Proton MRS of the peritumoral brain

Evaluation of multimodal MR imaging for differentiating infiltrative versus reactive edema in brain gliomas

OBJECTIVE

To determine the border of glial tumors by diffusion weighted imaging (DWI), apparent diffusion co-efficient (ADC), magnetic resonance spectroscopy (MRS) and perfusion brain MRI.

PATIENTS AND METHODS

Ten patients with brain gliomas were enrolled [mean age: 35.3 ± 13.2, range: 20-62]. Conventional MRI was performed for all patients. Besides, tumor mapping based on Choline (Cho)/Creatine (Cr) color map in MRS, perfusion and diffusion color maps, were gathered. Different tumoral and peritumoral regions [normal tissue, reactive edema, infiltrative edema, and tumor core] were defined. MRI criteria were evaluated in areas targeted for biopsy and histopathologic evaluation was determined.

RESULTS

Tumor cell positive samples [one necrosis, 26 infiltrative and nine tumor cores] composed 36 (75%) of the 48 samples. Seven (19.4%) of the positive samples were interpreted as not tumor on MRI. Five were identified as reactive edema and two as normal tissue] [kappa: .67, p-value < .001]. Mean of ADC, median of N-acetylaspartate (NAA) and NAA/Cho were statistically different between positive and negative samples (p = .02 and p < .001, respectively). Mean ADC and median Cho/NAA were statistically different in missed tumor containing tissue presented as reactive edema compared to normal and correctly diagnosed reactive edema samples together (p-values < .05).

CONCLUSIONS

Multimodal MRI could define infiltrated borders of brain gliomas.

Advanced MRI assessment of non-enhancing peritumoral signal abnormality in brain lesions

Evaluation of Central Nervous System (CNS) focal lesions has been classically made focusing on the assessment solid or enhancing component. However, the assessment of solitary peripherally enhancing lesions where the differential diagnosis includes High-Grade Gliomas (HGG) and metastasis, is usually challenging. Several studies have tried to address the characteristics of peritumoral non-enhancing areas, for better characterization of these lesions. Peritumoral hyperintense T2/FLAIR signal abnormality predominantly contains infiltrating tumor cells in HGG whereas CNS metastasis induce pure vasogenic edema. In addition, the accurate determination of the real extension of HGG is critical for treatment selection and outcome. Conventional MRI sequences are limited in distinguishing infiltrating neoplasm from vasogenic edema. Advanced MRI sequences like Diffusion Weighted Imaging (DWI), Diffusion Tensor Imaging (DTI), Perfusion Weighted Imaging (PWI) and MR spectroscopy (MRS) have all been utilized for this aim with acceptable results. Other advanced MRI approaches, less explored for this task such as Arterial Spin Labelling (ASL), Diffusion Kurtosis Imaging (DKI), T2 relaxometry or Amide Proton Transfer (APT) are also showning promising results in this scenario. In this article, we will discuss the physiopathological basis of peritumoral T2/FLAIR signal abnormality and review potential applications of advanced MRI sequences for its evaluation.

Identification of neural networks preferentially engaged by epileptogenic mass lesions through lesion network mapping analysis

Lesion network mapping (LNM) has been applied to true lesions (e.g., cerebrovascular lesions in stroke) to identify functionally connected brain networks. No previous studies have utilized LNM for analysis of intra-axial mass lesions. Here, we implemented LNM for identification of potentially vulnerable epileptogenic networks in mass lesions causing medically-refractory epilepsy (MRE). Intra-axial brain lesions were manually segmented in patients with MRE seen at our institution (EL_INST). These lesions were then normalized to standard space and used as seeds in a high-resolution normative resting state functional magnetic resonance imaging template. The resulting connectivity maps were first thresholded (p_{Bonferroni_cor} < 0.05) and binarized; the thresholded binarized connectivity maps were subsequently summed to produce overall group connectivity maps, which were compared with established resting-state networks to identify potential networks prone to epileptogenicity. To validate our data, this approach was also applied to an external dataset of epileptogenic lesions identified from the literature (EL_LIT). As an additional exploratory analysis, we also segmented and computed the connectivity of institutional non-epileptogenic lesions (NEL_INST), calculating voxel-wise odds ratios (VORs) to identify voxels more likely to be functionally-connected with EL_INST versus NEL_INST. To ensure connectivity results were not driven by anatomical overlap, the extent of lesion overlap between EL_INST, and EL_LIT and NEL_INST was assessed using the Dice Similarity Coefficient (DSC, lower index ~ less overlap). Twenty-eight patients from our institution were included (EL_INST: 17 patients, 17 lesions, 10 low-grade glioma, 3 cavernoma, 4 focal cortical dysplasia; NEL_INST: 11 patients, 33 lesions, all brain metastases). An additional 23 cases (25 lesions) with similar characteristics to the EL_INST data were identified from the literature (EL_LIT). Despite minimal anatomical overlap of lesions, both EL_INST and EL_LIT showed greatest functional connectivity overlap with structures in the Default Mode Network, Frontoparietal Network, Ventral Attention Network, and the Limbic Network-with percentage volume overlap of 19.5%, 19.1%, 19.1%, and 12.5%, respectively-suggesting them as networks consistently engaged by epileptogenic mass lesions. Our exploratory analysis moreover showed that the mesial frontal lobes, parahippocampal gyrus, and lateral temporal neocortex were at least twice as likely to be functionally connected with the EL_INST compared to the NEL_INST group (i.e. Peak VOR > 2.0); canonical resting-state networks preferentially engaged by EL_INSTs were the Limbic and the Frontoparietal Networks (Mean VOR > 1.5). In this proof of concept study, we demonstrate the feasibility of LNM for intra-axial mass lesions by showing that ELs have discrete functional connections and may preferentially engage in discrete resting-state networks. Thus, the underlying normative neural circuitry may, in part, explain the propensity of particular lesions toward the development of MRE. If prospectively validated, this has ramifications for patient counseling along with both approach and timing of surgery for lesions in locations prone to development of MRE.

Predictors and mechanisms of epilepsy occurrence in cerebral gliomas: What to look for in clinicopathology

Gliomas, especially low-grade gliomas, are highly epileptogenic brain tumors. Histopathological information is valuable in evaluating the diagnosis and/or biologic behavior of various gliomas. Here we explored the clinical data and histopathological predictors of the occurrence of epilepsy in patients with gliomas. A retrospective study examined 310 consecutive patients who had undergone surgical treatment for gliomas in our institution from January 2013 to January 2015. Clinical data and pathological examination results were analyzed. Literatures regarding the predictors and etiology of glioma associated epileptic seizures in the period of 1995-2015 were also reviewed. A total of 234 (75.5%) astrocytic tumors and 76 (24.5%) oligodendrial tumors were included. At diagnosis, 33.6% of patients had epileptic seizures. Multivariate analysis revealed cortex involvement (OR=7.991, 95%CI=1.599-39.926), lower World Health Organization grade (OR=3.584, 95%CI=1.032-12.346) and topoisomerase II (TopoII) positivity (OR=0.943, 95%CI=0.903-0.982) were strong predictors for preoperative epileptic seizures. Gender, disease course, tumor classification, location or volume did not significantly affect epileptic seizure occurrence. Forty-three publications involved glioma-associated epilepsy were found in PubMed online database and key data were extracted and summarized. The present studies on glioma-related epilepsy are relatively limited and inconsistent. Low-grade gliomas, cortex involvement and TopoII positivity were independent predictors of a history of epileptic seizures at diagnosis. Further studies to examine the underlying mechanism of topoisomerase II as well as other molecules in epilepsy occurrence in brain gliomas are needed in the future.

Predictors of Lesion Calcification in Patients with Solitary Cysticercus Granuloma and New-Onset Seizures

Solitary cysticercus granuloma is a common neuroimaging abnormality in Indian patients with new-onset epilepsy. Calcific transformation of cysticercus granuloma is frequently associated with seizure recurrence. We evaluated predictors of lesion calcification in patients with solitary cysticercus granuloma and new-onset seizures. One hundred twenty-two patients, with new-onset seizures and a solitary cysticercus granuloma of the brain, were enrolled. All patients were clinically and radiologically evaluated and were treated with antiepileptic drug drugs. No patient received albendazole or corticosteroids. The follow-up period was of 1 year. Follow-up computed tomography was performed after 3 and 6 months. In 68 (54.8%) patients, solitary cysticercus granuloma had transformed into a calcified lesion. On logistic regression analysis, moderate-to-severe edema was a significant factor that predicted calcific transformation of the cysticercus granuloma (odds ratio: 3.325; 95% confidence interval: 1.502-7.362). During 1 year of follow-up, 19 (15.6%) patients experienced seizure recurrence. In 16 patients with seizure recurrence, cysticercus granuloma had transformed in to a calcified lesion. In conclusion, in solitary cysticercus granuloma, calcification of the lesion can be predicted if larger amount of perilesional edema is present. Calcification of the granuloma significantly predicts seizure recurrence.

Fast spectroscopic multiple analysis (FASMA) for brain tumor classification: a clinical decision support system utilizing multi-parametric 3T MR data

INTRODUCTION

A clinical decision support system (CDSS) for brain tumor classification can be used to assist in the diagnosis and grading of brain tumors. A Fast Spectroscopic Multiple Analysis (FASMA) system that uses combinations of multiparametric MRI data sets was developed as a CDSS for brain tumor classification.

METHODS

MRI metabolic ratios and spectra, from long and short TE, respectively, as well as diffusion and perfusion data were acquired from the intratumoral and peritumoral area of 126 patients with untreated intracranial tumors. These data were categorized based on the pathology, and different machine learning methods were evaluated regarding their classification performance for glioma grading and differentiation of infiltrating versus non-infiltrating lesions. Additional databases were embedded to the system, including updated literature values of the related MR parameters and typical tumor characteristics (imaging and histological), for further comparisons. Custom Graphical User Interface (GUI) layouts were developed to facilitate classification of the unknown cases based on the user's available MR data.

RESULTS

The highest classification performance was achieved with a support vector machine (SVM) using the combination of all MR features. FASMA correctly classified 89 and 79% in the intratumoral and peritumoral area, respectively, for cases from an independent test set. FASMA produced the correct diagnosis, even in the misclassified cases, since discrimination between infiltrative versus non-infiltrative cases was possible.

CONCLUSIONS

FASMA is a prototype CDSS, which integrates complex quantitative MR data for brain tumor characterization. FASMA was developed as a diagnostic assistant that provides fast analysis, representation and classification for a set of MR parameters. This software may serve as a teaching tool on advanced MRI techniques, as it incorporates additional information regarding typical tumor characteristics derived from the literature.

Clinical decision support systems for brain tumor characterization using advanced magnetic resonance imaging techniques

In recent years, advanced magnetic resonance imaging (MRI) techniques, such as magnetic resonance spectroscopy, diffusion weighted imaging, diffusion tensor imaging and perfusion weighted imaging have been used in order to resolve demanding diagnostic problems such as brain tumor characterization and grading, as these techniques offer a more detailed and non-invasive evaluation of the area under study. In the last decade a great effort has been made to import and utilize intelligent systems in the so-called clinical decision support systems (CDSS) for automatic processing, classification, evaluation and representation of MRI data in order for advanced MRI techniques to become a part of the clinical routine, since the amount of data from the aforementioned techniques has gradually increased. Hence, the purpose of the current review article is two-fold. The first is to review and evaluate the progress that has been made towards the utilization of CDSS based on data from advanced MRI techniques. The second is to analyze and propose the future work that has to be done, based on the existing problems and challenges, especially taking into account the new imaging techniques and parameters that can be introduced into intelligent systems to significantly improve their diagnostic specificity and clinical application.

Analysis of diffusion tensor imaging metrics for gliomas grading at 3 T

OBJECTIVES

To assess the diagnostic accuracy of axial diffusivity (AD), radial diffusivity (RD), apparent diffusion coefficient (ADC) and fractional anisotropy (FA) values derived from DTI for grading of glial tumors, and to estimate the correlation between DTI parameters and tumor grades.

METHODS

Seventy-eight patients with glial tumors underwent DTI. AD, RD, ADC and FA values of tumor, peritumoral edema and contralateral normal-appearing white matter (NAWM) and AD, RD, ADC and FA ratios: lowest average AD, RD, ADC and FA values in tumor or peritumoral edema to AD, RD, ADC and FA of NAWM were calculated. DTI parameters and tumor grades were analyzed statistically and with Pearson correlation. Receiver operating characteristic (ROC) curve analysis was also performed.

RESULTS

The differences in ADC, AD and RD tumor values, and ADC and RD tumor ratios were statistically significant between grades II and III, grades II and IV, and between grades II and III-IV. The AD tumor ratio differed significantly among all tumor grades. Tumor ADC, AD, RD and glial tumor grades were strongly correlated. In the ROC curve analysis, the area under the curve (AUC) of the parameter tumor ADC was the largest for distinguishing grade II from grades III to IV (98.5%), grade II from grade IV (98.9%) and grade II from grade III (97.0%).

CONCLUSION

ADC, RD and AD are useful DTI parameters for differentiation between low- and high-grade gliomas with a diagnostic accuracy of more than 90%. Our study revealed a good inverse correlation between ADC, RD, AD and WHO grades II-IV astrocytic tumors.

Seizures in low-grade gliomas: natural history, pathogenesis, and outcome after treatments

Seizures represent a common symptom in low-grade gliomas; when uncontrolled, they significantly contribute to patient morbidity and negatively impact quality of life. Tumor location and histology influence the risk for epilepsy. The pathogenesis of tumor-related epilepsy is multifactorial and may differ among tumor histologies (glioneuronal tumors vs diffuse grade II gliomas). Gross total resection is the strongest predictor of seizure freedom in addition to clinical factors, such as preoperative seizure duration, type, and control with antiepileptic drugs (AEDs). Epilepsy surgery may improve seizure control. Radiotherapy and chemotherapy with alkylating agents (procarbazine + CCNU+ vincristine, temozolomide) are effective in reducing the frequency of seizures in patients with pharmacoresistant epilepsy. Newer AEDs (levetiracetam, topiramate, lacosamide) seem to be better tolerated than the old AEDs (phenobarbital, phenytoin, carbamazepine), but there is lack of evidence regarding their superiority in terms of efficacy.

Differentiation of glioblastoma multiforme from metastatic brain tumor using proton magnetic resonance spectroscopy, diffusion and perfusion metrics at 3 T

Purpose: To assess the contribution of ¹H-magnetic resonance spectroscopy (¹H-MRS), diffusion-weighted imaging (DWI), diffusion tensor imaging (DTI) and dynamic susceptibility contrast-enhanced (DSCE) imaging metrics in the differentiation of glioblastomas from solitary metastasis, and particularly to clarify the controversial reports regarding the hypothesis that there should be a significant differentiation between the intratumoral and peritumoral areas. Methods: Conventional MR imaging, ¹H-MRS, DWI, DTI and DSCE MRI was performed on 49 patients (35 glioblastomas multiforme, 14 metastases) using a 3.0-T MR unit. Metabolite ratios, apparent diffusion coefficient (ADC), fractional anisotropy (FA) and relative cerebral blood volume (rCBV) were measured in the intratumoral and peritumoral regions of the lesions. Receiver-operating characteristic analysis was used to obtain the cut-off values for the parameters presenting a statistical difference between the two tumor groups. Furthermore, we investigated the potential effect of the region of interest (ROI) size on the quantification of diffusion properties in the intratumoral region of the lesions, by applying two different ROI methods. Results: Peritumoral N-acetylaspartate (NAA)/creatine (Cr), choline (Cho)/Cr, Cho/NAA and rCBV significantly differentiated glioblastomas from intracranial metastases. ADC and FA presented no significant difference between the two tumor groups. Conclusions:¹H-MRS and dynamic susceptibility measurements in the peritumoral regions may definitely aid in the differentiation of glioblastomas and solitary metastases. The quantification of the diffusion properties in the intratumoral region is independent of the ROI size placed.

Spectroscopic evaluation of glioma grading at 3T: the combined role of short and long TE

Purpose. To evaluate the diagnostic value of 3T ¹H-MRS in grading cerebral gliomas using short and long echo times. Methods. 1H-MRS was performed on 71 patients with untreated cerebral gliomas. Metabolite ratios of NAA/Cr, Cho/Cr, Cho/NAA, and mI/Cr were calculated for short and long TE and compared between low and high grade gliomas. Lipids were qualitatively evaluated. ROC analysis was performed to obtain the cut-off values for the metabolic ratios presenting statistical difference between the two glioma grades. Results. Intratumoral Cho/Cr at both TEs and long TE Cho/NAA were significantly different between low and high grade gliomas. Peritumoral NAA/Cr of both TEs, as well as long TE Cho/Cr and Cho/NAA ratios, significantly differentiated the two tumor grades. Diagnostic sensitivity of peritumoral short TE NAA/Cr proved to be superior over the other metabolic ratios, whereas intratumoral short TE Cho/Cr reached the highest levels of specificity and accuracy. Overall, short TE 1H-MRS reached higher total sensitivity in predicting glioma grade, over long TE. Conclusion. An advantage was found in using short TE over long TE 1H-MRS in the discrimination of low versus high grade gliomas. Moreover, the results suggested that the peritumoral area of gliomas may be more valuable in predicting glioma grade than using only the intratumoral area.

MRS study of meningeal hemangiopericytoma and edema: a comparison with meningothelial meningioma

Intracranial hemangiopericytomas (HPCs) are rare tumors and their radiological appearance resembles that of meningiomas, especially meningothelial meningiomas. To increase the knowledge on the biochemical composition of this type of tumor for better diagnosis and prognosis, we performed a molecular study using ex vivo high resolution magic angle spinning (HR-MAS) magnetic resonance spectroscopy (MRS) perfomed on HPC and peritumoral edematous tissues. Moreover, to help in the discrimination between HPC and meningothelial meningioma we compared the ex vivo HR-MAS spectra of samples from one patient with HPC and 5 patients affected by meningothelial meningioma. Magnetic resonance imaging (MRI), in vivo localized single voxel 1H-MRS was also performed on the same patients prior to surgery and the in vivo and ex vivo MRS spectra were compared. We observed the presence of OH-butyrate, together with glucose in HPC and a low amount of N-acetylaspartate in the edema, that may reflect neuronal alteration responsible for associated epilepsy. Many differences between HPC and meningothelial meningioma were identified. The relative ratios of myo-inositol, glucose and gluthatione with respect to glutamate are higher in HPC compared to meningioma; whereas the relative ratios of creatine, glutamine, alanine, glycine and choline-containing compounds with respect to glutamate are lower in HPC compared to meningioma. These data will be useful to improve the interpretation of in vivo MRS spectra resulting in a more accurate diagnosis of these rare tumors.

The pathogenesis of tumor-related epilepsy and its implications for clinical treatment

Approximately 30-50% of patients with brain tumors present with seizures as the initial symptom. Seizures play a very important role in the quality of life, particularly in patients with slow-growing primary brain tumors. Tumor-related seizures are often refractory to antiepileptic treatment. Despite the importance of this subject to the fields of neurology, neurosurgery and neurooncology, the pathogenesis of tumor-related epilepsy remains poorly understood. This review summarizes possible mechanisms underlying the pathogenesis of tumor-related epilepsy, including both tumoral and peri-tumoral aspects. Tumor cells themselves may create intrinsic epileptogenicity, and inadequate homeostasis in the peri-tumoral tissues may lead to seizure susceptibility. Other local changes in electrolytes, perfusion, metabolism, and enzymes could also contribute. It is generally accepted that changes in amino acid neurotransmission are the most important mechanism underlying tumor-related seizures, and changes in extracellular ions also play an important role. Hypoxia, acidosis, and metabolic, immunological, and inflammatory changes may also be involved in the occurrence of seizures. Knowledge of these mechanisms may provide guidance in the search for new strategies for the surgical and medical treatment of tumor-related epilepsy.

¹H-MRS of intracranial meningiomas: what it can add to known clinical and MRI predictors of the histopathological and biological characteristics of the tumor?

OBJECTIVE

The main goal of the present study was evaluation of proton magnetic resonance spectroscopy (¹H-MRS) in diagnosis of histopathologically aggressive intracranial meningiomas.

METHODS

Single-voxel ¹H-MRS of 100 intracranial meningiomas was performed before their surgical resection. Investigated metabolites included mobile lipids, lactate, alanine, N-acetylaspartate (NAA), and choline-containing compounds (Cho). According to criteria of World Health Organization (WHO) 82 meningiomas were assigned histopathological grade I, 11 grade II, and 7 grade III. The MIB-1 index varied from 0% to 27.3% (median, 1.6%). In 43 cases tight adhesion of the tumor to the pia mater or brain tissue was macroscopically identified at surgery. The consistency of 49 meningiomas was characterized as soft, 26 as hard, and 25 as mixed.

RESULTS

No one metabolic parameter had statistically significant association with histopathological grade and subtype, invasive growth, and consistency of meningioma. Univariate statistical analysis revealed greater ¹H-MRS-detected Cho content (P=0.0444) and lower normalized NAA/Cho ratio (P=0.0203) in tumors with MIB-1 index 5% and more. However, both parameters lost their statistical significance during evaluation in the multivariate model along with other clinical and radiological variables. It was revealed that non-benign histopathology of meningioma (WHO grade II/III) is mainly predicted by irregular shape (P=0.0076) and large size (P=0.0316), increased proliferative activity by irregular shape (P=0.0056), and macroscopically invasive growth by prominent peritumoral edema (P=0.0021).

CONCLUSION

While ¹H-MRS may be potentially used for the identification of meningiomas with high proliferative activity, it, seemingly, could not add substantial diagnostic information to other radiological predictors of malignancy in these tumors.

Epilepsy and brain tumors

PURPOSE OF REVIEW

To present an overview of the recent findings in pathophysiology and management of epileptic seizures in patients with brain tumors.

RECENT FINDINGS

Low-grade gliomas are the most epileptogenic brain tumors. Regarding pathophysiology, the role of peritumoral changes [hypoxia and acidosis, blood-brain barrier (BBB) disruption, increase or decrease of neurotransmitters and receptors] are of increasing importance. Tumor-associated epilepsy and tumor growth could have some common molecular pathways. Total/subtotal surgical resection (with or without epilepsy surgery) allows a seizure control in a high percentage of patients. Radiotherapy and chemotherapy as well have a role. New antiepileptic drugs are promising, both in terms of efficacy and tolerability. The resistance to antiepileptic drugs is still a major problem: new insights into pathogenesis are needed to develop strategies to manipulate the pharmakoresistance.

SUMMARY

Epileptic seizures in brain tumors have been definitely recognized as one of the major problems in patients with brain tumors, and need specific and multidisciplinary approaches.

Measurements of diagnostic examination performance and correlation analysis using microvascular leakage, cerebral blood volume, and blood flow derived from 3T dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in glial tumor grading

INTRODUCTION

To assess the diagnostic accuracy of microvascular leakage (MVL), cerebral blood volume (CBV) and blood flow (CBF) values derived from dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC-MR imaging) for grading of cerebral glial tumors, and to estimate the correlation between vascular permeability/perfusion parameters and tumor grades.

METHODS

A prospective study of 79 patients with cerebral glial tumors underwent DSC-MR imaging. Normalized relative CBV (rCBV) and relative CBF (rCBF) from tumoral (rCBVt and rCBFt), peri-enhancing region (rCBVe and rCBFe), and the value in the tumor divided by the value in the peri-enhancing region (rCBVt/e and rCBFt/e), as well as MVL, expressed as the leakage coefficient K(2) were calculated. Hemodynamic variables and tumor grades were analyzed statistically and with Pearson correlations. Receiver operating characteristic (ROC) curve analyses were also performed for each of the variables.

RESULTS

The differences in rCBVt and the maximum MVL (MVL(max)) values were statistically significant among all tumor grades. Correlation analysis using Pearson was as follows: rCBVt and tumor grade, r = 0.774; rCBFt and tumor grade, r = 0.417; MVL(max) and tumor grade, r = 0.559; MVL(max) and rCBVt, r = 0.440; MVL(max) and rCBFt, r = 0.192; and rCBVt and rCBFt, r = 0.605. According to ROC analyses for distinguishing tumor grade, rCBVt showed the largest areas under ROC curve (AUC), except for grade III from IV.

CONCLUSION

Both rCBVt and MVL(max) showed good discriminative power in distinguishing all tumor grades. rCBVt correlated strongly with tumor grade; the correlation between MVL(max) and tumor grade was moderate.

Diagnostic examination performance by using microvascular leakage, cerebral blood volume, and blood flow derived from 3-T dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging in the differentiation of glioblastoma multiforme and brain metastasis

INTRODUCTION

Conventional magnetic resonance (MR) imaging has limited capacity to differentiate between glioblastoma multiforme (GBM) and metastasis. The purposes of this study were: (1) to compare microvascular leakage (MVL), cerebral blood volume (CBV), and blood flow (CBF) in the distinction of metastasis from GBM using dynamic susceptibility-weighted contrast-enhanced perfusion MR imaging (DSC-MRI), and (2) to estimate the diagnostic accuracy of perfusion and permeability MR imaging.

METHODS

A prospective study of 61 patients (40 GBMs and 21 metastases) was performed at 3 T using DSC-MRI. Normalized rCBV and rCBF from tumoral (rCBVt, rCBFt), peri-enhancing region (rCBVe, rCBFe), and by dividing the value in the tumor by the value in the peri-enhancing region (rCBVt/e, rCBFt/e), as well as MVL were calculated. Hemodynamic and histopathologic variables were analyzed statistically and Spearman/Pearson correlations. Receiver operating characteristic curve analysis was performed for each of the variables.

RESULTS

The rCBVe, rCBFe, and MVL were significantly greater in GBMs compared with those of metastases. The optimal cutoff value for differentiating GBM from metastasis was 0.80 which implies a sensitivity of 95%, a specificity of 92%, a positive predictive value of 86%, and a negative predictive value of 97% for rCBVe ratio. We found a modest correlation between rCBVt and rCBFt ratios.

CONCLUSION

MVL measurements in GBMs are significantly higher than those in metastases. Statistically, both rCBVe, rCBVt/e and rCBFe, rCBFt/e were useful in differentiating between GBMs and metastases, supporting the hypothesis that perfusion MR imaging can detect infiltration of tumor cells in the peri-enhancing region.

First intraoperative, shared-resource, ultrahigh-field 3-Tesla magnetic resonance imaging system and its application in low-grade glioma resection

OBJECT

The authors describe the first shared-resource, 3-T intraoperative MR (ioMR) imaging system and analyze its impact on low-grade glioma (LGG) resection with an emphasis on the use of intraoperative proton MR spectroscopy.

METHODS

The Acibadem University ioMR imaging facility houses a 3-T Siemens Trio system and consists of interconnected but independent MR imaging and surgical suites. Neurosurgery is performed using regular ferromagnetic equipment, and a patient can be transferred to the ioMR imaging system within 1.5 minutes by using a floating table. The ioMR imaging protocol takes < 10 minutes including the transfer, and the authors obtain very high-resolution T2-weighted MR images without the use of intravenous contrast. Functional sequences are performed when needed. A new 5-pin headrest-head coil combination and floating transfer table were specifically designed for this system.

RESULTS

Since the facility became operational in June 2004, 56 LGG resections have been performed using ioMR imaging, and > 19,000 outpatient MR imaging procedures have been conducted. First-look MR imaging studies led to further resection attempts in 37.5% of cases as well as a 32.3% increase in the number of gross-total resections. Intraoperative ultrasonography detected 16% of the tumor remnants. Intraoperative proton MR spectroscopy and diffusion weighted MR imaging were used to differentiate residual tumor tissue from peritumoral parenchymal changes. Functional and diffusion tensor MR imaging sequences were used both pre- and postoperatively but not intraoperatively. No infections or other procedure-related complications were encountered.

CONCLUSIONS

This novel, shared-resource, ultrahigh-field, 3-T ioMR imaging system is a cost-effective means of affording a highly capable ioMR imaging system and increases the efficiency of LGG resections.

Comparison of 1H-MRS-detected metabolic characteristics in single metastatic brain tumors of different origin

Various types of intracranial metastases exhibit different growth patterns, which can be reflected in their metabolic characteristics and investigated noninvasively by proton magnetic resonance spectroscopy (1H-MRS). The objective of the present study was comparison of the 1H-MRS-detected metabolic parameters in brain metastases of different origin. Twenty-five patients (15 men and 10 women; mean age, 62.0 years) with single, previously nontreated metastatic brain tumors were investigated by long-echo single-voxel volume-selected 1H-MRS. The primary cancer was located in the lungs (10 cases), colon and rectum (8 cases), breast (3 cases), kidney (2 cases), prostate (1 case), and cardiac muscle (1 case). Comparison of clinical and radiological variables, including type of tumor contrast enhancement and extension of peritumoral edema, did not disclose statistically significant differences in metastatic brain tumors of different origin. At the same time, comparison of 1H-MRS-detected metabolic characteristics revealed that metastases of colorectal carcinoma have greater content of mobile lipids (Lip) compared to other neoplasms. In conclusion, high Lip content in the viable brain metastases of colorectal carcinoma can be used as an additional diagnostic clue for noninvasive identification of these tumors and should be taken into consideration in cases of 1H-MRS-based differentiation of their recurrence and radiation-induced necrosis after radiosurgical or radiotherapeutic treatment.

Brain tumors and epilepsy: pathophysiology of peritumoral changes

Epilepsy commonly develops among patients with brain tumors, frequently even as the presenting symptom, and such patients consequently experience substantial morbidity from both the seizures and the underlying disease. At clinical presentation, these seizures are most commonly focal with secondary generalization and conventional medical management is often met with less efficacy. The molecular pathophysiology of these seizures is being elucidated with findings that both the tumoral and peritumoral microenvironments may exhibit epileptogenic phenotypes owing to disordered neuronal connectivity and regulation, impaired glial cell function, and the presence of altered vascular supply and permeability. Neoplastic tissue can itself be the initiation site of seizure activity, particularly for tumors arising from neuronal cell lines, such as gangliogliomas or dysembryoblastic neuroepithelial tumors. Conversely, a growing intracranial lesion can both structurally and functionally alter the surrounding brain tissue with edema, vascular insufficiency, inflammation, and release of metabolically active molecules, hence also promoting seizure activity. The involved mechanisms are certain to be multifactorial and depend on specific tumor histology, integrity of the blood brain barrier, and characteristics of the peritumoral environment. Understanding these changes that underlie tumor-related epilepsy may have roles in both optimal medical management for the seizure symptom and optimal surgical objective and management of the underlying disease.

Metabolic findings on 3T 1H-MR spectroscopy in peritumoral brain edema

BACKGROUND AND PURPOSE

Little is known about the metabolic properties of brain edema associated with tumors. This work was conducted on the basis of the assumption that, in the presence of intra-axial and extra-axial brain tumors, the white matter involved by the edema is a site of metabolic change that involves the structure of the myelin sheath.

MATERIALS AND METHODS

Thirteen patients comprised our cohort affected by intra-axial and extra-axial cerebral tumors with a peritumoral T2-weighted MR signal hyperintensity as a result of edema, where MR spectroscopy showed no increase in choline-containing compounds. Measurements on proton MR spectroscopy (1H-MR spectroscopy) were performed with a 3T whole-body scanner with use of a point-resolved spectroscopy sequence for localization (TR, 2000 ms; TE, 35 ms), and the metabolites were quantified with the SAGE method. Peak intensities of the main metabolites were expressed as ratios of one another and were compared with values obtained in the white matter of the left frontal region in a control group of 16 healthy volunteers.

RESULTS

Choline-to-creatine (Cho/Cr) and myo-inositol-to-creatine (mIns/Cr) signal intensity ratios were normal in all patients. N-acetylaspartate-to-creatine (NAA/Cr) and N-acetylaspartate-to-choline (NAA/Cho) ratios decreased in 4 patients. Glutamate plus glutamine-to-creatine (Glx/Cr) was increased in 10 patients. A resonance peak at 3.44 ppm, strongly suggesting the presence of glucose, was detected in all but 1 patient. Lactate was detected in 12 patients and lipids in 5. Moreover, the resonances that pertained to the aliphatic amino acids valine, leucine, and isoleucine were present in 12 patients.

CONCLUSIONS

Our findings on MR spectroscopy confirmed the hypothesis that in the edema surrounding brain tumors, an energy-linked metabolic alteration was associated with injury to the myelin sheath.

Carbamazepine treatment recovered low N-acetylaspartate+N-acetylaspartylglutamate (tNAA) levels in the megencephaly mouse BALB/cByJ-Kv1.1(mceph/mceph)

Megencephaly mice (BALB/cByJ-Kv1.1(mceph/mceph)) display excessive brain growth and seizures related to a mutation within the potassium channel gene Kv1.1 producing a malfunctioning protein. (1)H Magnetic resonance spectroscopy (MRS) provides means to study brain transmitters and metabolites in vivo. We applied MRS to pinpoint differences in hippocampus between mceph/mceph and wild type (wt) mice. Carbamazepine (CBZ) protects against brain overgrowth in mceph/mceph. Therefore, the effects of durable oral CBZ treatment on the MR spectra were investigated. LCModel was used for spectra quantification and multivariate data analysis applied to detect group differences. mceph/mceph mice had lower levels of N-acetylaspartate+N-acetylaspartylglutamate (tNAA) and choline-containing (tCho) compounds compared to wt mice. Glutamate, glutamine, taurine and myo-inositol levels were similar in wt and mceph/mceph. Furthermore, CBZ treatment recovered tCho and tNAA levels in mceph/mceph. Thus, distinct differences in MRS spectra between mceph/mceph and wt mice were depicted and treatment effects of CBZ were monitored using MRS.

Proton magnetic resonance spectroscopy (MRS) of metastatic brain tumors: variations of metabolic profile

BACKGROUND

Spectroscopic imaging can be helpful for the noninvasive identification of parenchymal brain tumors. The objective of the present study was the characterization of the metabolic profile of intracranial metastases, based on proton magnetic resonance spectroscopy (MRS).

METHODS

One hundred and four metastatic brain tumors were evaluated by long-echo (TR, 2000 ms; TE, 136 ms) single-voxel volume-selected proton MRS. In 83 patients the tumor fraction within the MRS voxel constituted more than 50%.

RESULTS

Compared to normal brain, the tumors showed statistically significant decreases of N-acetylaspartate (P < 0.0001), creatine (P < 0.0001), and the [NAA]/choline-containing compounds ratio (P < 0.0001), increases of [Cho] (P < 0.0001) and the mobile lipids/[Cr] ratio (P < 0.0001) and the lactate/[Cr] ratio (P < 0.05), and the more frequent presence of [Lip] (P < 0.0001) and [Lac] (P < 0.0001) resonances. However, the majority of these differences were lost when data for patients whose tumor fraction within the MRS voxel constituted less than 50% were analyzed separately. Determination of the predominant metabolite peak on the MR spectrum [NAA, Cho, Lip] permitted us to define three general metabolic patterns of brain metastases, which, showed statistically significant associations with the size of the neoplasm (P < 0.001), type of its contrast enhancement (P < 0.01), and the extent of perilesional edema (P < 0.05).

CONCLUSION

Proton MRS can define metabolically different subsets of metastatic brain tumors, and these characteristics should be taken into consideration during the differential diagnosis of parenchymal brain lesions.

Advanced neuroimaging of pediatric brain tumors: MR diffusion, MR perfusion, and MR spectroscopy

This article highlights the MR imaging techniques of MR perfusion, MR diffusion, and MR spectroscopy in the evaluation of the child with a pediatric brain tumor. These techniques are complementary to conventional MR imaging in providing tumor physiologic information useful for diagnosis and therapy.

Optimization of semi-quantification in metabolic PET studies with 18F-fluorodeoxyglucose and 11C-methionine in the determination of malignancy of gliomas

The treatment of the glioma patient depends on the nature of the lesion and on the aggressiveness of the tumor. The management of gliomas continues to be a challenging task, because morphological neuroimaging techniques do not always differentiate them from nontumoral lesions or high grade tumors from low grade lesions. Positron Emission Tomography (PET) offers the possibility of the in vivo quantitative characterization of brain tumors. Despite decades of useful application of PET in the clinical monitoring of gliomas, no consensus has been reached on the most effective image analysis approach for providing the best diagnostic performance under heavy-duty clinical diagnostic circumstances. The main objective of the present study was to find and validate optimal semi-quantitative search strategies for metabolic PET studies on gliomas, with special regard to the optimization of those metabolic tracer uptake ratios most sensitive in predicting histologic grade and prognosis. 11C-Methionine (11C-Met, n = 50) and/or 18F-Fluorodeoxyglucose (18F-FDG, n = 33) PET measurements were performed in 59 patients with primary and recurrent brain gliomas (22 high grade and 37 low grade tumors) in order to correlate the biological behavior and 11C-Met/18F-FDG uptake of tumors. Data were analyzed by region-of-interests (ROI) methods using standard uptake value calculation. Different ROI defining strategies were then compared with each other for two of the most commonly used metabolic radiotracers, 18F-FDG and 11C-Met, in order to determine their usefulness in grading gliomas. The results were compared to histological data in all patients. Both ANOVA and receiver operating characteristic (ROC) analysis indicated that the performance of 18F-FDG was superior to that of 11C-Met for most of the ratios. 18F-FDG is therefore suggested as the tracer of choice for noninvasive semi-quantitative indicator of histologic grade of gliomas. 11C-Methionine has been suggested as a complimentary tracer, useful in delineating the extent of the tumor. The best diagnostic performance was obtained by calculating the ratio of the peak 18F-FDG uptake of the tumor to that of white matter (p < 0.001; ANOVA). This metabolic tracer uptake ratio is therefore suggested as an easily obtained semi-quantitative PET indicator of malignancy and histological grade in gliomas.