Screening and Non-Invasive Evaluative Devices for Melanoma Detection A Comparison of Commercially Available Devices and Dermoscopic Evaluation

TBP: Total Body Photography
SDDI: Sequential Digital Dermoscopic Imaging
CAD: Computer-Assisted Diagnostic
SIA: Spectrophotometric Intracutaneous Analysis
CSLM: Confocal Scanning Laser Microscopy
ADD: Automated Dermoscopic Diagnostic
PSL: Pigmented Skin Lesion

Population-wide screening for melanoma may lead to long-term decreases in melanoma-specific mortality [1]. Additionally, detection of melanoma at earlier stages reduces morbidity and mortality and curtails healthcare costs [2]. Despite these benefits the US Preventive Services Task Force doesn’t endorse regular screening exams for melanoma in the general population due to the relatively rare incidence [3]. Barriers to screening also exist in the form of limited patient access as well as the ability to quickly and objectively determine whether a nevus is new or changing [4].

Further complications in diagnosing melanoma arise when there is uncertainty as to whether a lesion is benign or malignant, as tissue must be procured by biopsy to secure the diagnosis through histological review. While skin biopsies are fairly low risk, morbidity exists in the form of pain, scarring, bleeding and infection [5,6]. Patients with numerous atypical nevi pose a particular dilemma, as there is increased morbidity and risk of complications as the number of biopsies performed increases. Considering that melanoma has the one of the highest propensities for mortality among skin cancers, most physicians would choose to biopsy any lesions in which melanoma enter the differential.

The difficulties in screening and diagnosing melanoma have led to the development of devices that assist with detection of melanoma. These devices have the potential to improve the diagnostic accuracy of physicians by offering objective review on screening as well as providing information not otherwise available to the non-equipped eye. This article aims to provide an overview of these devices with comparison to current standard methods of detection.

Devices for inclusion were identified through PubMed database search and review of prominent related articles. Additional information on cost and device availability was garnered through review of manufacturer’s websites and direct telephone contact. Widely available or soon to be commercially available devices with reported diagnostic accuracy were included for comparison. Sensitivity and specificity (and biopsy ratios when available) for each device was reported. Geometric means were used to calculate the average biopsy ratios as well as sensitivities and specificities since it is more accurate than the traditional mean when averaging normalized results.

For ease of review, devices have been separated into two main categories: 1) screening devices which are used to identify and monitor new or concerning lesions; 2) evaluative devices which are intended to assist the clinician with the appraisal of a previously identified atypical or concerning nevus.

Screening devices use image modalities to evaluate or monitor the temporal evolution of lesions and provide objective data for comparison. Sensitivity measures have not been calculated for many of the devices as it often takes long periods of follow up to determine whether melanomas were missed using the screening method. Screening devices are helpful for monitoring lesions in patients likely to follow up as mildly suspicious lesions can be monitored with short term follow up for signs of evolution.

Total Body Photography (TBP) is designed to screen for the emergence of de novo lesions or the evolution of existing lesions by imaging the entire body in sections, permitting comparison to a photographed baseline at subsequent visits. In contrast to Full Skin Exam (FSE) or other methods of comparison imaging where only existing nevi are noted, TBP offers the ability to objectively determine whether a lesion is new by imaging areas where nevi are absent at baseline. This particular strength is evidenced by 25-75% of melanomas detected using TBP which presented as de novo pigmented lesions, many of which had gone undetected by the patients themselves [7-11]. However, these advantages remain somewhat theoretical since no studies used control groups for comparison of detection rates with FSE and none of the studies presented de novo detection rates on FSE prior to TBP image comparison.

Another potential advantage of TBP is enhanced specificity by enabling the clinician to make more informed decisions about which lesions to biopsy. By objectively identifying changes in nevi, clinicians are able to better determine which changes necessitate biopsy and which changes are benign and amenable to continued monitoring. Biopsy ratios, presented as the number of benign nevi excised for every melanoma excised, provide a helpful comparison between detection methods. Unfortunately, the interdependence of both sensitivity and specificity make diagnostic accuracy indeterminable without knowing both, thus isolated biopsy ratios are of limited value. The challenges of prolonged monitoring necessary to detect false-negatives and the uncertainty whether melanoma was actually present at the time of exam (true false-negative) or had evolved post-screening (de novo melanoma arising in a nevus) makes the determination of sensitivity extremely challenging, and has consequently limited the number of studies available for comparison. If sensitivity could be standardized then reductions in biopsy ratios would be useful, but unfortunately determining a cutoff in sensitivity will remain an academic debate.

TBP has been primarily used to screen patients at high risk for developing melanoma (variably defined as patients with greater than 100 nevi, more than ten atypical nevi, personal history of melanoma, history of melanoma in two primary family members, history of severe dysplastic nevi, or a genetic condition that enhances melanoma risk) resulting in a mean benign-to-malignant biopsy ratio of 6.1:1 (range from 2.8:1 to 17:1 [7,8,10,12,13] see also (Table 1). One retrospective study compared TBP with a control group and found no significant difference in the number of biopsies performed per patient (0.82 without TBP versus 0.80 with TBP p = 0.43) [9]. However, interpretation of this retrospective study is limited by the small sample size (n=53 per arm) and the lack of any melanomas detected in the TBP group. Another challenge that arises when comparing biopsy ratios between trials is the variability in biopsy ratios according to melanoma prevalence in the sample. This effect is most pronounced when trying to interpret the biopsy ratio from Fiet et al., which yielded the lowest benign-to-malignant biopsy ratio (2.8:1) out of all screening devices [10]. The 100% prevalence created by inclusion of only patients who had melanoma detected on at least one biopsy makes comparisons to prospective trials impossible, even in the extremely high-risk groups. Unfortunately better methods of comparison are lacking given the challenges of prolonged monitoring necessary to detect false-negatives and the uncertainty whether melanoma was actually present at the time of exam (true false-negative) or had evolved post-screening (de novo or melanoma arising in a nevus). Another notable finding was the low benign-to-malignant biopsy ratios (3:1) reported in the trial by Banky et al., [3], which incorporated additional dermoscopic examination of suspicious Pigmented Skin Lesions (PSL) identified by TBP. Comparison to results from Kelly et al., [7], which used TBP alone in the same clinic and yielded a benign-to-malignant biopsy ratio of 9.5:1, suggests that follow-up dermoscopy in conjunction with TBP may reduce biopsy ratios. In summary, it is clear that TBP could play a role in enhancing melanoma detection in patients with at least one risk factor, but determining the cost effectiveness of this approach requires larger, prospective trials.

Table 1: Summary comparison of screening modalities.

SDDI represents another screening method that employs digitized dermoscopic images for objective comparison overtime. Individual lesions for SDDI are identified by the clinician on a screening examination and subsequently photographed in isolation. The ability to capture detailed images for comparing interval changes makes SDDI more sensitive than traditional photographic methods or dermoscopy alone. A large observational study found that a third of all melanomas detected using SDDI were not detected by other methods of screening, providing strong support for the utility of this approach [22]. Furthermore, in patients at high risk for melanoma, SDDI detected invasive melanomas with a significantly lower mean Breslow depth (0.41 for SDDI versus 0.62 mm using other methods; p=0.04) [23]. While these results appear promising, another study comparing SDDI to TBP found that SDDI resulted in a significantly higher number of biopsies per patient (1.1 with SDDI versus 0.59 for TBP; p <0.001), possible lower melanoma detection rates (2.2% with SDDI versus 5.5% with TBP; p = 0.088) and longer estimated times for clinic appointments [7]. Two studies examining the use of SDDI in patients without at least one risk factor for melanoma (representing a low-risk population) failed to identify any malignancies despite median follow up durations of 6 and 24 months [30,31]. These results, in conjunction with the high biopsy ratio of 79:1 in the low risk arm of the Haenssle et al., trial; suggest that SDDI is of most utility in the high-risk groups [23]. Currently, it is unclear whether the improvements in diagnosis by SDDI would offset potential increases in healthcare costs from additional biopsies and longer clinic visits.

TBP has also been used in conjunction with SDDI for more detailed evaluation and comparison of identified lesions. Studies using TBP once for baseline images, dermoscopy for de novo interval lesions, and SDDI for monitoring suspicious lesions between visits have yielded benign-to-malignant ratios ranging from 5.4:1 to 18.4:1[22-24]. Two studies examining sequential TBP with SDDI (TBP and SDDI on each visit) yielded ratios of 4.2:1[11] and 10.7:1[25]. The geometric mean of benign-to-malignant biopsy ratios for TBP without SDDI is 6.1:1 vs. 8.2:1 for combined TBP and SDDI (including TBP for baseline imaging). However the limited number of trials, variability in prevalence, and study designs make meaningful comparison very difficult without data from prospective comparative trials.

Screening devices have demonstrated utility in the ability to provide objective evidence of lesion evolution or novelty and are most valuable in screening patients with numerous nevi that are at higher risk for melanoma. Some of the largest limitations of the devices include the cost of use, patient modesty while obtaining images, as well as the time needed to gather and compare images. Due to the time constraints and cost it seems unlikely that population wide screening would be practical using these methods. Another limitation that originates from the provider using the device rather than the device itself is the subjectivity of the clinician’s decision to biopsy or monitor a lesion once detected. Further research should be aimed at determining what criteria would enable safe monitoring while limiting unnecessary biopsies.

Evaluative devices provide diagnostic information not available to the clinician by examination with the unaided eye. Methods of obtaining this information include use of higher levels of magnification, using polarized and different wavelengths of light to highlight features associated with malignancy, as well as analysis of genetic material for aberrations associated with melanoma. The intended use of the evaluative device is as an adjunct to assist with the decision to biopsy, as histological examination of tissue remains the gold standard for diagnosis.

Multiple studies have shown that dermatologists trained in dermoscopy with two or more years of clinical experience with the device had superior diagnostic accuracy compared to unaided visual examination [32-34]. Dermoscopy (also called epiluminescence microscopy) improves biopsy ratios by enhancing the diagnostic confidence of providers, and has been extensively reviewed in the literature [35,36]. Melanoma diagnosis with dermoscopy is subjective and varies with provider experience [30,37,38]. Consequently, Automated Dermoscopic Diagnostic (ADD) programs have been applied to dermoscopy images in an attempt to reduce subjective analysis. In general, ADD programs analyze an imaged lesion for malignancy-associated features that are weighted, summed and then compared to a predetermined (usually experimentally-obtained) cut-off score to differentiate between benign and malignant lesions. Two meta-analyses comparing the accuracy of ‘expert-implemented’ dermoscopy to ADD found no significant difference between the two [39,40]. While sensitivity for melanoma between expert dermoscopists and ADD was equivalent, dermoscopy specificity was significantly better than ADD (86% compared to 78% P < 0.001) [40]. In-clinic comparison of three different ADD devices revealed an inability of all devices to reliably discriminate dysplastic nevi from early melanoma, resulting in a greater number of unnecessary biopsies.

MelaFind (Electro-Optical Sciences Inc., Irvington, NY) is an FDA-approved device (limited to use by dermatologists only) that analyzes ten images from different spectra and then provides a recommendation to biopsy or monitor the lesion. The use of multispectral digital dermoscopy by Melafind enables the characterization of certain morphologies otherwise imperceptible on dermoscopic exam. In addition to melanoma, MelaFind also recommends severely atypical nevi for biopsy. MelaFind’s reported sensitivity and specificity for melanoma are 92-100% and 9.9-85%, respectively (Table 2) [41-43]. Comparison of MelaFind to experienced dermoscopists yielded a biopsy sensitivity and specificity for melanoma of 98% and 44% for MelaFind compared to 71% and 49% for dermoscopy [43]. The accuracy for dermoscopy in this study was notably lower than in prior meta-analyses, and the authors postulated that the lower specificities might be due to the inclusion of a greater proportion of smaller melanomas (<6mm). Another multi-center, prospective RCT found a biopsy sensitivity of 98.4% and specificity of 9.9% for MelaFind [42]. Study authors explained the low rates of specificity as a product of utilizing lesions pre-selected by clinical exam for biopsy. By comparison, trial data generated estimates of 98% sensitivity and 7% specificity for melanoma diagnosis by participating dermatologists. In another study where dermatologists blinded to the results of MelaFind scans were asked to evaluate PSLs, sensitivities for melanoma were 96% for MelaFind and 80% for dermatologists, while specificities were 8% and 43%, respectively [44]. MelaFind was found to increase biopsy sensitivity for melanoma from 69% to 94% if providers integrated the results of their clinical exam with a MelaFind scan, while biopsy specificity for melanoma decreased from 54% to 40% [45]. Unfortunately, the generalizability of findings from the studies on MelaFind remains limited, as all participating clinicians were asked to make a diagnosis based on images of lesions previously biopsied. Consequently real-life sensitivities and specificities for use in the clinic are difficult to extrapolate from existing studies. More trials with in-clinic use comparing the diagnostic accuracy of MelaFind with existing techniques are necessary before a full recommendation can be made for its regular use.

SIAscopy (Astron Clinica, Lake Success, NY) is another FDA-approved device that uses spectral data to gather information regarding collagen, hemoglobin content, melanin, and melanin distribution in the dermis and epidermis. While MelaFind provides recommendations to biopsy or monitor, SIAscopic data is presented in graphs that the provider interprets and incorporates in his/her decision to biopsy or monitor. Software (MoleMate or SIMSYS, MedX corp.) can be added to SIAscopic information to assist the provider with interpretation of images by providing an interactive decision tree to guide lesion management. The SIMSYS system also provides the capability of scoring lesions according to a 7-point dermoscopy checklist and saving the data for later comparison. Sensitivity and specificity for melanoma with SIAscopy ranges from 81-100% and 59-91% respectively [46-50,58]. A prospective study comparing SIAscopy to dermoscopy found no significant difference between sensitivity of the two methods for melanoma diagnosis, although calculated positive likelihood ratios were higher for dermoscopy (5 compared to 2.45 with SIAscopy) suggesting it is overall a more accurate diagnostic test than SIAscopy [48]. In light of two other studies that also found no significant difference in melanoma diagnosis between an experienced dermoscopist and SIAscopy [46,58], the utility of SIAscopy in dermatologic practice appears to be limited given its subjectivity and the absence of significant improvements in diagnostic accuracy. Another potential limitation of SIAscopy is that hyperkeratosis has been interpreted as dermal melanin, yielding false positive results [59].

Raman spectroscopy is a rapid, non-invasive, non-destructive technique that uses laser light to characterize tissue composition based on changes in molecular bonds. This technology is based on the theory that melanoma can be differentiated from other types of tissue based on its molecular signature. A study on the in vivo use of a handheld Raman spectrographic device (Verisante Aura) for melanoma detection reported specificities ranging from 15-54% depending on selected sensitivities which ranged from 90-99% [51]. No studies directly comparing the accuracy of trained dermatologists to this technique have been published, and consequently it is unclear if spectroscopic diagnosis is any better than dermoscopy. Other limitations that will need to be factored into device utility in the future include a clinician’s ability to become facile with interpreting the graphic representation of this type of data. The device has already been approved for sale in Canada, Europe and Australia with estimated commercial availability in late 2012, and could eventually make its way to the US marketplace.

Confocal Scanning Laser Microscopy (CSLM) uses lasers and high-resolution optics to visualize tissue morphology on a cellular level in vivo, non-invasively, and in real time. The best-known device in this class is the FDA-approved Vivascope (Lucid, Inc, Rochester, NY). CSLM penetrates deep enough to visualize the stratum corneum to the upper papillary dermis with resolution slightly inferior to conventional light microscopy [60-63]. CSLM can be used in two modes, Reflectance (RCM) and fluorescence, with reflectance mode more suitable for clinical use as it visualizes melanin well and fluorescence requires the use of markers [64]. Like other evaluative devices, RCM requires lesion selection and scanning by the clinician. Images can either be interpreted in real-time by a clinician who has undergone training in interpreting images, or can transmitted to specialized dermatopathologist trained to read RCM images with interpretation of images within 24 hours [65]. The reported sensitivity and specificity of RCM for melanoma ranges from 88%-92% and 69%-98%, respectively [53-55]. A direct comparison of dermoscopy to RCM found no significant difference between the sensitivity and specificity for melanoma between these two methods [56]. Attempts have also been made to integrate automated computer analysis with RCM images and have resulted in 93.6% sensitivity and 90.4% specificity for melanoma detection in learning sets [66]. An additional strength of RCM is the ability to identify amelanotic lesions [67] and early melanoma in situ with a sensitivity of 85% and specificity of 76% for these tumors [68,69]. Limitations to the clinical use of RCM include a lack of prospective in-clinic assessment as all studies have been retrospective and used pre-selected images (which may have been selected based on ease of identifying morphology). The lowest priced Vivascope costs $70,000, so RCM may be a financially limiting for many clinicians in standard practice (Table 3). Despite these limitations, RCM remains promising, as it could also be useful for delineating tumor borders in vivo for excisions, and offers the chance for real-time histologic diagnosis.

Costs via website and direct contact with manufactures. Ranges are given as cost and capabilities of devices vary depending on hardware selected and the integration of different software packages.

Tape stripping is a non-invasive, relatively painless method for recovering cells that can be examined for gene expression profiles indicative of melanoma. In this method tape is applied to the pigmented lesion and the borders are outlined. Removal of the tape strips a layer of cells from the stratum corneum, providing RNA for genetic analysis. The commercialized version of this technique has been developed by DermTech (LaJolla, CA) and is called the Epidermal Genetic Information Retrieval (EGIR) system. Using EGIR and a 17-gene classification signature, researchers were able to identify melanomas in a 128 lesion test set with 100% sensitivity and 88% specificity [57]. EGIR analysis of control samples taken from normal skin (n=79), solar lentigenies (n=22) and basal cell carcinoma (n=18) was able to identify all but one BCC lesion as non-melanoma. Interestingly, additional review of the 13 false positives by two separate dermatopathologist also identified a superficial spreading melanoma missed on initial reads. The combination of a sensitivity superior to any other examination technique with a specificity equivalent to a skilled dermatopathologist in early trials of EGIR make it a promising modality for evaluating pigmented lesions. Larger clinical trials on diagnostically challenging lesions are necessary to verify its efficacy. Limitations of the technique include a potential inability to accurately test patients who have eczema, photosensitivity, psoriasis, allergies to tape or latex, or used topical steroids on the lesion within the last 30 days as well as the use of lotion or sunscreen in the previous 24 hours. EGIR is not yet on the market but is projected to be available soon. Sample results are expected to be available in 5-7 days, with no cost yet reported.

Evaluative devices are able to provide additional information about atypical pigmented lesions which can enhance the diagnostic accuracy of the user. The degree of utility however, is highly dependent on the skill of the provider in diagnosing PSL and their proficiency with a dermatoscope. Providers with minimal experience diagnosing PSL stand to benefit the most by using devices to enhance diagnostic accuracy. By contrast, a dermatologist facile with a dermatoscope would receive little enhancement in diagnostic accuracy with their use. Given the relatively low cost, portability of a dermatoscope and equivalent diagnostic accuracy in trained users, such individuals may have less of a need for other evaluative devices.

It should be noted that the lack of a standardized lesion set to compare evaluative devices limits the scope of comparison; however general conclusions can still be made. For instance, it is clear that the majority of evaluative devices sacrifice specificity to enhance overall sensitivity. While the thresholds of sensitivity and specificity in the decision to biopsy an atypical lesion will remain an ongoing debate, providers should be cognizant of this trade-off when employing these devices. Lastly, it will be important to continue to re-examine the utility and cost effectiveness of devices as new technology and algorithms become available.

The use of screening devices enhances the sensitivity of the clinician to detect new and changing lesions, however these devices are most limited by cost and the time constraints required to take images and review them. Selecting patients at highest risk for melanoma will be essential to maximize the utility of screening devices. Similarly, despite recent technical advances and innovations in evaluative devices, these methods have not established significantly improved accuracy compared to a dermatologist experienced with the dermatoscope. In their current state, non-dermoscopic devices perpetuate the existing problem in diagnosing melanoma, and may not warrant the additional costs of implementation. Consequently, greater efforts should be taken to integrate dermoscopy into dermatologic practice.

Alternatively, the high sensitivity of evaluative devices could be useful to the primary care provider trying to screen lesions for referrals. Use of these devices in primary care are already a subject of debate and raise questions regarding the role of the provider in triaging, diagnosing and managing skin lesions. Further investigation of the use of these devices in primary care remains warranted, and energy should be devoted to whether their employment improves dermatologic access to the general population without compromising the quality of care otherwise received from the dermatologist.

1. Breitbart EW, Waldmann A, Nolte S, Capellaro M, Greinert R, et al. (2012) Systematic skin cancer screening in Northern Germany. J Am Acad Dermatol 66: 201-211.
2. Mitchell JK, Leslie KS (2013) Melanoma death prevention: moving away from the sun. J Am Acad Dermatol 68: 169-175.
3. Wolff T, Tai E, Miller T (2009) Screening for skin cancer: an update of the evidence for the US Preventive Services Task Force. Ann Intern Med 150: 194-198.
4. Federman DG, Kravetz JD, Kirsner RS (2002) Skin cancer screening by dermatologists: prevalence and barriers. J Am Acad Dermatol 46: 710-714.
5. Amici JM, Rogues AM, Lasheras A, Gachie JP, Guillot P, et al. (2005) A prospective study of the incidence of complications associated with dermatological surgery. Br J Dermatol 153: 967-971.
6. Wahie S, Lawrence CM (2007) Wound complications following diagnostic skin biopsies in dermatology inpatients. Arch Dermatol 143: 1267-1271.
7. Goodson AG, Florell SR, Hyde M, Bowen GM, Grossman D (2010) Comparative analysis of total body and dermatoscopic photographic monitoring of nevi in similar patient populations at risk for cutaneous melanoma. Dermatol Surg 36: 1087-1098.
8. Banky JP, Kelly JW, English DR, Yeatman JM, Dowling JP (2005) Incidence of new and changed nevi and melanomas detected using baseline images and dermoscopy in patients at high risk for melanoma. Arch Dermatol 141: 998-1006.
9. Risser J, Pressley Z, Veledar E, Washington C, Chen SC (2007) The impact of total body photography on biopsy rate in patients from a pigmented lesion clinic. J Am Acad Dermatol 57: 428-434.
10. Feit NE, Dusza SW, Marghoob AA (2004) Melanomas detected with the aid of total cutaneous photography. Br J Dermatol 150: 706-714.
11. Malvehy J, Puig S (2002) Follow-up of melanocytic skin lesions with digital total-body photography and digital dermoscopy: a two-step method. Clin Dermatol 20: 297-304.
12. Kelly JW, Yeatman JM, Regalia C, Mason G, Henham AP (1997) A high incidence of melanoma found in patients with multiple dysplastic naevi by photographic surveillance. Med J Aust 167: 191-194.
13. Lucas CR, Sanders LL, Murray JC, Myers SA, Hall RP, et al. (2003) Early melanoma detection: nonuniform dermoscopic features and growth. J Am Acad Dermatol 48: 663-671.
14. Fuller SR, Bowen GM, Tanner B, Florell SR, Grossman D (2007) Digital dermoscopic monitoring of atypical nevi in patients at risk for melanoma. Dermatol Surg 33: 1198-1206.
15. Bauer J, Blum A, Strohhäcker U, Garbe C (2005) Surveillance of patients at high risk for cutaneous malignant melanoma using digital dermoscopy. Br J Dermatol 152: 87-92.
16. Haenssle HA, Vente C, Bertsch HP, Rupprecht R, Abuzahra F, et al. (2004) Results of a surveillance programme for patients at high risk of malignant melanoma using digital and conventional dermoscopy. Eur J Cancer Prev 13: 133-138.
17. Argenziano G, Mordente I, Ferrara G, Sgambato A, Annese P, et al. (2008) Dermoscopic monitoring of melanocytic skin lesions: clinical outcome and patient compliance vary according to follow-up protocols. Br J Dermatol 159: 331-336.
18. Robinson JK, Nickoloff BJ (2004) Digital epiluminescence microscopy monitoring of high-risk patients. Arch Dermatol 140: 49-56.
19. Kittler H, Pehamberger H, Wolff K, Binder M (2000) Follow-up of melanocytic skin lesions with digital epiluminescence microscopy: patterns of modifications observed in early melanoma, atypical nevi, and common nevi. J Am Acad Dermatol 43: 467-476.
20. Menzies SW, Gutenev A, Avramidis M, Batrac A, McCarthy WH (2001) Short-term digital surface microscopic monitoring of atypical or changing melanocytic lesions. Arch Dermatol 137: 1583-1589.
21. Altamura D, Avramidis M, Menzies SW (2008) Assessment of the optimal interval for and sensitivity of short-term sequential digital dermoscopy monitoring for the diagnosis of melanoma. Arch Dermatol 144: 502-506.
22. Haenssle HA, Krueger U, Vente C, Thoms KM, Bertsch HP, et al. (2006) Results from an observational trial: digital epiluminescence microscopy follow-up of atypical nevi increases the sensitivity and the chance of success of conventional dermoscopy in detecting melanoma. J Invest Dermatol 126: 980-985.
23. Haenssle HA, Korpas B, Hansen-Hagge C, Buhl T, Kaune KM, et al. (2010) Selection of patients for long-term surveillance with digital dermoscopy by assessment of melanoma risk factors. Arch Dermatol 146: 257-264.
24. Kovalyshyn I, Dusza SW, Siamas K, Halpern AC, Argenziano G, et al. (2011) The impact of physician screening on melanoma detection. Arch Dermatol 147: 1269-1275.
25. Salerni G, Carrera C, Lovatto L, Puig-Butille JA, Badenas C, et al. (2012) Benefits of total body photography and digital dermatoscopy (“two-step method of digital follow-up”) in the early diagnosis of melanoma in patients at high risk for melanoma. J Am Acad Dermatol 67: 17-27.
26. Sidhu S, Bodger O, Williams N, Roberts DL (2012) The number of benign moles excised for each malignant melanoma: the number needed to treat. Clin Exp Dermatol 37: 6-9.
27. Chia AL, Simonova G, Dutta B, Lim A, Shumack S (2008) Melanoma diagnosis: Australian dermatologists’ number needed to treat. Australas J Dermatol 49: 12-15.
28. Argenziano G, Cerroni L, Zalaudek I, Staibano S, Hofmann-Wellenhof R, et al. (2012) Accuracy in melanoma detection: a 10-year multicenter survey. J Am Acad Dermatol 67: 54-59.
29. Marks R, Jolley D, McCormack C, Dorevitch AP (1997) Who removes pigmented skin lesions? J Am Acad Dermatol 36: 721-726.
30. Schiffner R, Wilde O, Schiffner-Rohe J, Stolz W (2003) Difference between real and perceived power of dermoscopical methods for detection of malignant melanoma. Eur J Dermatol 13: 288-293.
31. Braun RP, Lemonnier E, Guillod J, Skaria A, Salomon D, et al. (1998) Two types of pattern modification detected on the follow-up of benign melanocytic skin lesions by digitized epiluminescence microscopy. Melanoma Res 8: 431-437.
32. Nachbar F, Stolz W, Merkle T, Cognetta AB, Vogt T, et al. (1994) The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. J Am Acad Dermatol 30: 551-559.
33. Vestergaard ME, Macaskill P, Holt PE, Menzies SW (2008) Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting. Br J Dermatol 159: 669-676.
34. Bafounta ML, Beauchet A, Aegerter P, Saiag P (2001) Is dermoscopy (epiluminescence microscopy) useful for the diagnosis of melanoma? Results of a meta-analysis using techniques adapted to the evaluation of diagnostic tests. Arch Dermatol. 137: 1343-1350.
35. Terushkin V, Oliveria SA, Marghoob AA, Halpern AC (2010) Use of and beliefs about total body photography and dermatoscopy among US dermatology training programs: an update. J Am Acad Dermatol 62: 794-803.
36. Benvenuto-Andrade C, Dusza SW, Hay JL, Agero AL, Halpern AC, et al. (2006) Level of confidence in diagnosis: clinical examination versus dermoscopy examination. Dermatol Surg 32: 738-744.
37. Binder M, Schwarz M, Winkler A, Steiner A, Kaider A, et al. (1995) Epiluminescence microscopy. A useful tool for the diagnosis of pigmented skin lesions for formally trained dermatologists. Arch Dermatol 131: 286-291.
38. Kittler H, Pehamberger H, Wolff K, Binder M (2002) Diagnostic accuracy of dermoscopy. Lancet Oncol 3: 159-165.
39. Rosado B, Menzies S, Harbauer A, Pehamberger H, Wolff K, et al. (2003) Accuracy of computer diagnosis of melanoma: a quantitative meta-analysis. Arch Dermatol 139: 361-367.
40. Rajpara SM, Botello AP, Townend J, Ormerod AD (2009) Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma. Br J Dermatol 161: 591-604.
41. Elbaum M, Kopf AW, Rabinovitz HS, Langley RG, Kamino H, et al. (2001) Automatic differentiation of melanoma from melanocytic nevi with multispectral digital dermoscopy: a feasibility study. J Am Acad Dermatol 44: 207-218.
42. Monheit G, Cognetta AB, Ferris L, Rabinovitz H, Gross K, et al. (2011) The performance of MelaFind: a prospective multicenter study. Arch Dermatol 147: 188-194.
43. Friedman RJ, Gutkowicz-Krusin D, Farber MJ, Warycha M, Schneider-Kels L, et al. (2008) The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas. Arch Dermatol 144: 476-482.
44. Wells R, Gutkowicz-Krusin D, Veledar E, Toledano A, Chen SC (2012) Comparison of diagnostic and management sensitivity to melanoma between dermatologists and MelaFind: a pilot study. Arch Dermatol 148: 1083-1084.
45. Rigel DS, Roy M, Yoo J, Cockerell CJ, Robinson JK, et al. (2012) Impact of guidance from a computer-aided multispectral digital skin lesion analysis device on decision to biopsy lesions clinically suggestive of melanoma. Arch Dermatol 148: 541-543.
46. Haniffa MA, Lloyd JJ, Lawrence CM (2007) The use of a spectrophotometric intracutaneous analysis device in the real-time diagnosis of melanoma in the setting of a melanoma screening clinic. Br J Dermatol. England 156: 1350-1352.
47. Moncrieff M, Cotton S, Claridge E, Hall P (2002) Spectrophotometric intracutaneous analysis: a new technique for imaging pigmented skin lesions. Br J Dermatol 146: 448-457.
48. Glud M, Gniadecki R, Drzewiecki KT (2009) Spectrophotometric intracutaneous analysis versus dermoscopy for the diagnosis of pigmented skin lesions: prospective, double-blind study in a secondary reference centre. Melanoma Res 19: 176-179.
49. Tomatis S, Carrara M, Bono A, Bartoli C, Lualdi M, et al. (2005) Automated melanoma detection with a novel multispectral imaging system: results of a prospective study. Phys Med Biol 50: 1675-1687.
50. Carrara M, Bono A, Bartoli C, Colombo A, Lualdi M, et al. (2007) Multispectral imaging and artificial neural network: mimicking the management decision of the clinician facing pigmented skin lesions. Phys Med Biol 52: 2599-2613.
51. Lui H, Zhao J, McLean D, Zeng H (2012) Real-time Raman spectroscopy for in vivo skin cancer diagnosis. Cancer Res 72: 2491-2500.
52. Gniadecka M, Philipsen PA, Sigurdsson S, Wessel S, Nielsen OF, et al. (2004) Melanoma diagnosis by Raman spectroscopy and neural networks: structure alterations in proteins and lipids in intact cancer tissue. J Invest Dermatol 122: 443-449.
53. Gerger A, Koller S, Kern T, Massone C, Steiger K, et al. (2005) Diagnostic applicability of in vivo confocal laser scanning microscopy in melanocytic skin tumors. J Invest Dermatol 124: 493-498.
54. Pellacani G, Cesinaro AM, Seidenari S (2005) Reflectance-mode confocal microscopy of pigmented skin lesions--improvement in melanoma diagnostic specificity. J Am Acad Dermatol 53: 979-985.
55. Pellacani G, Guitera P, Longo C, Avramidis M, Seidenari S, et al. (2007) The impact of in vivo reflectance confocal microscopy for the diagnostic accuracy of melanoma and equivocal melanocytic lesions. J Invest Dermatol 127: 2759-2765.
56. Langley RG, Walsh N, Sutherland AE, Propperova I, Delaney L, et al. (2007) The diagnostic accuracy of in vivo confocal scanning laser microscopy compared to dermoscopy of benign and malignant melanocytic lesions: a prospective study. Dermatology 215: 365-372.
57. Wachsman W, Morhenn V, Palmer T, Walls L, Hata T, et al. (2011) Noninvasive genomic detection of melanoma. Br J Dermatol 164: 797-806.
58. Powell J, Moncrieff M, Hall P (2002) A comparison between dematoscopy and Spectrophotometric Intracutaneous Analysis (SIAscopy) for the diagnosis of melanoma. Addenbrooke’s Hospital, Cambridge, USA.
59. Hall PN, Hunter JE, Walter FM, Norris P (2008) Use of a spectrophotometric intracutaneous analysis device in the real-time diagnosis of melanoma. Br J Dermatol 158: 420-421.
60. Rajadhyaksha M, González S, Zavislan JM, Anderson RR, Webb RH (1999) In vivo confocal scanning laser microscopy of human skin II: advances in instrumentation and comparison with histology. J Invest Dermatol 113: 293-303.
61. Rajadhyaksha M, Anderson RR, Webb RH (1999) Video-rate confocal scanning laser microscope for imaging human tissues in vivo. Appl Opt 38: 2105-2115.
62. Calzavara-Pinton P, Longo C, Venturini M, Sala R, Pellacani G (2008) Reflectance confocal microscopy for in vivo skin imaging. Photochem Photobiol 84: 1421-1430.
63. Gareau DS, Li Y, Huang B, Eastman Z, Nehal KS, et al. (2008) Confocal mosaicing microscopy in Mohs skin excisions: feasibility of rapid surgical pathology. J Biomed Opt 13: 054001.
64. Meyer LE, Otberg N, Sterry W, Lademann J (2006) In vivo confocal scanning laser microscopy: comparison of the reflectance and fluorescence mode by imaging human skin. J Biomed Opt 11: 044012.
65. O’Donnell AT, Kim CC (2012) Update and clinical use of imaging technologies for pigmented lesions of the skin. Semin Cutan Med Surg 31: 38-44.
66. Koller S, Wiltgen M, Ahlgrimm-Siess V, Weger W, Hofmann-Wellenhof R, et al. (2011) In vivo reflectance confocal microscopy: automated diagnostic image analysis of melanocytic skin tumours. J Eur Acad Dermatol Venereol 25: 554-558.
67. Busam KJ, Hester K, Charles C, Sachs DL, Antonescu CR, et al. (2001) Detection of clinically amelanotic malignant melanoma and assessment of its margins by in vivo confocal scanning laser microscopy. Arch Dermatol 137: 923-929.
68. Ahlgrimm-Siess V, Massone C, Scope A, Fink-Puches R, Richtig E, et al. (2009) Reflectance confocal microscopy of facial lentigo maligna and lentigo maligna melanoma: a preliminary study. Br J Dermatol 161: 1307-1316.
69. Guitera P, Pellacani G, Crotty KA, Scolyer RA, Li LX, et al. (2010) The impact of in vivo reflectance confocal microscopy on the diagnostic accuracy of lentigo maligna and equivocal pigmented and nonpigmented macules of the face. J Invest Dermatol 130: 2080-2091.