Episode 33 - 3D total body photography identifies phenotypes associated with melanoma risk

In this episode of BJD Talks, Sam and Meera discuss the article ‘Three dimensional total body photography identifies cutaneous phenotypes associated with late-onset invasive melanoma risk’ by Kahler et al. The full article can be accessed at https://doi.org/10.1093/bjd/ljaf440 

*This podcast was generated by an AI tool created by 67Bricks for the British Association of Dermatologists* 

Transcript

SPEAKER_01 0:00

Welcome to BJD Talks, the official podcast of the BJD. I'm Sam.

SPEAKER_00 0:04

And I'm Mira. In this episode, we will be discussing the article by Sam Carla et al. Three-dimensional total body photography identifies cutaneous phenotypes associated with late-onset invasive melanoma risk from November 2025 and included in the March 2026 issue.

SPEAKER_01 0:24

This paper is a brilliant step forward, Mira, connecting technology with personalised dermatology care. It delves into using three-dimensional total body photography or 3D TBP alongside AI to identify skin patterns associated with invasive melanoma. But can you set the scene on why this is so significant?

SPEAKER_00 0:43

Of course, Sam. Melanoma remains a serious skin cancer heavily influenced by factors like high NAVIS counts and ultraviolet photodamage. Until now, clinicians typically viewed these across the body as a whole. This research, though, focuses on variations at specific body sites, which makes it unique. By doing so, they uncovered more refined risk patterns.

SPEAKER_01 1:06

Exactly. The study included individuals over 50 years old with a personal history of melanoma, a high-risk group. Remarkably, despite many having years of surveillance, the researchers still identified previously unrecognised phenotypic patterns.

SPEAKER_00 1:21

Indeed, the methodology is particularly noteworthy. Participants underwent 3D TBP using the Vectra WB360 imaging system. This created detailed 3D avatars of their entire bodies. AI then analysed NIVIS counts and photodamage levels for specific body sites. The data was clustered using DB scan, an unsupervised algorithm, to reveal meaningful patterns.

SPEAKER_01 1:48

The results were striking. They identified four phenotypic profiles: moderate V-neck photo damage with few NEVI, moderate generalized photodamage with several NEVI, moderate V-NEC photodamage with many NEVI, and severe generalized photodamage but few NEVI. Interestingly, no one exhibited both high NAVIS counts and severe photodamage. That's quite compelling.

SPEAKER_00 2:11

It is. They also noted distinct links between these profiles and melanoma risk. For example, invasive melanoma occurred more often in those with severe photodamage. However, for individuals with moderate photodamage, risk was highest in areas with large NEVI. This differentiation hints at distinct pathways of tumour development, UV-related versus Nevis-driven.

SPEAKER_01 2:34

Another key observation was that melanoma in situ did not show much variation across these phenotypes. The major differences were seen in invasive melanoma, suggesting that these may follow distinct biological mechanisms.

SPEAKER_00 2:49

Precisely. Clinically, this has big implications. Knowing that certain body sites and phenotypes are higher risk means surveillance could be tailored. For instance, if someone has moderate photo damage and numerous large Nevee, monitoring can target specific at-risk areas more effectively.

SPEAKER_01 3:07

And it's not just risk identification, there's efficiency too. Think about AI-powered tools paired with 3D imaging, supporting clinicians with precise, patient-specific risk profiles. It would revolutionise early detection and personalised care.

SPEAKER_00 3:23

Absolutely. But this study has its limits. It focused on individuals over 50, predominantly of British or Irish ancestry, and all with regular access to skin checks. How applicable these findings are to younger or more diverse populations remains uncertain.

SPEAKER_01 3:39

True. Also, while advanced technology was integral here, these imaging systems aren't yet widely accessible. Nonetheless, this makes a strong case for investing in such tools. Any final thoughts, Mira?

SPEAKER_00 3:51

The takeaway is clear. Understanding melanoma risks at a site-specific level is essential. This study highlights how advanced imaging and AI can lead the way in personalised care. It's a step towards a more nuanced approach to dermatology.

SPEAKER_01 4:06

Well said, this is Sam signing off from BJD Talks.

SPEAKER_00 4:10

And I'm Mira. Join us next time for more cutting edge dermatology research. Stay curious.