New technique images tumor vessel leakiness to predict breast cancer chemothera...( Chemotherapy is an integral part of ...)

Chemotherapy is an integral part of modern cancer treatment, but it's not always effective. Successful chemotherapy depends on the ability of anticancer drugs to escape from the bloodstream through the leaky blood vessels that often surround tumors.

Predicting chemotherapy's efficacy could save thousands of individuals from unnecessary toxicity and the often difficult side effects of the treatments.

In a study published in the February issue of the journal Radiology, researchers describe a technique for determining the "leakiness" of tumor blood vessels using a simple digital mammography unit. The researchers designed nanometer-sized capsules containing a contrast agent that could only leak into tumors with blood vessels that were growing and therefore leaky. The digital mammography-based quantification of "leakiness" is closely correlated to the ability of a clinically approved chemotherapy agent to enter the tumor, allowing the researchers to predict the agent's therapeutic efficacy.

"We developed a quantitative way to measure the leakiness of the blood vessels, which is directly linked to the amount of drug that gets to the cancer and in turn determines effectiveness," said Ravi Bellamkonda, a professor in the Wallace H. Coulter Department of Biomedical Engineering at Georgia Tech and Emory University. "By simply measuring how much contrast agent reaches the tumor, we can predict how much of a clinically approved chemotherapeutic will reach the tumor, allowing physicians to personalize the dose and predict effectiveness."

In some cases, one chemotherapy drug may not be effective in treating the tumor, but this new technique allows oncologists to investigate other drugs sooner since they know the drug is reaching the tumor. Studies are currently underway to determine if mammography can predict the optimal dose of a wide range of breast cancer chemotherapeutics.

Bellamkonda and Coulter Department postdoc
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