Introduction

The incidence and mortality from melanoma, the most serious type of skin cancer, continues to rise worldwide with around 7000 cases per year in NZ.  Since the 1990s the incidence rates have almost doubled but MIS is now more common than invasive melanoma. However NZ still has one of the highest rates of melanoma in the world  Melanoma is the 4^th most common type of cancer in NZ, [1]. There has been significant improvements in the management of advanced melanoma in the last few years with the advent of immunotherapy and targeted therapies. However early detection of melanoma is crucial as surgical removal of early stage disease usually results in cure.  There is good evidence showing that adequate screening of high risk individuals leads to better pick-up rates of early-stage thin melanomas with a more favourable prognosis [2] and reduced medical costs [3,4].

Benefits of mole mapping

Standard approaches to skin cancer diagnosis traditionally have relied on patients or skin cancer doctors to identify individual skin lesions of concern which may result in missed melanomas [5].  The use of “mole mapping” enables early detection of melanoma by assessing for new and changing skin lesions which is the most sensitive way of detecting melanomas at a stage where treatment confers excellent prognosis.The technique utilizes digital whole body imaging in addition to dermoscopy (a 10-15X magnified image of individual skin lesions providing detail on additional structures that cannot be seen by eye) to capture images of moles.

Sequential imaging at follow up visits allows for monitoring with greater accuracy and identifies minor skin changes which may indicate early malignancy. This allows clinicians to detect subtle signs of in-situ (precancerous) melanoma or invasive melanoma with a higher sensitivity and specificity [6] before they are apparent to the naked eye/ to the patient. Sequential digital photography has also been shown to improve the detection rate of early-stage melanoma which may lack dermoscopic (magnified) features of melanoma [7-9] thus improving outcomes.  In addition, it enables moles to be monitored over time for stability minimizing the need for unnecessary removal of multiple benign moles.

A personalised approach

The use of photography for the management of patients at higher risk for melanoma with atypical moles (irregular in size, shape and colour) is further supported by the National Institute for Health and Care Excellence (NICE) guidelines for melanoma [10] that stipulate that clinically atypical melanocytic lesions that do not need excision at first presentation should have baseline photography and then subsequent  review of the lesion in order to identify early signs of melanoma.  Furthermore the NICE guidance also recommends the consideration of personalised follow-up for people who are at increased risk of melanomas (for example people with multiple moles including atypical moles, a previous melanoma, family history of melanoma).   Mole mapping for individuals at risk of melanoma is therefore recommended.

2D total body photography has been used for many years to assist in skin cancer surveillance and is used both within the NHS and many private mole screening clinics (Molemap, Skintracker at Skin Institute).  Taking 2D images involves taking multiple separate photographs of the patient standing in a variety of positions which can either overlap or fail to include moles if they are not captured on the specific anatomical angle required.  It is a time consuming process often taking up to 30 to 60 minutes.  Recent technological advances however have led to the development of 3D imaging which is designed to facilitate 360 degree rotation to view all body angles including curved surfaces that are often not captured adequately with 2D imaging.  Early adopters of the technology worldwide have demonstrated the additive benefit of 3D image capture due to the capability of imaging almost the entire skin surface [11-12].

Using the VECTRA WB 360

Skinscape 360 are fortunate to have been able to acquire the state of the art VECTRA WB360 Total Body Photography 3 Dimensional Imaging system (Canfield Scientific)[13], the first of its kind in NZ. It uses 92 cameras to image the skin surface and stereophotogrammetry to construct a high-resolution 3D avatar of the patient. The patient stands in the device and image capture is taken within a matter of milliseconds- allowing for convenient, efficient and discrete acquisition of the required body images. In Australia, where the technology has been more widely adopted, a survey of over 1000 patients has indicated a high level of patient acceptance and confidence in the technology [14].  On subsequent visits with repeat imaging, usually recommended on an annual basis, an inbuilt AI system is able to identify new and changing skin lesions which is able to guide the clinician to areas on the skin requiring examination, reducing the risk of missing subtle early changes.  The machine is able to detect changes in moles, new suspicious pigmented lesions in addition to non- melanoma skin cancers such as basal cell carcinomas and squamous cell carcinomas.  Patients are provided with an email link to access their securely encrypted images and are encouraged to use these to check for new and changing skin lesions in between appointments.

Ongoing research using the VECTRA 360 is currently underway to further develop the AI technology to allow for automated melanoma detection/ diagnosis, rather than relying on clinician examination of lesions.  Researchers have recently demonstrated the possibility of automated melanoma detection using the machine and AI [15,16, 17,18] however larger studies are required to further evaluate this capability.

We believe that human/machine skin cancer diagnostics and tracking are the best way of utilizing AI and human skill for skin cancer diagnosis.

Summary

In summary, 3D total body photography allows for significantly enhanced monitoring of the skin in combination with skin cancer doctors or dermoscopists and patient examination to allow for early detection and treatment of skin cancer.

References

1. Daniel Wen D, Pullman J, Sharma A, van der Werf B, Martin RCW .Exploring melanoma shifts: a two decade analysis in New Zealand. NZMJ 2024 Jun 7; 137(1596)
2. Gershenwald JE, Scolyer RA, Hess KR et al. AJCC Version 9, online. https://ajccstaging.org/en
3. Ferris LK, Saul MI, Lin Y, Ding F, Weinstock MA, Geller AC, et al. A Large Skin Cancer Screening Quality Initiative: Description and First-Year Outcomes. JAMA Oncol. 2017;3(8):1112-5.
4. Epstein DS, Lange JR, Gruber SB, Mofid M, Koch SE. Is physician detection associated with thinner melanomas? JAMA. 1999;281(7):640-3.
5. Fried L, Tan A, Bajaj S, Leibman TN, Polsky D, Stein JA. Technological advances for the detection of melanoma: advances in in diagnostic techniques. J Am Acad Dermatol 2020;83(4):983-92.
6. 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.
7. 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.
8. Kittler H, Guitera P, Riedl E, Avramidis M, Teban L, Fiebiger M, et al. Identification of clinically featureless incipient melanoma using sequential dermoscopy imaging. Arch Dermatol. 2006;142(9):1113-9.
9. Menzies SW, Gutenev A, Avramidis M, Batrac A, McCarthy WH. Short-term digital surface microscopic monitoring of atypical or changing melanocytic lesions. Arch Dermatol. 2001;137(12):1583-9.
10. National Insitute for Health and Care Excellence (NICE) Guidance, Skin cancer, Melanoma: assessment and management Published 2015 and updated 2022.
11. Rayner JE, Laino AM, Nufer KL, Adams L, Raphael AP, Menzies SW, Soyer HP. Clinical Perspective of 3D Total Body Photography for Early Detection and Screening of Melanoma. Front Med. 2018;5:152
12. Grochulska K, Betz- Stablein B, Rutjes C, Po-Chao Chiu F, Menzies SW, Soyer PH. The Additive Value of 3D Total Body Imaging for Sequential Monitoring of Skin Lesions: A Case Series. Dermatol. 2022;238(10):12-17
13. VECTRA 3D While Body 3D Imaging. Canfield https://www.canfieldsci.com/imaging-systems/vectra-wb360-imagingsystem/
14. Pounamu T. Hona TW, Horsham C, Silva CV, Lawn C, Sanjida S, Gillepsie N, Soyer P, Janda M. On behalf of ACEMID group. Consumer views of early melanoma detection using 3D total body photography: cross-sectional survey. Int J Dermatol. 2023; 62:524-533
15. Marchetti MA, Nazir ZH, Nanda JK, Dusza SW, D‘Alessandro BM, DeFazio J, Halpern AC, Rotemberg VM, Marghoob AA. 3D Whole- body skin imaging for automated melanoma detection.  J Eur Acad Dermatol Venereol 2023;37:945-950
16. Kurtansky N, Gillis M, Codella N et al. Digital Medecine 2025. https//doi.org/10.1038/s41746-025-02070-7
17. Combining Automated Lesion Risk and Change Assessment Improves Melanoma Detection: A Retrospective Accuracy Study.Rutjes C, Mothershaw A, Soyer P, Janda M et al. JID 2023; 145(3): 703-706
18. Artificial intelligence in the detection of skin cancer. Beltrami E, Brown A, Salmon P et al. JAAD 2022; 87(6): 1336-1442

Enquire now

Written by Associate Professor Richard Martin Associate Professor Richard Martin is New Zealand’s leading Melanoma Specialist and Surgical Oncologist. After two and half years training in Sydney at the Melanoma Institute of Australia he returned to NZ to set up Melanoma Specialists and the Auckland Regional Melanoma Multidisciplinary meeting. Richard is a board member of Melanoma New Zealand since 2008 and has spent extensive time on the boards of Melnet and Melanoma and Skin Cancer trials group. He has published over 50 peer reviewed journal articles and is a regular presenter at national and international conferences. (click here to access his Publications and Presentations)