Melanoma spread pattern model
Hayley Reynolds, from the Auckland Bioengineering Institute, is developing a computerised 3D model of the body that will help doctors predict where a patient’s cancerous melanoma cells are more likely to spread. Melanoma develops in skin cells, but can metastasise (spread) from the skin to other sites in the body. Unfortunately, once melanoma has spread, there is not yet any reliable cure.
Creating the Model
Hayley Reynolds (Auckland Bioengineering Institute) describes how, using images from the Visible Human project, she has created a 3D computer model of the human skin and mapped the location of lymph nodes onto this.
It spreads very quickly and not always in predictable ways. The earliest sign that melanoma has spread is usually found in the lymph nodes, but it is often difficult for doctors to know which lymph nodes to check and to be sure they have checked all the likely lymph nodes – there are over 600 lymph nodes in the body with 43 lymph node fields where melanoma is likely to spread.
Learn more about lymphatic system.
Melanoma spread patterns model
Hayley Reynolds from the Auckland Bioengineering Institute briefly describes the focus of her PhD research. Hayley has developed a 3D computer-based human model to visualise where a melanoma is likely to spread from any area of the skin.
The aim of Hayley’s research was to develop an efficient way of displaying which lymph nodes melanoma is most likely to have spread to, from any skin site in the body.
Benefits of Hayley's research
Hayley Reynolds (Auckland Bioengineering Institute) outlines the practical clinical benefits of the 3D model for doctors and their patients.
Building the computer model
To build her 3D anatomical computer model, Hayley used photographic images from the Visible Human Project, which has over 18,000 cross section photos of the human body, obtained from slicing a male cadaver into 1 mm slices. Hayley ‘stacked’ these 2D photos in 3D computer space and used this to create a 3D computer skin mesh. She then located and mapped lymph nodes onto her 3D model, also using the Visible Human. Hayley’s 3D man is an accurate model of the skin and lymph nodes.
Using lymphoscintigraphy data
As well as building the computer model of skin and lymph nodes, Hayley needed to record data about melanoma sites and dissemination on the model. She did this using lymphoscintigraphy data from melanoma patients. In some hospitals, all patients with early melanoma undergo a hospital test called lymphoscintigraphy (LSG) – a radioactive tracer and blue tracer dye are injected into the skin around the melanoma, and over 2–3 hours, these travel to the lymph nodes. The first lymph node(s) that drains the melanoma site is called the sentinel lymph node(s). Obviously, this is very useful before surgery.
Data for the model
Hayley Reynolds (Auckland Bioengineering Institute) and Associate Professor Rod Dunbar (University of Auckland) explain how lymphoscintigraphy provides the data needed for Hayley to generate her model. This clip should be viewed with What is lymphoscintigraphy?
Hayley has used lymphoscintigraphy data from the Sydney Melanoma Unit (SMU) to develop her computer model. The SMU has the world’s largest LSG database of over 5,000 melanoma patients. They have recorded in 2D the location of each patient’s melanoma site and have also recorded which lymph node(s) it has spread to. Hayley has used these 2D maps and the Sydney Melanoma Unit’s database and has mapped this 2D data onto her 3D computerised model to reveal patterns of melanoma spread. This allows doctors to predict where tumours may develop if the melanoma has spread so they can focus on these high risk areas.
What is lymphoscinitigraphy?
Associate Professor Rod Dunbar (University of Auckland) explains the procedure of lymphoscintigraphy as a technique to determine the first lymph nodes melanoma will spread to.
Acknowledgements:
TVNZ TELEVISION ARCHIVE
Dr Roger Uren
Using the computer model
The heat map and skin selection tool
Hayley Reynolds (Auckland Bioengineering Institute) discusses two features of her 3D model – heat maps and the skin selection tool – both developed using data from over 5,000 patients.
Acknowledgements:
Heat map image with kind permission of Hayley Reynolds and Elsevier Ltd (published in The Lancet Oncology - Vol. 8, Issue 9, September 2007, Pages 806-812, Three-dimensional visualisation of lymphatic drainage patterns in patients with cutaneous melanoma
Hayley M Reynolds, Rod Dunbar, Roger F Uren, Shane A Blackett, John F Thompson, Nicolas P Smith)
Instead of looking at data from over 5,000 patients on 2D sheets of paper, doctors can click on an area of skin on the 3D body displayed on the screen and can see all the sentinel lymph nodes sites previously found by the SMU. They can instantly see a display of the lymph nodes where cancer cells have spread to from that site in other patients. This means they can decide where to check for signs of cancer spread.
Nature of science
Models are used by scientists when developing explanations about their data. Often the model is used as a predictive tool.
Hayley has also developed heat maps that show the likelihood of spread to a particular lymph node site. A skin selection tool allows doctors to select an area of skin to see potential lymph node sites and how many patients have been sampled with melanoma in the particular skin site.
Hayley’s software has built-in capability for doctors to record their patients’ data straight away in 3D. This means that the database can continue to expand.
Why this kind of research in particular?
New Zealand has one of the highest melanoma rates in the world, with over 200 deaths per year. According to New Zealand skin cancer statistics, skin cancer is the most common cancer here. Hayley, whose 17-year-old brother Wayne lost a long battle with leukaemia, wanted to pursue research that would have a useful practical outcome, something that would enable doctors to diagnose and treat their patients more quickly and effectively.
Hayley’s research is supervised by Maurice Wilkins Centre investigators Associate Professor Rod Dunbar (School of Biological Sciences) and Dr Nicolas Smith (Bioengineering Institute) at the University of Oxford.
