cancer Center and the 4D-lung dataset. RESULTS: The average centre position error, dice similarity coefficient (DSC), 95%-Hausdorff distance and mean distance to agreement of the tumour surfaces were 1.29 mm, 0.924, 2.76 mm, and 1.13 mm without simulated noise, respectively. With simulated noise, these values were 1.33 mm, 0.920, 2.79 mm, and 1.15 mm, respectively. CONCLUSIONS: A patient-specific model was proposed and validated that was constructed using only EOE and EOI 3D CT images and real-time skin surface images to predict internal tumour motion and deformation during respiratory motion. ADVANCES IN KNOWLEDGE: The proposed method achieves comparable accuracy to state-of-the-art methods with fewer pre-treatment planning CT images, which holds potential for application in precise image-guided radiation therapy.

Transdermal drug delivery mediated by acoustic vortex beam.

Ultrasound-mediated transdermal drug delivery exhibits various advantages such as biocompatibility, controllability and safety, which attracts plenty of interests within biomedical field. Current researches mostly emphasizes the acoustic cavitation generated by planar or focused waves while neglecting other physics that occur during transportation. Our experimental study illustrates the presence of an acoustic vortex (AV) beam that exhibits a lower acoustic intensity and typically means a lower dose of inertial cavitation, yet achieves a more efficient delivery. Such a result calls for the fundamental mechanism of ultrasound-mediated transdermal transfer using the AV beam. In this work, according to our knowledge, the AV beam is firstly introduced to ultrasound-mediated transdermal medication delivery. The transversal acoustic radiation force (T-ARF), which is the primary characteristic carried by the acoustic vortex beam, and its contribution to the transport enhancement are investigated. It is shown that a focused AV (FAV) beam with a maximal acoustic pressure of 200 kPa induces a pN-level T-ARF, which promotes the enlargement of pores on the stratum corneum and thereby enhances the permeability, as compared with a zero-order (non-vortex) counterpart. This contribution of the T-ARF is validated by the experimental transport on the cellulose membrane, which exhibits a significantly increased membrane porosity and delivery efficiency. The favorable results introduce the new degree of freedom into the ultrasound-mediated transdermal drug transport based on AV beam, and thereby promotes the development of a combined control strategy for more precise and efficient transdermal drug delivery in conjunction with the administration of acoustic cavitation.

Hand-held electron spin resonance scanner for subcutaneous oximetry using OxyChip.

PURPOSE: Electron spin resonance (ESR) is used to measure oxygen partial pressure (pO2) in biological media with many clinical applications. Traditional clinical ESR involves large magnets that encompass the subject of measurement. However, certain applications might benefit from a scanner operating within local static magnetic fields. Our group recently developed such a compact scanner for transcutaneous (surface) pO2 measurements of skin tissue. Here we extend this capability to subsurface (subcutaneous) pO2 measurements and verify it using an artificial tissue emulating (ATE) phantom. METHODS: We introduce a new scanner, tailored for subcutaneous measurements up to 2 mm beneath the skin's surface. This scanner captures pulsed ESR signals from embedded approximate 1-mm oxygen-sensing solid paramagnetic implant, OxyChip. The scanner features a static magnetic field source, producing a uniform region outside its surface, and a compact microwave resonator, for exciting and receiving ESR signals. RESULTS: ESR readings derived from an OxyChip, positioned approximately 1.5 mm from the scanner's surface, embedded in ATE phantom, exhibited a linear relation of 1/T2 versus pO2 for pO2 levels at 0, 7.6, 30, and 160 mmHg, with relative reading accuracy of about 10%. CONCLUSION: The compact ESR scanner can report pO2 data in ATE phantom from an external position relative to the scanner. Implementing this scanner in preclinical and clinical applications for subcutaneous pO2 measurements is a feasible next phase for this development. This innovative design also has the potential to operate in conjunction with artificial skin graft for wound healing, combining therapeutic and pO2 diagnostic features.