MELA Sciences Inc. (NASDAQ:MELA) poster wins Poster of the Day at Winter Clinical Derm Conf in HI. Physical Properties, Novel Features and Clinical Validation of a Multispectral Digital Skin Lesion Analysis Device for Melanoma Detection MelaFind is a multispectral digital skin lesion analysis device for melanoma detection and works as a non-invasive, objection computer vision system helping dermatologists in the detection of melanoma. By combining multispectral data acquisition with automatic quantitative analysis, this lesion classifier uses 75 features to evaluate the degree of 3-D morphological disorganization of pigmented lesions. The MelaFind lesion classifier produces scores that range from -5.25 to +9.00, with scores below zero considered to be “low disorganization” and scores above to be considered “high disorganization.” A large prospective clinical study of melanoma detection showed sensitivity to melanoma and high-grade dysplastic lesions to be 98.3% with statistically higher biopsy specificity than dermatologists. In this poster, which evaluated over 1600 lesions, the average classifier score of melanomas, high-grade lesions, and non-melanoma/high grade lesions were 3.5, 2.7, and 1.6, respectively. This study validates MelaFind as a validated tool capable of aiding the dermatologist by capturing information that is not visible to the human eye to aid in the detection of high-grade dysplastic lesions as well as melanoma.

1. Physical Properties, Novel Features and Clinical Validation of a Multispectral Digital Skin Lesion Analysis Device for Melanoma Detection
Darrell 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
Multispectral Images and Analysis
LESION TYPE
(N = 1632)
Histologically Benign*
Non-melanoma skin cancers
High grade lesions
Melanomas
Path ology: In vasive M elan om a
Description
• 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.
N
1424
33
48
127
MEAN CLASSIFIER MEDIAN CLASSIFIER
SCORE
SCORE
1.74
1.61
2.64
2.56
2.68
2.51
3.47
3.49
*excludes melanomas, high grade lesions and non-melanoma skin cancers
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Table 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.
Classifier Score By Clinical Characteristics
Path ology: Low Gr ad e Dysp lastic Nevu s
Function
• 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.
Classifier Score By Lesion Type
E X A M P L ES – M S D S L A D ATA
NUMBER CLINICAL/HISTORICAL
CHARACTERISTICS
N
MEAN CASSIFIER
MEDIAN
SCORE
CLASSIFIER SCORE
0
11
0.84
1
86
0.96
1.07
2
194
1.40
1.44
3
408
1.50
1.44
4
421
1.94
1.72
BAND WAVELENGTH DEPTH
5
260
2.36
2.32
Contribution
MSDSLA visual representations of this invasive melanoma and low grade dysplastic
nevus are displayed below
MULTISPECTRAL ASYMMETRY
TEXTURE
STRUCTURE
6
156
2.67
2.40
• The purpose of multispectral data capture is to improve differentiation of
cutaneous melanoma from other pigmented skin lesions.
Band 0
7
80
3.00
2.44
8
16
4.03
4.13
• 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.
Classifier Score Description
• 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
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MELANOMA NEVUS MELANOMA NEVUS MELANOMA NEVUS MELANOMA NEVUS
430 nm
0.4mm
(blue/violet)
Band 1
460 nm
(blue)
0.7mm
Band 2
500 nm
(green)
0.8mm
Band 3
510 nm
(green)
0.9mm
0.25
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.
Performance by Varying Thresholds
Band 5
Band 6
Band 7
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
Band 4
THRESHOLD
98.9% (95.9-99.9%)
3.6% (2.7-4.7%)
1.7mm
≥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%)
1.9mm
≥2
75.4% (78.4-81.6%)
60.0% (57.4-62.5%)
600 nm
1.3mm
(yellow-green)
600 nm
(red)
700 nm
(red)
780 nm
2.0mm
(near infrared)
Band 8
880 nm
2.2mm
(near infrared)
Band 9
950 nm 2.5mm
(near infrared)
 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
≥3
54.3% (46.6-61.8%)
81.8% (79.7-83.8%)
≥4
≥5
30.9% (24.1-38.3%)
91.4% (89.9-92.8%)
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%)
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.
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.