A new technology to help combat breast cancer
There seems to be an awful lot of medical scourges in our present times, from illnesses that were once declared extinct and are now making a comeback - TB, for example - to new arrivals, such as AIDS. But I think everyone will agree with me that of all these scourges, cancer is currently one of the most visible - not to mention widespread.
Fortunately, a combined team of pathologists and computer scientists from Stanford University just made a tantalizing breakthrough in the diagnosis and treatment of breast cancer. No, not a cure for breast cancer. But it is something that has the potential to improve the chances of many patients out there.
Doctors' strategies for identifying the presence and severity of breast cancer in a patient hasn't changed in any significant manner since the early twentieth century. They take a sample, put it under a microscope, and peer at it. They look for only three different features in the cellular composition and behavior of the sample, assign to each factor a qualitative score, and then calculate a general score that - hopefully - gives them an idea of what the patient can expect.
The drawback of this old-school method, according to new research, is that it looks at too narrow a set of factors. Many scientists today argue that cancers should be viewed as if they were ecosystems, and that clinical diagnoses could be much more accurate if the tumor and its surrounding structures were analyzed as a whole.
This is more or less the idea behind the Stanford team's new invention: C-Path (Computational Pathologist), a computer program that assesses images of breast cancer in order to judge severity and predict patient survival. To this end, C-Path measures, compares, and combines thousands of different factors. The results, according to the Stanford team, are significantly more accurate than those of the old-school method.
The development of C-Path has a lot of promise in the field of cancer diagnosis and treatment. Pathologists will have a more accurate tool to help their patients; C-Path could also make their work easier. Likewise, C-Path offers more personalized results, so to speak, instead of the generalizations that result from the old diagnosis method. The new system also holds tantalizing hints of further progress in this area of computerized medicine. We could learn to do the same for other forms of cancer. We could also learn to identify precancerous stages, or judge the sort of treatment that would be adequate for each individual patient.
All of that, of course, is still in the future. The Stanford computer program is just taking off the ground - but it is nevertheless a wonder. The full research paper will be published in Science Transitional Medicine today (Nov 9th).
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