July 2009 Archives

It seems that one out of every few fictional villains ends up resorting to the same method for destroying the earth: hitting it with a giant laser. Although these fictional plans never elaborate on the real world physics, in some ways the villains have the right idea. Lasers are powerful tools and simply used as a heating device, they can kill cells. Thermal therapy is being used to kill cancer cells in tumors that other methods fail to eliminate, but as with radiation therapy there is a risk of overheating healthy cells, or not heating the tumor cells enough.  

A new idea for improving thermal therapy was recently published in PNAS and presented at the AAPM session "Frontiers in Medical Physics," by the young research assistant Xuangfang (Leo) Ding from Wake Forest University. Using multi-walled carbon nanotubes (MWCN's - shown above) Ding and his collaborators hope to make guided laser cancer removal safer and more effective.

The treatment injects cancer tumors with MWCN's,  and uses a guided near infrared laser to heat them up and deliver a fatal temperature rise to the cancer cells.  The laser pulse is low energy (3 W/cm²) and fast (30 seconds per dose). The team uses Magnetic Resonance Temperature Imaging, MRTI, to identify the tumor and then to monitor the tumor's temperature as well as the temperature of the surrounding tissue. Trials with mice showed a significant rise in the temperature of the cancer cells injected with the MWCN's, compared to without. And, the tumors were far less likely to come back.

The treatment can be used non-invasively on superficial tumors like skin cancer, and with minimal invasivity to deeper tumors by inserting a small laser optic fiber into the target as well as the MWCN's. The exception is lung cancer, where the motion of the tumor would cause too great an error in the MRTI.

Since carbon nanotubes are not approved by the FDA, it's uncertain when the team can begin clinical trials, and they are still investigating any potential side effects of the MWCN's.

One of the largest disadvantages of therapies that require accelerators is the size and cost of the accelerators themselves. These factors limit who can receive care and where. So for medicine and the future of accelerators in general, the community is pushing for smaller and more affordable (but of course, that's the case with all technology isn't it?). At a very intriguing session I got to hear about an approach that a group of scientists at Stanford University and Fluence LLC are developing to make smaller particle accelerators for medical applications.  They are also collaborating with the Stanford medical school and SLAC National Accelerator Laboratory, who are contributing expertise in Monte Carlo simulations for beam transport and dose calculations.

Their technique is called electromagnetic plasma acceleration (not to be confused with other plasma accelerators that use lasers) and it goes something like this: get a neutral gas in-between two electrodes and let it break down into electrons and ions. The currents that flow through the plasma then generate  their own magnetic field (this is a big advantage because no magnets are needed); this exerts a force to the right, and the electrons start to move.

This alone is not a new approach.  But normally the ions upstream form a wall, sort of like a piston, and push the other particles forward.  This works for lower energies, but when one tries to accelerate the piston faster it starts to tilt and downstream gas can blow by it without being accelerated. This is like a piston with a hole in it, which doesn't push anything. So there's a definite limit to how fast you can get those particles to move.

But new research has shown that you can make tweaks to the system and cause the piston wall to disappear. Early work performed on this topic by Dah Yu Cheng in the 1970's already showed that there are two ways to accelerate these particles. One (the piston) moves the particles like an explosion. The other moves them the way a jet engine does, in a more jet or bullet-like shape that is also more efficient. The Stanford team is now trying to understand this second mode of acceleration. While there was previously a limit on how fast you could accelerate the particles until the piston tipped, this limitation does not apply to the second mode.  They've got particles moving at around 100 keV, which is still far short of the 100 MeV's needed for proton accelerators, but that's what the Stanford team is dedicated to reaching. They'll have other challenges as well, including reducing the wide energy distribution that the particle jets tend to have.

Flavio Poehlmann, who delivered the talk in place of professor Mark Cappelli who was unable to attend, said the team expects another ten years of work before they reach their energy goal. They're currently in the process of submitting patents before they publish any papers on the subject.

At a meeting with such a heavy emphasis on breast cancer, Debra Ikeda's talk offered some great information to put all of the new innovations into focus. While most of the speakers were medical physicists working at the cutting edge of technology, Ikeda is a professor of Radiology at Stanford and is working to better define a standard of care for breast MRI and MRI biopsy. So her view of the problem stems from a growing understanding of the biological nature of breast cancer and the problems that face doctors in the field. "I just want to say as a radiologist that I'm very excited to hear about what you guys are working on," Ikeda said to her fellow presenters.

Breast cancer originates near the root of the milk ducts in the breast, and cancerous cells can move from the ball-shaped root down the ducts.  This early form of breast cancer, known as ductal carcinoma in situ (DCIS), is very difficult to detect.  Later on the cancerous cells can break out of the ducts and become invasive, growing into more recognizable tumors.  While Ikeda promoted MRI treatment, she noted that traditional mammography is actually 25% more effective at identifying this early stage of breast cancer than MRI. 

Most breast cancer patients have their entire breast radiated after the removal of a tumor, to eliminate the risk of the cancer returning through the ducts. Because each breast has multiple ducts, there can be multiple cancer foci in the breast.

Typical tumors usually possess a very high amount of blood vessels. This is one easy to way to spot a tumor - by injecting the patient with a marker or angiogenesis drug, a tumor will uptake the injection faster than the rest of the breast because of the number of blood vessels (although this isn't always the case).

MRI is more effective than traditional mammography in identifying tumors, especially in high risk patients with dense breast tissue (Ikeda does note, however, that they should be used together, as they both have their advantages). One study of over seven hundred US practices showed that three quarters offer MRI for breast cancer screenings, although the majority of those only do about 5 a week (which is relatively low). 31% percent of those, however, do not do MRI biopsy, which Ikeda believes needs to change. A biopsy is an invasive process that takes tissue samples from an identified abnormality and identifies it as cancer or benign. "It's important to be able to biopsy when you see something abnormal," says Ikeda. "It would be horrible to be told 'You've got something...but we can't biopsy it.'" Ideally of course, methods would increase for discerning between benign lumps in the breast without the need for biopsy.

To more fully understand exactly what physicians will see on MRI scans of different patients, how to look for signs of early cancer, and what standard screening steps to take, Ikeda sits on the BIRAD Lexicon Committee, which constructs the yearly ACR Atlas. The Atlas will compile information to hopefully answer those questions, but it will rely on detailed information from physicians.

The committee's requests to radiologists include doing bilateral screening in patients (comparing both breasts), comparative studies among patients, and careful descriptions background enhancement.

Background enhancement describes how much of the dense tissue in the breast is enhancing; it's more of a change in the dense tissue rather than the volume of dense tissue. Background enhancement can change due to natural hormone cycles which can fool an MRI into looking like cancerous tissue Different types of background enhancement filters can better differentiate dense tissue fluctuations.

Four to five percent of women who develop breast cancer will develop it in both breasts, so Ikeda emphasizes the need for doctors to do bilateral care and report their findings. The bilateral studies also make it easier to identify abnormalities in each breast.

As I mentioned before, breast cancer imaging, screening, diagnosis and treatment were discussed in more sessions than perhaps any other topic on the IPF agenda. While the science was all fascinating, this session brought home the human aspect of all the research. It was held in memoriam of Carolyn Kimme-Smith, a leading radiologist in the field of breast cancer study who also suffered from breast cancer. Ikeda began her talk with a quick tribute of her own to Kimme-Smith, saying she was always kind to and respectful of other people, even when their ideas conflicted.

Speaker Michael O'Connor cited a study by the National Cancer Institute which shows that in women with dense breast tissue,  traditional mammogram successfully identified cancerous tumors only 40% of the time, and ultrasound 43%. But MRI successfully spots cancerous tumors at 80%. Women with dense breast tissue have a significantly increased risk of developing breast cancer, yet the sensitivity of mammography drops with tissue density. It's a frustrating contrast especially because offering these women MRI's isn't a fiscal option, as they cost about $3,000. Even with health insurance, this might not be an option for many women.

For the past six years, O'Connor and his colleagues at the Mayo Clinic have been investigating different molecular imaging techniques for screening for breast cancer, in the hope of finding a cheaper, equally reliable method to MRI. They've focused many of their efforts on scintigraphy, which images the body by catching gamma rays emitted from the patient (thanks to an injected radioactive tracer), rather than passing X-rays through them. But this technique has been difficult to apply to breast imaging because it's tricky to get the breast into the field of view of the camera without missing segments or getting signals from the rest of the body as well (which washes out the resolution). Thus, many groups are working on small field of view gamma cameras, with only one currently commercially available.

The gamma camera itself contains crystals that respond to the gamma rays by emitting a little pop of light. Collectively they create an image. O'Connor and his colleagues are putting their money on Cadium Zinc Telluride (CZT) crystals, which are currently a bit pricey, but they believe the cost will drop when they're made commercially available. These crystals can be operated at room temperature (some detectors had to be cooled to liquid nitrogen temperatures which would be a bit chilly for breast imaging!), and they have no "dead space" so you can get very close to the breast tissue.

The resolution on the scintimammography (so called when imaging the breast) using CZT crystals is striking. O'Connor showed mammography images of a breast that appeared to have no tumors or other build up, and then showed the image of the same breast imaged under the gamma camera. The tumors appeared as clear as day in the gamma image; but were completely invisible to the mammogram. In a clinical trial of dense breast tissue the gamma camera caught 10 tumors out of twelve while the mammogram only caught three. Its resolution is comparable, but not better than MRI.

Two vendors are working on making the technology commercially available, and O'Connor estimates the cost of the procedure will be about $400.

But there are some key drawbacks that O'Connor and his colleagues are still working on. First, there are some false positives from the gamma camera, identifying non-cancerous objects like pampillomas as tumors. Secondly, while the radioactive tracer is FDA approved, the treatment delivers a dose of radiation 6-7 times larger than a mammogram. While this is still below the level of natural background radiation, the group is "very sensitive" to the size of the doze and are trying to reduce it for both the patients and the radiologists who deliver the treatment.  

Computer scientist Ian Foster admitted in front of a few hundred medical physicists that he steered clear of anything to do with biology or medicine for many years. Hailed as "the father of grid computing," Foster (shown left) has always been highly focused on computer science and has subsequently garnered a very impressive resume. But the crowd didn't hold it against him, because recently Foster's had a change of heart, and says healthcare is presenting many fascinating challenges for computer scientists.

As the medical community accumulates an ever growing sea of information, data, clinical trials, research, ect. ect. ect....how can the community hope to transform all that information into useful knowledge? In his talk Foster presented a compelling case for a growing theme in the medical community known as quantitative medicine,which would attempt to answer this question. It starts with computer science.

Thanks to increase computer capabilities, biologists have been able to construct a map of the human arterial tree, and thanks to lowered storage costs, gene banks can store tens of billions of base pairs. It's easy to share high resolution images over the internet or through file sharing programs. There's no doubt medicine has entered the information age.

But, more information does not always mean more knowledge.  "We should be thinking about new ways of knowing," says Foster. He links Aristotle's notion of empiricism (go out and experience the world if you want to know it), Newtons laws, and more recently the science of simulations as paradigm changes in ways of knowing. The next link in that chain, he says, will be finding way to organize and then utilize the vast amounts of data we can obtain.

Quantitative medicine aims to take advantage of the vast amount of data available, and ultimately use it to promote more individualized medicine. When doctors diagnose patients based on a set of symptoms, there remains a degree of qualitative treatment. In this information age there are more ways than ever to treat patients quantitatively, but that relies on comparing information on a massive scale.

Foster gives an example of lymphoma. In the 1950's this was diagnosed as disorders of the blood, and survival rates were very low. Today we know an incredible amount about the many varieties of this disease, and yet it can still evade a physician's analysis. 17% of patients with what's known as Burkitt's lymphoma are misdiagnosed as having diffuse large b cell lymphoma. The correct treatment for Burkitts have very high success rates; but an incorrect treatment for diffuse large b cell lymphoma almost always leads to death.

In the case of Burkitt's lymphoma, spectrographs of gene expression in the patient can indicate which disease the patient is likely to have. There is also evidence that the two diseases produce different effects in the brain, which can be detected in brain scans. Imagine if doctors had access to these images from other Burkitt's patients, which they could then compare with their own patients. They could reduce or eliminate that 17%

The challenges of establishing an organized, connected data base of this information are mighty. Namely, this isn't simply a question of uploading information to a cloud or grid. It would require a more interactive, closely linked system to connect members of the community with the right information; to help them find out what information they need. Foster uses this quote from the NRC Report on Computational Technology for Effective Health Care: Immediate Steps and Strategic Decisions (2009): "...have to pay attention to cognitive support...computer-based tools and systems that offer clinicians and patients assistance for thinking about and solving problems related to specific instances of health care."

For all this to happen, Foster says small groups within the health care system need to come together and form virtual organizations (VO's) - groups with no official affiliation, but who have some agreement about their desired outcomes and the certainty of those outcomes. These small groups may begin sharing information, images and data and communicating to figure out the best ways to utilize the growing database. This will require new channels of communication from basic research labs, to clinics and up to hospitals.

There are already examples of medical institutions instigating this kind of system, including the South Side Healthcare Collaborative in Chicago, the Neuroblastoma Cancer Foundation and the Children's Oncology Grid. The COG is already sharing images from clinical trials through public servers that can be accessed by tens or even more than a hundred participants. For the COG, information is already harder to come by than with adult cancers, so the sharing program was highly sought after.

But for some groups, this may not be the case. It's true that one of the most difficult aspects of forming these VO's will finding incentives for people to participate. The activities required will demand time, resources and money. What's crucial to all these systems is human interaction, either through specialized software or more immeidate contact. "These are human systems," says Foster. Ultimately, the community will have to make some sacrifices if they hope to have their vast amounts of data mean anything.

The morning of the President's Symposium, TV's in the hotel lobby showed news of the continued debate among policy makers over the proposed health care reform bill. This is one of the largest issues bearing down on our nation at the moment, and may change the way medical institutions are linked together. But Foster emphasizes that the change must begin on the small scale, with small VO's that grow and change and accumulate other groups.

Foster wraps up with a quote from his colleague Alan Kay (from 1997): "The computer revolution hasn't happened yet." For healthcare, he says, it still hasn't.