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Sizing up cancer imaging
Imaging plays an integral role at all stages of cancer care.
“We use imaging for cancer in a few different settings,” says Dennis Hallahan, M.D., Ingram Professor of Cancer Research and professor and chair of Radiation Oncology at Vanderbilt-Ingram Cancer Center.
One of the most common uses for imaging is in screening for cancer, for example, traditional mammography screening for breast cancer. When cancer is suspected, imaging is used to find where the cancer is located in the body.
Beyond diagnosis, imaging plays an important role in determining how advanced the disease is. This process, called staging, Hallahan explains, “tells us the best way to manage the disease. For example, if a patient has metastatic disease, they’re probably not going to undergo surgery.”
Imaging can also help physicians and researchers evaluate a patient’s response to therapy and monitor for cancer recurrence. This use is particularly important for measuring the effectiveness of new therapeutics.
While standard imaging modalities have been central to improving diagnosis and cancer care, the measurements they give are crude estimates of cancer response.
“Historically, the things imaging is used for…are all based on morphology – sizes and shapes and volumes of the tumor,” says Thomas Yankeelov, Ph.D., Cancer Center member and director of Cancer Imaging at VUIIS. To monitor tumor response to therapy, for example, the size of the tumor after treatment is compared to tumor size before treatment based on a CT or MRI scan. But these measurements are only recorded for the two longest dimensions.
“That’s very limiting because every object in the known universe has three dimensions,” he says. “You can imagine, if (the tumor) is shifting, you may not even necessarily be measuring the same two dimensions before and after treatment.”
Yankeelov notes that only recently has the refinement of existing technologies – like CT and MRI – made it possible to obtain 3-D views of tumors and to determine their volume, a better indicator of long-term response than the “longest dimension” criteria.
Using these criteria, changes in tumor size can usually only be detected after several weeks or months of treatment – a delay that can waste valuable time on ineffective treatments. Since the earliest responses to a cancer treatment occur on a much smaller (cellular) scale, the next generation of imaging methods will have to move beyond these rough physical parameters and probe the invisible realm – the biology of the tumor.
“What we’re trying to do now is to figure out what are the next generation of imaging devices and how should they be used in the clinic,” says Yankeelov. “We’re trying to be more quantitative in characterizing tumors. Instead of just measuring the tumor’s longest dimension, we want to know the volume, the tumor’s metabolic rate, the blood flow, hypoxia distribution, etc.”
Some of these features can be determined invasively with biopsies, says Yankeelov. But repeated biopsies are not practical in the clinic, and biopsies, by their nature, sample only a small portion of the tumor.
“We want to figure out how we can make those measurements with imaging, so that we can do it longitudinally and over time without having to cut into people,” Yankeelov says. Bringing these methods into the clinic for use in humans, however, first requires thorough studies in animals.
Animal models of cancer – especially genetically engineered mice – are central to bringing new imaging techniques to the clinic.
The VUIIS recently received a five-year, $2.2 million grant from the National Cancer Institute (NCI) to apply new imaging techniques for studying cancer in small laboratory animals. This funding helped establish VUIIS as one of only 12 Centers for Small Animal Imaging in the nation.
The center houses scaled-down and more refined versions of all of the major medical imaging devices – including CT, MRI, PET, SPECT and ultrasound. Some other imaging methods, like optical imaging, are so far used mostly in preclinical (animal) research, with a few specialized clinical applications.
“All of them have a lot more flexibility than what you might find in the clinic,” says Yankeelov. And they all provide different information about the tumor.
“There’s no one imaging method that will answer all questions – they all have different strengths and weaknesses.”
Researchers often use different combinations of imaging methods to study cancer. But matching up the data from one imaging method to data from another is a major technical obstacle. To facilitate this process for use in small animal research, VUIIS members, whose expertise range from biology to physics and mathematics, have been developing procedures to help facilitate this process, called “registration.”
Yankeelov, a mathematician by training, is building mathematical models that synthesize data from multiple modalities, “so that you can truly have a comprehensive imaging characterization of tumor response.” |
