Physical Properties, Novel Features and Clinical Validation of a Multispectral Digital Skin Lesion Analysis Device for Melanoma DetectionDarrell S. Rigel, MD, MS, NYU School of Medicine, New York, NY; Laura Ferris, MD, PhD, University of Pittsburgh, Pittsburgh, PA; Arthur Sober, MD, Harvard University, Boston, NY; Clay J. Cockerell, MD, University of Texas Southwestern, Dallas, TX

LESION TYPE(N = 1632)

NMEAN

CLASSIFIER SCORE

MEDIAN CLASSIFIER

SCORE

Histologically Benign* 1424 1.74 1.61

Non-melanoma skin cancers 33 2.64 2.56

High grade lesions 48 2.68 2.51

Melanomas 127 3.47 3.49*excludes melanomas, high grade lesions and non-melanoma skin cancersTable 1. The mean and median scores by lesion type, as observed on the pivotal study. Benign lesions had a mean

score of 1.74, non-melanoma skin cancers 2.64, high grade lesions 2.68 and melanomas 3.47.

NUMBER CLINICAL/HISTORICAL

CHARACTERISTICSN

MEAN CASSIFIER

SCORE

MEDIAN CLASSIFIER

SCORE0 11 0.84 0.25

1 86 0.96 1.07

2 194 1.40 1.44

3 408 1.50 1.44

4 421 1.94 1.72

5 260 2.36 2.32

6 156 2.67 2.40

7 80 3.00 2.44

8 16 4.03 4.13

Table 3. The sensitivity and specificity at varying thresholds and 95% confidence intervals. As the threshold moves toward a higher classifier score, the sensitivity decreases and specificity increases. Conversely, as a negative classifier score threshold is set, the sensitivity increases and the specificity decreases.

Table 2. For all lesions enrolled into the study, clinical or historical characteristics observed by the examining dermatologists were recorded. The more clinical or historical characteristics present, the higher the mean and median raw classifier scores. Characteristics include Asymmetry, Border Irregularity, Color Variegation, Diameter greater than 6 mm, Evolution, Patient’s Concern, Regression and/or Ugly Duckling.

MSDSLA visual representations of this invasive melanoma and low grade dysplastic nevus are displayed below

Band 0 430 nm 0.4mm (blue/violet)

Band 1 460 nm 0.7mm (blue)

Band 2 500 nm 0.8mm (green)

Band 3 510 nm 0.9mm (green)

Band 4 600 nm 1.3mm (yellow-green)

Band 5 600 nm 1.7mm (red)

Band 6 700 nm 1.9mm (red)

Band 7 780 nm 2.0mm (near infrared)

Band 8 880 nm 2.2mm (near infrared)

Band 9 950 nm 2.5mm (near infrared)

MULTISPECTRAL

ASYMMETRY

TEXTURE STRUCTUREMELANOMA NEVUS MELANOMA NEVUS MELANOMA NEVUS MELANOMA NEVUS

MelaFind discerns 5000 features, 75 of which are taken together to generate information about the morphological disorganization of a lesion.

Multispectral data is transformed to enhance various features for analysis, such as asymmetry, texture and structure (displayed above)

Benign lesion is more uniform, structured and robust in appearance for selected features displayed, from the blue to near infrared bands

Cl inical C lose-upCl inical Overview Dermoscopic

Cl inical Overview Cl inical C lose-up Dermoscopic

BAND WAVELENGTH DEPTH

Pathology: Invasive Melanoma

Pathology: Low Grade Dysplasti c Nevus

EXAMP LES – MSD SLA DATA

• MSDSLA is a non-invasive and objective computer vision system intended to aid dermatologists in the detection of melanoma (MelaFind®, MelaSciences, Inc., Irvington, NY).

• MSDSLA acquires multi-spectral data in 10 different spectral bands from blue light (430 nm) to near-infrared (950 nm).1

• MSDSLA uses information not visible to the human eye to characterize the morphological disorganization of pigmented skin lesions that are clinically ambiguous.

• MSDSLA samples the 3-dimensional morphology of a pigmented skin lesion and surrounding skin by analyzing multi-spectral data directly or by enhancing the morphological patterns characteristic of melanoma.

• Lesions are dark at short wavelengths due to strong absorption by superficial melanin.

• With increasing wavelengths, images of a benign nevus tend to become uniformly brighter while images of a melanoma tend to show more irregular morphology.

• The purpose of multispectral data capture is to improve differentiation of cutaneous melanoma from other pigmented skin lesions.

• Early melanomas may mimic benign look-alikes and present a challenge to clinicians.• MSDSLA provides information about the entire three dimensional structure of the

lesion up to 2.5 mm in depth.• MSDSLA utilizes 20-micron resolution allowing it to discern clusters of 3

melanocytes.

• MSDSLA combines multispectral data acquisition and novel feature generation with automatic quantitative analysis.

• The lesion classifier uses 75 features (some with correlations) to evaluate the degree of 3-dimensional morphological disorganization of pigmented skin lesions.

• This classifier was successfully tested in the largest positive prospective clinical study of melanoma detection to-date, which demonstrated a sensitivity to melanomas and high grade dysplastic nevi of 98.3% with a statistically significant higher biopsy specificity than dermatologists (9.9% versus 3.7%, p = 0.022).2

• In this study, the classifier scores ranged from -5.25 to +9.00; scores below zero were considered to be “low disorganization” and scores of zero and above were considered “high disorganization.”

1Gutkowicz-Krusin D, Elbaum M, Jacobs A, Keem S, Kopf AW, Kamino H, Wang S, Rubin P, Rabinovitz H, Oliviero M. Precision of automatic measurements of pigmented skin lesion parameters with a MelaFind(TM) multispectral digital dermoscope Melanoma Res. 2000 Dec;10(6):563-70.2Monheit, G et al. The Performance of MelaFind: A Prospective Multicenter Study. Arch Dermatol 2011 Feb; 147 (2): 188-94

Description

Function

Contribution

CONCLUSIONS: In this study, the classifier scores ranged from -5.25 to +9.00; scores below zero were considered to be “low disorganization” and scores of zero and above were considered “high disorganization.” The average classifier score of melanomas, high grade lesions, and non-melanoma/high grade lesions were 3.5, 2.7, 2.6, and 1.6, respectively, providing further clinical validation of the novel MSDSLA features.

THRESHOLD SENSITIVITY (95% CI) SPECIFICITY (95% CI)

≥ -3 100.0% (97.9-100%) 0.8% (0.4-1.4%)

≥ -2 99.4% (96.9-100%) 1.3% (0.8-2.0%)

≥ -1 98.9% (95.9-99.9%) 3.6% (2.7-4.7%)

≥ 0 98.3% (95.1-99.6%) 10.8% (9.2-12.5%)

≥ 1 93.1% (88.3-96.4%) 29.8% (27.4-32.2%)

≥ 2 75.4% (78.4-81.6%) 60.0% (57.4-62.5%)

≥ 3 54.3% (46.6-61.8%) 81.8% (79.7-83.8%)

≥ 4 30.9% (24.1-38.3%) 91.4% (89.9-92.8%)

≥ 5 15.4% (10.4-21.7%) 96.1% (95.0-97.0%)

≥ 6 7.4% (4.0-12.4%) 98.8% (98.2-99.4%)

Classifier Score By Clinical Characteristics

Performance by Varying Thresholds

Multispectral Images and Analysis

Classifier Score Description

Classifier Score By Lesion Type