Inspired innovators continue to push the limits of diagnostic imaging.

Alan Waxman, MD, Director of Nuclear Medicine, S. Mark Taper Foundation Imaging Center at Cedars-Sinai Medical Center.

Alzheimer’s disease. Breast cancer. Lung cancer. For years, physicians have been struggling to diagnose and effectively treat these diseases.

Alan Waxman, MD, Michael O’Connor, PhD, and Claudia Henschke, MD, have all been instrumental in using new technologies to diagnose these diseases more efficiently and—consequently—have done much to bring these technologies widespread attention.

Alan Waxman, MD—Neurodegenerative Diseases and Brain Imaging

For the longest time, the diagnosis of neurodegenerative diseases such as Alzheimer’s was less than an exact science. But the development of pharmaceuticals such as donepezil, galantamine, and rivastigmine—known as cholinesterase inhibitors—can help in the management of the symptoms of early Alzheimer’s.

Which means, says Alan Waxman, MD, that there is now a greater interest among neurologists in making an early—and correct—diagnosis of Alzheimer’s.

“And we’re providing them with the tools to do that, and we’re doing a pretty good job,” said Waxman, who is director of nuclear medicine at the S. Mark Taper Foundation Imaging Center at Cedars-Sinai Medical Center in Los Angeles. The tool of choice, he says, has become PET-FDG.

For a PET scan, a patient is injected with a radiotracer, fluorodeoxyglucose (FDG). The brain uses glucose for energy, so tracking the distribution of FDG throughout sections of the brain is an excellent way of mapping brain function. The brains of individuals with dementia consume less sugar and do so in patterns that are characteristic of certain diseases.

“So we can see characteristic patterns that allow us to diagnose Alzheimer’s or frontotemporal dementia,” Waxman said. “Our sensitivity for picking up early Alzheimer’s has increased tremendously—I believe we’re up to 80% to 85%.”

This means, Waxman says, “we are getting very good at identifying that MCI [mild cognitive impairment] population—those who might benefit early on from some of those cholinesterase inhibitors.”

Waxman also points out there is “growing enthusiasm” for the use of PET in imaging amyloid plaques that are associated with Alzheimer’s disease.

These amyloid detecting agents—thioflavin-T analogs—correlate very well with the presence of Alzheimer’s, Waxman says, and could allow physicians to diagnose the disease 10 or 15 years before the patient is clinically symptomatic.

“Whether it is specific enough hasn’t been determined, although it has a good negative producing value,” he said. “So, if the amyloid test is negative, the probability of developing Alzheimer’s is very low.”

Waxman points out that there have been some exciting new developments in the ability of physicians to diagnose other neurodegenerative diseases, such as Parkinson’s disease. He says he is now doing quite a few scans with a new agent called Ioflupane I 123 Injection or DaTscan, which works by binding to dopamine transporters in the brain.

DaTscan, approved by the FDA last year, “is a very good agent for determining whether the parts of the brain involved in movement disorders are abnormal,” said Waxman, who adds that its real benefit is in helping physicians make an early diagnosis of Parkinson’s.

The use of techniques such as FDG-PET and amyloid plaque imaging in diagnosing Alzheimer’s is an exciting development, Waxman says, but he adds that researchers will have to come up with a way of slowing down the disease or curing it at an early state for this type of imaging to really take off.

Until then, the economics of the issue—the question of whether money should be spent diagnosing a disease that can’t be cured—could hold back widespread use of these imaging techniques, even though Waxman suggests that patients could start putting pressure on physicians to diagnose them with FDG-PET and amyloid testing (once approved).

“How many people have memory lapses and get worried. They want to know what’s going on—what’s happening to them,” Waxman said. “And a physician might do the best he can with neurological exams, but they have a specificity of maybe 50%, so they’re often wrong and they are creating [a diagnosis of] Alzheimer’s in a lot of people who don’t have it.” FDG PET or amyloid testing can eliminate that uncertainty and help physicians come up with a correct diagnosis.

And should researchers come up with a palliative method for treating this disease or even develop an outright cure that is more effective when the disease is detected early, “then everyone is going to want one of these tests,” said Waxman. “The demand for this type of imaging will literally explode.”

Mayo Clinic colleagues Deborah J. Rhodes, MD, Associate Professor of Medicine, and Michael O?Connor, PhD, Professor of Medical Physics, worked together to develop and study a new gamma camera for breast imaging.

Michael O’Connor, PhD—Molecular Breast Imaging

While regular screening mammography can significantly reduce the mortality rate associated with breast cancer, mammography’s effectiveness is reduced when it comes to certain women, particularly those with radiographically dense breasts.

Breast density is categorized in four groups—from DI to D4, with D3 and D4 containing the denser fibroglandular breast tissue. Those two categories represent about 25% of the female population, says Michael O’Connor, PhD, professor of medical physics at Mayo Clinic in Rochester, Minn. “So we’re not talking about a small percentage here.”

The problem with mammography when it comes to dense breast tissue is that it’s very difficult to tell the difference between tumors and dense breast tissue, and “with D4 it’s basically impossible for the mammogram to see anything,” said O’Connor.

But there was a technology that held out great promise for detecting early stage cancers in women with dense breasts—gamma ray imaging, which, unlike x-ray imaging, is not affected by breast density.

The imaging technique now characterized as molecular breast imaging was originally referred to as scintimammography, which involved the use of a conventional gamma camera to image the uptake of a radiotracer in breast tumors. While this technique showed good overall sensitivity and specificity, it had poor sensitivity for detecting small breast tumors.

The problem with using larger conventional gamma cameras, according to O’Connor, was that areas of dead space at the edge of the camera required the patient to be positioned in a way that increased the distance between the breast and the camera and therefore reduced resolution.

So O’Connor and his colleagues built a prototype system that involved the use of smaller gamma cameras utilizing cadmium zinc telluride (CZT). “So now, with the technology, we can reduce the dead space and construct the detectors so they are much like mammographic units in terms of their appearance,” he said.

The design incorporates two opposing CZT detectors. The breast is lightly compressed between the two detectors, and two images of each breast are acquired. The 40-minute procedure is supposed to be much less uncomfortable than conventional mammography (the patient is seated and the pressure exerted on the breast is about one-third that used in conventional mammography). Most importantly, O’Connor says, “when you have the two detectors together, the tumor is never very far away from a detector face, so we get far, far, better resolution and can see everything.”

The result, as reported in an article in the January 2011 issue of Radiology, is that “we’re finding a definite statistical difference between mammography and this technology,” O’Connor said. “We picked up 11 [tumors] per 1,000 where mammography was about three per 1,000.”

Although the procedure is currently FDA-approved as a diagnostic tool, “our goal is to prove that it has a certain value as a screening tool in a certain subset of the population [women with dense breast tissue],” O’Connor said. The initial challenge was that the use of gamma rays involves high doses of radiation that make it problematic to do this kind of imaging on a single patient on a regular basis.

The initial prototype, for example, required the emission of a 20 mCi dose of radiation, which is five times the amount of radiation necessary to perform a digital mammogram.

O’Connor says he and his colleagues made a number of changes to the technology, the biggest improvement of which was to redesign the collimator, which has resulted in an increase in sensitivity by a factor of three. He also used software algorithms to reduce the effects of background noise on the images and, with other refinements, has been able to reduce dose while maintaining resolution.

“And that’s something you can’t normally do in nuclear medicine,” O’Connor said. “You can’t have high resolution and high sensitivity, but by optimizing the design, we’ve kept the resolution and gained dramatically in sensitivity.” And they were able to reduce the radiation dose so that it now approaches that which is comparable to the dose emitted by digital mammography.

Claudia Henschke, MD—Helical CT and Lung Cancer Screening

Claudia Henschke, MD

When Claudia Henschke, MD, decided to focus on chest radiology, it was inevitable that she would become closely involved with the disease that is one of the biggest killers—lung cancer.

And the development of the helical computed tomography scanner was critical to the way in which her career evolved. Its use involves a technique that allows the table holding the patient to move, enabling radiologists to image entire anatomic regions—such as the lungs—in a single breath hold of 20 seconds or less. “So you get fast, very good images, and don’t miss any part of the lungs,” said Henschke, professor of radiology at Mount Sinai Medical Center in New York. “So it revolutionized chest imaging.”

While the introduction of the helical CT scan made screening for lung cancer possible, says Henschke, “what really stimulated me was that we were starting to see all of these nodules as more and more CT scans were obtained. And we had no rational basis on which to make recommendations.”

With a background in statistics as well as radiology, she believed this situation was “exactly what statisticians are looking for,” she recalled. “We needed a data base from which we could make scientific decisions on when these nodules should be followed or whether they should be followed at all.”

With the launch of the Early Lung Cancer Action Project (ELCAP), Henschke and her fellow investigators began developing the protocol for screening people at high risk for lung cancer.

The original study enrolled 1,000 participants over the age of 60 who had been smokers for at least 10 pack years. Participants each received a CT scan and chest x-ray that were read independently; 27 lung cancer cases were diagnosed with CT, while chest x-ray found just seven.

“Any person who’s at high risk of developing lung cancer is going to want to know how likely they are to find a nodule at a certain age, with their smoking history,” said Henschke. “Then how likely is that nodule going to be cancer, and, if cancer, how likely can they be cured. The database of these 1,000 people helped answer that question.”

Advances in imaging technology that have occurred since the time when the ELCAP was launched have been incorporated into the screening protocol, and the program has been extended to more than 60 institutions in nine countries, so that it now includes about 60,000 participants.

Published findings of the study showed some significant results. An article in the New England Journal of Medicine in 2006 reported that the ELCAP protocol for screening allows for at least 80% of lung cancers to be diagnosed at stage I and could lead to a 10-year survival rate of between 80% and 90% among those diagnosed with stage I lung cancer.

Her findings also created controversy. For example, critics suggested screening could detect small lung tumors that might not progress and lead to cancer, but would instead lead to risky, expensive procedures like biopsies that are not really necessary. Other critics suggested that the claims about the survival benefits of CT screening were overstated and that the ELCAP study itself was inadequate because it wasn’t a randomized control trial.

Henschke says she never dreamed her work would create so much turmoil. “When we started, I never thought we would end getting the attention we received,” she said. “And I never realized that can lead to controversy, and pretty violent controversy. That was a big revelation for me.

“There are certain people who are just violently against screening, and it doesn’t matter what you demonstrate,” she said. “And then there are those people who are involved in clinical care, and are interested in screening and have an open mind, but if something is considered to be the gold standard [like traditional mammography] and it’s something they accept, then you’re going to have to go through a lot of additional verification.”

Which came in 2010, when the National Cancer Institute released the results of the National Lung Screening Trial. A $250 million study conducted in 22 sites, it involved 53,000 people, age 55 to 74, who had smoked at least 30 pack years. The participants were given either a standard chest x-ray or a CT scan and followed for up to 5 years.

The study found that CT screening resulted in a 20.3% reduction in lung cancer mortality—above the 20% threshold considered to be statistically significant and a result that was so strong that it persuaded an independent board to stop the trial.

Henschke says that while she was “delighted” with the results, she questioned the basis for deciding whether CT screening was beneficial or not. “What if the result had been that there was a 19.9% reduction?” she asks. “Would the trial have been considered a failure—yet 20% would have meant CT is worth doing?”

The bottom line, she says, is that helical CT has been around for 20 years—time in which it could have been used to save a lot of lives lost to lung cancer. When a new technology—a new MRI scan or a new PET scan—is introduced, “it shouldn’t be dependent on clinical trials that take 10 years and cost a quarter of a billion dollars to put together,” she said. “Trials need to be nimble and efficient because the technology is improving all the time.”

Michael Bassett is a contributing writer for Axis Imaging News.