Color (all the same or not)
Diameter greater than 6 mm
Evolving size, shape or color (over time)
Now, based on this, we would then probably biopsy the lesion (any dermatologists lurking on HN wish to chime in?) and send to pathology to interpret.
Will this method beat out the clinical diagnosis in terms of sensitivity (number of false negatives, which is what I would care more about) and specificity (number of false positives), such that we could biopsy more of the patients that we missed before? Additionally, would we see these changes earlier with this software and hardware?
Cool idea, nonetheless. I'd be more than happy to set up some sort of clinical study looking at this technique though if there are enough tools out there to implement this myself.
What's exciting about this one to me is that if the detection mechanism is truly sound, this is a great leap over the ABCD(E) criteria which have been the clinician's main tool, and which has a high false negative for one of the deadliest forms of melanoma, nodular melanoma. This often does not present with varigated coloration and because it tends to invade tissue rather that spread superficially its morphological characteristics aren't as apparent until its more developed, greatly increasing the risk of metastases. This was the case with my wife's primary, which her dermatologist almost didn't send out for a pathological workup, and had been missed by a couple of different doctors thanks to its atypical presentation.
All of which is not to say that ABCDE isn't a valuable rule of thumb, but its always struck me as somewhat subjective, which I guess is tempered with the experience of the physician but also does have the false negative problem, even with specialists.
ABCDE is awful, don't get me wrong. I've always felt it was like holding your finger out to see what the wind direction is like. It has a horrible sensitivity (50%-90% depending on the type, I'd err on the side of lower). But if this technique also only has a 50% sensitivity, that is what would bother me. Hopefully the sensors they are using are sensitive enough to detect these temperature changes well.
Agree wrt sensitivity—obviously while this is novel and exciting to me at least, it bears further study before becoming part of the standard of care.
If the sensitivity of the two techniques are not correlated, a 50% improvement on top of ABCDE would be fantastic.
These features (ABCD) are very helpful for patients and other doctors in highlighting moles that should be checked. However, dermatologists generally use a dermatoscope (magnified image) to examine the pattern of pigment within the mole as an important part of deciding whether it is benign or malignant.
There is a long list of dermoscopic criteria that can help to identify melanoma and this is used by doctors training in dermatology but in practice I think that it is seeing lots of normal moles that is the most useful. The brain becomes trained to recognise a normal mole and when it sees something that does not match this pattern it is labeled as suspicious - often I cannot say exactly why.
Recognizing a clear cut melanoma is very straightforward, even for a medical student the difficulty is in distinguishing moles that look abnormal but are actually harmless. At the present time these would be excised and examined under the microscope and as a consequence a large fraction (up to 90%) of moles removed are harmless moles.
I suspect that this device will not increase the number of melanomas diagnosed, but if it is sufficiently sensitive and specific it might reduce the number of normal moles removed.
I have more than a thousand moles and is lucky to be at Sloan Memorial. They found my second one by pointing some laser onto the mole without biopsy and could see the malanoma there. I have 3d images of me and all sorts of things.
This sounds more like something I would need (given my high number of moles) if I am lucky enough that this third one either isn't a melanoma or early stage.
One thing to note out which I learned. Asymmetry needs to be understood a little different. I have a lot of asymmetric moles that are just fine. They can even grow and it will be fine as long as their internal network nodes grows the same (think of it as a vector image that will grow uniformly.
The machine is called vivascope
Basically what it comes down to is that doctors get really good at bayesian inference at some point in their career, definitely not while we are students. I am however confident that we can build models that learn in a similar manner.
I'm actually trying to build a model for a class project that uses bayesian inference in a CNN as per Gal et al (https://arxiv.org/abs/1506.02158) to try and detect diabetic retinopathy. Their paper actually tries to detect different skin cancers.
I don't want to pay with my personal data. Is such an app recommended and are there open source alternatives?
 with the purpose of enabling our Image Pattern Processing system in 3.12 http://miiskin.com/legals/
The only other app I know is SkinIO, developed by some northwestern students if I recall correctly. I'm not certain how it all works, but maybe look into that?
The question of how many of those treatments are affordable is largely driven by the country they're in—many countries regulate the cost of pharma in general, so they'd be more affordable than in the US.
Anyone know what kind of potential regulatory/FDA issue will this kind of apps have?
Hopefully thia one will do better.
If I understand correctly, the process they're using is something like the following...
1) Cool the skin down to some depth by applying an icepack
2) Remove icepack and take a video of the skin with infra-red (a temperature map) as the skin reaches thermal equilibrium.
3) Process the "stack" of images by measuring the thermal conductivity at each point-- you do this by getting a curve of the temperature for each point.
This will give you a map of structures underneath the skin which have different material properties (a different thermal conductivity).
It seems likely to me that there would be a difference in reflectivity/transmittivity too that could be detected by using a strong light source that could penetrate the exterior dermal layers. Presumably active scanning like MRI (or microwave heating - probably too risky) would show the differences well too?
Would be interesting to read about the range of methods that have been tested (conductivity using surface contact probes would seem another obvious method?).
The benefit, as it appears, of the current method is probably simplicity but it doesn't appear to scale to scanning the full surface readily.