Correlation between dynamic contrast-enhanced perfusion MRI relative cerebral blood volume and vascular endothelial growth factor expression in meningiomas

Is arterial spin labelling necessarily low perfusion for cavernous sinus venous malformation? A case of hyperperfusion cavernous sinus venous malformation

Generally, due to the complexity of the skull base structures, it is difficult to differentiate cavernous vascular malformation and meningioma in the cavernous sinus area using conventional imaging studies. Cavernous sinus venous malformation are characterized by increased capillary masses without a direct arterial supply, typically leading to low perfusion. On the other hand, meningiomas receive arterial blood supply to the tumour and often exhibit high perfusion. So, arterial spin labelling (ASL) can be helpful in distinguishing between the 2 tumour types. However, in our specific case of a cavernous sinus venous malformation, the ASL imaging showed hyperperfusion. Further analysis revealed that this hyperperfusion on ASL can occur when cavernous sinus venous malformation is associated with arteriovenous fistula malformation.

Imaging biomarkers associated with extra-axial intracranial tumors: a systematic review

Extra-axial brain tumors are extra-cerebral tumors and are usually benign. The choice of treatment for extra-axial tumors is often dependent on the growth of the tumor, and imaging plays a significant role in monitoring growth and clinical decision-making. This motivates the investigation of imaging biomarkers for these tumors that may be incorporated into clinical workflows to inform treatment decisions. The databases from Pubmed, Web of Science, Embase, and Medline were searched from 1 January 2000 to 7 March 2022, to systematically identify relevant publications in this area. All studies that used an imaging tool and found an association with a growth-related factor, including molecular markers, grade, survival, growth/progression, recurrence, and treatment outcomes, were included in this review. We included 42 studies, comprising 22 studies (50%) of patients with meningioma; 17 studies (38.6%) of patients with pituitary tumors; three studies (6.8%) of patients with vestibular schwannomas; and two studies (4.5%) of patients with solitary fibrous tumors. The included studies were explicitly and narratively analyzed according to tumor type and imaging tool. The risk of bias and concerns regarding applicability were assessed using QUADAS-2. Most studies (41/44) used statistics-based analysis methods, and a small number of studies (3/44) used machine learning. Our review highlights an opportunity for future work to focus on machine learning-based deep feature identification as biomarkers, combining various feature classes such as size, shape, and intensity. Systematic Review Registration: PROSPERO, CRD42022306922.

Imaging Characteristics of Meningiomas

Contemporary neuroimaging of meningiomas has largely relied on computed tomography, and more recently magnetic resonance imaging. While these modalities are frequently used in nearly all clinical settings where meningiomas are treated for the routine diagnosis and follow-up of these tumors, advances in neuroimaging have provided novel opportunities for prognostication and treatment planning (including both surgical planning and radiotherapy planning). These include perfusion MRIs, and positron emission tomography (PET) imaging modalities. Here we will summarize the contemporary uses for neuroimaging in meningiomas, and future applications of novel, cutting edge imaging techniques that may be routinely implemented in the future to enable more precise treatment of these challenging tumors.

Use of advanced neuroimaging and artificial intelligence in meningiomas

Anatomical cross‐sectional imaging methods such as contrast‐enhanced MRI and CT are the standard for the delineation, treatment planning, and follow‐up of patients with meningioma. Besides, advanced neuroimaging is increasingly used to non‐invasively provide detailed insights into the molecular and metabolic features of meningiomas. These techniques are usually based on MRI, e.g., perfusion‐weighted imaging, diffusion‐weighted imaging, MR spectroscopy, and positron emission tomography. Furthermore, artificial intelligence methods such as radiomics offer the potential to extract quantitative imaging features from routinely acquired anatomical MRI and CT scans and advanced imaging techniques. This allows the linking of imaging phenotypes to meningioma characteristics, e.g., the molecular‐genetic profile. Here, we review several diagnostic applications and future directions of these advanced neuroimaging techniques, including radiomics in preclinical models and patients with meningioma.

Peritumoral Brain Edema in Metastases May Be Related to Glymphatic Dysfunction

Objectives

The proliferation of microvessels with increased permeability is thought to be the cause of peritumoral brain edema (PTBE) in metastases. The contribution of the glymphatic system to the formation of PTBE in brain metastases remains unexplored. We aimed to investigate if the PTBE volume of brain metastases is related to glymphatic dysfunction.

Materials and Methods

A total of 56 patients with brain metastases who had preoperative dynamic susceptibility contrast-enhanced perfusion-weighted imaging for calculation of tumor cerebral blood volume (CBV) and diffusion tensor imaging for calculations of tumor apparent diffusion coefficient (ADC), tumor fractional anisotropy (FA), and analysis along perivascular space (ALPS) index were analyzed. The volumes of PTBE, whole tumor, enhancing tumor, and necrotic and hemorrhagic portions were manually measured. Additional information collected for each patient included age, sex, primary cancer, metastasis location and number, and the presence of concurrent infratentorial tumors. Linear regression analyses were performed to identify factors associated with PTBE volume.

Results

Among 56 patients, 45 had solitary metastasis, 24 had right cerebral metastasis, 21 had left cerebral metastasis, 11 had bilateral cerebral metastases, and 11 had concurrent infratentorial metastases. On univariable linear regression analysis, PTBE volume correlated with whole tumor volume (β = -0.348, P = 0.009), hemorrhagic portion volume (β = -0.327, P = 0.014), tumor ADC (β = 0.530, P <.001), and ALPS index (β = -0.750, P <.001). The associations of PTBE volume with age, sex, tumor location, number of tumors, concurrent infratentorial tumor, enhancing tumor volume, necrotic portion volume, tumor FA, and tumor CBV were not significant. On multivariable linear regression analysis, tumor ADC (β = 0.303; P = 0.004) and ALPS index (β = -0.624; P < 0.001) were the two independent factors associated with PTBE volume.

Conclusion

Metastases with higher tumor ADC and lower ALPS index were associated with larger peritumoral brain edema volumes. The higher tumor ADC may be related to increased periarterial water influx into the tumor interstitium, while the lower ALPS index may indicate insufficient fluid clearance. The changes in both tumor ADC and ALPS index may imply glymphatic dysfunction, which is, at least, partially responsible for peritumoral brain edema formation.

Perfusion and Permeability MRI Predicts Future Cavernous Angioma Hemorrhage and Growth

BACKGROUND

Cerebral cavernous angioma (CA) is a capillary vasculopathy affecting more than a million Americans with a small fraction of cases demonstrating lesional bleed or growth with major clinical sequelae. Perfusion and permeability are fundamental features of CA pathophysiology, but their role as prognostic biomarkers is unclear.

PURPOSE

To investigate whether perfusion or permeability lesional descriptors derived from dynamic contrast-enhanced quantitative perfusion (DCEQP) magnetic resonance imaging (MRI) can predict subsequent lesional bleed/growth in the year following imaging.

STUDY TYPE

Single-site case-controlled study.

SUBJECTS

Two hundred and five consecutively enrolled patients (63.4% female).

FIELD STRENGTH/SEQUENCE

Three-Tesla/T₁ -mapping with contrast-enhanced dynamic two-dimensional (2D) spoiled gradient recalled acquisition (SPGR) sequences.

ASSESSMENT

Prognostic associations with bleed/growth (present or absent) in the following year were assessed in 745 CA lesions evaluated by DCEQP in the 205 patients in relation to lesional descriptors calculated from permeability and perfusion maps. A subgroup of 30 cases also underwent peripheral blood collection at the time of DCEQP scans and assays of plasma levels of soluble CD14, IL-1β, VEGF, and soluble ROBO4 proteins, whose weighted combination had been previously reported in association with future CA bleeding.

STATISTICAL TESTS

Mann-Whitney U-test for univariate analyses. Logistic regression models minimizing the Bayesian information criterion (BIC), testing sensitivity and specificity (receiver operating characteristic curves) of weighted combinations of parameters.

RESULTS

The best prognostic biomarker for lesional bleed or growth included brainstem lesion location, mean lesional permeability, and low-value perfusion cluster mean (BIC = 201.5, sensitivity = 77%, specificity = 72%, P < 0.05). Adding a previously published prognostic plasma protein biomarker improved the performance of the imaging model (sensitivity = 100%, specificity = 88%, P < 0.05).

DATA CONCLUSION

A combination of MRI-based descriptors reflecting higher lesional permeability and lower perfusion cluster may potentially predict future bleed/growth in CAs. The sensitivity and specificity of the prognostic imaging biomarker can be enhanced when combined with brainstem lesion location and a plasma protein biomarker of CA hemorrhage.

LEVEL OF EVIDENCE

2 TECHNICAL EFFICACY: Stage 5.

Peritumoral brain edema volume in meningioma correlates with tumor fractional anisotropy but not apparent diffusion coefficient or cerebral blood volume

PURPOSE

Pathogenesis of peritumoral brain edema (PTBE) in meningiomas remains unclear. Associations between PTBE volume and diffusion or perfusion properties of meningioma have not been studied. We aimed to investigate if diffusion and perfusion properties of meningioma correlate with its PTBE volume.

METHODS

Seventy consecutive patients (mean age, 58.9 ± 13.7 years; 37 women) with meningiomas who had preoperative DTI and DSC-PWI were retrospectively analyzed. PTBE volume, tumor volume, and mean T2 signal, ADC, FA, and CBV of the tumor were measured. Between meningiomas with and without PTBE, patient age and sex, as well as T2 signal intensity, volume, ADC, FA, and CBV of tumors, were compared. In meningiomas with PTBE, correlations of PTBE volume with patient age and sex, as well as T2 signal intensity, volume, ADC, FA, and CBV of tumors, were analyzed. Multivariable linear regression analysis was performed to identify factors associated with PTBE volume.

RESULTS

On univariable analysis, meningiomas without PTBE were more frequently found in women (P = 0.033) and demonstrated lower ADC (P = 0.020), higher FA (P < 0.001), and lower CBV (P < 0.001). PTBE volume of meningiomas correlated with tumor ADC (r = 0.444; P = 0.001), tumor FA (r = - 0.655; P < 0.001), and tumor CBV (r = 0.402; P = 0.003). On multivariable analysis, tumor FA was the only factor associated with PTBE volume (P < 0.001).

CONCLUSION

PTBE volume in meningioma correlates with tumor FA. DTI may help to understand the mechanism of PTBE in meningiomas.

Imaging and diagnostic advances for intracranial meningiomas

The archetypal imaging characteristics of meningiomas are among the most stereotypic of all central nervous system (CNS) tumors. In the era of plain film and ventriculography, imaging was only performed if a mass was suspected, and their results were more suggestive than definitive. Following more than a century of technological development, we can now rely on imaging to non-invasively diagnose meningioma with great confidence and precisely delineate the locations of these tumors relative to their surrounding structures to inform treatment planning. Asymptomatic meningiomas may be identified and their growth monitored over time; moreover, imaging routinely serves as an essential tool to survey tumor burden at various stages during the course of treatment, thereby providing guidance on their effectiveness or the need for further intervention. Modern radiological techniques are expanding the power of imaging from tumor detection and monitoring to include extraction of biologic information from advanced analysis of radiological parameters. These contemporary approaches have led to promising attempts to predict tumor grade and, in turn, contribute prognostic data. In this supplement article, we review important current and future aspects of imaging in the diagnosis and management of meningioma, including conventional and advanced imaging techniques using CT, MRI, and nuclear medicine.

Performance of diffusion and perfusion MRI in evaluating primary central nervous system lymphomas of different locations

Background

Diffusion and perfusion MRI can invasively define physical properties and angiogenic features of tumors, and guide the individual treatment. The purpose of this study was to investigate whether the diffusion and perfusion MRI parameters of primary central nervous system lymphomas (PCNSLs) are related to the tumor locations.

Methods

We retrospectively reviewed the diffusion, perfusion, and conventional MRI of 68 patients with PCNSLs at different locations (group 1: cortical gray matter, group 2: white matter, group 3: deep gray matter). Relative maximum cerebral blood volume (rCBV_max) from perfusion MRI, minimum apparent diffusion coefficients (ADC_min) from DWI of each group were calculated and compared by one-way ANOVA test. In addition, we compared the mean apparent diffusion coefficients (ADC_mean) in three different regions of control group.

Results

The rCBV_max of PCNSLs yielded the lowest value in the white matter group, and the highest value in the cortical gray matter group (P < 0.001). However, the ADC_min of each subgroup was not statistically different. The ADC_mean of each subgroup in control group was not statistically different.

Conclusion

Our study confirms that rCBV_max of PCNSLs are related to the tumor location, and provide simple but effective information for guiding the clinical practice of PCNSLs.

Can we predict intraoperative blood loss in meningioma patients? Application of dynamic susceptibility contrast-enhanced magnetic resonance imaging

PURPOSE

To evaluate the potential of quantitative dynamic susceptibility contrast (DSC) perfusion MR imaging parameters as imaging biomarkers for predicting intraoperative blood loss in meningioma.

METHODS

Fifty-one non-embolized meningioma patients who had undergone preoperative DSC perfusion MR imaging were retrospectively included. The corrected relative cerebral blood volume (rCBV) and leakage coefficient (K₂) of the entire enhanced tumor were obtained using leakage correction. Tumor volume, location, grade, and other clinical variables, were also analyzed. To investigate the vascularity and vascular permeability of meningiomas, and their correlation with predicting estimated blood loss (EBL) using preoperative DSC perfusion MR imaging, the authors proposed an index reflecting the inherent tendency of meningiomas to bleed after controlling volume (i.e., EBL/cm³). Simple regression was performed to identify predictors of EBL/cm³; subsequently, the relevant variables included in the stepwise multiple linear regression.

RESULTS

On univariate analysis, EBL/cm³ was correlated with rCBV (r=0.677; P<0.001), K₂ (r=0.294; P=0.036), and tumor volume (r=-0.312, P=0.026). EBL/cm³ was not correlated with age (P=0.873), sex (P=0.404), tumor location (P=0.327), or histological grade (P=0.230). On multiple linear regression, rCBV (β=0.663 [0.463-0.864], B=1.293 [0.903-1.684; P<0.001) and K₂ (β=0.260 [0.060-0.460], B=2.277 [0.523-4.031], P=0.012), were the only independent predictors of EBL/cm³.

CONCLUSION

The rCBV and K₂ derived from DSC perfusion MR imaging in meningiomas may serve as feasible tools for clinicians to predict intraoperative blood loss and facilitate surgical planning.

Histogram analysis of absolute cerebral blood volume map can distinguish glioblastoma from solitary brain metastasis

Glioblastoma multiforme (GBM) is difficult to be separated from solitary brain metastasis (sBM) in clinical practice. This study aimed to distinguish two entities by the histogram analysis of absolute cerebral blood volume (CBV) map.From March 2016 to June 2018, 24 patients with GBM and 18 patients with sBM were included in this retrospective study. The enhancing area was first segmented on the post-contrast T1WI, then the segmentation was copied to the absolute CBV map and histogram analysis was finally performed. Unpaired t test was used to select the features that could separate two entities and receiving operating curve was used to test the diagnostic performance. Finally, a machine learning method was used to test the diagnostic performance combing all the selected features.Six of 19 features were feasible to distinguish GBM from sBM (all P < .001), among which energy had the highest diagnostic performance (area under curve, 0.84; accuracy, 88%), while a machine learning method could improve the diagnostic performance (area under curve, 0.94; accuracy, 95%).Histogram analysis of the absolute CBV in the enhancing area could help us distinguish GBM from sBM, in addition, a machine learning method with combined features is preferable. It is quite helpful in the condition that the biological nature of peritumoral edema could not separate these two entities.

Dynamic contrast-enhanced magnetic resonance imaging perfusion characteristics in meningiomas treated with resection and adjuvant radiosurgery

OBJECTIVE

There is a need for advanced imaging biomarkers to improve radiation treatment planning and response assessment. T1-weighted dynamic contrast-enhanced perfusion MRI (DCE MRI) allows quantitative assessment of tissue perfusion and blood-brain barrier dysfunction and has entered clinical practice in the management of primary and secondary brain neoplasms. The authors sought to retrospectively investigate DCE MRI parameters in meningiomas treated with resection and adjuvant radiation therapy using volumetric segmentation.

METHODS

A retrospective review of more than 300 patients with meningiomas resected between January 2015 and December 2018 identified 14 eligible patients with 18 meningiomas who underwent resection and adjuvant radiotherapy. Patients were excluded if they did not undergo adjuvant radiation therapy or DCE MRI. Demographic and clinical characteristics were obtained and compared to DCE perfusion metrics, including mean plasma volume (vp), extracellular volume (ve), volume transfer constant (Ktrans), rate constant (kep), and wash-in rate of contrast into the tissue, which were derived from volumetric analysis of the enhancing volumes of interest.

RESULTS

The mean patient age was 64 years (range 49–86 years), and 50% of patients (7/14) were female. The average tumor volume was 8.07 cm3 (range 0.21–27.89 cm3). The median Ki-67 in the cohort was 15%. When stratified by median Ki-67, patients with Ki-67 greater than 15% had lower median vp (0.02 vs 0.10, p = 0.002), and lower median wash-in rate (1.27 vs 4.08 sec−1, p = 0.04) than patients with Ki-67 of 15% or below. Logistic regression analysis demonstrated a statistically significant, moderate positive correlation between ve and time to progression (r = 0.49, p < 0.05). Furthermore, there was a moderate positive correlation between Ktrans and time to progression, which approached, but did not reach, statistical significance (r = 0.48, p = 0.05).

CONCLUSIONS

This study demonstrates a potential role for DCE MRI in the preoperative characterization and stratification of meningiomas, laying the foundation for future prospective studies incorporating DCE as a biomarker in meningioma diagnosis and treatment planning.

Overview of established and emerging immunohistochemical biomarkers and their role in correlative studies in MRI

Clinical practice in radiology and pathology requires professional expertise and many years of training to visually evaluate and interpret abnormal phenotypic features in medical images and tissue sections to generate diagnoses that guide patient management and treatment. Recent advances in digital image analysis methods and machine learning have led to significant interest in extracting additional information from medical and digital whole-slide images in radiology and pathology, respectively. This has led to significant interest and research in radiomics and pathomics to correlate phenotypic features of disease with image analytics in order to identify image-based biomarkers. The expanding role of big data in radiology and pathology parallels the development and role of immunohistochemistry (IHC) in the daily practice of pathology. IHC methods were initially developed to provide additional information to help classify tumors and then transformed into an indispensable tool to guide treatment in many types of cancer. IHC markers are used in daily practice to identify specific types of cells and highlight their distributions in tissues in order to distinguish benign from neoplastic cells, determine tumor origin, subclassify neoplasms, and support and confirm diagnoses. In this regard, radiomics, pathomics, and IHC methods are very similar since they enable the extraction of image-based features to characterize various properties of diseases. Due to the dramatic advancements in recent radiomics research, we provide a brief overview of the role of established and emerging IHC biomarkers in various tumor types that have been correlated with radiologic biomarkers to improve diagnostic accuracy, predict prognosis, guide patient management, and select treatment strategies. Level of Evidence: 5 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2020;51:341-354.

3D-ASL perfusion correlates with VEGF expression and overall survival in glioma patients: Comparison of quantitative perfusion and pathology on accurate spatial location-matched basis

BACKGROUND

There is a need for an imaging-based tool for measuring vascular endothelial growth factor (VEGF) expression and overall survival (OS) in patients with glioma.

PURPOSE

To assess the correlation between cerebral blood flow (CBF), measured by 3D pseudo-continuous arterial spin-labeling (3D-ASL), and VEGF expression in gliomas on the basis of coregistered localized biopsy, and investigate whether CBF correlated with survival month (SM) in glioma patients.

STUDY TYPE

Prospective cohort.

SUBJECTS

Thirty-seven patients with gliomas from whom 63 biopsy specimens were obtained.

SEQUENCE

3D-ASL acquired with a 3.0T MR unit.

ASSESSMENT

Biopsy specimens were grouped as high-grade (HGG) or low-grade glioma (LGG). CBF measurements were spatially matched with VEGF expression by coregistered localized biopsies, and the CBF value was correlated with quantitative VEGF expression for each specimen. Patients' survival information was derived and connected with CBF.

STATISTICAL TESTS

Patients' OS was analyzed by Kaplan-Meier and Cox-regression methods. VEGF expression and CBF were compared in both LGG and HGG. The Spearman rank correlation was calculated for CBF and VEGF expression, SM. Significance level, P < 0.05.

RESULTS

CBF-derived 3D-ASL positively correlated significantly with VEGF expression in both LGG (31 specimens) and HGG (32 specimens), r = 0.604 (P < 0.001) and r = 0.665 (P < 0.001), respectively. LGG and HGG together gave a correlation coefficient r = 0.728 (P < 0.001). Median survival for LGG and HGG patients was 34.19 and 17.17 months, respectively (P = 0.037); CBF value negatively correlated significantly with SM with r = -0.714 (P < 0.001) regardless of glioma grade. CBF was an independent risk factor for OS with HR = 1.027 (P = 0.044), 1.028 (P = 0.010) for univariate/multivariate regression analysis.

DATA CONCLUSION

CBF determined by 3D-ASL correlates with VEGF expression in glioma and is an independent risk factor for OS in these patients.

LEVEL OF EVIDENCE

1 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2019;50:209-220.

Application of arterial spin labeling perfusion MRI to differentiate benign from malignant intracranial meningiomas

PURPOSE

Differentiating WHO grade I-III of meningioma by non-invasive imaging is challenging. This study investigated the potential of MR arterial spin labeling (ASL) to establish tumor grade in meningioma patients.

MATERIAL AND METHODS

Pseudo-continuous ASL with 3D background suppressed gradient and spin echo (GRASE) was acquired on 54 patients with newly diagnosed or recurrent intracranial meningioma. Perfusion patterns characterized in CBF color maps were independently evaluated by three neuroradiologists blinded to patient history, and correlated with tumor grade from histo-pathological review.

RESULTS

Three perfusion patterns could be discerned by visual evaluation of CBF maps. Pattern 1 consisted of homogeneous hyper-perfusion of the entire tumor; pattern 2 demonstrated heterogeneous hyper-perfusion; pattern 3 showed no substantial hyper-perfusion. Evaluation of the perfusion patterns was highly concordant among the three readers (Kendall W=0.9458, P<0.0001). Pattern 1 was associated with WHO Grade I meningioma of (P<0.0001). Patterns 2 and 3 were predictive of WHO Grade II and III meningioma (P<0.0001), with an odds ratio (OR, versus pattern 1) of 49.6 (P<0.01) in a univariate analysis, and an OR of 186.4 (P<0.01) in a multivariate analysis.

CONCLUSION

Qualitative evaluation of ASL CBF maps can help differentiate benign (WHO Grade I) from higher grade (WHO Grade II and III) intracranial meningiomas, potentially impacting therapeutic strategy.

The preliminary radiogenomics association between MR perfusion imaging parameters and genomic biomarkers, and their predictive performance of overall survival in patients with glioblastoma

The radiogenomics association of neovascularization is important for overall survival (OS) in glioblastoma patients and remains unclear. The purpose of this study is to assess the association between MR perfusion imaging derived parameters and genomic biomarkers of glioblastoma, and to evaluate their prognostic value. This retrospective study enrolled 41 patients with newly diagnosed glioblastoma. The mean and maximal relative cerebral blood volume (rCBV) ratio (rCBV_mean and rCBV_max), derived from MR perfusion weighted imaging, of the enhancing tumor, as well as maximal rCBV ratio of peri-enhancing tumor area (rCBV_peri-tumor) were measured. The ki-67 labeling index, mammalian target of rapamycin (mTOR) activation, epidermal growth factor receptor (EGFR) amplification, isocitrate dehydrogenase (IDH) mutation and TP53 were assessed. There was a significant correlation between rCBV_max and mTOR based on Pearson's correlations with Benjamini-Hochberg adjustment for controlling false discovery rate, p = 0.047. The rCBV_peri-tumor showed significant correlation with mTOR (p = 0.0183) after adjustment of gender and EGFR status. The mean rCBV_peri-tumor value of the patients with OS shorter than 14 months was significantly higher than patients with OS longer than 14 months, p = 0.002. The rCBV_peri-tumor and age were the two strongest predictors of OS (hazard ratio = 1.29 and 1.063 respectively) by Cox regression analysis. This study showed that hemodynamic abnormalities of glioblastoma were associated with genomics activation status of mTOR-EGFR pathway, however, the radiogenomics associations are different in enhancing and peri-enhancing area of glioblastoma. The rCBV_peri-tumor has better prognostic value than genomic biomarkers alone.

Relative cerebral blood volume is a potential biomarker in late delayed radiation-induced brain injury

PURPOSE

To assess whether relative cerebral blood volume (rCBV) can provide information to reliably evaluate the stages of late delayed radiation-induced brain injury.

MATERIALS AND METHODS

Forty patients diagnosed with late delayed radiation-induced brain injury were enrolled. The patients were examined using a 1.5T magnetic resonance imaging (MRI) system equipped with an 8-channel head coil. An echo planar imaging (EPI) sequence was used in perfusion-weighted imaging (PWI). The location of 1H-MR spectroscopy scanning was acquired by a point-resolved spectroscopy sequence. Lesions of the temporal lobe were divided into one of two groups according to rCBV value: rCBV<1 (low rCBV [group 1; n = 45]); and rCBV>1 (elevated rCBV [group 2; n = 14]). PWI and MRS parameters, as well as morphological lesion types, in these two groups were compared. Morphological severity was assessed independently and agreed on by two imaging specialists (J.L. and H.X.S., with 16 and 24 years' experience, respectively). If necessary, a third imaging professor (Z.M.H.) with 30 years' experience resolved disagreement(s). Standards for evaluating morphological lesion types were based on previously published criteria. After testing the skewness of data, the Mann-Whitney U-test or Student's t-test was used, as appropriate.

RESULTS

rCBV, relative cerebral blood flow (rCBF), and relative mean transit time (rMTT) in group 2 (n = 14) were significantly higher than in group 1 (n = 45) (rCBV: 1.21 ± 0.38 vs. 0.72 ± 0.32, respectively; P < 0.001; rCBF: 1.13 ± 0.02 vs. 0.74 ± 0.04, respectively; P < 0.001; rMTT: 1.10 ± 0.26 vs. 0.96 ± 0.20, P < 0.001). The levels of choline-containing compounds (CHO) / creatine (Cr) and CHO/N-acetylaspartate (NAA) in group 1 were significantly greater than in group 2 (CHO/Cr: 1.89 ± 1.83 vs. 1.22 ± 1.31, respectively; P = 0.016; CHO/NAA: 1.85 ± 3.50 vs. 1.17 ± 0.75, respectively; P = 0.022). More severe morphological lesions were present in lesions with low rCBV compared with elevated rCBV (overall severity: 7.00 ± 4.25 vs. 5.00 ± 5.13, respectively; P = 0.029).

CONCLUSION

Elevated rCBV accompanied by a more conservative metabolic pattern and milder lesion(s) may represent a less advanced stage in the development of late delayed radiation-induced brain injury.

LEVEL OF EVIDENCE

4 Technical Efficacy: Stage 3 J. Magn. Reson. Imaging 2018;47:1112-1118.

[Value of diffusion-weighted imaging, 1H-magnetic resonance spectroscopy and 3D whole-brain arterial spin labeling in the diagnosis of medulloblastoma]

OBJECTIVE

To explore the value of diffusion-weighted imaging (DWI), ¹H-magnetic resonance spectroscopy (1H-MRS) and 3D whole-brain arterial spin labeling (3D ASL) in the diagnosis of medulloblastoma in the posterior cranial fossa.

METHODS

The magnetic resonance imaging (MRI) findings of 16 patients with pathologically confirmed medulloblastoma in the posterior cranial fossa were analyzed retrospectively. All the patients were examined with plane and enhanced brain MRI scans; 5 patients also underwent examinations with DWI, 12 with MRS, and 5 with 3D ASL.

RESULTS

Medulloblastomas were found in the vermis and the fourth ventricle in 9 cases, in the cerebellar hemisphere in 5 cases, and in the cerebellopontine angle in 1 case; in 1 case multiple lesions were detected. The tumors showed iso-intense or slightly hypo-intense signals on T₁WI, and iso-intense or hyper-intense signals on T₂WI and FLAIR. The lesions showed high signals in DWI and low signals in ADC. Intra-lesion cysts were common (n=12), and calcification and bleeding were rarely seen. Mild patchy enhancement (n=6) or significant enhancement (n=10) was seen after contrast agent administration. Obstructive hydrocephalus was found in 12 cases and the subarachnoid space was involved in 3 cases. In all the 12 patients receiving MRS examination, high Cho and low NAA were found with significantly increased Cho/Cr (≥3.5) and Cho/NAA (≥4.0) ratios; Tau peak was seen in 8 cases, and Lip peak was found in 4 cases. All the 5 patients receiving 3D ASL examination showed decreased cerebral blood flow (CBF).

CONCLUSION

The characteristic features of medulloblastomas in DWI, MRS and 3D ASL offer assistance to the diagnosis of atypical medulloblastoma.

IDH mutation status is associated with a distinct hypoxia/angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging in human glioma

The recent identification of IDH mutations in gliomas and several other cancers suggests that this pathway is involved in oncogenesis; however effector functions are complex and yet incompletely understood. To study the regulatory effects of IDH on hypoxia-inducible-factor 1-alpha (HIF1A), a driving force in hypoxia-initiated angiogenesis, we analyzed mRNA expression profiles of 288 glioma patients and show decreased expression of HIF1A targets on a single-gene and pathway level, strong inhibition of upstream regulators such as HIF1A and downstream biological functions such as angio- and vasculogenesis in IDH mutant tumors. Genotype/imaging phenotype correlation analysis with relative cerebral blood volume (rCBV) MRI - a robust and non-invasive estimate of tumor angiogenesis - in 73 treatment-naive patients with low-grade and anaplastic gliomas showed that a one-unit increase in rCBV corresponded to a two-third decrease in the odds for an IDH mutation and correctly predicted IDH mutation status in 88% of patients. Together, these findings (1) show that IDH mutation status is associated with a distinct angiogenesis transcriptome signature which is non-invasively predictable with rCBV imaging and (2) highlight the potential future of radiogenomics (i.e. the correlation between cancer imaging and genomic features) towards a more accurate diagnostic workup of brain tumors.

The role of magnetic resonance diffusion-weighted imaging and three-dimensional arterial spin labelling perfusion imaging in the differentiation of parasellar meningioma and cavernous haemangioma

Objective

To evaluate the diagnostic value of magnetic resonance diffusion-weighted imaging (DWI) and three-dimensional arterial spin labelling perfusion imaging (3D-ASL) in distinguishing cavernous haemangioma from parasellar meningioma, using histological data as a reference standard.

Methods

Patients with parasellar meningioma or parasellar cavernous haemangioma underwent conventional T1- and T2-weighted magnetic resonance imaging (MRI) followed by DWI and 3D-ASL using a 3.0 Tesla MRI. The minimum apparent diffusion coefficient (minADC) from DWI and the maximal normalized cerebral blood flow (nCBF) from 3D-ASL were measured in each tumour. Diagnosis was confirmed by histology.

Results

MinADC was significantly lower and nCBF significantly higher in meningioma ( n = 19) than cavernous haemangioma ( n = 15). There was a significant negative correlation between minADC and nCBF ( r = −0.605).

Conclusion

DWI and 3D-ASL are useful in differentiating cavernous haemangiomas from parasellar meningiomas, particularly in situations when the appearance on conventional MRI sequences is otherwise ambiguous.

Tumor-associated edema in brain cancer patients: pathogenesis and management

The long-term treatment of peritumoral edema remains a major challenge in clinical neuro-oncology. Steroids have been and will remain the backbone of any anti-edematous therapy because of their striking activity, convenient oral administration and also because of their cost-effectiveness. Their side effects, however, can compromise quality of life, particularly upon continuous administration. Therapeutic alternatives which may replace or - at least - help to reduce the steroid dose are limited. However, with the development of new agents such as corticorelin acetate, there is a hope that steroid-induced side effects can be delayed and reduced. The administration of anti-angiogenic agents with steroid-sparing effects, for example, bevacizumab, is limited due to their costs. Increased knowledge on boswellic acids and cyclooxygenase-2 inhibitors which are available for clinical application may help to exploit their anti-edema activity more efficiently in the future.

Assessment of angiographic vascularity of meningiomas with dynamic susceptibility contrast-enhanced perfusion-weighted imaging and diffusion tensor imaging

BACKGROUND AND PURPOSE

The roles of DTI and dynamic susceptibility contrast-enhanced-PWI in predicting the angiographic vascularity of meningiomas have not been studied. We aimed to investigate if these 2 techniques could reflect the angiographic vascularity of meningiomas.

MATERIALS AND METHODS

Thirty-two consecutive patients with meningiomas who had preoperative dynamic susceptibility contrast-enhanced-PWI, DTI, and conventional angiography were retrospectively included. The correlations between angiographic vascularity of meningiomas, classified with a 4-point grading scale, and the clinical or imaging variables-age and sex of patient, as well as size, CBV, fractional anisotropy, and ADC of meningiomas-were analyzed. The meningiomas were dichotomized into high-vascularity and low-vascularity groups. The differences in clinical and imaging variables between the 2 groups were compared. Receiver operating characteristic curve analysis was used to determine the diagnostic performance of these variables.

RESULTS

In meningiomas, angiographic vascularity correlated positively with CBV but negatively with fractional anisotropy. High-vascularity meningiomas demonstrated significantly higher CBV but lower fractional anisotropy as compared with low-vascularity meningiomas. In differentiating between the 2 groups, the area under the curve values were 0.991 for CBV and 0.934 for fractional anisotropy on receiver operating characteristic curve analysis.

CONCLUSIONS

CBV and fractional anisotropy correlate well with angiographic vascularity of meningiomas. They may differentiate between low-vascularity and high-vascularity meningiomas.