Sample Outputs and Deliverables

This page shows the concrete outputs that sponsors, CROs, and investigators receive from each psoriasis PASI assessment. The AI generates structured APASI reports immediately after image submission — no central reader, no manual scoring, no delays.

Per-visit PASI report

Each image submission generates a complete APASI report with per-region breakdowns, accessible within seconds of upload:

Psoriasis Area and Severity Index

PASI 13.6

Report Information

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Timestamp

3/28/2026, 12:50:58 AM

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Analysis performed in

2.1 seconds

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Status

Not reviewed

Body region

Head

Image quality

91%

Erythema

2

Desquam.

2

Induration

1

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BSA covered

30%

Region PASI

1.0

Body region

Trunk

Image quality

89%

Erythema

3

Desquam.

2

Induration

2

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BSA covered

15%

Region PASI

4.2

Body region

Upper extremities

Image quality

93%

Erythema

2

Desquam.

1

Induration

2

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BSA covered

10%

Region PASI

2.0

Body region

Lower extremities

Image quality

87%

Erythema

3

Desquam.

3

Induration

2

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BSA covered

20%

Region PASI

6.4

PASI = 1.0 + 4.2 + 2.0 + 6.4 = 13.6

What the report contains

Output	Detail
Global APASI score	Composite PASI score (0–72)
Per-region erythema	Intensity score (0–4) for head, trunk, upper extremities, lower extremities
Per-region desquamation	Intensity score (0–4) per body region
Per-region induration	Intensity score (0–4) per body region (estimated from visual cues)
Per-region BSA	Affected body surface area (%) via pixel-level segmentation
Per-region PASI contribution	Weighted PASI component per region
PASI response flags	PASI 75, PASI 90, PASI 100 vs. baseline (when applicable)
Image quality (DIQA)	Quality score per perspective; failed images flagged for recapture
Timestamp	UTC timestamp of capture and AI processing

PASI response rates from day one

PASI 75, PASI 90, and PASI 100 responder flags are computed automatically at every visit relative to baseline. Sponsors can track response rates in real time without waiting for data transfer or manual calculation.

Longitudinal PASI tracking

The platform tracks PASI evolution across all visits for each patient. At each timepoint the system computes:

• Absolute PASI change from baseline
• Percentage change from baseline
• PASI response classification: PASI 75 / 90 / 100 flag at each visit
• Per-region trend: Which body region is driving improvement or worsening
• Score trajectory: Visual evolution from screening through long-term extension

This enables per-patient treatment response monitoring and facilitates data review meetings without requiring database lock.

Phase 3 deployment example

In the JNJ-77242113 Phase 3 trial for moderate-to-severe plaque psoriasis, patients captured 11 standardised photographs at home across 6 timepoints. The AI processed all images and delivered APASI scores and response rate data to the sponsor's data science team via automated monthly S3 exports. Across 130+ sites in 12 countries, all data was available without a single central reader.

Data export for EDC integration

All assessment outputs are structured for export to the sponsor's EDC system. Fields exported at each visit:

Field	Description	Format
Patient identifier	Study-specific pseudonymised ID	String
Visit date	Date and timestamp of the assessment	ISO 8601
Global APASI score	Composite PASI score (0–72)	Float
Per-region PASI	Regional PASI contribution for head, trunk, upper extremities, lower extremities	Float per region
Erythema per region	Erythema intensity score (0–4) per body region	Integer
Desquamation per region	Desquamation intensity score (0–4) per body region	Integer
Induration per region	Induration intensity score (0–4) per body region	Integer
BSA per region	Affected body surface area percentage per region	Float (%)
DIQA scores	Image quality score per perspective	Float
PASI response	PASI 75/90/100 response flag (percentage improvement from baseline)	Boolean per threshold

Data is transferred automatically via RESTful API, scheduled S3 export, or CSV/Excel. Legit.Health provides IQ/OQ documentation and data mapping specifications for all major EDC platforms (Medidata Rave, Oracle InForm, Veeva Vault EDC).

AI visual outputs

Beyond scores, the AI produces visual artefacts that demonstrate exactly what the system detected and how it reached its conclusion.

BSA segmentation masks

For each body region, the AI generates a pixel-level segmentation overlay showing exactly which skin areas are classified as affected by psoriasis. This replaces the most subjective component of manual PASI scoring — visual BSA estimation — with an objective measurement.

Input: standardised body region photograph

Output: psoriatic plaques highlighted by AI segmentation

Per-sign intensity scoring

Each PASI component sign (erythema, desquamation, induration) is scored independently from the close-up perspective for each body region. The AI analyses the representative plaque photograph to determine the 0–4 integer score for each sign.

Head: E2 / D2 / I1

Trunk: E3 / D2 / I2

Upper extremities: E2 / D1 / I2

Lower extremities: E3 / D3 / I2

Pose estimation and perspective alignment

The 11-perspective full-body protocol uses body pose estimation to confirm which body region each photograph captures and to ensure correct PASI regional attribution. The AI maps anatomical landmarks to align images with the four PASI body regions.

Body pose estimation

Perspective identification via body landmarks

PASI region mapping

Automatic attribution to head / trunk / upper / lower extremities

Anonymization

All photographs are processed with automatic face anonymization. The system applies irreversible blurring to facial features, ensuring no patient is identifiable from stored or exported images. Body images are inherently less identifiable; anonymization is applied where faces are visible.

Before anonymization

Original full-body capture

After anonymization

Irreversible face blurring applied

Reliability of the scores

The APASI system components are each validated to perform at the level of expert inter-rater agreement:

Component	AI performance	Expert inter-rater variability	Verdict
Erythema	RMAE 0.13	RMAE ~0.14	AI meets expert level
Desquamation	RMAE 0.14	RMAE ~0.17	AI meets expert level
Induration	RMAE 0.151	RMAE ~0.17	AI meets expert level
BSA (segmentation)	IoU 0.61	—	Pixel-level objectivity

The AI produces the identical score for the same image every time, across every site, without calibration drift. For the full validation evidence: Clinical Evidence →