Intended use or purpose
Intended use
The device is a computational software-only medical device intended to support health care providers in the assessment of skin structures, enhancing efficiency and accuracy of care delivery, by providing:
- quantification of intensity, count, extent of visible clinical signs
- interpretative distribution representation of possible International Classification of Diseases (ICD) classes.
Quantification of intensity, count and extent of visible clinical signs
The device provides quantifiable data on the intensity, count and extent of clinical signs such as erythema, desquamation, and induration, among others; including, but not limited to:
- erythema,
- desquamation,
- induration,
- crusting,
- dryness,
- oedema,
- oozing,
- excoriation,
- swelling,
- lichenification,
- exudation,
- depth,
- edges,
- undermining,
- pustulation,
- hair density,
- type of necrotic tissue,
- amount of necrotic tissue,
- type of exudate,
- peripheral tissue edema,
- peripheral tissue induration,
- granulation tissue,
- epithelialization,
- nodule count,
- papule count,
- pustule count,
- cyst count,
- comedone count,
- abscess count,
- draining tunnel count,
- lesion count
Image-based recognition of visible ICD classes
The device is intended to provide an interpretative distribution representation of possible International Classification of Diseases (ICD) classes that might be represented in the pixel content of the image
Device description
The device is computational software-only medical device leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures. Its principal function is to provide a wide range of clinical data from the analyzed images to assist healthcare practitioners in their clinical evaluations and allow healthcare provider organisations to gather data and improve their workflows.
The generated data is intended to aid healthcare practitioners and organizations in their clinical decision-making process, thus enhancing the efficiency and accuracy of care delivery.
The device should never be used to confirm a clinical diagnosis. On the contrary, its result is one element of the overall clinical assessment. Indeed, the device is designed to be used when a healthcare practitioner chooses to obtain additional information to consider a decision.
Intended medical indication
The device is indicated for use on images of visible skin structure abnormalities to support the assessment of all diseases of the skin incorporating conditions affecting the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis).
Patient population
The device is intended for use on images of skin from patients presenting visible skin structure abnormalities, across all age groups, skin types, and demographics.
Intended user
The medical device is intended for use by healthcare providers to aid in the assessment of skin structures.
User qualification and competencies
In this section we specificy the specific qualifications and competencies needed for users of the device, to properly use the device, provided that they already belong to their professional category. In other words, when describing the qualifications of HCPs, it is assumed that healthcare professionals (HCPs) already have the qualifications and competencies native to their profession.
Healthcare professionals
No official qualifications are needes, but it is advisable if HCPs have some competencies:
- Knowledge on how to take images with smartphones.
IT professionals
IT professionals are responsible for the integration of the medical device into the healthcare organisation's system.
No specific official qualifications are needed, but it is advisable that IT professionals using the device have some competencies:
- Basic knowledge of FHIR
- Understanding of the output of the device.
Use environment
The device is intended to be used in the setting of healthcare organisations and their IT departments, which commonly are situated inside hospitals or other clinical facilities.
The device is intended to be integrated into the healthcare organisation's system by IT professionals.
Operating principles
The device is computational medical tool leveraging computer vision algorithms to process images of the epidermis, the dermis and its appendages, among other skin structures.
Body structures
The device is intended to use on images of the epidermis, its appendages (hair, hair follicle, sebaceous glands, apocrine sweat gland apparatus, eccrine sweat gland apparatus and nails) and associated mucous membranes (conjunctival, oral and genital), the dermis, the cutaneous vasculature and the subcutaneous tissue (subcutis).
In fact, the device is intended to use on visible skin structures. As such, it can only quantify clinical signs that are visible, and distribute the probabilities across ICD classes that are visible.
Explainability
For visual signs that can be quantified in terms of count and extent, the underlying models not only calculate a final value, such as the number of lesions, but also determine their locations within the image. Consequently, the output for these visual signs is accompanied by additional data, which varies depending on whether the quantification involves count or extent.
- Count. When a visual sign is quantifyed by counting, the device generates bounding boxes for each detected entity. These bounding boxes are defined by their x and y coordinates, as well as their height and width in pixels.
- Extent. When a visual sign is quantifyed by its extent, the device outputs a mask. This mask, which is the same size as the image, consists of 0's for pixels where the visual sign is absent and 1's for pixels where it is present.
The explainability output can be found with the explainabilityMedia
key. Here is an example:
"explainabilityMedia": {
"explainabilityMedia": {
"content": "base 64 image",
"detections": [
{
"confidence": 98,
"label": "nodule",
"p1": {
"x": 202,
"y": 101
},
"p2": {
"x": 252,
"y": 154
}
},
{
"confidence": 92,
"label": "pustule",
"p1": {
"x": 130,
"y": 194
},
"p2": {
"x": 179,
"y": 245
}
}
]
}
}