Alexandra Constantin1, Llewellyn Jalbert1, Adam Elkhaled2, Rupa Parvataneni2, Annette Molinaro2, Joanna Phillips2, Soonmee Cha2, Susan M. Chang2, Sarah J. Nelson2
1University of California, Berkeley, Berkeley, CA, United States; 2University of California, San Francisco
A multivariate diagnostic model was built to estimate the probability that a recurrent low grade glioma had progressed to a higher grade based on in vivo MR imaging parameters. The model was able to discriminate between recurrent low grade gliomas that upgraded versus those that remained grade 2 with 93% cross-validation accuracy and 84% bootstrapping accuracy, based on the 75th percentile normalized choline height, the 25th percentile recovery to baseline of the perfusion susceptibility curve, the 75th percentile ratio of choline to n-acetylaspartate height, and the maximum choline height inside the T2 lesion.