Comparison of the Effect of Vessel Size Imaging and Cerebral Blood Volume Derived from Perfusion MR Imaging on Glioma Grading

Advanced MR Techniques for Preoperative Glioma Characterization: Part 1

Preoperative clinical magnetic resonance imaging (MRI) protocols for gliomas, brain tumors with dismal outcomes due to their infiltrative properties, still rely on conventional structural MRI, which does not deliver information on tumor genotype and is limited in the delineation of diffuse gliomas. The GliMR COST action wants to raise awareness about the state of the art of advanced MRI techniques in gliomas and their possible clinical translation or lack thereof. This review describes current methods, limits, and applications of advanced MRI for the preoperative assessment of glioma, summarizing the level of clinical validation of different techniques. In this first part, we discuss dynamic susceptibility contrast and dynamic contrast-enhanced MRI, arterial spin labeling, diffusion-weighted MRI, vessel imaging, and magnetic resonance fingerprinting. The second part of this review addresses magnetic resonance spectroscopy, chemical exchange saturation transfer, susceptibility-weighted imaging, MRI-PET, MR elastography, and MR-based radiomics applications. Evidence Level: 3 Technical Efficacy: Stage 2.

Microvasculature Features Derived from Hybrid EPI MRI in Non-Enhancing Adult-Type Diffuse Glioma Subtypes

In this study, we used the vessel size imaging (VSI) MRI technique to characterize the microvasculature features of three subtypes of adult-type diffuse glioma lacking enhancement. Thirty-eight patients with confirmed non-enhancing glioma were categorized into three subtypes: Oligo (IDH-mut&1p/19q-codeleted), Astro (IDH-mut), and GBM (IDH-wt). The VSI technique provided quantitative maps of cerebral blood volume (CBV), microvasculature (µCBV), and vessel size for each patient. Additionally, tissue samples of 21 patients were histopathologically analyzed, and microvasculature features were quantified. Both MRI- and histology-derived features were compared across the three glioma subtypes with ANOVA or Kruskal–Wallis tests. Group averages of CBV, μCBV, and vessel size were significantly different between the three glioma subtypes (p < 0.01). Astro (IDH-mut) had a significantly lower CBV and µCBV compared to Oligo (IDH-mut&1p/19q-codeleted) (p = 0.004 and p = 0.001, respectively), and a higher average vessel size compared to GBM (IDH-wt) (p = 0.01). The histopathological analysis showed that GBM (IDH-wt) possessed vessels with more irregular shapes than the two other subtypes (p < 0.05). VSI provides a good insight into the microvasculature characteristics of the three adult-type glioma subtypes even when lacking enhancement. Further investigations into the specificity of VSI to differentiate glioma subtypes are thus warranted.

Differentiation of Cerebral Neoplasms with Vessel Size Imaging (VSI)

PURPOSE

Cerebral neoplasms of various histological origins may show comparable appearances on conventional Magnetic Resonance Imaging (MRI). Vessel size imaging (VSI) is an MRI technique that enables noninvasive assessment of microvasculature by providing quantitative estimates of microvessel size and density. In this study, we evaluated the potential of VSI to differentiate between brain tumor types based on their microvascular morphology.

METHODS

Using a clinical 3T MRI scanner, VSI was performed on 25 patients with cerebral neoplasms, 10 with glioblastoma multiforme (GBM), 8 with primary CNS lymphoma (PCNSL) and 7 with cerebral lung cancer metastasis (MLC). Following the postprocessing of VSI maps, mean vessel diameter (vessel size index, vsi) and microvessel density (Q) were compared across tumors, peritumoral areas, and healthy tissues.

RESULTS

The MLC tumors have larger and less dense microvasculature compared to PCNSLs in terms of vsi and Q (p = 0.0004 and p < 0.0001, respectively). GBM tumors have higher yet non-significantly different vsi values than PCNSLs (p = 0.065) and non-significant differences in Q. No statistically significant differences in vsi or Q were present between GBMs and MLCs. GBM tumor volume was positively correlated with vsi (r = 0.502, p = 0.0017) and negatively correlated with Q (r = -0.531, p = 0.0007).

CONCLUSION

Conventional MRI parameters are helpful in differentiating between PCNSLs, GBMs, and MLCs. Additionally incorporating VSI parameters into the diagnostic protocol could help in further differentiating between PCNSLs and metastases and potentially between PCNSLs and GBMs. Future studies in larger patient cohorts are required to establish diagnostic cut-off values for VSI.

Mapping of microvascular architecture in the brain of an Alzheimer's disease mouse model using MRI

Increasing evidence suggests that alterations in cerebral microvasculature play a critical role in the pathogenesis of Alzheimer's disease (AD). The objective of this study was to characterize and evaluate the cerebral microvascular architecture of AD transgenic (Tg) mice and compare it with that of non-Tg mice using brain microvascular indices obtained by MRI. Seven non-Tg mice and 10 5xFAD Tg mice were scanned using a 7-T animal MRI system to measure the transverse relaxation rates of R2 and R2* before and after the injection of the monocrystalline iron oxide nanoparticle contrast agent. After calculating ΔR2* and ΔR2, the vessel size index (VSI), mean vessel diameter (mVD), mean vessel density, mean vessel-weighted image (MvWI) and blood volume fraction (BVf) were mapped. Voxel-based analyses and region of interest (ROI)-based analyses were performed to compare the indices of the non-Tg and Tg groups. Voxel comparisons showed that BVf, mVD, VSI and MvWI were greater in the Tg group than in the non-Tg group. Additionally, the ROI-based analysis showed that ΔR2*, BVf, mVD, MvWI and VSI increased in several brain regions of the Tg group compared with those in the non-Tg group. VSI and mVD increased in Tg mice; these findings indicated microvascular disruption in the brain that could be related to damage to the neurovascular unit in AD caused by cerebral amyloid angiopathy.

Vessel Size Imaging is Associated with IDH Mutation and Patient Survival in Diffuse Lower-Grade Glioma

Background

Patients with isocitrate dehydrogenase (IDH) mutant gliomas have better survival and appear to be more sensitive to chemotherapy than their IDH wild-type counterparts. We attempted to assess the correlations of vessel size imaging (VSI) values with IDH mutation status and patient survival in diffuse lower-grade glioma (LGG).

Methods

We enrolled 60 patients with diffuse LGGs, among which 43 had IDH-mutant tumors. All patients underwent VSI examination and VSI values for active tumors were calculated. Receiver operating characteristic (ROC) curves were established to evaluate the detection efficiency. Logistic regression was employed to determine the ability of variables to discriminate IDH mutational status. Kaplan–Meier survival analysis and Cox proportional hazards models were utilized to estimate the correlations of VSI values and other risk factors with patient survival.

Results

We observed that VSI values were lower in IDH-mutant LGGs than IDH wild-type LGGs. The VSImax and VSImean values had AUC values of 0.7305 and 0.7401, respectively, in distinguishing IDH-mutant LGGs from IDH wild-type LGGs. Logistic regression showed that VSImean values, age and tumor location were associated with IDH-mutant status, and the formula integrating the three factors had an AUC value of 0.7798 when distinguishing IDH-mutant LGGs from IDH wild-type LGGs. Moreover, LGG patients with high VSI values exhibited worse survival rates than those with low VSI values for both progression-free survival (PFS) and overall survival (OS). Multivariate Cox proportional hazards regression analysis suggested that IDH mutation status, VSImean values and multiple lesions or lobes were risk factors for PFS of LGG patients.

Conclusion

VSI value is associated with IDH genotype and maybe an independent predictor of the survival of patients with LGGs.

Exploring Two Methods of CBV Estimation in Two Groups of Grade III Gliomas with Different Appearance on Post-Contrast T1 Images

BACKGROUND

Many studies have used Cerebral Blood Volume (CBV) for gliomas grading and there has been in good agreement between CBV and tumor grade. Almost all of those studies have emphasized the importance of leakage correction due to the underestimation/overestimation of CBV caused by T1/T2* leakage effect in enhanced cases of tumors, especially high grade ones.

OBJECTIVES

The aim of this study is to investigate two methods of CBV estimation in two groups of gliomas with the same grade and different appearance on post contrast T1 images (Enhanced vs. Non-enhanced ones).

MATERIAL AND METHODS

In this retrospective study, eight glioma patients with histopatologically confirmed grade III were equally divided into two groups (with enhancement (group 1) and without enhancement (group 2)), and retrospectively studied. Imaging was performed on a 3 tesla MR Scanner and included gradient-echo DSC, 3D T1-weighted dataset and FLAIR images. The conventional method of CBV measurement (Integration over the whole curve of CTC- method 1) and the GVF fitting (method 2) was done using Matlab.

RESULTS

The observed mean rCBV in the tumor ROI was 2.85 and 2.12 for group 1 with method 1 and 2, respectively. Mean rCBV in the tumor ROI for group 2 was 1.24 and 1.11 with method 1 and 2, respectively.

CONCLUSION

In conclusion, this pilot study demonstrated that with combined use of pre-bolus and accounting for T2* effect, CBV could be considered as a criterion for the categorization of glioma tumors.

Evaluation of contrast agent dose and diffusion coefficient measurement on vessel size index estimation

OBJECTIVES

The goal of this study is to examine the effect of contrast agent (CA) dose and diffusion coefficient on the estimation of vessel size index (VSI).

MATERIALS AND METHODS

Three groups of four participants were enrolled in this study and two different experiments were performed. Different dose of CA, namely 0.1 mmol/kg and 0.05 mmol/kg were assessed in two groups of normal subjects. Diffusion coefficient effect was assessed in the third group with high-grade glioma. Imaging included gradient echo and spin-echo DSC and DTI on a 3-T MR Scanner.

RESULTS

VSI estimation using half of standard dose of CA showed higher values compared to the application of standard, with a ratio of 2 for the WM and 1.5 for the GM. VSI estimates for tumor tissues (22 µm) were considerably higher compared to contra-lateral Normal-Appearing WM (NAWM, 4 µm, P < 0.01) and Normal-Appearing GM (NAGM, 8 µm, P < 0.04).

DISCUSSION

Application of standard dose for CA injection and also taking into account the effect of diffusion coefficient can lead to a better correlation of VSI with previous theoretically predicted values and improvement of individual diagnostics in tumor evaluations.

Quantifying effects of radiotherapy-induced microvascular injury; review of established and emerging brain MRI techniques

Microvascular changes are increasingly recognised not only as primary drivers of radiotherapy treatment response in brain tumours, but also as an important contributor to short- and long-term (cognitive) side effects arising from irradiation of otherwise healthy brain tissue. As overall survival of patients with brain tumours is increasing, monitoring long-term sequels of radiotherapy-induced microvascular changes in the context of their potential predictive power for outcome, such as cognitive disability, has become increasingly relevant. Ideally, radiotherapy-induced significant microvascular changes in otherwise healthy brain tissue should be identified as early as possible to facilitate adaptive radiotherapy and to proactively start treatment to minimise the influence on these side-effects on the final outcome. Although MRI is already known to be able to detect significant long-term radiotherapy induced microvascular effects, more recently advanced MR imaging biomarkers reflecting microvascular integrity and function have been reported and might provide a more accurate and earlier detection of microvascular changes. However, the use and validation of both established and new techniques in the context of monitoring early and late radiotherapy-induced microvascular changes in both target-tissue and healthy tissue currently are minimal at best. This review aims to summarise the performance and limitations of existing methods and future opportunities for detection and quantification of radiotherapy-induced microvascular changes, as well as the relation of these findings with key clinical parameters.

An evidence-based approach to assess the accuracy of intravoxel incoherent motion imaging for the grading of brain tumors

BACKGROUND

Differentiation of high-grade gliomas (HGGs) and low-grade gliomas (LGGs) is an important clinical problem because treatment strategies vary greatly. This study was performed to investigate the potential diagnostic value of incoherent intravoxel motion imaging (IVIM) to distinguish HGG from LGG by meta-analysis.

METHODS

A computerized search of the literature was performed using the free-access PubMed database, Web of Science, and Chinese biomedical database, and relevant articles until September 18, 2018 that used IVIM to distinguish HGG from LGG were included. All analyses were performed using Review Manager 5.3 and Stata. Mean difference (MD) at 95% confidence interval (CI) of the apparent diffusion coefficient (ADC), diffusion coefficient value (D), perfusion fraction value (f), and perfusion coefficient value (D*) were summarized.

RESULTS

Nine studies were used for general data pooling. In the tumor parenchyma (TP) regions, subgroup analysis revealed D* in HGG is higher than in LGG (MD = 1.19, P = .002), and D in HGG is lower than in LGG (MD = -1.06, P = .001). However, no significant difference in f (MD = 0.89, P = .056) was detected between HGG and LGG. In the white matter regions, HGG had higher D* (MD = 0.76, P = .04) compared with LGG, while no marked differences between the D value (P = .07) and f (P = .09) values.

CONCLUSION

The present meta-analysis shows that the ADC, D, and D* values derived from IVIM may be useful in differentiating HGG from LGG. Considering the small sample of this study, we need to be cautious when interpreting the results of this study. Other prospective and large-sample randomized controlled trials were needed to establish the value of IVIM in differentiating HGG from LGG.

Microvascular characteristics of lower-grade diffuse gliomas: investigating vessel size imaging for differentiating grades and subtypes

Objectives

Vessel size imaging (VSI) could reveal average microvessel diameter. The aim was to investigate microvascular characteristics and the efficacy of VSI in lower-grade glioma (LGG) grading and subtype differentiation based on 2016 classification of central nervous system tumours.

Methods

Fifty-seven LGG (grade II/III, 36/21) patients who received VSI examination before surgery were retrospectively analysed. The average (R_mean) and maximum (R_max) vessel size indexes were obtained. The long (VD_max) and short (VD_min) vascular diameter, microvascular area (MVA) and density (MVD) were obtained using paraffin specimens. The patients were divided into grades II and III, and histological and molecular subtypes. The differences among microvascular parameters of different subtypes and grades were compared. Two-sample t-test, analysis of variance test, Mann-Whitney test, the Kruskal-Wallis test and Pearson correlation analysis were used for statistics.

Results

R_mean, R_max, VD_min, VD_max, and MVA were higher in grade-III than in grade-II LGGs (p < 0.05) in each type except the isocitrate dehydrogenase (IDH) mutant with 1p/19q-intact type. For grade II, the IDH mutant with 1p/19q co-deleted and IDH wildtype possessed more dominant angiogenesis than IDH mutant with 1p/19q-intact type, revealed by lower R_mean, R_max and VD_min while higher MVD for the former (p < 0.05), the same as oligodendroglioma versus astrocytoma. R_mean and R_max correlated with VD_min (r = 0.804, 0.815, p < 0.05), VD_max (r = 0.766, 0.774, p < 0.05) and MVA (r = 0.755, 0.759, p < 0.05), respectively, while they had no correlation with MVD (r = -0.085, -0.080, p > 0.05).

Conclusions

VSI holds great potential for non-invasively revealing microvascular characteristics of LGGs pre-surgery and differentiating their grades and molecular subtypes.

Key Points

• VSI can assist in differentiating grade-II and -III gliomas.

• The IDH gene and 1p/19q chromosome may influence the angiogenesis in grade-II gliomas.

• VSI is valuable for differentiating the molecular subtypes of grade-II gliomas.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5738-y) contains supplementary material, which is available to authorized users.

Dynamic MR imaging for functional vascularization depends on tissue factor signaling in glioblastoma

Glomeruloid vascular proliferation (GVP) is a diagnostic hallmark and links to aggressive behavior, therapy resistance and poor prognosis in glioblastoma (GBM). It lacks clinical approaches to predict and monitor its formation and dynamic change. Yet the mechanism of GVPs also remains largely unknown. Using an in situ GBM xenograft mouse model, combined clinical MRI images of pre-surgery tumor and pathological investigation, we demonstrated that the inhibition of tissue factor (TF) decreased GVPs in Mouse GBM xenograft model. TF shRNA reduced microvascular area and diameter, other than bevacizumab. TF dominantly functions via PAR2/HB-EGF-dependent activation under hypoxia in endothelial cells (ECs), resulting in a reduction of GVPs and cancer cells invasion. TF expression strongly correlated to GVPs and microvascular area (MVA) in GBM specimens from 56 patients, which could be quantitatively evaluated in an advanced MRI images system in 33 GBM patients. This study presented an approach to assess GVPs that could be served as a MRI imaging biomarker in GBM and uncovered a molecular mechanism of GVPs.

Brain Tumor Imaging

Modern imaging techniques, particularly functional imaging techniques that interrogate some specific aspect of underlying tumor biology, have enormous potential in neuro-oncology for disease detection, grading, and tumor delineation to guide biopsy and resection; monitoring treatment response; and targeting radiotherapy. This brief review considers the role of magnetic resonance imaging and spectroscopy, and positron emission tomography in these areas and discusses the factors that limit translation of new techniques to the clinic, in particular, the cost and difficulties associated with validation in multicenter clinical trials.

MR Imaging-derived Oxygen Metabolism and Neovascularization Characterization for Grading and IDH Gene Mutation Detection of Gliomas

Purpose To explore the diagnostic performance of physiological magnetic resonance (MR) imaging of oxygen metabolism and neovascularization activity for grading and characterization of isocitrate dehydrogenase (IDH) gene mutation status of gliomas. Materials and Methods This retrospective study had institutional review board approval; written informed consent was obtained from all patients. Eighty-three patients with histopathologically proven glioma (World Health Organization [WHO] grade II-IV) were examined with quantitative blood oxygen level-dependent imaging and vascular architecture mapping. Biomarker maps of neovascularization activity (microvessel radius, microvessel density, and microvessel type indicator [MTI]) and oxygen metabolism (oxygen extraction fraction [OEF] and cerebral metabolic rate of oxygen [CMRO₂]) were calculated. Receiver operating characteristic analysis was used to determine diagnostic performance for grading and detection of IDH gene mutation status. Results Low-grade (WHO grade II) glioma showed areas with increased OEF (+18%, P < .001, n = 20), whereas anaplastic glioma (WHO grade III) and glioblastoma (WHO grade IV) showed decreased OEF when compared with normal brain tissue (-54% [P < .001, n = 21] and -49% [P < .001, n = 41], respectively). This allowed clear differentiation between low- and high-grade glioma (area under the receiver operating characteristic curve [AUC], 1) for the patient cohort. MTI had the highest diagnostic performance (AUC, 0.782) for differentiation between gliomas of grades III and IV among all biomarkers. CMRO₂ was decreased (P = .037) in low-grade glioma with a mutated IDH gene, and MTI was significantly increased in glioma grade III with IDH mutation (P = .013) when compared with the IDH wild-type counterparts. CMRO₂ showed the highest diagnostic performance for IDH gene mutation detection in low-grade glioma (AUC, 0.818) and MTI in high-grade glioma (AUC, 0.854) and for all WHO grades (AUC, 0.899) among all biomarkers. Conclusion MR imaging-derived oxygen metabolism and neovascularization characterization may be useful for grading and IDH mutation detection of gliomas and requires only 7 minutes of extra imaging time. ^© RSNA, 2016 Online supplemental material is available for this article.