Imaging Protocol
This page describes the image capture methodology, quality control system, and protocol flexibility available for hidradenitis suppurativa clinical trials using Legit.Health.
Smartphone-based capture
Legit.Health uses standard smartphone cameras for image acquisition. No specialised photography equipment is required.
Traditional clinical photography often relies on systems like Canfield VISIA, which require per-site hardware, per-site calibration, and significant rental or purchase costs. Smartphone-based capture eliminates these costs while maintaining the image quality needed for AI scoring.
The Legit.Health mobile application guides investigators through the capture process with visual perspective silhouettes, real-time DIQA quality checks, and immediate feedback on image adequacy.
Standard anatomical region protocol
HS lesions concentrate in specific anatomical regions (intertriginous areas). The standard imaging protocol captures close-up photographs of affected areas:
| Anatomical region | Approach | Notes |
|---|---|---|
| Axillae (bilateral) | 1 close-up per axilla | Most common HS site |
| Groin/inguinal (bilateral) | 1 close-up per side | Second most common site |
| Perianal/perineal | If applicable per protocol | Configurable inclusion |
| Submammary/inframammary | If applicable per protocol | Configurable inclusion |
| Other affected sites | Configurable per study protocol | Gluteal, abdominal folds, etc. |
Photographs are captured at standardised distance and angle using the Legit.Health mobile application. The DIQA algorithm validates image quality in real time before submission.
Protocol flexibility
The imaging protocol is configurable to the study's anatomical scope:
| Protocol | Regions | Use case |
|---|---|---|
| Full anatomical | All affected regions | Complete IHS4 assessment |
| Axillary focus | Bilateral axillae only | Axillary-predominant studies |
| Target lesion | Specific identified lesions | Lesion-level tracking |
| Custom | Sponsor-defined regions | Per protocol requirement |
DIQA: Dermatology Image Quality Assessment
What is DIQA?
DIQA (Dermatology Image Quality Assessment) is an AI-powered image quality assessment algorithm that evaluates every captured image in real time before it is accepted for analysis. It was developed by Legit.Health and published in the Journal of the American Academy of Dermatology (Hernández Montilla et al., 2023).
What DIQA evaluates
| Quality dimension | What it checks | Why it matters |
|---|---|---|
| Focus | Sharpness of the image; absence of motion blur | Out-of-focus images can obscure small lesions, leading to undercounting |
| Lighting | Adequate, even illumination; absence of harsh shadows or glare | Poor lighting creates shadows that mimic or hide lesions |
| Framing | Correct anatomical region captured at the required angle | Incorrect framing means the AI analyses the wrong area |
| Resolution | Sufficient pixel density for lesion detection | Low resolution makes small features undetectable |
How it works in the workflow
- The investigator captures an image through the mobile application
- DIQA evaluates the image immediately (sub-second processing)
- If the image passes: it is accepted and queued for AI scoring
- If the image fails: the investigator receives immediate feedback explaining the quality issue and must recapture
Configurable thresholds
The DIQA pass/fail threshold is configurable per study protocol. Sponsors can choose stricter thresholds for pivotal studies (rejecting more images to ensure the highest quality) or more lenient thresholds for real-world evidence studies.
Patient preparation
- Clean and dry the affected area
- Remove any dressings or wound coverings for the assessment
- Position for clear visibility of the target anatomical region
- Neutral, well-lit environment; smartphone flash or even illumination
Environmental conditions
- Patient positioning: Positioned to expose the target anatomical region clearly (arms raised for axillae, etc.)
- Background: Neutral, non-reflective background
- Lighting: Even illumination without harsh shadows. Smartphone flash provides consistent lighting for close-up captures.
- Distance: Approximately 20–30 cm from camera to skin surface for close-up captures
Consistency across visits
The most important principle is consistency: the same lighting, distance, angle, and patient positioning at every visit. For HS in particular, consistent positioning of anatomical regions (e.g., arm elevation angle for axillae) ensures that score changes reflect clinical changes, not variations in image acquisition.
Anonymization
For anatomically sensitive areas (axillae, groin, perianal), the platform applies automatic region-aware anonymization to ensure patient privacy for all stored and exported images.
Original capture of affected region
Privacy-preserving output with lesion data retained