New MRI Technique Images Can Predict Brain Tumors Recurrence

Although their physicians monitor the tumor closely with sophisticated imaging modalities, it is difficult to determine with certainty whether cancer has returned in a more malignant state that requires aggressive treatment.

Now a team of investigators from the University of California, San Francisco (UCSF; USA) has developed methods to reveal a molecular marker in tissue samples from brain tumors that has been linked to better survival odds. Monitoring this marker in the brain could provide clinicians with a better approach to follow their patients after surgery.

Although this technique has not yet been modified for routine use in the clinic, it may help clinicians better assess cancer recurrence, make follow-up treatment decisions, and evaluate how a patient responds to recommended treatments-- specifically in patients with low-grade forms of the cancer. “If a tumor transforms to a higher grade, then it is important to use more aggressive treatments,” said Sarah Nelson, PhD, a professor of advanced imaging at UCSF and a professor in the department of radiology and biomedical imaging.

The research group at UCSF used MRI methods to obtain data from image-guided tissue samples from more than 50 patients with glioma that demonstrated the presence of a chemical called 2-HG, associated with mutations in a gene known as IDH1. Research performed in the last two years has shown these mutations are more common in low-grade tumors and are associated with longer survival. More than 70% of patients with low-grade gliomas have mutations to the IDH1 genes in their cancer cells.

Published January 11, 2012, in the journal Science Translational Medicine, the study required the use of specialized methods and equipment that was sensitive enough to detect the 2-HG in small tissue samples. A companion paper from a group at Harvard University (Cambridge, MA, USA) was published in the same issue and revealed dearly findings indicating that 2-HG could be detected noninvasively from comparatively large regions of tumor in two patients with IDH1 mutations.

The techniques now used must be refined so that standard hospital MRI scanners can image the presence of 2-HG. “Developing methods to obtain images in a clinical setting is an engineering challenge now,” Dr. Nelson concluded.

Related Links:
University of California, San Francisco
Harvard University