A new optical imaging system uses red and NIR light to identify breast cancer patients who may benefit most from chemotherapy. The dynamic diffuse optical tomography system could predict response to chemotherapy as early as two weeks after a patient begins treatment. These series of images are cross sections of a breast with a tumor, taken during a breath hold. As a patient holds their breath, the blood concentration increases by up to 10 percent. Researchers found that analyzing the increase and decrease in blood concentrations inside a tumor could help them determine which patients would respond to chemotherapy. Courtesy of Andreas Hielscher/Columbia Engineering. The tomographic breast imaging system offers a non-invasive method of measuring blood flow dynamics in response to a single breath hold. The system generates 3D images of both breasts simultaneously, enabling researchers to look at blood flow in the breasts and see how the vasculature changes and how the blood interacts with the tumor. “This helps us distinguish malignant from healthy tissue and tells us how the tumor is responding to chemotherapy earlier than other imaging techniques can,” said professor Andreas Hielscher. Blood flows freely through healthy breasts, but in breasts with tumors, blood gets soaked up by the tumor, inhibiting blood flow. Chemotherapy drugs kill cancer cells, but they also affect the vasculature inside the tumor. The research team from Columbia University surmised that clues of these vascular changes could be picked up optically, since blood is a strong absorber of light. Researchers analyzed imaging data from 34 patients with invasive breast cancer between June 2011 and March 2016. They captured a series of images during a breath hold of at least 15 seconds, which is long enough to inhibit the backflow of blood through the veins but not the inflow through the arteries. Additional images were captured after the breath was released, allowing the blood to flow out of the veins in the breasts. Images were obtained before and two weeks after starting chemotherapy. The researchers compared the images with the patients’ outcomes after five months of chemotherapy. They found that various aspects of the blood inflow and outflow could be used to distinguish between patients who responded and those who did not respond to therapy. For example, the rate of blood outflow could be used to correctly identify responders in 92.3 percent of patients, while the initial increase of blood concentration inside the tumor could be used to identify non-responders in 90.5 percent of patients. “There is currently no method that can predict treatment outcome of chemotherapy early on in treatment,” said Hielscher. “If we can confirm these results in the larger study that we are planning to begin soon, this imaging system may allow us to personalize breast cancer treatment and offer the treatment that is most likely to benefit individual patients," said professor Dawn Hershman, MD. Hielscher and Hershman are currently refining and optimizing the imaging system and are planning a larger, multicenter clinical trial. They hope to commercialize their technology in the next three to five years. The research was published in Radiology (doi: 10.1148/radiol.2018161041). These series of images are cross sections of a breast with a tumor, taken during a breath hold. As a patient holds their breath, the blood concentration increases by up to 10 percent. Researchers at Columbia found that analyzing the increase and decrease in blood concentrations inside a tumor could help them determine which patients would respond to chemotherapy. Courtesy of Andreas Hielscher/Columbia Engineering. These series of images are cross sections of a breast with a tumor, taken during a breath hold. As a patient holds their breath, the blood concentration increases by up to 10 percent. Researchers at Columbia found that analyzing the increase and decrease in blood concentrations inside a tumor could help them determine which patients would respond to chemotherapy. Courtesy of Andreas Hielscher/Columbia Engineering.