Introduction: Multi-voxel MR spectroscopic imaging (MRSI) provides chemical metabolite information that can supplement conventional MR imaging in the study of intracranial neoplasia. Our purpose was to use a robust semi-automated spectroscopic analysis to distinguish intracranial tumours from non-neoplastic disease. Materials and Methods: Twenty intracranial tumours and 15 patients with non-neoplastic disease confirmed on histological examination or serial neuroimaging were studied with 2-dimensional MRSI using point-resolved spectroscopic (PRESS) imaging localisation. Using semi-automated post-processing software, spectra were analysed for peak heights of choline (Cho), creatine (Cr), N-acetyl aspartate (NAA), lactate (Lac) and lipid (Lip). Normalised Cho (nCho) ratios, computed by dividing maximum Cho in the lesion by the normal-appearing brain, were compared between intracranial tumours and non-neoplastic disease. Results: Meningiomas displayed homogenously elevated Cho. Malignant tumours, especially large glioblastoma multiforme, displayed inhomogeneity of metabolites within the tumour. All tumours had elevation of nCho >1 (mean 1.91 ± 0.65), and non-neoplastic diseases had tumour nCho <1 (mean 0.91 ± 0.46), which was significantly lower (P <0.05). Two patients with non-neoplastic lesions, one with subacute cerebral infarction and the other with cryptococcoma, had elevated Cho compared to normal tissue (false positive rate 13%). Conclusion: Using semi-automated MRSI method, a simplified normalised Cho algorithm provides a method to distinguish intracranial tumours from non-neoplastic disease.
The presence of focal intracranial disease may be due to a variety of diseases, including primary neoplasm, metastatic tumour, abscess, subacute infarction and developmental anomalies. It is important to distinguish tumours from non-neoplastic mimics as the appropriate treatment is very different in each pathology. Although magnetic resonance imaging (MRI) is important for the diagnosis of intracranial disease, sometimes the appearances on conventional contrast-enhanced MRI may not be specific. This limits the accuracy and capability of MRI for distinguishing tumour from non-neoplastic conditions and benign from malignant disease. Therefore, a non-invasive imaging method that can improve the diagnostic accuracy would be desirable, especially in ambiguous or atypical cases, to avoid delay in starting treatment and unnecessary biopsy.
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