[Grading of adults primitive glial neoplasms using arterial spin-labeled perfusion MR imaging]

The value of arterial spin labelling in adults glioma grading: systematic review and meta-analysis

This study aimed to evaluate the diagnostic performance of arterial spin labelling (ASL) in grading of adult gliomas. Eighteen studies matched the inclusion criteria and were included after systematic searches through EMBASE and MEDLINE databases. The quality of the included studies was assessed utilizing Quality Assessment of Diagnostic Accuracy Studies-2 (QUADAS-2). The quantitative values were extracted and a meta-analysis was subsequently based on a random-effect model with forest plot and joint sensitivity and specificity modelling. Hierarchical summary receiver operating characteristic (HROC) curve analysis was also conducted. The absolute tumour blood flow (TBF) values can differentiate high-grade gliomas (HGGs) from low-grade gliomas (LGGs) and grade II from grade IV tumours. However, it lacked the capacity to differentiate grade II from grade III tumours and grade III from grade IV tumours. In contrast, the relative TBF (rTBF) is effective in differentiating HGG from LGG and in glioma grading. The maximum rTBF (rTBFmax) demonstrated the best results in glioma grading. These results were also reflected in the sensitivity/specificity analysis in which the rTBFmax showed the highest discrimination performance in glioma grading. The estimated effect size for the rTBF was approximately similar between HGGs and LGGs, and grade II and grade III tumours, (-1.46 (-2.00, -0.91), p-value < 0.001), (-1.39 (-1.89, -0.89), p-value < 0.001), respectively; while it exhibited smaller effect size between grade III and grade IV (-1.05 (-1.82, -0.27)), p < 0.05). Sensitivity and specificity analysis replicate these results as well. This meta-analysis suggests that ASL is useful for glioma grading, especially when considering the rTBFmax parameter.

Intra-Arterial MR Perfusion Imaging of Meningiomas: Comparison to Digital Subtraction Angiography and Intravenous MR Perfusion Imaging

BACKGROUND AND PURPOSE

To evaluate the ability of IA MR perfusion to characterize meningioma blood supply.

METHODS

Studies were performed in a suite comprised of an x-ray angiography unit and 1.5T MR scanner that permitted intraprocedural patient movement between the imaging modalities. Patients underwent intra-arterial (IA) and intravenous (IV) T2* dynamic susceptibility MR perfusion immediately prior to meningioma embolization. Regional tumor arterial supply was characterized by digital subtraction angiography and classified as external carotid artery (ECA) dural, internal carotid artery (ICA) dural, or pial. MR perfusion data regions of interest (ROIs) were analyzed in regions with different vascular supply to extract peak height, full-width at half-maximum (FWHM), relative cerebral blood flow (rCBF), relative cerebral blood volume (rCBV), and mean transit time (MTT). Linear mixed modeling was used to identify perfusion curve parameter differences for each ROI for IA and IV MR imaging techniques. IA vs. IV perfusion parameters were also directly compared for each ROI using linear mixed modeling.

RESULTS

18 ROIs were analyzed in 12 patients. Arterial supply was identified as ECA dural (n = 11), ICA dural (n = 4), or pial (n = 3). FWHM, rCBV, and rCBF showed statistically significant differences between ROIs for IA MR perfusion. Peak Height and FWHM showed statistically significant differences between ROIs for IV MR perfusion. RCBV and MTT were significantly lower for IA perfusion in the Dural ECA compared to IV perfusion. Relative CBF in IA MR was found to be significantly higher in the Dural ICA region and MTT significantly lower compared to IV perfusion.

Brain perfusion: computed tomography and magnetic resonance techniques

Cerebral perfusion imaging provides assessment of regional microvascular hemodynamics in the living brain, enabling in vivo measurement of a variety of different hemodynamic parameters. Perfusion imaging techniques that are used in the clinical setting usually rely upon X-ray computed tomography (CT) or magnetic resonance imaging (MRI). This chapter reviews CT- and MRI-based perfusion imaging techniques, with attention to image acquisition, clinically relevant aspects of image postprocessing, and fundamental differences between CT- and MRI-based techniques. Correlations with cerebrovascular physiology and potential clinical applications of perfusion imaging are reviewed, focusing upon the two major classes of neurologic disease in which perfusion imaging is most often performed: primary perfusion disorders (including ischemic stroke, transient ischemic attack, and reperfusion syndrome), and brain tumors.

Optimization of arterial spin labeling MRI for quantitative tumor perfusion in a mouse xenograft model

Perfusion is an important biomarker of tissue function and has been associated with tumor pathophysiology such as angiogenesis and hypoxia. Arterial spin labeling (ASL) MRI allows noninvasive and quantitative imaging of perfusion; however, the application in mouse xenograft tumor models has been challenging due to the low sensitivity and high perfusion heterogeneity. In this study, flow-sensitive alternating inversion recovery (FAIR) ASL was optimized for a mouse xenograft tumor. To assess the sensitivity and reliability for measuring low perfusion, the lumbar muscle was used as a reference region. By optimizing the number of averages and inversion times, muscle perfusion as low as 32.4 ± 4.8 (mean ± standard deviation) ml/100 g/min could be measured in 20 min at 7 T with a quantification error of 14.4 ± 9.1%. Applying the optimized protocol, heterogeneous perfusion ranging from 49.5 to 211.2 ml/100 g/min in a renal carcinoma was observed. To understand the relationship with tumor pathology, global and regional tumor perfusion was compared with histological staining of blood vessels (CD34), hypoxia (CAIX) and apoptosis (TUNEL). No correlation was observed when the global tumor perfusion was compared with these pathological parameters. Regional analysis shows that areas of high perfusion had low microvessel density, which was due to larger vessel area compared with areas of low perfusion. Nonetheless, these were not correlated with hypoxia or apoptosis. The results suggest that tumor perfusion may reflect certain aspect of angiogenesis, but its relationship with other pathologies needs further investigation.

Early detection of antiangiogenic treatment responses in a mouse xenograft tumor model using quantitative perfusion MRI

Angiogenesis plays a major role in tumor growth and metastasis, with tumor perfusion regarded as a marker for angiogenesis. To evaluate antiangiogenic treatment response in vivo, we investigated arterial spin labeling (ASL) magnetic resonance imaging (MRI) to measure tumor perfusion quantitatively. Chronic and 24-h acute treatment responses to bevacizumab were assessed by ASL and dynamic-contrast-enhanced (DCE) MRI in the A498 xenograft mouse model. After the MRI, tumor vasculature was assessed by CD34 staining. After 39 days of chronic treatment, tumor perfusion decreased to 44.8 ± 16.1 mL/100 g/min (P < 0.05), compared to 92.6 ± 42.9 mL/100 g/min in the control group. In the acute treatment study, tumor perfusion in the treated group decreased from 107.2 ± 32.7 to 73.7 ± 27.8 mL/100 g/min (P < 0.01; two-way analysis of variance), as well as compared with control group post dosing. A significant reduction in vessel density and vessel size was observed after the chronic treatment, while only vessel size was reduced 24 h after acute treatment. The tumor perfusion correlated with vessel size (r = 0.66; P < 0.005) after chronic, but not after acute treatment. The results from DCE-MRI also detected a significant change between treated and control groups in both chronic and acute treatment studies, but not between 0 and 24 h in the acute treatment group. These results indicate that tumor perfusion measured by MRI can detect early vascular responses to antiangiogenic treatment. With its noninvasive and quantitative nature, ASL MRI would be valuable for longitudinal assessment of tumor perfusion and in translation from animal models to human.