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Quantification of Nonenhancing Tumor Burden in Gliomas Using Effective T2 Maps Derived from Dual-Echo Turbo Spin-Echo
Benjamin M Ellingson1, Albert Lai2, Huytram N Nguyen3
1UCLA Neuro-Oncology Program, David Geffen School of Medicine, University of California, Los Angeles, California. Department of Radiological Sciences, David Geffen School of Medicine, University of California, Los Angeles, California. Biomedical Physics Program, David Geffen School of Medicine, University of California, Los Angeles, California. Department of Bioengineering, Henry Samueli School of Engineering and Applied Science, University of California, Los Angeles, California. UCLA Brain Research Institute, David Geffen School of Medicine, University of California, Los Angeles, California. Jonsson Comprehensive Cancer Center, University of California, Los Angeles, California. bellingson@mednet.ucla.edu.
Purpose:
Evaluation of nonenhancing tumor (NET) burden is an important yet challenging part of brain tumor response assessment. This study focuses on using dual-echo turbo spin-echo MRI as a means of quickly estimating tissue T2, which can be used to objectively define NET burden.
Experimental Design:
A series of experiments were performed to establish the use of T2 maps for defining NET burden. First, variation in T2 was determined using the American College of Radiology (ACR) water phantoms in 16 scanners evaluated over 3 years. Next, the sensitivity and specificity of T2 maps for delineating NET from other tissues were examined. Then, T2-defined NET was used to predict survival in separate subsets of patients with glioblastoma treated with radiotherapy, concurrent radiation, and chemotherapy, or bevacizumab at recurrence.
Results:
Variability in T2 in the ACR phantom was 3% to 5%. In training data, ROC analysis suggested that 125 ms < T2 < 250 ms could delineate NET with a sensitivity of >90% and specificity of >65%. Using this criterion, NET burden after completion of radiotherapy alone, or concurrent radiotherapy, and chemotherapy was shown to be predictive of survival (Cox, P < 0.05), and the change in NET volume before and after bevacizumab therapy in recurrent glioblastoma was also a predictive of survival (P < 0.05).
Conclusions:
T2 maps using dual-echo data are feasible, stable, and can be used to objectively define NET burden for use in brain tumor characterization, prognosis, and response assessment. The use of effective T2 maps for defining NET burden should be validated in a randomized, clinical trial.
