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About the Author

Michael Copley

Michael Copley, MD, PhD, FRCPC

Dr. Michael Copley is a medical dermatologist with dual board-certification in Canada and the United States. He also holds a PhD in Experimental Medicine from the University of British Columbia (UBC) and maintains a keen interest in both clinical and basic research. As a clinical instructor within UBC’s Department of Dermatology and Skin Science, he is passionate about both undergraduate and graduate level dermatology education. His clinical interests include skin cancer, autoimmune diseases of the skin and telemedicine.

Canadian Dermatology Today, Volume 2, Issue 4, December 2021

Non-Invasive Diagnostic Technologies for Melanoma

Clinical examination followed by excisional biopsy and histopathologic analysis of suspicious pigmented lesions remains the gold-standard for melanoma diagnosis. Unfortunately, the performance of the unaided “melanoma detection pathway” is far from optimal with dermatologists demonstrating only 63.6% sensitivity1 and primary care physicians only 40.2% sensitivity for correct melanoma identification2 in a community-based screening setting. The accuracy of unaided melanoma detection is also low with a number needed to excise (NNE), defined as the number of suspicious lesions that must be excised to detect a single melanoma, of 29.4 for non-specialists and 8.7 for specialists.3 In order to improve melanoma detection, new non-invasive techniques have emerged including dermoscopy, total body photography, reflectance confocal microscopy and the pigmented lesion assay, which have a potential capacity to improve melanoma diagnosis. Such techniques used either alone, in combination, or with computational approaches including artificial intelligence (AI), have the potential to revolutionize the melanoma detection pathway for the benefit of patients and clinicians alike. Some of these technologies also provide an alternative to surgical biopsy in cases where patients decline such a procedure or to aid in the decision of whether to proceed with surgical biopsy when the clinical findings are equivocal. Such techniques also have application in the assessment and monitoring of high-risk patients including those with a history of melanoma, with multiple atypical nevi or with melanoma predisposition syndromes. They may also improve triage of referrals from non-specialists and help reduce healthcare costs by decreasing unnecessary surgical biopsies. In this review, the key features of established and emerging visual and non-visual non-invasive melanoma diagnostic technologies are highlighted. 

Visual Techniques: Dermoscopy, Sequential Digital Dermoscopic Imaging and Total Body Photography 


Of all technological advances aimed at increasing the sensitivity and specificity of melanoma detection, dermoscopy has arguably had the most substantive impact. While the technique dates back more than 100 years, it was not until the publication of a seminal paper by Pehamberger et al. in 1987 that a formalized approach to the interpretation of dermoscopic findings of pigmented lesions, termed “pattern analysis”, was established.4 This study was followed soon after by descriptions of algorithmic approaches to pigmented lesion dermoscopy including the ABCD rule for dermoscopy5, the 7-point checklist6, the Menzies rule7, the CASH algorithm8 and the chaos and clues method.9 In a study comparing the validity and reliability of such criteria when used by dermatologists, general practitioners, medical students and residents, sensitivity for melanoma detection was found to be between 70 and 95%; however, all methods showed poor interobserver agreement.10 Additionally, many dermatologists likely do not employ any of these algorithms and instead rely on pattern analysis which has been defined as “the simultaneous assessment of the diagnostic value of all dermoscopy features shown by the lesion”, an approach which has been shown in one study to have a higher diagnostic accuracy than the ABCD rule and the 7-point checklist.11 Regardless of the method used for interpretation, there is now an overwhelming body of evidence, including four meta-analyses12-15, for improvement of melanoma detection through the routine use of dermoscopy. 

Sequential Digital Dermoscopic Imaging 

Although clinical appearance with the addition of dermoscopy can provide important static information about a pigmented lesion’s probability of being classified as melanoma, dermatologists rely on subjective patient history to gain knowledge of dynamic features suggestive of melanoma including lesional change or symptoms. Sequential digital dermoscopic imaging (SDDI) represents a variation of classical dermoscopy which permits objective assessment of lesional evolution. This is accomplished by obtaining baseline digital dermoscopic images and follow-up images and comparing these images for change in size, colour or structure/pattern16 (Table 1). For patients at high-risk for melanoma including those with the familial typical mole and multiple melanoma syndrome or atypical mole syndrome, the use of SDDI has been shown to increase melanoma detection 2-fold compared to the use of the 7-point checklist alone.17 Additionally, melanomas detected by SDDI are significantly thinner at the time of diagnosis.17 In low-risk patient groups, however, the addition of SDDI appears to be of limited additional value18,19 and may in fact lead to false positives.20 One of the reasons for this, particularly in younger patients, may be that growth represents a normal biologic feature of benign nevi and thus the interpretation of any changes noted with this technique requires careful interpretation to distinguish an expected change of benign nevi from a pathologic feature of melanoma. Features that should prompt excision include (1) architectural changes, (2) asymmetric increase in size, (3) new colors, depigmentation and focal colour changes and (4) the appearance of a melanoma criteria such as black dots or regression (Table 1).21 Limitations of this technique include the possibility of decreased sensitivity if a patient does not return for their follow-up visit, the requirement for digital storage and organization of photos and the additional time required for image comparison. Despite these limitations, SDDI appears to be an effective strategy for improvement in sensitivity as compared to dermoscopy for detecting melanoma which is particularly valuable in high-risk patient populations. 

Table 1. Differentiating features of nevus and melanoma in follow-up images (Adapted from Tschandl et al.)21


Total Body Photography 

Another technique aimed at increasing detection of melanoma in patients with numerous nevi is total body photography (TBP). Advantages of this technique over SDDI are its ability to detect de novo melanomas or melanomas arising within benign appearing nevi not otherwise selected for monitoring.22 In a study of U.S. academic dermatologists in 2010, 71% of respondents reported regular use of TBP23; however, this is likely much lower in the community setting. 

In a recent 5-year cohort study of melanoma patients, 48.1% of second primary melanomas were detected using TBP with a number needed to excise of 1:1.3.24 It has also been associated with a reduction in biopsies and a lower NNE25,26 in some studies but no difference in biopsy rates in others.27 Part of the reason for such discrepancies might be the rapidly changing technology available to both acquire and interpret TBP images with the most advancements being automated and 3-dimensional TBP.27 Limitations of this technique include the significant cost of equipment, the need for a dedicated space and personnel, and the time required for image acquisition and analysis. An added benefit of TBP is the decrease in cancer worry.28 

Non-Visual Techniques: Reflectance Confocal Microscopy and Pigmented Lesion Assay 

Reflectance Confocal Microscopy 

Reflectance confocal microscopy (RCM) is a technique which allows for imaging to a depth of the upper papillary dermis (a depth of 200 μm) with a near-infrared laser (830 nm).29 In a recent meta-analysis, RCM was found to have a pooled sensitivity of 92.7% and specificity of 78.3% for melanoma detection.29 Additionally, in a prospective study of RCM in combination with dermoscopy, the addition of RCM decreased the NNE from 14.6 to 6.8.30 When compared to dermoscopy, it is superior for recognition of in situ melanoma and diagnosis of amelanotic lesions and mucosal lesions; however, it cannot be used on acral skin.29 Its widespread use is also limited by the significant cost of purchase and maintenance as well as the substantial training required to gain proficiency. 

Pigmented Lesion Assay 

The pigmented lesion assay (PLA) is a proprietary test developed by DermTech, Inc. (La Jolla, CA) which is designed to aid in deciding whether to proceed with surgical biopsy of pigmented lesions. Its use involves harvesting cells from the stratum corneum overlying a pigmented lesion in question using a non-invasive “tape stripping” method, followed by the measurement of transcript levels of two genes that are expressed predominantly by melanoma as compared to benign pigmented lesions (LINC00518 and PRAME). While the validation and registry studies for the PLA showed a 91-95% sensitivity and 53-91% specificity for melanoma detection with an estimated negative predictive value (NPV) of 99%31,32, several follow-up analyses have been critical of the prevalence rates used to calculate this NPV and propose less impressive performance metrics in the real-world setting.10,33 Further studies are required to establish the role of the PLA in the melanoma detection pathway; nevertheless, it provides a promising proof-of-concept for in vivo molecular diagnostics for melanoma. 

Conclusion and Future Directions 

Melanoma remains a challenge for even the most experienced dermatologist with significant clinical consequences for a delayed or missed diagnosis. As clinicians, we must be judicious with the employment of any new diagnostic technique, particularly those that carry significant financial costs or potential for harm, but also open to their use if they can improve diagnostic accuracy thereby leading to earlier detection and treatment. The non-invasive techniques described herein, along with new and emerging techniques including high-frequency ultrasound, optical coherence tomography and electric impedance spectroscopy, have the potential to improve the efficiency and efficacy of the melanoma detection pathway for the benefit of both dermatologists and their patients (Table 2). Nonetheless, clinicians must remain vigilant of “technological creep” and only adopt such techniques when there is ample comfort with their evidence and risk-benefit ratio. 

Table 2. Comparisons of non-invasive melanoma diagnostic technologies (Adapted from Fried et al.34,35) SDDI, serial digital dermoscopic imaging; TBP, total body photography; RCM, reflectance confocal microscopy; PLA, pigmented lesion assay 


1. Fritschi L, Dye SA, Katris P. Validity of melanoma diagnosis in a community-based screening program. Am J Epidemiol. 2006;164(4):385-90. 

2. Aitken JF, Janda M, Elwood M, Youl PH, Ring IT, Lowe JB. Clinical outcomes from skin screening clinics within a community-based melanoma screening program. J Am Acad Dermatol. 2006;54(1):105-14. 

3. Argenziano G, Cerroni L, Zalaudek I, Staibano S, Hofmann-Wellenhof R, Arpaia N, et al. Accuracy in melanoma detection: a 10-year multicenter survey. J Am Acad Dermatol. 2012;67(1):54-9. 

4. Pehamberger H, Steiner A, Wolff K. In vivo epiluminescence microscopy of pigmented skin lesions. I. Pattern analysis of pigmented skin lesions. J Am Acad Dermatol. 1987;17(4):571-83. 

5. Nachbar F, Stolz W, Merkle T, Cognetta AB, Vogt T, Landthaler M, et al. The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. J Am Acad Dermatol. 1994;30(4):551-9. 

6. Argenziano G, Fabbrocini G, Carli P, De Giorgi V, Sammarco E, Delfino M. Epiluminescence microscopy for the diagnosis of doubtful melanocytic skin lesions. Comparison of the ABCD rule of dermatoscopy and a new 7-point checklist based on pattern analysis. Arch Dermatol. 1998;134(12):1563-70. 

7. Menzies S. An Atlas of Surface Microscopy of Pigmented Skin Lesions: Dermoscopy.: McGraw Hill Professional; 2003 2003. 

8. Henning JS, Dusza SW, Wang SQ, Marghoob AA, Rabinovitz HS, Polsky D, et al. The CASH (color, architecture, symmetry, and homogeneity) algorithm for dermoscopy. J Am Acad Dermatol. 2007;56(1):45-52. 

9. Rosendahl C, Tschandl P, Cameron A, Kittler H. Diagnostic accuracy of dermatoscopy for melanocytic and nonmelanocytic pigmented lesions. J Am Acad Dermatol. 2011;64(6):1068- 73. 

10. Carrera C, Marchetti MA, Dusza SW, Argenziano G, Braun RP, Halpern AC, et al. Validity and Reliability of Dermoscopic Criteria Used to Differentiate Nevi From Melanoma: A Web-Based International Dermoscopy Society Study. JAMA Dermatol. 2016;152(7):798-806. 

11. Carli P, Quercioli E, Sestini S, Stante M, Ricci L, Brunasso G, et al. Pattern analysis, not simplified algorithms, is the most reliable method for teaching dermoscopy for melanoma diagnosis to residents in dermatology. Br J Dermatol. 2003;148(5):981-4. 

12. Dinnes J, Deeks JJ, Chuchu N, Ferrante di Ruffano L, Matin RN, Thomson DR, et al. Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults. Cochrane Database Syst Rev. 2018;12:CD011902. 

13. Kittler H, Pehamberger H, Wolff K, Binder M. Diagnostic accuracy of dermoscopy. Lancet Oncol. 2002;3(3):159-65. 

14. Bafounta ML, Beauchet A, Aegerter P, Saiag P. 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. 2001;137(10):1343-50. 

15. Vestergaard ME, Macaskill P, Holt PE, Menzies SW. 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. 2008;159(3):669-76. 

16. Kittler H, Pehamberger H, Wolff K, Binder M. 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. 2000;43(3):467-76. 

17. Haenssle HA, Korpas B, Hansen-Hagge C, Buhl T, Kaune KM, Johnsen S, et al. Selection of patients for long-term surveillance with digital dermoscopy by assessment of melanoma risk factors. Arch Dermatol. 2010;146(3):257-64. 

18. Argenziano G, Mordente I, Ferrara G, Sgambato A, Annese P, Zalaudek I. Dermoscopic monitoring of melanocytic skin lesions: clinical outcome and patient compliance vary according to follow-up protocols. Br J Dermatol. 2008;159(2):331-6. 

19. Schiffner R, Schiffner-Rohe J, Landthaler M, Stolz W. Long-term dermoscopic follow-up of melanocytic naevi: clinical outcome and patient compliance. Br J Dermatol. 2003;149(1):79-86. 

20. Rinner C, Tschandl P, Sinz C, Kittler H. Long-term evaluation of the efficacy of digital dermatoscopy monitoring at a tertiary referral center. J Dtsch Dermatol Ges. 2017;15(5):517-22. 

21. Tschandl P. Sequential digital dermatoscopic imaging of patients with multiple atypical nevi. Dermatol Pract Concept. 2018;8(3):231-7. 

22. Salerni G, Carrera C, Lovatto L, Marti- Laborda RM, Isern G, Palou J, et al. Characterization of 1152 lesions excised over 10 years using total-body photography and digital dermatoscopy in the surveillance of patients at high risk for melanoma. J Am Acad Dermatol. 2012;67(5):836-45. 

23. Terushkin V, Oliveria SA, Marghoob AA, Halpern AC. Use of and beliefs about total body photography and dermatoscopy among US dermatology training programs: an update. J Am Acad Dermatol. 2010;62(5):794-803. 

24. Lallas A, Apalla Z, Kyrgidis A, Papageorgiou C, Boukovinas I, Bobos M, et al. Second primary melanomas in a cohort of 977 melanoma patients within the first 5 years of monitoring. J Am Acad Dermatol. 2020;82(2):398-406. 

25. Truong A, Strazzulla L, March J, Boucher KM, Nelson KC, Kim CC, et al. Reduction in nevus biopsies in patients monitored by total body photography. J Am Acad Dermatol. 2016;75(1):135-43 e5. 

26. Goodson AG, Florell SR, Hyde M, Bowen GM, Grossman D. Comparative analysis of total body and dermatoscopic photographic monitoring of nevi in similar patient populations at risk for cutaneous melanoma. Dermatol Surg. 2010;36(7):1087-98. 

27. Risser J, Pressley Z, Veledar E, Washington C, Chen SC. The impact of total body photography on biopsy rate in patients from a pigmented lesion clinic. J Am Acad Dermatol. 2007;57(3):428-34. 

28. Moye MS, King SM, Rice ZP, DeLong LK, Seidler AM, Veledar E, et al. Effects of total-body digital photography on cancer worry in patients with atypical mole syndrome. JAMA Dermatol. 2015;151(2):137-43. 

29. Waddell A, Star P, Guitera P. Advances in the use of reflectance confocal microscopy in melanoma. Melanoma Manag. 2018;5(1):MMT04. 

30. Pellacani G, Pepe P, Casari A, Longo C. Reflectance confocal microscopy as a second-level examination in skin oncology improves diagnostic accuracy and saves unnecessary excisions: a longitudinal prospective study. Br J Dermatol. 2014;171(5):1044-51. 

31. Gerami P, Yao Z, Polsky D, Jansen B, Busam K, Ho J, et al. Development and validation of a noninvasive 2-gene molecular assay for cutaneous melanoma. J Am Acad Dermatol. 2017;76(1):114-20 e2. 

32. Ferris L, Moy, R, Gerami, P, Sligh, JE, Jansen, B,Yao, Z, Cockerell, C. Real-world experience and clinical utility of a non-invasive gene expression test for primary cutaneous melanoma and validation against high risk driver muations in BRAF, NRAS and the TERT promoter. International Society for Investigative Dermatology Meeting, Late Breaking Abstract; May 16-19, 2018; Orlando, FL2018. 

33. Beatson M, Weinstock MA. Further Consideration of the Pigmented Lesion Assay. JAMA Dermatol. 2019;155(3):393. 

34. Fried L, Tan A, Bajaj S, Liebman TN, Polsky D, Stein JA. Technological advances for the detection of melanoma: Advances in molecular techniques. J Am Acad Dermatol. 2020;83(4):996-1004. 

35. Fried L, Tan A, Bajaj S, Liebman TN, Polsky D, Stein JA. Technological advances for the detection of melanoma: Advances in diagnostic techniques. J Am Acad Dermatol. 2020;83(4):983-92.