0
We're unable to sign you in at this time. Please try again in a few minutes.
Retry
We were able to sign you in, but your subscription(s) could not be found. Please try again in a few minutes.
Retry
There may be a problem with your account. Please contact the AMA Service Center to resolve this issue.
Contact the AMA Service Center:
Telephone: 1 (800) 262-2350 or 1 (312) 670-7827  *   Email: subscriptions@jamanetwork.com
Error Message ......
Study |

The Performance of MelaFind:  A Prospective Multicenter Study FREE

Gary Monheit, MD; Armand B. Cognetta, MD; Laura Ferris, MD, PhD; Harold Rabinovitz, MD; Kenneth Gross, MD; Mary Martini, MD; James M. Grichnik, MD, PhD; Martin Mihm, MD; Victor G. Prieto, MD, PhD; Paul Googe, MD; Roy King, MD; Alicia Toledano, ScD; Nikolai Kabelev, BCSc; Maciej Wojton, MS; Dina Gutkowicz-Krusin, PhD
[+] Author Affiliations

Author Affiliations: Total Skin and Beauty Dermatology, Birmingham, Alabama (Dr Monheit); Dermatology Associates of Tallahassee, Tallahassee, Florida (Dr Cognetta); Department of Dermatology, University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania (Dr Ferris); Skin and Cancer Associates, Plantation, Florida (Dr Rabinovitz); Skin Surgery Medical Group Inc, San Diego, California (Dr Gross); Department of Dermatology, Northwestern University, Chicago, Illinois (Dr Martini); Department of Dermatology, University of Miami Health System, Miami, Florida (Dr Grichnik); Department of Dermatology, Harvard Medical School, Boston, Massachusetts (Dr Mihm); University of Texas M. D. Anderson Cancer Center, Houston (Dr Prieto); Knoxville Dermatopathology Laboratory, Knoxville, Tennessee (Drs Googe and King); Statistics Collaborative, Washington, DC (Dr Toledano); and MELA Sciences, Irvington, New York (Messrs Kabelev and Wojton and Dr Gutkowicz-Krusin).


Arch Dermatol. 2011;147(2):188-194. doi:10.1001/archdermatol.2010.302.
Text Size: A A A
Published online

In 2009, there were an estimated 68 700 new cases of invasive melanoma and over 53 000 new cases of melanoma in situ in the United States.1 The actual number might be significantly higher because melanoma incidence is considered to be underreported by 30% to 40% in cancer registries.2 The number of deaths due to melanoma was estimated at 8650 in 2009.1 Melanoma is virtually 100% curable if detected when it is confined to the epidermis (melanoma in situ). Thin melanomas, with a Breslow thickness of 1 mm or thinner, have a 94% rate of survival after 5 years.3 However, once melanoma has advanced and metastasized to other parts of the body, it is difficult to treat. The survival rate for patients with stage IV melanoma is less than 15% for 5 years, with most patients dying within 6 to 10 months.4 Therefore, early detection and prompt treatment are essential to improve the prognosis for patients with melanoma. The challenge is that early melanoma may be difficult to differentiate from many benign simulants.

This multicenter prospective trial was designed to establish the safety and effectiveness of MelaFind (MELA Sciences Inc, Irvington, New York) as an aid in evaluating pigmented lesions (PLs) that have 1 or more clinical or historical characteristics of melanoma. MelaFind is a noninvasive, fully automatic, computer-vision diagnostic system designed as an aid to detection of early melanoma and developed to identify PLs that should be considered for biopsy to rule out melanoma. This study evaluates the performance of MelaFind using sensitivity and specificity as metrics and comparing the specificity of MelaFind to that of the study investigators.

PROSPECTIVE INCLUSION AND EXCLUSION CRITERIA

Patients with at least 1 PL scheduled for biopsy in toto were invited to participate in the trial. Exclusion criteria were as follows: (1) failure to give informed consent; (2) known allergy to isopropyl alcohol; (3) diameter of the PL less than 2 mm or greater than 22 mm; (4) anatomic site of PL not accessible to the device; (5) lesion previously biopsied, excised, or traumatized; (6) skin not intact (eg, open sores, ulcers, bleeding); (7) lesion within 1 cm of the eye; (8) lesion on palmar, plantar, or mucosal (eg, lips, genitals) surface or under nails; (9) lesion in an area of visible scarring; or (10) lesion containing foreign matter (eg, tattoo ink, splinter, marker).

OUTCOME MEASURES

The primary outcome measures were the sensitivity and specificity of the computer-vision system, MelaFind, and the specificity of clinicians, among PLs with the diagnoses of “melanoma cannot be ruled out” or “not melanoma.” Pigmented lesions with prebiopsy clinical diagnoses of melanoma were excluded from the analysis because such lesions would be biopsied by examining dermatologists regardless of MelaFind results. Melanomas and borderline lesions such as high-grade dysplastic nevi (HGDN) and atypical melanocytic hyperplasias (AMH) or proliferations (AMP) were defined as histologically positive lesions.

MelaFind produces a binary output: (1) positive, the lesion should be considered for biopsy to rule out melanoma; and (2) negative, the lesion should be considered for later evaluation. Clinicians were blinded to MelaFind output, and participation in the trial did not affect patient treatment. Thus investigators managed the patient care based on their clinical information, and in the study, the PL was considered positive if the prebiopsy dermatologic diagnosis was melanoma or melanoma cannot be ruled out, and negative if the prebiopsy dermatologic diagnosis was not melanoma.

The dermatologic diagnosis was the dermoscopic diagnosis, if available, or the clinical diagnosis without dermoscopy otherwise. When the prebiopsy dermoscopic diagnosis was not melanoma and the reason for the biopsy was “clinical concern,” the dermatologic diagnoses were the diagnoses without dermoscopy. The diagnostic performances of MelaFind and of the examining clinicians were evaluated using the histologic reference standard.

DATA ACQUIRED IN THE CLINICAL TRIAL

Digital multispectral MelaFind images (in 10 bands) were acquired for every lesion in the trial. In addition, 2 standard clinical images were acquired with a Fuji FinePix Pro SR camera (FUJIFILM Corporation, Tokyo, Japan) (an overview from about 55 cm away and a close-up from about 20 cm away) and a contact dermoscopic image with a Nikon Coolpix 4300 camera (Nikon Corporation, Tokyo, Japan) with a 3Gen dermoscopic attachment (3Gen LLC, San Juan Capistrano, California). The electronic Case Record Forms contained information about patient demographics and melanoma risk factors. The presence of clinical and historical characteristics of melanoma such as ABCDE (asymmetry, border irregularity, color variegation, diameter ≥6 mm, and evolution),3,5,6 regression, “ugly duckling” sign,7 and patient's concern was also recorded for each lesion. If dermoscopic evaluation was used, dermoscopic characteristics of lesions enrolled were recorded. Prebiopsy diagnoses (without dermoscopy and, if available, with dermoscopy) by the examining dermatologists were also included; if the dermatologic diagnosis was not melanoma, the reason for the biopsy was selected from the following: nonmelanoma skin cancer, patient's concern, patient's discomfort, cosmetic, or, if dermoscopic evaluation was used, clinical concern. A histologic specimen with the standard hematoxylin-eosin staining was provided for each lesion.

HISTOLOGIC EVALUATION AS THE REFERENCE STANDARD

Since the prebiopsy dermatologic diagnosis might not match the histologic diagnosis, the diagnostic performance of MelaFind and of clinicians were evaluated using dermatopathology as the reference standard. Borderline lesions that are currently excised in clinical practice, such as HGDN, AMP, and AMH, were included in the analysis because HGDN are sometimes considered melanoma precursors or early evolving melanomas and are difficult to differentiate from melanoma in situ.8,9 The diagnoses AMP and AMH may be used when dermatopathologists are uncertain about diagnosis and cannot rule out melanoma.10,11

Because concordance of histologic interpretation is limited with early melanomas,1214 histologic slides for each lesion in the trial were evaluated by 2 independent dermatopathologists. In cases of significant discordance, histologic slides were evaluated independently by a third dermatopathologist. When 1 dermatopathologist diagnosed melanoma and 2 others diagnosed a benign lesion, histologic slides were sent again to the dermatopathologist who diagnosed melanoma for a blind rereview. The final histologic diagnosis was determined following the algorithm detailed in Table 1.

Table Graphic Jump LocationTable 1 Algorithm for Final Histologic Diagnosisa
BLINDING AND MASKING

Clinicians did not receive the results of the MelaFind lesion classification algorithm, and information from MelaFind was not used in diagnosing or treating lesions. An independent entity acted as a secure data custodian and verified the integrity of the data received from the clinical sites. In addition, the data custodian analyzed all MelaFind images, using software provided by MELA Sciences Inc. At the conclusion of the accrual phase of the trial, the statistician (A.T.) received the electronic Case Record Forms and lesion classification results from the data custodian, as well as the results of histologic evaluations, and analyzed the performance of MelaFind and of clinicians participating in this trial.

CLINICAL SITES

Seven clinical sites with 23 investigators participated in this trial. Three sites were academic institutions (University of Pittsburgh, Duke University, and Northwestern University), and 4 sites were dermatologic practices highly experienced in managing PLs. All sites were approved to participate in the study by the appropriate institutional review boards.

PILOT STUDY OF BIOPSY SENSITIVITY (READER STUDY)

The reader study investigated the biopsy sensitivity of dermatologists. It used 25 randomly selected melanomas (11 invasive and 14 in situ) and 25 nonmelanomas, matched to melanomas by anatomic location and patient age and sex. Borderline lesions (HGDN, AMP, and AMH) were excluded. The clinical history and images (clinical overview, clinical close-up, and dermoscopy images) were reviewed by the readers. The readers, dermatologists who did not participate in the clinical trial, reported for each lesion whether they would biopsy it to rule out melanoma.

MELAFIND

MelaFind acquires digital multispectral images of a PL in 10 different spectral bands, from blue (430 nm) to near infrared (950 nm). These are contact images that use 91% isopropyl alcohol for refractive index matching. Each image is 1280 × 1024 pixels, with the pixel size in the lesion plane 20 × 20 μm. MelaFind uses automatic image analysis and statistical pattern recognition to help identify lesions to be considered for biopsy to rule out melanoma. The properties of these images as well as image analysis methods have been previously described.1521

All image analysis and lesion classification algorithms are automatic and were tested prospectively in the clinical trial: (1) calibration algorithms reduce noise and artifacts in the images and determine the diffuse reflectance of the skin; (2) image quality control algorithms detect image problems (eg, overexposure, underexposure, lesion too big, lesion too small, too much hair on the lesion, too many bubbles on the lesion, motion of the handheld imaging device during imaging) and, when appropriate, request the operator to reimage; (3) lesion segmentation algorithm identifies image pixels that belong to the lesion; (4) feature extraction algorithms compute quantitative lesion parameters; (5) lesion classification algorithm differentiates lesions to be considered for biopsy to rule out melanoma (MelaFind positive) from those to be considered for later evaluation (MelaFind negative).

PIGMENTED LESIONS

Between January 2007 and July 2008, 1383 patients with 1831 PLs were enrolled. More female than male patients entered the study, and the median age was 47 years. Most patients (about 98%) were white, consistent with the fact that melanoma is much more frequent among whites.22 There were no significant differences between the group of enrolled patients (1383) and those with evaluable lesions (1257) (Table 2).

Table Graphic Jump LocationTable 2 Demographic Characteristics of Enrolled Patients and Patients With Eligible and Evaluable Lesionsa

Of the 1831 registered lesions, 1 patient with 1 lesion withdrew from the trial. Three lesions were determined to be ineligible by clinicians, and 14 by dermatopathologists (mostly owing to previous scarring that was not identified clinically); 19 lesions were not evaluable because of missing or inadequate histologic slides. One hundred sixty-two lesions were not evaluable owing to unsuccessful imaging attempts: 65 owing to operator errors (eg, too much hair, too many bubbles, lesion not centered in the field of view), 36 owing to MelaFind or standard camera malfunctions, and 61 owing to causes that might have been either operator errors or MelaFind malfunctions (ie, either lesion too small or failure of automatic segmentation). MelaFind does not provide a result if the image fails automatic image quality control algorithms, but all enrolled lesions were imaged during the trial.

Of 1632 eligible and evaluable lesions, 143 (8.8%) required more than 2 evaluations by the dermatopathologists. Melanomas made up about 8% of all eligible and evaluable PLs; borderline lesions (HGDN, AMP, and AMH) accounted for about 3% (Table 3). Most lesions were nevi, with 61% being low-grade dysplastic nevi. About 15% of lesions were nonmelanocytic, including seborrheic keratoses, actinic lentigines, and pigmented nonmelanoma skin cancers. About 45% of melanomas were in situ, which are almost 100% curable by complete excision.23 The invasive melanomas were thin (median thickness, 0.36 mm). Most of the invasive melanomas were of the most common, superficial spreading type. Only 2 melanomas (both nodular) were relatively thick: 1.0 and 1.2 mm. Thus, almost all melanomas in this trial were early lesions that are difficult to differentiate from benign simulants.

Table Graphic Jump LocationTable 3 The Histologic Reference Standard for all Eligible and Evaluable Lesions

Dermoscopic characteristics were provided for 645 lesions, including 60 melanomas. Among the 29 lesions considered not melanoma dermoscopically—but melanoma cannot be ruled out clinically—and that were biopsied because of clinical concern, 1 was found to be melanoma and another HGDN by histologic analysis (Table 4). There were 82 lesions with a final dermatologic diagnosis of not melanoma (5%), most of which were biopsied owing to patient's concern (57 of 82); among these lesions 1 was melanoma and 1 HGDN (Table 4). Most of the histologically verified melanomas were diagnosed prior to biopsy as melanoma cannot be ruled out, with about a third of melanomas considered unlikely (ie, likelihood between 1% and 33%). These results indicate that the lesions enrolled in this trial presented a significant diagnostic challenge to the investigators.

Table Graphic Jump LocationTable 4 Dermatologic and Histologic Diagnoses of Evaluable Lesions
PILOT STUDY OF BIOPSY SENSITIVITY (READER STUDY)

A small study investigated the biopsy sensitivity of dermatologists who did not participate in the clinical study but who served as readers. The average biopsy sensitivity to melanoma of the 39 readers was 78%. The interreader variability (SD) was high, κ = 0.22 (0.01), indicating only fair agreement. This variability is illustrated in the Figure, which shows that some of the readers made biopsy decisions very similar to those of examining clinicians, who biopsied all of these lesions to rule out melanoma; it also shows that many did not. Only 5 of 25 melanomas would have been biopsied by all readers, and different readers missed different melanomas.

Place holder to copy figure label and caption
Figure

Biopsy decisions by 39 dermatologists participating in the pilot reader study. Small black circles represent individual readers; big black circles, pairs of readers; and the diamond, examining clinicians in the clinical trial on the same set of lesions.

Graphic Jump Location
CLINICAL TRIAL END POINTS

There were 1612 lesions (including 114 melanomas) evaluable for primary end points, ie, excluding lesions with the prebiopsy dermatologic diagnosis of melanoma. The data on these 114 melanomas were pooled to determine the sensitivity of MelaFind to melanoma and the 95% lower confidence bound (LCB) on sensitivity. Since the measured values of sensitivity were very high, the exact mid-P method was used to compute the LCB.24 Because of the high degree of variability among investigators (specificity range, 0%-25%), the specificity was determined separately for the set of lesions from each investigator. The specificities for MelaFind and clinicians were obtained by averaging over investigators and then compared (Table 5).

Table Graphic Jump LocationTable 5 Sensitivity and Specificity of MelaFinda Biopsy Recommendation

The secondary end points included all eligible and evaluable lesions with any prebiopsy dermatologic diagnosis. Since no comparisons between MelaFind and study investigators were performed, the data were pooled. These end points are summarized in Table 6. Measured negative predictive values are very high (>98%) owing to the very high sensitivity of MelaFind.

Table Graphic Jump LocationTable 6 Summary of the Biopsy Performance (Pooled) of MelaFinda for All Eligible and Evaluable Lesions With Any Prebiopsy Diagnosis

In this multicenter prospective trial, MelaFind achieved very high sensitivity to thin melanomas and borderline lesions (>98%; 95% LCB, >95%). For lesions that were not melanomas and had prebiopsy diagnoses of melanoma cannot be ruled out or not melanoma, MelaFind had an average specificity of 9.5%, ie, significantly higher than that of investigators (3.7%) (P = .02). However, this trial could not determine the true sensitivity of dermatologists, since melanomas that were not scheduled for biopsy, ie, missed by the examining clinicians, would not be evaluable. The pilot reader study found that dermatologists miss thin melanomas. Thus, even though all lesions in the clinical trial were biopsied by the examining dermatologists, many of the melanomas would not have been biopsied by other dermatologists.

The sensitivity of physicians can be assessed by longitudinal studies, ie, long-term follow-up of the patients to determine whether lesions considered benign later turned out to be clinically suspect for melanoma. In the 9-year longitudinal study at a PL clinic in the United Kingdom by Bataille et al,25 221 melanomas (both invasive and in situ) were detected. Melanomas on 14 patients were diagnosed as benign on the first visit and biopsied on the second or third visit; one of these patients died of metastatic melanoma. The biopsy sensitivity to melanoma measured in this study was 93.7% (95% LCB, 90.5%). The median Breslow thickness of melanomas in this study was 0.9 mm. The study by Carli et al26 found biopsy sensitivity to melanoma to be 86.7% (95% LCB, 66.7%) based on a comparison with the cancer registry, but the sample was very small.26 Thus, the 95% LCB on MelaFind's sensitivity is higher than the biopsy sensitivities of longitudinal studies reported in the literature.

Another method of assessing physician sensitivity is through reader studies. Such studies have been widely used to evaluate diagnostic performance in mammography and colonoscopy.27,28 In dermatology, readers are presented with a series of images of lesions (clinical and/or dermoscopic) and, for each image, may be asked to decide whether a lesion is a melanoma and whether it should be biopsied to rule out melanoma. Assuming acceptable quality of images (clinical and/or dermoscopic) and availability of patient history, and taking into account the fact that most of the training of dermatologists is actually done with such images, reader studies can provide estimates of sensitivity to melanoma. Such studies have been performed in dermatology to evaluate the effectiveness of teledermatology,29,30 to compare the diagnostic performance of dermatologists and primary care physicians,31 to assess the dermoscopic examination of lesions,32 and to determine the diagnostic and biopsy sensitivities of dermatologists.33

The pilot reader study conducted as a part of this clinical trial included a random sample of lesions enrolled in the trial and provided readers with the clinical overview, a clinical close-up image, contact dermoscopic images, and patient demographic and melanoma risk factor information; all images were checked for quality by an experienced dermatologist. The average biopsy sensitivity of 39 dermatologist readers was 78%, which is similar to a prior reader study by Friedman et al33 for small (<6 mm in diameter) PLs from the MelaFind database. Among 10 expert dermoscopists reviewing a series of 99 small PLs, the average biopsy sensitivity to melanoma was 71%; the biopsy sensitivity to melanoma in situ was 63%. Interreader variability was very high for lesion management decisions (κ = 0.34), indicating that different experts make different biopsy decisions.

A limitation of the present study is that since only PLs scheduled for biopsy in toto were evaluable in the trial, the benign lesions are not representative of such lesions in the general population. As a result, the specificity reported here cannot be generalized to the general population, for either clinicians or MelaFind. Tsao et al34 estimated that, in the general population in the United States, there are about 70 000 nevi for every invasive melanoma or about 35 000 nevi per invasive or in situ melanoma; the overwhelming majority of these nevi have no clinical or historical characteristics of melanoma. A study by Schäfer et al35 examined common and atypical melanocytic nevi in the general adult population in Germany and found that the average number of atypical nevi per person was 0.074.35 In the US population of about 300 million, with about 120 000 new cases of invasive and in situ melanomas per year,1 this implies about 200 atypical nevi per melanoma. So, even if all atypical nevi were selected for biopsy to rule out melanoma, the specificity in the general population would be over 99% (ie, about [35 000 − 200]/35 000). Therefore, the fact that the specificities of examining clinicians and MelaFind are rather low in the clinical trial does not mean that the specificities of clinicians and MelaFind would be low in the general population. It is only a reflection of the fact that almost all the lesions in this trial were sufficiently atypical to be selected for biopsy to rule out malignant melanoma.

MelaFind is intended to be used on lesions with 1 or more clinical or historical characteristics of melanoma, ie, atypical lesions. If all atypical lesions were to be biopsied to rule out melanoma, the biopsy ratio (number of false-positive biopsy findings per true-positive biopsy finding) of about 200:1 would be very high. In the trial, the biopsy ratio for MelaFind was 10.8:1 for melanomas and 7.6:1 for melanomas and borderline lesions. The values of the biopsy ratio reported in the literature are highly variable. A study by Cohen et al36 reported biopsy ratios of about 135:1 for patients with a history of melanoma and about 576:1 for patients without personal history of melanoma. Among general practitioners in Australia, the biopsy ratio varied from 82:1 in the youngest patients to 10:1 in the oldest patients.37 For dermatologists, prospective studies reported biopsy ratios of about 8:1 in the general population,38 and from 33:1 to 47:1 among high-risk patients with atypical nevi.3941 One study by Banky et al42 reported a very low biopsy ratio of about 3:1 in patients at high risk for melanoma using a combination of baseline images and dermoscopy. However, this study also reported that at least 5 of 18 melanomas (4 in situ and 1 invasive at the time of biopsy) were not detected on the first examination. Thus, MelaFind's biopsy ratio is at the lower end of the values reported in the literature.

MelaFind is a safe and effective tool to help identify PLs to be considered for biopsy to rule out melanoma. In this trial, MelaFind demonstrated very high sensitivity to early melanomas and borderline lesions, specificity superior to that of clinicians, and a biopsy ratio of about 8:1. Direct comparison of the results of this study with those of other studies is not possible. As pointed out by Menzies et al,43 diagnostic performance depends on the difficulty of lesions included in the study. It would be helpful if the dermatologic community could agree on a standard mix of lesions to be used for future testing of methods developed for early detection of melanoma.

Correspondence: Dina Gutkowicz-Krusin, PhD, MELA Sciences Inc, 50 S Buckhout St, Ste 1, Irvington, NY 10533 (gutkowicz@melasciences.com).

Accepted for Publication: August 11, 2010.

Published Online: October 18, 2010. doi:10.1001/archdermatol.2010.302

Author Contributions: Drs Toledano and Gutkowicz-Krusin had full access to all the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Study concept and design: Rabinovitz, Toledano, Kabelev, and Gutkowicz-Krusin. Acquisition of data: Monheit, Cognetta, Ferris, Rabinovitz, Gross, Martini, Grichnik, Mihm, Prieto, and Googe. Analysis and interpretation of data: Gross, Martini, Mihm, Prieto, Googe, King, Toledano, Kabelev, Wojton, and Gutkowicz-Krusin. Drafting of the manuscript: Monheit, Prieto, and Gutkowicz-Krusin. Critical revision of the manuscript for important intellectual content: Monheit, Cognetta, Ferris, Rabinovitz, Gross, Martini, Grichnik, Mihm, Prieto, Googe, King, Toledano, Kabelev, and Wojton. Statistical analysis: Toledano and Gutkowicz-Krusin. Administrative, technical, and material support: Martini, Mihm, Wojton, and Gutkowicz-Krusin. Study supervision: Monheit, Mihm, Prieto, and Kabelev. Provided additional literature and references: Grichnik. Research and development: Kabelev.

Financial Disclosure: Dr Monheit has served and/or currently serves as consultant and/or clinical investigator for Allergan Corporation (Juvederm), Dermik Laboratories (Sculptra), Genzyme Corporation (Captique, Prevelle), Colbar LifeScience Ltd (now owned by Johnson & Johnson) (Evolence), Contura (Aquamid), Ipsen/Medici (Dysport), Stiefel, Electro-Optic Sciences Inc (MelaFind), Revance, Kythera, Galderma, Mentor, and Mertz. Drs Cognetta, Rabinovitz, and Mihm are members of the MELA Sciences Advisory Committee. Drs Monheit, Cognetta, Ferris, Grichnik, Rabinovitz, Prieto, King, and Toledano serve as consultants to MELA Sciences Inc. Messrs Kabelev and Wojton and Dr Gutkowicz-Krusin are employees of MELA Sciences Inc.

Funding/Support: This study was supported by MELA Sciences Inc.

Jemal  ASiegel  RWard  EHao  YXu  JThun  MJ Cancer statistics, 2009. CA Cancer J Clin 2009;59 (4) 225- 249
PubMed Link to Article
Cockburn  MSwetter  SMPeng  DKeegan  THDeapen  DClarke  CA Melanoma underreporting: why does it happen, how big is the problem, and how do we fix it? J Am Acad Dermatol 2008;59 (6) 1081- 1085
PubMed Link to Article
Rigel  DSFriedman  RJKopf  AWPolsky  D ABCDE: an evolving concept in the early detection of melanoma. Arch Dermatol 2005;141 (8) 1032- 1034
PubMed Link to Article
Tsao  HAtkins  MBSober  AJ Management of cutaneous melanoma. N Engl J Med 2004;351 (10) 998- 1012
PubMed Link to Article
Abbasi  NRShaw  HMRigel  DS  et al.  Early diagnosis of cutaneous melanoma: revisiting the ABCD criteria. JAMA 2004;292 (22) 2771- 2776
PubMed Link to Article
Thomas  LTranchand  PBerard  FSecchi  TColin  CMoulin  G Semiological value of ABCDE criteria in the diagnosis of cutaneous pigmented tumors. Dermatology 1998;197 (1) 11- 17
PubMed Link to Article
Grob  JJBonerandi  JJ The ‘ugly duckling’ sign: identification of the common characteristics of nevi in an individual as a basis for melanoma screening. Arch Dermatol 1998;134 (1) 103- 104
PubMed Link to Article
Arumi-Uria  MMcNutt  NSFinnerty  B Grading of atypia in nevi: correlation with melanoma risk. Mod Pathol 2003;16 (8) 764- 771
PubMed Link to Article
Cook  MGClarke  TJHumphreys  S  et al.  The evaluation of diagnostic and prognostic criteria and the terminology of thin cutaneous malignant melanoma by the CRC Melanoma Pathology Panel. Histopathology 1996;28 (6) 497- 512
PubMed Link to Article
Kossard  S Atypical lentiginous junctional naevi of the elderly and melanoma. Australas J Dermatol 2002;43 (2) 93- 101
PubMed Link to Article
Kelley  SWCockerell  CJ Sentinel lymph node biopsy as an adjunct to management of histologically difficult to diagnose melanocytic lesions: a proposal. J Am Acad Dermatol 2000;42 (3) 527- 530
PubMed Link to Article
Farmer  ERGonin  RHanna  MP Discordance in the histopathologic diagnosis of melanoma and melanocytic nevi between expert pathologists. Hum Pathol 1996;27 (6) 528- 531
PubMed Link to Article
Corona  RMele  AAmini  M  et al.  Interobserver variability on the histopathologic diagnosis of cutaneous melanoma and other pigmented skin lesions. J Clin Oncol 1996;14 (4) 1218- 1223
PubMed
Veenhuizen  KCDe Wit  PEMooi  WJScheffer  EVerbeek  ALRuiter  DJ Quality assessment by expert opinion in melanoma pathology: experience of the pathology panel of the Dutch Melanoma Working Party. J Pathol 1997;182 (3) 266- 272
PubMed Link to Article
Gutkowicz-Krusin  DElbaum  MSzwajkowski  PKopf  AW Can early malignant melanoma be differentiated from atypical melanocytic nevi by in-vivo techniques? part II: automatic machine vision classification. Skin Res Technol 1997;3 (1) 15- 22
Link to Article
Elbaum  MKopf  AWRabinovitz  HS  et al.  Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: a feasibility study. J Am Acad Dermatol 2001;44 (2) 207- 218
PubMed Link to Article
Gutkowicz-Krusin  DElbaum  MJacobs  A  et al.  Precision of automatic measurements of pigmented skin lesion parameters with a MelaFind(TM) multispectral digital dermoscope. Melanoma Res 2000;10 (6) 563- 570
PubMed Link to Article
Gutkowicz-Krusin  DElbaum  MGreenebaum  MJacobs  A Systems and methods for the multispectral imaging and characterization of skin tissue. US Patent No. 6 208 749 B1 (March 27, 2001)
Gutkowicz-Krusin  DElbaum  MGreenebaum  MJacobs  ABogdan  A Systems and methods for the multispectral imaging and characterization of skin tissue. US Patent No. 6 081 612 (June 27, 2000)
Elbaum  M Computer-aided melanoma diagnosis. Dermatol Clin 2002;20 (4) 735- 747, x-xi
PubMed Link to Article
Gutkowicz-Krusin  DRabinovitz  HS Multispectral image analysis.  In: Soyer  HP, Argenziano  G, Hofmann-Wellenhof  R, Johr  RH, eds. Color Atlas of Melanocytic Lesions of the Skin. Berlin, Germany: Springer; 2007:52-56
Cormier  JNXing  YDing  M  et al.  Ethnic differences among patients with cutaneous melanoma. Arch Intern Med 2006;166 (17) 1907- 1914
PubMed Link to Article
Megahed  MSchön  MSelimovic  DSchön  MP Reliability of diagnosis of melanoma in situ.  Lancet 2002;359 (9321) 1921- 1922
PubMed Link to Article
Vollset  SE Confidence intervals for a binomial proportion. Stat Med 1993;12 (9) 809- 824
PubMed Link to Article
Bataille  VSasieni  PCurley  RKCook  MGMarsden  RA Melanoma yield, number of biopsies and missed melanomas in a British teaching hospital pigmented lesion clinic: a 9-year retrospective study. Br J Dermatol 1999;140 (2) 243- 248
PubMed Link to Article
Carli  PNardini  PCrocetti  EDe Giorgi  VGiannotti  B Frequency and characteristics of melanomas missed at a pigmented lesion clinic: a registry-based study. Melanoma Res 2004;14 (5) 403- 407
PubMed Link to Article
Beam  CALayde  PMSullivan  DC Variability in the interpretation of screening mammograms by US radiologists: findings from a national sample. Arch Intern Med 1996;156 (2) 209- 213
PubMed Link to Article
Johnson  CDToledano  AYHerman  BA  et al. American College of Radiology Imaging Network A6656, Computerized tomographic colonography: performance evaluation in a retrospective multicenter setting. Gastroenterology 2003;125 (3) 688- 695
PubMed Link to Article
Shapiro  MJames  WDKessler  R  et al.  Comparison of skin biopsy triage decisions in 49 patients with pigmented lesions and skin neoplasms: store-and-forward teledermatology vs face-to-face dermatology. Arch Dermatol 2004;140 (5) 525- 528
PubMed Link to Article
Warshaw  EMLederle  FAGrill  JP  et al.  Accuracy of teledermatology for pigmented neoplasms. J Am Acad Dermatol 2009;61 (5) 753- 765
PubMed Link to Article
Chen  SCPennie  MLKolm  P  et al.  Diagnosing and managing cutaneous pigmented lesions: primary care physicians versus dermatologists. J Gen Intern Med 2006;21 (7) 678- 682
PubMed Link to Article
Argenziano  GSoyer  HPChimenti  S  et al.  Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet. J Am Acad Dermatol 2003;48 (5) 679- 693
PubMed Link to Article
Friedman  RJGutkowicz-Krusin  DFarber  MJ  et al.  The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas. Arch Dermatol 2008;144 (4) 476- 482
PubMed Link to Article
Tsao  HBevona  CGoggins  WQuinn  T The transformation rate of moles (melanocytic nevi) into cutaneous melanoma: a population-based estimate. Arch Dermatol 2003;139 (3) 282- 288
PubMed Link to Article
Schäfer  TMerkl  JKlemm  EWichmann  HERing  JKORA Study Group, The epidemiology of nevi and signs of skin aging in the adult general population: results of the KORA-survey 2000. J Invest Dermatol 2006;126 (7) 1490- 1496
PubMed Link to Article
Cohen  MHCohen  BJShotkin  JDMorrison  PT Surgical prophylaxis of malignant melanoma. Ann Surg 1991;213 (4) 308- 314
PubMed Link to Article
English  DRDel Mar  CBurton  RC Factors influencing the number needed to excise: excision rates of pigmented lesions by general practitioners. Med J Aust 2004;180 (1) 16- 19
PubMed
Collas  HDelbarre  MDe Preville  PA  et al. Dermatologists of the Postgraduate Association of Haute-Normandie, Evaluation of the diagnosis of pigmented tumors of the skin and factors leading to a decision to excise. Ann Dermatol Venereol 1999;126 (6-7) 494- 500
PubMed
Nathansohn  NOrenstein  ATrau  HLiran  ASchachter  J Pigmented lesions clinic for early detection of melanoma: preliminary results. Isr Med Assoc J 2007;9 (10) 708- 712
PubMed
Fuller  SRBowen  GMTanner  BFlorell  SRGrossman  D Digital dermoscopic monitoring of atypical nevi in patients at risk for melanoma. Dermatol Surg 2007;33 (10) 1198- 1206
PubMed Link to Article
Robinson  JKNickoloff  BJ Digital epiluminescence microscopy monitoring of high-risk patients. Arch Dermatol 2004;140 (1) 49- 56
PubMed
Banky  JPKelly  JWEnglish  DRYeatman  JMDowling  JP Incidence of new and changed nevi and melanomas detected using baseline images and dermoscopy in patients at high risk for melanoma. Arch Dermatol 2005;141 (8) 998- 1006
PubMed Link to Article
Menzies  SWBischof  LTalbot  H  et al.  The performance of SolarScan: an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma. Arch Dermatol 2005;141 (11) 1388- 1396
PubMed Link to Article

Figures

Place holder to copy figure label and caption
Figure

Biopsy decisions by 39 dermatologists participating in the pilot reader study. Small black circles represent individual readers; big black circles, pairs of readers; and the diamond, examining clinicians in the clinical trial on the same set of lesions.

Graphic Jump Location

Tables

Table Graphic Jump LocationTable 1 Algorithm for Final Histologic Diagnosisa
Table Graphic Jump LocationTable 2 Demographic Characteristics of Enrolled Patients and Patients With Eligible and Evaluable Lesionsa
Table Graphic Jump LocationTable 3 The Histologic Reference Standard for all Eligible and Evaluable Lesions
Table Graphic Jump LocationTable 4 Dermatologic and Histologic Diagnoses of Evaluable Lesions
Table Graphic Jump LocationTable 5 Sensitivity and Specificity of MelaFinda Biopsy Recommendation
Table Graphic Jump LocationTable 6 Summary of the Biopsy Performance (Pooled) of MelaFinda for All Eligible and Evaluable Lesions With Any Prebiopsy Diagnosis

References

Jemal  ASiegel  RWard  EHao  YXu  JThun  MJ Cancer statistics, 2009. CA Cancer J Clin 2009;59 (4) 225- 249
PubMed Link to Article
Cockburn  MSwetter  SMPeng  DKeegan  THDeapen  DClarke  CA Melanoma underreporting: why does it happen, how big is the problem, and how do we fix it? J Am Acad Dermatol 2008;59 (6) 1081- 1085
PubMed Link to Article
Rigel  DSFriedman  RJKopf  AWPolsky  D ABCDE: an evolving concept in the early detection of melanoma. Arch Dermatol 2005;141 (8) 1032- 1034
PubMed Link to Article
Tsao  HAtkins  MBSober  AJ Management of cutaneous melanoma. N Engl J Med 2004;351 (10) 998- 1012
PubMed Link to Article
Abbasi  NRShaw  HMRigel  DS  et al.  Early diagnosis of cutaneous melanoma: revisiting the ABCD criteria. JAMA 2004;292 (22) 2771- 2776
PubMed Link to Article
Thomas  LTranchand  PBerard  FSecchi  TColin  CMoulin  G Semiological value of ABCDE criteria in the diagnosis of cutaneous pigmented tumors. Dermatology 1998;197 (1) 11- 17
PubMed Link to Article
Grob  JJBonerandi  JJ The ‘ugly duckling’ sign: identification of the common characteristics of nevi in an individual as a basis for melanoma screening. Arch Dermatol 1998;134 (1) 103- 104
PubMed Link to Article
Arumi-Uria  MMcNutt  NSFinnerty  B Grading of atypia in nevi: correlation with melanoma risk. Mod Pathol 2003;16 (8) 764- 771
PubMed Link to Article
Cook  MGClarke  TJHumphreys  S  et al.  The evaluation of diagnostic and prognostic criteria and the terminology of thin cutaneous malignant melanoma by the CRC Melanoma Pathology Panel. Histopathology 1996;28 (6) 497- 512
PubMed Link to Article
Kossard  S Atypical lentiginous junctional naevi of the elderly and melanoma. Australas J Dermatol 2002;43 (2) 93- 101
PubMed Link to Article
Kelley  SWCockerell  CJ Sentinel lymph node biopsy as an adjunct to management of histologically difficult to diagnose melanocytic lesions: a proposal. J Am Acad Dermatol 2000;42 (3) 527- 530
PubMed Link to Article
Farmer  ERGonin  RHanna  MP Discordance in the histopathologic diagnosis of melanoma and melanocytic nevi between expert pathologists. Hum Pathol 1996;27 (6) 528- 531
PubMed Link to Article
Corona  RMele  AAmini  M  et al.  Interobserver variability on the histopathologic diagnosis of cutaneous melanoma and other pigmented skin lesions. J Clin Oncol 1996;14 (4) 1218- 1223
PubMed
Veenhuizen  KCDe Wit  PEMooi  WJScheffer  EVerbeek  ALRuiter  DJ Quality assessment by expert opinion in melanoma pathology: experience of the pathology panel of the Dutch Melanoma Working Party. J Pathol 1997;182 (3) 266- 272
PubMed Link to Article
Gutkowicz-Krusin  DElbaum  MSzwajkowski  PKopf  AW Can early malignant melanoma be differentiated from atypical melanocytic nevi by in-vivo techniques? part II: automatic machine vision classification. Skin Res Technol 1997;3 (1) 15- 22
Link to Article
Elbaum  MKopf  AWRabinovitz  HS  et al.  Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: a feasibility study. J Am Acad Dermatol 2001;44 (2) 207- 218
PubMed Link to Article
Gutkowicz-Krusin  DElbaum  MJacobs  A  et al.  Precision of automatic measurements of pigmented skin lesion parameters with a MelaFind(TM) multispectral digital dermoscope. Melanoma Res 2000;10 (6) 563- 570
PubMed Link to Article
Gutkowicz-Krusin  DElbaum  MGreenebaum  MJacobs  A Systems and methods for the multispectral imaging and characterization of skin tissue. US Patent No. 6 208 749 B1 (March 27, 2001)
Gutkowicz-Krusin  DElbaum  MGreenebaum  MJacobs  ABogdan  A Systems and methods for the multispectral imaging and characterization of skin tissue. US Patent No. 6 081 612 (June 27, 2000)
Elbaum  M Computer-aided melanoma diagnosis. Dermatol Clin 2002;20 (4) 735- 747, x-xi
PubMed Link to Article
Gutkowicz-Krusin  DRabinovitz  HS Multispectral image analysis.  In: Soyer  HP, Argenziano  G, Hofmann-Wellenhof  R, Johr  RH, eds. Color Atlas of Melanocytic Lesions of the Skin. Berlin, Germany: Springer; 2007:52-56
Cormier  JNXing  YDing  M  et al.  Ethnic differences among patients with cutaneous melanoma. Arch Intern Med 2006;166 (17) 1907- 1914
PubMed Link to Article
Megahed  MSchön  MSelimovic  DSchön  MP Reliability of diagnosis of melanoma in situ.  Lancet 2002;359 (9321) 1921- 1922
PubMed Link to Article
Vollset  SE Confidence intervals for a binomial proportion. Stat Med 1993;12 (9) 809- 824
PubMed Link to Article
Bataille  VSasieni  PCurley  RKCook  MGMarsden  RA Melanoma yield, number of biopsies and missed melanomas in a British teaching hospital pigmented lesion clinic: a 9-year retrospective study. Br J Dermatol 1999;140 (2) 243- 248
PubMed Link to Article
Carli  PNardini  PCrocetti  EDe Giorgi  VGiannotti  B Frequency and characteristics of melanomas missed at a pigmented lesion clinic: a registry-based study. Melanoma Res 2004;14 (5) 403- 407
PubMed Link to Article
Beam  CALayde  PMSullivan  DC Variability in the interpretation of screening mammograms by US radiologists: findings from a national sample. Arch Intern Med 1996;156 (2) 209- 213
PubMed Link to Article
Johnson  CDToledano  AYHerman  BA  et al. American College of Radiology Imaging Network A6656, Computerized tomographic colonography: performance evaluation in a retrospective multicenter setting. Gastroenterology 2003;125 (3) 688- 695
PubMed Link to Article
Shapiro  MJames  WDKessler  R  et al.  Comparison of skin biopsy triage decisions in 49 patients with pigmented lesions and skin neoplasms: store-and-forward teledermatology vs face-to-face dermatology. Arch Dermatol 2004;140 (5) 525- 528
PubMed Link to Article
Warshaw  EMLederle  FAGrill  JP  et al.  Accuracy of teledermatology for pigmented neoplasms. J Am Acad Dermatol 2009;61 (5) 753- 765
PubMed Link to Article
Chen  SCPennie  MLKolm  P  et al.  Diagnosing and managing cutaneous pigmented lesions: primary care physicians versus dermatologists. J Gen Intern Med 2006;21 (7) 678- 682
PubMed Link to Article
Argenziano  GSoyer  HPChimenti  S  et al.  Dermoscopy of pigmented skin lesions: results of a consensus meeting via the Internet. J Am Acad Dermatol 2003;48 (5) 679- 693
PubMed Link to Article
Friedman  RJGutkowicz-Krusin  DFarber  MJ  et al.  The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas. Arch Dermatol 2008;144 (4) 476- 482
PubMed Link to Article
Tsao  HBevona  CGoggins  WQuinn  T The transformation rate of moles (melanocytic nevi) into cutaneous melanoma: a population-based estimate. Arch Dermatol 2003;139 (3) 282- 288
PubMed Link to Article
Schäfer  TMerkl  JKlemm  EWichmann  HERing  JKORA Study Group, The epidemiology of nevi and signs of skin aging in the adult general population: results of the KORA-survey 2000. J Invest Dermatol 2006;126 (7) 1490- 1496
PubMed Link to Article
Cohen  MHCohen  BJShotkin  JDMorrison  PT Surgical prophylaxis of malignant melanoma. Ann Surg 1991;213 (4) 308- 314
PubMed Link to Article
English  DRDel Mar  CBurton  RC Factors influencing the number needed to excise: excision rates of pigmented lesions by general practitioners. Med J Aust 2004;180 (1) 16- 19
PubMed
Collas  HDelbarre  MDe Preville  PA  et al. Dermatologists of the Postgraduate Association of Haute-Normandie, Evaluation of the diagnosis of pigmented tumors of the skin and factors leading to a decision to excise. Ann Dermatol Venereol 1999;126 (6-7) 494- 500
PubMed
Nathansohn  NOrenstein  ATrau  HLiran  ASchachter  J Pigmented lesions clinic for early detection of melanoma: preliminary results. Isr Med Assoc J 2007;9 (10) 708- 712
PubMed
Fuller  SRBowen  GMTanner  BFlorell  SRGrossman  D Digital dermoscopic monitoring of atypical nevi in patients at risk for melanoma. Dermatol Surg 2007;33 (10) 1198- 1206
PubMed Link to Article
Robinson  JKNickoloff  BJ Digital epiluminescence microscopy monitoring of high-risk patients. Arch Dermatol 2004;140 (1) 49- 56
PubMed
Banky  JPKelly  JWEnglish  DRYeatman  JMDowling  JP Incidence of new and changed nevi and melanomas detected using baseline images and dermoscopy in patients at high risk for melanoma. Arch Dermatol 2005;141 (8) 998- 1006
PubMed Link to Article
Menzies  SWBischof  LTalbot  H  et al.  The performance of SolarScan: an automated dermoscopy image analysis instrument for the diagnosis of primary melanoma. Arch Dermatol 2005;141 (11) 1388- 1396
PubMed Link to Article

Correspondence

CME


You need to register in order to view this quiz.
Submit a Comment

Multimedia

Some tools below are only available to our subscribers or users with an online account.

Web of Science® Times Cited: 31

Related Content

Customize your page view by dragging & repositioning the boxes below.

Articles Related By Topic
Related Collections
PubMed Articles