APASI
What is APASI?
The Automatic Psoriasis Area and Surface Index (APASI) is the automated implementation of the most extensively employed scoring system for evaluating psoriasis severity in clinical trials. However, the complexity, substantial effort, and time demands associated with completing the assessment have led to the prevalent use of PASI in day-to-day practice. An additional constraint lies in the issue of inter-observer variability.
Addressing these challenges, APASI uses smartphone-captured images. The algorithm identifies the extent and intensity of visual signs such as erythema, induration, and desquamation, enabling the computation of the PASI score.
Body zones
The PASI defines 4 body zones:
- Head: scalp and neck.
- Upper Extremities: arms, hands, palms.
- Trunk: armpits, torso, and genitals.
- Lower Extremities: buttocks, legs, and feet.
Each body zone contributes a different percentage to the final score: head 10%, upper extremities 20%, trunk 30%, and lower extremities 40%.
Local APASI
The classic PASI is calculated with the patient in consultation, which means it is based on observation by the dermatologist. However, when it comes to clinical images taken with a smartphone, we rely on the photographer and the limitations of the capturing device.
The local APASI is calculated similarly to the PASI, but it is given for a single image. It is calculated using the intensity of the visual signs on a scale from 0 to 4 and the extent of the surface. By using an AI Marker, a colour sticker used for calibration and resolution measurement, a Body Surface Area (BSA) formula, and the percentage of the body zone, we can estimate the extent of the surface on that specific body zone.
General APASI
The general APASI is computed by adding multiple photos of the patient into the equation. Only photos of affected areas are required, and the procedure for acquisition is explained in the next section.
When several pictures of the same zone are captured (for example, right and left arms, both part of the upper extremities category), the maximum intensity is the one used for that zone. This follows the definition of the PASI, where a representative area of psoriasis is selected for each body region.
How to take pictures
Image quality affects algorithm performance. A guide with essential tips for image acquisition is available. This section is dedicated to the photo capture process for APASI computation.
How does APASI work?
APASI uses convolutional neural networks trained on a dataset comprising thousands of images annotated by experts.
Estimating Body Surface Area (BSA)
The extent of psoriasis-affected skin is assessed across four distinct body regions. Within each region, the affected area is classified into categories: absent (0), 1-9% (score 1), 10-29% (score 2), 30-49% (score 3), 50-69% (score 4), 70-89% (score 5), or 90-100% (score 6). APASI employs pixel-level detection to ascertain disease extent, leverages the calibration marker to derive surface measurements in square centimetres, and employs a formula for estimating overall body surface area, thereby determining the percentage of the body affected.
Assessing Visual Sign Intensity
The algorithm quantifies the intensity of psoriasis characteristics (redness, thickness, and scaling) based on a scale of absence (0), mild (1), moderate (2), severe (3), or very severe (4). The resulting intensity value for each visual sign is used in the computation of the score.
Interpreting the APASI score
The APASI output is a PASI score derived from the intensity of erythema, induration and desquamation and from the extent of the affected surface in each of the four body zones. It is interpreted in the same way as a PASI score obtained by direct observation, and it is one element of the overall clinical assessment rather than a confirmation of a diagnosis or a substitute for the assessment of the treating clinician.
Request APASI score
{
"requestId": "90925097-820b-403d-a75d-4cd989903df1",
"data": {
"type": "image",
"modality": "clinical",
"operator": "Practitioner",
"bodySite": "ARM_LEFT",
"knownConditionForThisImage": {
"conclusion": "Psoriasis"
},
"previousMedia": [
{
"content": "base64 image",
"date": "2022-02-22T12:16:59+01:00"
}
],
"subject": {
"identifier": "6ec724a0-6fa3-11eb-a15f-0242ac160004",
"gender": "m",
"height": 175,
"weight": 71,
"birthdate": "1986-10-21",
"generalPractitioner": {
"identifier": "44f89a8c-6f8a-11eb-9c8a-0242ac160004"
},
"managingOrganization": {
"identifier": "b13cd636-327b-11ec-86b0-0242ac180004",
"display": "Hospital Central"
}
},
"scoringSystems": ["APASI_LOCAL", "PASI_LOCAL", "DLQI", "PURE4"],
"questionnaireResponse": {
"DLQI": {
"question1": 2,
"question2": 3,
"question3": 1,
"question4": 2,
"question5": 1,
"question6": 2,
"question7": 2,
"question8": 2,
"question9": 3,
"question10": 2
},
"APASI_LOCAL": {
"surface": 1
},
"PASI_LOCAL": {
"surface": 1,
"erythema": 1,
"induration": 2,
"desquamation": 2
},
"PURE4": {
"question1Pure": "0",
"question2Pure": "1",
"question3Pure": "0",
"question4Pure": "0"
}
},
"content": "base64 image"
}
}
Questionnaire for the scoring system
{
"code": "APASI_LOCAL",
"questions": [
{
"code": "surface",
"label": "Affected area",
"answers": [
{ "label": "0", "value": "0" },
{ "label": "0-10%", "value": "1" },
{ "label": "10-30%", "value": "2" },
{ "label": "30-50%", "value": "3" },
{ "label": "50-70%", "value": "4" },
{ "label": "70-90%", "value": "5" },
{ "label": "90-100%", "value": "6" }
],
"openField": false
}
]
}
Response
"evolution": {
"domains": {
"APASI_LOCAL": {
"explainabilityMedia": {
"content": "base 64 image",
"detections": null
},
"facets": {
"desquamation": {
"intensity": 0,
"value": 0
},
"erythema": {
"intensity": 0,
"value": 0
},
"induration": {
"intensity": 0,
"value": 0
},
"surface": {
"intensity": 1,
"value": 10
}
},
"grade": {
"category": "None",
"score": 0.0
}
}
}
}