(1) H 2D MRSI tissue type analysis of gliomas.

PURPOSE: To decompose 1H MR spectra of glioma patients into normal and abnormal tissue proportions for tumor classification and delineation. METHODS: Anatomical imaging and 1H magnetic resonance spectroscopic imaging data have been acquired from 11 grade II and 13 grade IV glioma patients. LCModel was used to decompose the magnetic resonance spectroscopic imaging data into normal brain, grade II, and grade IV tissue proportions using a tissue type basis set. Simulations were conducted to evaluate the accuracy of the methodology. Results were visualized using colormaps and abnormality contours showing tumor grade and extent. RESULTS: Simulations suggest that infiltrative tumor proportions as low as 20% can be identified at the typical 1H magnetic resonance spectroscopy signal-to-noise found in vivo. Tumor grading according to the highest estimated tumor grade within a lesion gave a classification accuracy of 86% discriminating between grade II and grade IV glioma. Voxels with significant proportions of tumor type spectra were found beyond the margins of contrast enhancement for most grade IV cases consistent with infiltration whereas the abnormality contours show that some tumors are confined within the hyperintensities shown by both post contrast T1 weighted and T2 weighted imaging. CONCLUSION: LCModel can be used to decompose 1H MR spectra into proportions of normal and abnormal tissue to identify tumor extent, infiltration, and overall grade.

Combined use of neuroradiology and 1H-MR spectroscopy may provide an intervention limiting diagnosis of glioblastoma multiforme.

PURPOSE: To evaluate the accuracy of (1)H-MR spectroscopy ((1)H-MRS) as an intervention limiting diagnostic tool for glioblastoma multiforme. GBM is the most common and aggressive primary brain tumor, with mean survival under a year. Oncological practice currently requires histopathological diagnosis before radiotherapy. MATERIALS AND METHODS: Eighty-nine patients had clinical computed tomography (CT) and MR imaging and 1.5T SV SE (1)H-MRS with PRESS localization for neuroradiological diagnosis and tumor classification with spectroscopic and automated pattern recognition analysis (TE 30 ms, TR 2000 ms, spectral width 2500 Hz and 2048 data points, 128-256 signal averages were acquired, depending on voxel size (8 cm(3) to 4 cm(3)). Eighteen patients from a cohort of 89 underwent stereotactic biopsy. RESULTS: The 18 stereotactic biopsies revealed 14 GBM, 2 grade II astrocytomas, 1 lymphoma, and 1 anaplastic astrocytoma. All 14 biopsied GBMs were diagnosed as GBM by a protocol combining an individual radiologist and an automated spectral pattern recognition program. CONCLUSION: In patients undergoing stereotactic biopsy combined neuroradiological and spectroscopic evaluation diagnoses GBM with accuracy that could replace the need for biopsy. We do not advocate the replacement of biopsy in all patients; instead our data suggest a specific intervention limiting role for the use of (1)H-MRS in brain tumor diagnosis.

Ex-vivo HRMAS of adult brain tumours: metabolite quantification and assignment of tumour biomarkers.

BACKGROUND: High-resolution magic angle spinning (HRMAS) NMR spectroscopy allows detailed metabolic analysis of whole biopsy samples for investigating tumour biology and tumour classification. Accurate biochemical assignment of small molecule metabolites that are "NMR visible" will improve our interpretation of HRMAS data and the translation of NMR tumour biomarkers to in-vivo studies. RESULTS: 1D and 2D 1H HRMAS NMR was used to determine that 29 small molecule metabolites, along with 8 macromolecule signals, account for the majority of the HRMAS spectrum of the main types of brain tumour (astrocytoma grade II, grade III gliomas, glioblastomas, metastases, meningiomas and also lymphomas). Differences in concentration of 20 of these metabolites were statistically significant between these brain tumour types. During the course of an extended 2D data acquisition the HRMAS technique itself affects sample analysis: glycine, glutathione and glycerophosphocholine all showed small concentration changes; analysis of the sample after HRMAS indicated structural damage that may affect subsequent histopathological analysis. CONCLUSIONS: A number of small molecule metabolites have been identified as potential biomarkers of tumour type that may enable development of more selective in-vivo 1H NMR acquisition methods for diagnosis and prognosis of brain tumours.