Epidermolysis bullosa - How does remote wound care in rare skin diseases work?

Epidermolysis bullosa - How does remote wound care in rare skin diseases work?

Author

Epidermolysis Bullosa (EB) is a group of rare diseases affecting about 1 in 50,000 births (Fine, 2010) and is represented by fragile, blistering skin with a compromised wound healing process.

Children living with Epidermolysis Bullosa are also known as "Butterfly Children", comparing the fragility of the skin with that of butterfly wings. Patients with severe EB show a lower life expectancy, partially because of the increased susceptibility to skin cancer and complications due to the delayed healing of wounds. Besides surgical and psychological care, regular checkups, pain, and wound management are essential parts of therapy to improve patients' quality of life.

Wound care has become increasingly important given the rise of dermatological disorders causing wounds and lesions on the skin surface. Medical professionals are in need of an innovative tool for the accurate documentation and assessment of the severity and manifestation of EB as well as a technology allowing high quality remote wound care. The use of digital health medical devices enables healthcare service providers to improve patient management processes through remote monitoring and follow-ups, ensuring the continuity of access to day-to-day care.

In this context, SCARLETRED, an Austrian digital health company, has developed a novel solution, Scarletred®Vision, for the standardized documentation, assessment, quantification, and analysis of conditions ranging from dermatological indications to drug reactions to fungal conditions.

Scarletred®Vision is a CE certified Class I Medical Device, the system is ICH-GCP, GDPR- and HIPAA-compliant and is a certified ISO-13485 Quality Management System. It is used in a wide variety of settings, including clinical trials (preclinical to phase IV), routine clinical work, hospital care as well as remote monitoring of patients. Scarletred®Vision’s scalability allows doctors to easily empower their subjects to participate and provide valuable data remotely, from the comfort of their home. 


How does Scarletred®Vision work?

Scarletred®Vision consists of the following components:

Mobile App: generation of high-quality images in conformity with data protection regulations and patient anonymity

QR-Code: information that could be used to identify study participants is not stored (e.g. name, date of birth, etc.); each patient is assigned an anonymized QR-code

Skin Patches: calibration for color, lighting conditions, and size/distance of the captured images

Online Platform: documentation, data management, analytical assessment, and quantification of patient data

 

Scarletred®Vision Mobile App

Imaging and Documentation

Step 1: Place the Skin Patch on the healthy skin next to the area of interest.

Step 2: Take an image using the Mobile App, which is then automatically uploaded to the secure online platform.

Step 3: The analysis can be performed on the Online Platform, which offers analytical- and AI-powered tissue classification tools to assist medical professionals.

Step 4 (Optional): electronic Patient Reported Outcomes (ePROs) and questionnaires can be customized according to the physician's or study requirements and configured to appear after the image has been taken (Figure 1). The answers and the resulting scores are documented centrally on the platform together with the corresponding EB image. 

Figure 1. Scarletred®Vision in-app QoLEB. The ePROs can be customized and configured to appear automatically at specific timepoints, as per clinician/study requirements. In this example, the Epidermolysis Bullosa specific Quality of Life (QoLEB) has been configured to appear after an image of the area of interest has been captured.


Scarletred®Vision Online Platform

Documentation and Measurement

Images generated by the Scarletred®Vision mobile app are automatically uploaded to the online platform, which can be used for documentation and image analysis. 

SCARLETRED has developed the distinguished Standard Erythema Value (SEV*), which augments the visualization of erythema through pseudo-signal maps with adjustable signal intensities- it highlights erythema using easily distinguishable colors, while taking into account the native skin color of the patient (Figure 2). The customizable tools on the platform enable the standardized assessment and quantification in additional signal maps, each highlighting a specific parameter: redness (+a*), yellowness (+b*), and lightness (L*) (Figure 3).

Combined with the customizable analytical tools, the online platform allows experts to quantify specific parameters and to remotely and objectively monitor, assess, and quantify the severity and progression of EB over time.

Epidermolysis bullosa wound original and SEV image on the ScarletredVision platform

Documentation overview of an epidermolysis bullosa wound on the ScarletredVision online platform
Figure 3. Documentation on the Scarletred®Vision Online Platform: Detailed overview of a patient's wound. All relevant information is displayed next to the wound image, including the data/time stamp, notes by the doctor (e.g. concomitant medication, psychological state, etc.), the imaged body region (useful for data management), wound score (a variety of scoring methods can be configured) as well as in-app questionnaires/ePRO results (e.g. QoLEB, and other customizable ePROs). If desired, the analytical tools can also be embedded here. The image is depicted in the Scarletred®Vision's distinguished Standard Erythema Value (SEV*), which augments the visualization of erythema while taking the native skin color into account. Not depicted in this figure, yet available as additional visualization tools are the following pseudo-signal maps; redness (+a*), lightness (L*), yellowness (+b*), Individual Typology Angle (ITA°), and Skin Texture (Txr).

AI-Powered Classification Tool

Scarletred®Vision offers an AI-powered classification tool which allows the automatic classification and quantification of areas with minimal input by the expert, resulting in a highly efficient, effective, and precise data analysis. After the selection of a few (3-4) representative areas for each of the tissue types, the algorithm automatically classifies the entire selected area according to the expert's initial input. The resulting classification and quantification, which can be repeated on multiple images over time, allow doctors to closely follow the progression of the different tissue types during a treatment plan. In the case of Epidermolysis Bullosa, the tissue classes are defined as epithelial, necrotic, induration, and granulation (Figure 4). However, the tissue classes can be defined as per clinician or study requirements.

The better the user teaches the program (i.e. the better the initial selection of representative areas are), the better the AI can be trained to differentiate between the configured EB tissue types. 

Tissue lassification results shown on the Scarletred Vision platform for an epidermolysis bullosa patient
Figure 4. Classification results on the Scarletred®Vision Platform. After the selection of the area of interest (AOI) and some representative areas of each tissue type, the AI will present the percentages of the different tissue types in relation to the entire selected area. For this EB wound, the percentages of epithelial, necrotic cells as well as induration and granulation are listed in the middle panel. In the lower panel, the software also measures the mean values of erythema (SEV*), redness (+a*), lightness (L*) and yellowness (+b*) for the classified tissue types.


Skin Texture Analysis

The determination of skin texture is of particular importance in dermatology as such measurements can be used for skin diagnosis and for the evaluation of therapeutic treatments. Furthermore, it offers valuable insight for doctors in addition to the wound scores and the measurement of other important metrics, such as surface area and erythema. Skin texture refers to visual patterns or spatial arrangement of pixels which cannot be efficiently described and measured by regional color and intensity. SCARLETRED tackled this issue and developed a tool that analyzes and quantifies skin texture alterations (Figure 5).

The tool takes numerous metrics into consideration, including energy, contrast, and entropy. In addition, the algorithm scans the image(s) and the resulting values indicate the homogeneity and smoothness of the skin.

Skin texture analysis combined with the quantification of erythema, surface area measurement, and other centralized assessments on the Scarletred®Vision online platform, render the medical device a powerful tool giving experts a complete and thorough overview on the patient progression over time.

Skin texture analysis result on the ScarletredVision online platform for an epidermolysis bullosa patient
Figure 5. Skin texture analysis on the Scarletred®Vision platform. After the global reference area (healthy skin) and the AOI have been selected, the measurement results with all the corresponding information, such as date and time stamp, notes by the doctor, a body tag of the imaged area, score for severity assessment, and in-app questionnaire results are summarized next to the image. The platform presents the skin texture analysis results in the form of values assigned for energy, contrast, entropy, homogeneity, and overall smoothness. In this example, the algorithm classified the skin's smoothness at 23.0% and detected higher heterogeneity in skin texture in areas with induration.


Scarletred®Vision’s innovative approach to creating digital solutions is the first of its kind. Its modular framework makes it applicable to all skin conditions (dermatological diseases, injection sites, drug reactions, allergic reactions, cosmeceuticals and many more). The certified Medical Device offers digital documentation and analytical tools that have been proven, both in the clinical and home-based settings, to increase data quality, enable doctors to quantify visual parameters, to improve patient treatment regimen and patient compliance, save doctors time, and generate analyses that are not obtainable with other technologies in the field.

Don’t be a stranger!  Get in touch with our Team so that we can discuss how to best tailor our solution to fit your needs: support@scarletred.com. 


Like the article? Spread the word

linkedin-icon