4.6 Article

Treatment Monitoring in Gliomas Comparison of Dynamic Susceptibility-Weighted Contrast-Enhanced and Spectroscopic MRI Techniques for Identifying Treatment Failure

Journal

INVESTIGATIVE RADIOLOGY
Volume 46, Issue 6, Pages 390-400

Publisher

LIPPINCOTT WILLIAMS & WILKINS
DOI: 10.1097/RLI.0b013e31820e1511

Keywords

Glioma; radio-chemotherapy; magnetic resonance imaging; MR spectroscopy; dynamic contrast-enhanced MRI; perfusion

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Objective: To evaluate whether dynamic susceptibility-weighted contrast-enhanced (DSC), dynamic contrast-enhanced (DCE), and proton spectroscopic imaging (H-1-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 H-1-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.

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