In transforming low-grade glioma, susceptibility-weighted MR perfusion imaging can demonstrate significant increases in rCBV up to 12 months before contrast enhancement is apparent on T1-weighted MR images.

The subtypes of glioma are known to have different prognosis and response to treatment. The purpose of this work was to investigate whether apparent diffusion coefficient (ADC) histograms of untreated low-grade astrocytomas and oligodendrogliomas exhibit different characteristics due to their biological differences, and whether a diagnosis of tumour subtype can be made at presentation using the histogram alone, which, if possible, would have an impact on clinical practise. Fifteen patients with astrocytoma (AC) [11 male (mean age +/- standard deviation) 40 +/- 11 years], nine with oligodendroglioma (OD) (four male, 45 +/- 13 years) and three with oligoastrocytoma (OA) (two male, 60 +/- 11 years) were recruited and diffusion-weighted images (b = 0 and 1000 s mm(-2)) were acquired every 6 months to date or until malignant transformation. Whole tumour ADC histograms were calculated, a multiple discriminant analysis was performed and quantitative morphological parameters extracted, the AC and OD subtypes were then compared using Student's unpaired t-test. Classification of the histograms was also performed. ODs had significantly lower group ADC values than ACs and up to 83% of the subjects could be correctly classified into the OD and AC groups by reference to the histogram. The group differences were most significant for the multiple discriminant analysis (p = 1 x 10(-5)) and at the 10th centile point [AC = 1170 +/- 170, OD = (1030 +/- 80) x 10(-6) mm(2) s(-1)] (p = 0.01). ODs have a lower ADC than ACs with differences throughout the histogram. Both tumour types show similar intra-tumour heterogeneity, as seen from the equal group peak heights, but ACs shows more intra-group heterogeneity. ADC histogram analysis may aid non-invasive sub-classification of low-grade glioma histological subtypes.

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Six-month tumor growth helps predict outcome in patients with LGG better than parameters derived from perfusion- or diffusion-weighed MR imaging. Tumor growth can readily be calculated from volume measurements on images acquired with standard MR imaging protocols and may well prove most useful among various MR imaging findings in clinical practice.