Towards MRI Differentiation of Recurring Tumor from Delayed Radiation Necrosis
Carlos J Perez-Torres, John A Engelbach, Jeremy Cates, Dinesh K Thotala, Robert E Drzymala, Joseph JH Ackerman, and Joel R Garbow Department of Radiology, Washington University in Saint Louis, Saint Louis, Missouri, United States, Department of Radiation Oncology, Washington University in Saint Louis, Saint Louis, Missouri, United States, Department of Chemistry, Washington University in Saint Louis, Saint Louis, Missouri, United States
The role of diffusion-weighted imaging in patients with brain tumors.
BACKGROUND AND PURPOSE
Diffusion-weighted images (DWIs) have been used to study various diseases, particularly since echo-planar techniques shorten examination time. Our hypothesis was that DWIs and tumor apparent diffusion coefficients (ADCs) could provide additional useful information in the diagnosis of patients with brain tumors.


METHODS
Using a 1.5-T MR unit, we examined 56 patients with histologically verified or clinically diagnosed brain tumors (17 gliomas, 21 metastatic tumors, and 18 meningiomas). We determined ADC values and signal intensities on DWIs both in the solid portion of the tumor and in the peritumoral, hyperintense areas on T2-weighted images. We also evaluated the correlation between ADC values and tumor cellularity in both gliomas and meningiomas.


RESULTS
The ADCs of low-grade (grade II) astrocytomas were significantly higher (P =.0004) than those of other tumors. Among astrocytic tumors, ADCs were higher in grade II astrocytomas (1.14 +/- 0.18) than in glioblastomas (0.82 +/- 0.13). ADCs and DWIs were not useful in determining the presence of peritumoral neoplastic cell infiltration. The ADC values correlated with tumor cellularity for both astrocytic tumors (r = -.77) and meningiomas (r = -.67).


CONCLUSION
The ADC may predict the degree of malignancy of astrocytic tumors, although there is some overlap between ADCs of grade II astrocytomas and glioblastomas.
MR Spectroscopic Changes in the Rat Hippocampus following Proton Radiosurgery
Purpose: To identify MR spectroscopic changes in the rat hippocampus following proton radiosurgery. Methods and Materials: A group of 12 rats were treated with Bragg peak proton beam irradiation involving the right hippocampus. Single doses of 30 CGE, 50 CGE, 70 CGE, 90 CGE were delivered to groups of 3 animals using single fraction technique. Animals were imaged using a standard 3 T GE Signa MRI at 4 months following treatment. An untreated animal was also studied. A 3″ surface coil was employed to obtain T1 weighted coronal pre- and post-gadolinium images (TR 600 and TE 30) and dual echo T2 weighted coronal images (TR 3000, TE 30/90). Volumetric analysis with custom software was done to evaluate areas of increased signal on T2 weighted images and the development of hydrocephalus was examined. Animals were sacrificed and specimens of the treated hippocampus were harvested for High Resolution Magic Angle Spinning MR Spectroscopy (HRMAS) followed by histopathology of the tissue samples. Peak values of choline, creatine, N-acetyl aspartate and lipids were evaluated and compared. Results: Peak tissue injury occurred in the surviving 90 CGE animal by both T2 weighted and post-gadolinium imaging. Gadolinium enhancement was seen in decreasing volumes of tissue at dosage levels from 90 to 50 CGE. Hydrocephalus was seen on the untreated side in the 90 CGE animal likely because of mass effect, while it was seen in small degrees in the side of treatment in the 70 and 50 CGE animals. Histopathology showed changes at 90 and 70 CGE, but not at 50 or 30 CGE at this time point using H and E stains. HRMAS showed spectroscopic changes in the surviving 90 and 70 CGE animals but not in the 50 and 30 CGE animals. Statistical significance was not reached because of the small sample size. Conclusions: Following single dose proton radiosurgery of rat hippocampus, HRMAS is able to identify metabolic changes induced by radiation. Studies built on these principles may help develop non-invasive MR spectroscopic methods to distinguish radiation changes from tumor recurrence.