MR-Perfusions- und spektroskopische Bildgebung bei WHO-Grad-II-Astrozytomen

Treatment monitoring in gliomas: comparison of dynamic susceptibility-weighted contrast-enhanced and spectroscopic MRI techniques for identifying treatment failure

OBJECTIVE

To evaluate whether dynamic susceptibility-weighted contrast-enhanced (DSC), dynamic contrast-enhanced (DCE), and proton spectroscopic imaging ((1)H-MRSI) can identify progression and predict treatment failure during follow-up before tumor size changes, contrast agent uptake, or when new lesions become obvious. The aim was also to find out which of the aforementioned techniques had the best diagnostic performance compared with each other and standard magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Thirty-seven patients with gliomas (21 women, 16 men; mean age at inclusion, 48 ± 14 years [standard deviation]) were assessed prospectively by (1)H-MRSI (point-resolved spectroscopy), DCE, and DSC perfusion MRI, each after a single dose of gadobenate dimeglumine during follow-up. Histology was available in all cases (resection, N = 18; biopsy, N = 19). All patients with low-grade gliomas (n = 20) did not receive any radio- or chemotherapy after partial resection (n = 7) or biopsy (n = 13), whereas 17 patients with high-grade gliomas had received adjuvant radiotherapy immediately after surgery. Tumor progression (progressive disease, PD) was defined as increase in longest glioma diameter by at least 20% (Response Evaluation Criteria in Solid Tumors), appearance of new lesions, or new contrast-enhancement. DSC, DCE, and MRSI image analyses comprised a detailed semiquantitative region of interest (ROI) analysis of the different parameters. Wilcoxon signed-rank test, Wilcoxon rank sum test, and Cox regression were used for statistical analysis.

RESULTS

The median follow-up time was 607 days. Twenty patients showed PD (54%), 8 of 20 with low-grade (40%) and 12 of 17 with high-grade gliomas (71%). In PD, significant positive differences between log2-transformed ROI ratios at the last measurement in comparison to the first measurement (baseline) could be detected for tumor blood flow (P < 0.006) and volume (P < 0.001) derived from DSC and for maximum choline within tumor tissue (P = 0.0029) and Cho/Cr (P = 0.032) but not choline/N-acetyl-aspartate (P = 0.37) derived from MRSI. In contrast, these parameters were not significantly higher at last measurement in stable disease. Also, the differences between last value and baseline were significantly different between PD and stable disease for tumor blood flow (P < 0.004) and volume (P < 0.002) as well as for maximum choline within tumor tissue (P = 0.0011). The best prognostic parameter for PD at Cox analysis was time-dependent difference to baseline of log2 of relative regional cerebral blood flow normalized on gray matter (hazard ratio, 2.67; 95% confidence interval, 1.25-6.08; P = 0.01), while a prognostic value of MRS parameters could not be demonstrated.

CONCLUSION

DSC perfusion imaging can identify progression and can predict treatment failure during follow-up of gliomas with the best diagnostic performance.

MRI for identification of progression in brain tumors: from morphology to function

For monitoring of brain tumors, it is crucial to identify progression or treatment failure early during follow-up to change treatment schemes and, thereby, optimize patient outcome. In the past years, several areas within the field of magnetic resonance (MR) have seen considerable advances: modern contrast media, advanced morphologic approaches and several functional techniques, for example, in the visualization of tumor perfusion or tumor cell metabolism. This review presents these recent advances by introducing the different techniques and outlining their benefit for identification of progression in brain tumors, with a focus on gliomas, metastases and meningiomas. After radiotherapy, MR spectroscopy helps to more accurately discriminate between radiation necrosis and glioma progression. In low-grade gliomas, perfusion MR techniques enable a more sensitive detection of anaplastic transformation than conventional MRI. Modern contrast media, as well as diffusion tensor imaging, allow for an improved tumor delineation and assessment of tumor extension. We will also highlight the biological background of these techniques, their applicability and current limitations. In conclusion, modern MRI techniques have been developed that are on the doorstep to be integrated in clinical routine.