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New imaging method gives early indication if brain cancer therapy is effective, U-M study shows

later that it had no effect? Using MRI tumor diffusion values to accurately predict the treatment response early on could allow some patients to switch to a more beneficial therapy and avoid the side effects of a prolonged and ineffective treatment," said Brian Ross, Ph.D., professor of radiology and biological chemistry at the U-M Medical School and a member of the U-M Comprehensive Cancer Center.

In the study, 20 participants with brain tumors underwent diffusion MRI before beginning a new treatment involving chemotherapy, radiation therapy or a combination. Three weeks later, they had another diffusion MRI. After finishing their treatment, the participants underwent standard MRI to determine whether their tumor responded to the therapy.

After three weeks ?more than two months before the final MRI scan ?researchers found significant differences between the patients' scans. Some areas reflected an increase in water diffusion, suggesting tumor cell death; other areas saw a decrease in diffusion, which Ross said could be accounted for by the swelling some cells undergo before dying; and in some participants, researchers saw no change in diffusion.

"In the end, we found if the diffusion changes in any way, up or down, it correlates to a positive outcome. The magnitude or amount of change relates to the effectiveness of treatment. This indicates a different mixture of cell death pathways within the tumors. In the end, any change is good. When you think about it, if the treatment is not having an effect, the tumor will continue to grow without any change to water diffusion," Ross said.

The researchers found that for each of the 20 patients, a change in the diffusion MRI accurately predicted the tumor's response. Researchers plan to test the technique with breast cancer and head and neck cancer.

In addition to Ross, U-M study authors are Bradford Moffat, Ph.D., assistant professor of radiology; Thomas Chenevert, Ph.D., professor of
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Source:University of Michigan Health System


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