Melanoma, what is it?
According collaborative partnership between the French network of cancer registries (Francim), the biostatistics-bioinformatics department of the Hospices Civils de Lyon (HCL), Public Health France and the National Cancer Institute (INCa), approximately 15,500 new cases of were detected in France in 2018 and nearly 2,000 people died. According , melanoma thus represents about 4% of all cancers, and it affects as many men as women. This is the cancer for which per year increases the most: for 30 years, the evolution of is 4% per year for men and 2.7% for women.
Nevertheless, early identification considerably increases the survival rate: the standardized net survival at 5 years is thus estimated at 93%, with an excess mortality rate of almost zero beyond 5 years of follow-up.
Usually, patients considered high risk have their whole body photographed and inspected by ato identify any indication that existing moles may have changed to melanoma. However, this process is extremely time consuming as it requires highly skilled dermatologists and it often relies on some degree of self-diagnosis by patients.
The MoleGazer project: from mapping the sky to that of moles
The MoleGazer project (literally “mole spotter”), a collaboration between the and the, aims to combine the analysis of astronomical data with whole-body photography used by dermatologists to monitor patients. In the project, a patient’s skin is treated like the background sky in an astronomical image, and all moles are treated like stars. the finds these “stars” and can see the changes over time to warn of potential danger. This enables automated identification and analysis of moles as they change over time.
Using whole-body images of a set of high-risk patients, MoleGazer provided the evolutionary history of individual moles, which will now be used for moles at risk of developing into melanoma. Researchers would like to go one step further and create a map of how benign moles turn into melanoma to helpas early as possible, because early identification is the key to better results.
What you must remember
- Astronomical software used to identify and analyze the stars photographed but also to map their evolution has been adapted to monitor the evolution of moles in patients at high risk of developing melanoma.
- A patient’s skin is treated like the background sky in an astronomical image, and all moles are treated like stars.
- This analogy allows automated identification and analysis of moles as they evolve over time and helps in the earliest possible diagnosis of a possible melanoma.