Computer Detection Effective In Spotting Cancer 89
Anti-Globalism notes a large study out of the UK indicating that computer-aided detection can be as effective at spotting breast cancer as two experts reading the x-rays. Mammograms in Britain are routinely checked by two radiologists or technicians, which is thought to be better than a single review (in the US only a single radiologist reads each mammogram). In a randomized study of 31,000 women, researchers found that a single expert aided by a computer does as well as two pairs of eyes. CAD spotted nearly the same number of cancers, 198 out of 227, compared to 199 for the two readers. "In places like the United States, 'Where single reading is standard practice, computer-aided detection has the potential to improve cancer-detection rates to the level achieved by double reading,' the researchers said."
As many? Or more? (Score:3, Interesting)
Link (Score:2, Interesting)
http://content.nejm.org/cgi/content/full/NEJMoa0803545 [nejm.org]
That's the original research. If you read the Yahoo article you'll see the researchers got money from the manufacturer of a computer-aided reading system.
Re:WTF? just WTF? (Score:5, Interesting)
Worry not, this is standard practice. Although there is general support that CAD (computer-assisted diagnosis) is effective vs. a second reader, there is still a bit of controversy in the field from time to time, since the results have not been overwhelmingly in favor of CAD yet. There's always at least one talk on the general usefulness of CAD at conferences. Sometimes whole sections get devoted to the topic.
What is a bit more puzzling is why it isn't as prevalent in diagnosis of other types of cancer. Most of the computer-aided detection algorithms draw on general machine learning and image processing techniques rather than specific domain-knowledge of the breast, and thus many of them can be applied, sometimes without any changes, to other organs. There is nothing particularly special about the breast.
My group developed a CAD system for MRI images of the brain, and in the course of performing experiments to put in the paper, I decided to run a few images from a breast CAD project through the classifier. Sure enough, the classifier we had developed for MRIs correctly classified 96% of the mammograms we fed it as well.
Re:WTF? just WTF? (Score:1, Interesting)
Well, let me tell my tale of working as an assistant in a hospital in Germany.
Medical care is first and foremost bureaucratic, and I guess it's no different in other countries. If it's socialized medicines fault or not is another topic.
The fact is that the processes are horribly inefficient - the computer systems for cancer therapy were from the 1970, and I literally had to hack OpenVMS commands into a terminal with a monocrome green-black display. Then I would have to wait 5 minutes or so to receive ~10mb of data (CT Images).
We had another, "modern" system that should eventually replace the old system, but it was basically the old OpenVMS code with a buggy Win32 GUI glued on. In some aspects, it was even *worse* than the old one. Id would crash randomly, didn't provide shortcuts for the most basic tasks. It was literally so bad that I would not use it for planning my garden - and we were using it for treating cancer patients! Cost of the new system? About 300.000 Euro (415 000 Dollar).
How can this kind of business go on? In my opinion, because it isn't a real business. Money isn't a big deal. The people who made the decision, mostly doctors, aren't really qualified and are easily impressed with what the salesguy tells them. They are in their 50ies and don't really understand this new fancy computerstuff anyways.
I hope this technology, which is based on image recognition (as far as I can tell from the Article), will advance, because it is so obvious and was already obvious to me when I worked there. There is much more to be done in terms of software/engineering in the medical field. I am talking about getting rid of the endless paper trails, not storing images physically in the smelly hangar with the leaky roof, not having to hear doctor say "I can't decipher this.. does this say 'left' or 'right'?"....
/anonymous rant
Re:WTF? just WTF? (Score:1, Interesting)
As far as I know, they're roughly equally prevalent and equally dangerous.
No, they are (very) roughly equally prevalent, but not nearly equally dangerous. They typically present very differently, for example there is not a significant population of aggressive cancers in younger people with prostate like there is in mammo.
Re:WTF? just WTF? (Score:4, Interesting)
I fell right into that one, didn't I? :)
I agree. I actually much prefer working with brains; the organs themselves are more interesting and analyzing the images tends to involve more challenges than 2D mammograms. Volumes vs. static images, spatiotemporal analysis, the option of acquiring functional data to map the lesion to cognitive deficits... I find it a very interesting area. Unfortunately, early diagnosis doesn't always make a difference in certain forms of brain cancer. This needs more research in treatment rather than in diagnosis.
Now we're going into the sociological dynamics of research, which turn out to be really messy, but I'm pretty sure the disproportionate amount of interest in breast cancer is in no small part fueled by the ample funding that gets provided to it vs. other types of cancer. However, as I mentioned in the other post, a lot of the CAD methods tend to be general, and breast cancer is really only a specific application, so this is perhaps not as bad as it sounds (if others apply existing methods elsewhere). Given that other forms of cancer strike more often or have greater mortality rates, and that this one tends to strike only half of the population with any frequency (although it is possible for it to develop in men as well), I think something like pancreatic or colon cancer would be more useful to direct some of the study towards, particularly because the current methods for diagnosis are wholly inadequate in the case of pancreatic cancer and rather invasive in the case of colon cancer.
Prostate cancer may also be a useful cancer to study more due to its high prevalence, but it's also gender-specific and the survival rates are rather high already, so I don't think it would be the first cancer to research on my list.
Having worked on a different computer diagnosis... (Score:5, Interesting)
system, there is a synergy between man and machine. Our system was for a general practitioner (general diagnosis with symptoms, physical findings, history, tests, etc as input). The computer is somewhat "dumb", but it always checks all the possibilities. The doctor would be looking for the usual stuff, and sometimes miss the more exotic diseases that would turn up from time to time. The machine would flag some exotic condition with a high probability, and the doctor would go "Interesting! I hadn't thought of that, let's check it out." Dr. House probably doesn't need one :-)
Re:WTF? just WTF? (Score:3, Interesting)
been done. (Score:1, Interesting)
i built the original software which was deployed by the NHS around 1998. The systems now are several generations ahead. Both groups would find different 28s with large amounts of overlap based on the smaller studies we did. Unfortunately mine was torpedoed due to liability issues the first time around. Mayber theyve figured out a way around the liabilit caused by the computer missing a tumor but probably not.
BTW, mine was open source http://yhs.sf.net for your code viewing cancer analyzing pleasure.