MR spectroscopy of brain tumors

The Utility of Spectroscopic MRI in Stereotactic Biopsy and Radiotherapy Guidance in Newly Diagnosed Glioblastoma

Current diagnostic and therapeutic approaches for gliomas have limitations hindering survival outcomes. We propose spectroscopic magnetic resonance imaging as an adjunct to standard MRI to bridge these gaps. Spectroscopic MRI is a volumetric MRI technique capable of identifying tumor infiltration based on its elevated choline (Cho) and decreased N-acetylaspartate (NAA). We present the clinical translatability of spectroscopic imaging with a Cho/NAA ≥ 5x threshold for delineating a biopsy target in a patient diagnosed with non-enhancing glioma. Then, we describe the relationship between the undertreated tumor detected with metabolite imaging and overall survival (OS) from a pilot study of newly diagnosed GBM patients treated with belinostat and chemoradiation. Each cohort (control and belinostat) were split into subgroups using the median difference between pre-radiotherapy Cho/NAA ≥ 2x and the treated T1-weighted contrast-enhanced (T1w-CE) volume. We used the Kaplan-Meier estimator to calculate median OS for each subgroup. The median OS was 14.4 months when the difference between Cho/NAA ≥ 2x and T1w-CE volumes was higher than the median compared with 34.3 months when this difference was lower than the median. The T1w-CE volumes were similar in both subgroups. We find that patients who had lower volumes of undertreated tumors detected via spectroscopy had better survival outcomes.

Machine learning decision tree models for multiclass classification of common malignant brain tumors using perfusion and spectroscopy MRI data

Background

To investigate the contribution of machine learning decision tree models applied to perfusion and spectroscopy MRI for multiclass classification of lymphomas, glioblastomas, and metastases, and then to bring out the underlying key pathophysiological processes involved in the hierarchization of the decision-making algorithms of the models.

Methods

From 2013 to 2020, 180 consecutive patients with histopathologically proved lymphomas (n = 77), glioblastomas (n = 45), and metastases (n = 58) were included in machine learning analysis after undergoing MRI. The perfusion parameters (rCBVmax, PSRmax) and spectroscopic concentration ratios (lac/Cr, Cho/NAA, Cho/Cr, and lip/Cr) were applied to construct Classification and Regression Tree (CART) models for multiclass classification of these brain tumors. A 5-fold random cross validation was performed on the dataset.

Results

The decision tree model thus constructed successfully classified all 3 tumor types with a performance (AUC) of 0.98 for PCNSLs, 0.98 for GBM and 1.00 for METs. The model accuracy was 0.96 with a RSquare of 0.887. Five rules of classifier combinations were extracted with a predicted probability from 0.907 to 0.989 for that end nodes of the decision tree for tumor multiclass classification. In hierarchical order of importance, the root node (Cho/NAA) in the decision tree algorithm was primarily based on the proliferative, infiltrative, and neuronal destructive characteristics of the tumor, the internal node (PSRmax), on tumor tissue capillary permeability characteristics, and the end node (Lac/Cr or Cho/Cr), on tumor energy glycolytic (Warburg effect), or on membrane lipid tumor metabolism.

Conclusion

Our study shows potential implementation of machine learning decision tree model algorithms based on a hierarchical, convenient, and personalized use of perfusion and spectroscopy MRI data for multiclass classification of these brain tumors.

Predicting TERT promoter mutation status using 1H-MR spectroscopy and stretched-exponential model of diffusion-weighted imaging in IDH-wildtype diffuse astrocytic glioma without intense enhancement

PURPOSE

Isocitrate dehydrogenase (IDH)-wildtype diffuse astrocytic glioma with telomerase reverse transcriptase (TERT) promoter mutation is defined as glioblastoma by the WHO 2021 criteria, revealing that TERT promotor mutation is highly associated with tumor aggressiveness. The aim of this study was to identify features from MR spectroscopy (MRS) and multi-exponential models of DWI distinguishing wild-type TERT (TERTw) from TERT promoter mutation (TERTm) in IDH-wildtype diffuse astrocytic glioma.

METHODS

Participants comprised 25 adult patients with IDH-wildtype diffuse astrocytic glioma. Participants were classified into TERTw and TERTm groups. Point-resolved spectroscopy sequences were used for MRS data acquisition. DWI was performed with 13 different b-factors. Peak height ratios of NAA/Cr and Cho/Cr were calculated from MRS data. Mean apparent diffusion coefficient (ADC), perfusion fraction (f), diffusion coefficient (D), pseudo-diffusion coefficient (D*), distributed diffusion coefficient (DDC), and heterogeneity index (α) were obtained using multi-exponential models from DWI data. Each parameter was compared between TERTw and TERTm using the Mann-Whitney U test. Correlations between parameters derived from MRS and DWI were also evaluated.

RESULTS

NAA/Cr and Cho/Cr were both higher for TERTw than for TERTm. The α of TERTw was smaller than that of TERTm, while the f of TERTw was higher than that of TERTm. NAA/Cr correlated negatively with α, but not with other DWI parameters. Cho/Cr did not show significant correlations with any DWI parameters.

CONCLUSION

The combination of NAA/Cr and α may have merit in clinical situation to predict the TERT mutation status of IDH-wildtype diffuse astrocytic glioma without intense enhancement.

In vivo brain MR spectroscopy in gliomas: clinical and pre-clinical chances

Purpose

Gliomas, the most common primary brain tumours, have recently been re-classified incorporating molecular aspects with important clinical, prognostic, and predictive implications. Concurrently, the reprogramming of metabolism, altering intracellular and extracellular metabolites affecting gene expression, differentiation, and the tumour microenvironment, is increasingly being studied, and alterations in metabolic pathways are becoming hallmarks of cancer. Magnetic resonance spectroscopy (MRS) is a complementary, non-invasive technique capable of quantifying multiple metabolites. The aim of this review focuses on the methodology and analysis techniques in proton MRS (1H MRS), including a brief look at X-nuclei MRS, and on its perspectives for diagnostic and prognostic biomarkers in gliomas in both clinical practice and preclinical research.

Methods

PubMed literature research was performed cross-linking the following key words: glioma, MRS, brain, in-vivo, human, animal model, clinical, pre-clinical, techniques, sequences, 1H, X-nuclei, Artificial Intelligence (AI), hyperpolarization.

Results

We selected clinical works (n = 51), preclinical studies (n = 35) and AI MRS application papers (n = 15) published within the last two decades. The methodological papers (n = 62) were taken into account since the technique first description.

Conclusions

Given the development of treatments targeting specific cancer metabolic pathways, MRS could play a key role in allowing non-invasive assessment for patient diagnosis and stratification, predicting and monitoring treatment responses and prognosis. The characterization of gliomas through MRS will benefit of a wide synergy among scientists and clinicians of different specialties within the context of new translational competences. Head coils, MRI hardware and post-processing analysis progress, advances in research, experts’ consensus recommendations and specific professionalizing programs will make the technique increasingly trustworthy, responsive, accessible.

The Brain Imaging Collaboration Suite (BrICS): A Cloud Platform for Integrating Whole-Brain Spectroscopic MRI into the Radiation Therapy Planning Workflow

Glioblastoma has poor prognosis with inevitable local recurrence despite aggressive treatment with surgery and chemoradiation. Radiation therapy (RT) is typically guided by contrast-enhanced T1-weighted magnetic resonance imaging (MRI) for defining the high-dose target and T2-weighted fluid-attenuation inversion recovery MRI for defining the moderate-dose target. There is an urgent need for improved imaging methods to better delineate tumors for focal RT. Spectroscopic MRI (sMRI) is a quantitative imaging technique that enables whole-brain analysis of endogenous metabolite levels, such as the ratio of choline-to-N-acetylaspartate. Previous work has shown that choline-to-N-acetylaspartate ratio accurately identifies tissue with high tumor burden beyond what is seen on standard imaging and can predict regions of metabolic abnormality that are at high risk for recurrence. To facilitate efficient clinical implementation of sMRI for RT planning, we developed the Brain Imaging Collaboration Suite (BrICS; https://brainimaging.emory.edu/brics-demo), a cloud platform that integrates sMRI with standard imaging and enables team members from multiple departments and institutions to work together in delineating RT targets. BrICS is being used in a multisite pilot study to assess feasibility and safety of dose-escalated RT based on metabolic abnormalities in patients with glioblastoma (Clinicaltrials.gov NCT03137888). The workflow of analyzing sMRI volumes and preparing RT plans is described. The pipeline achieved rapid turnaround time by enabling team members to perform their delegated tasks independently in BrICS when their clinical schedules allowed. To date, 18 patients have been treated using targets created in BrICS and no severe toxicities have been observed.

Adult Brain Tumors: Clinical Applications of Magnetic Resonance Spectroscopy

Proton magnetic resonance spectroscopy (H-MRS) may be helpful in suggesting tumor histology and tumor grade and may better define tumor extension and the ideal site for biopsy compared with conventional magnetic resonance (MR) imaging. A multifunctional approach with diffusion-weighted imaging, perfusion-weighted imaging, and permeability maps, along with H-MRS, may enhance the accuracy of the diagnosis and characterization of brain tumors and estimation of therapeutic response. Integration of advanced imaging techniques with conventional MR imaging and the clinical history help to improve the accuracy, sensitivity, and specificity in differentiating tumors and nonneoplastic lesions.

Simulating the Effect of Spectroscopic MRI as a Metric for Radiation Therapy Planning in Patients with Glioblastoma

Due to glioblastoma's infiltrative nature, an optimal radiation therapy (RT) plan requires targeting infiltration not identified by anatomical magnetic resonance imaging (MRI). Here, high-resolution, whole-brain spectroscopic MRI (sMRI) is used to describe tumor infiltration alongside anatomical MRI and simulate the degree to which it modifies RT target planning. In 11 patients with glioblastoma, data from preRT sMRI scans were processed to give high-resolution, whole-brain metabolite maps normalized by contralateral white matter. Maps depicting choline to N-Acetylaspartate (Cho/NAA) ratios were registered to contrast-enhanced T1-weighted RT planning MRI for each patient. Volumes depicting metabolic abnormalities (1.5-, 1.75-, and 2.0-fold increases in Cho/NAA ratios) were compared with conventional target volumes and contrast-enhancing tumor at recurrence. sMRI-modified RT plans were generated to evaluate target volume coverage and organ-at-risk dose constraints. Conventional clinical target volumes and Cho/NAA abnormalities identified significantly different regions of microscopic infiltration with substantial Cho/NAA abnormalities falling outside of the conventional 60 Gy isodose line (41.1, 22.2, and 12.7 cm³, respectively). Clinical target volumes using Cho/NAA thresholds exhibited significantly higher coverage of contrast enhancement at recurrence on average (92.4%, 90.5%, and 88.6%, respectively) than conventional plans (82.5%). sMRI-based plans targeting tumor infiltration met planning objectives in all cases with no significant change in target coverage. In 2 cases, the sMRI-modified plan exhibited better coverage of contrast-enhancing tumor at recurrence than the original plan. Integration of the high-resolution, whole-brain sMRI into RT planning is feasible, resulting in RT target volumes that can effectively target tumor infiltration while adhering to conventional constraints.

COMPARISON BETWEEN PROTON MAGNETIC RESONANCE SPECTROSCOPY FINDINGS IN DOGS WITH TICK-BORNE ENCEPHALITIS AND CLINICALLY NORMAL DOGS

In vivo diagnosis of tick-borne encephalitis is difficult due to high seroprevalence and rapid viral clearance, limiting detection of antibodies in blood and cerebrospinal fluid. Magnetic resonance imaging (MRI) characteristics of tick-borne encephalitis have been reported, however MRI studies can also be negative despite the presence of neurologic signs. Magnetic resonance spectroscopy (¹ H MRS) is an imaging method that provides additional information about the metabolic characteristics of brain tissues. The purpose of this retrospective cross-sectional study was to describe brain metabolites using short echo time single-voxel ¹ H MRS in dogs with confirmed tick-borne encephalitis and compare them with healthy dogs. Inclusion criteria for the affected dogs were neurological symptoms suggestive of tick-borne encephalitis, previous endemic stay and tick-bite, diagnostic quality brain MRI and ¹ H MRS studies, and positive antibody titers or confirmation of tick-borne encephalitis with necropsy. Control dogs were 10, clinically normal beagles that had been used in a previous study. A total of six affected dogs met inclusion criteria. All dogs affected with tick-borne encephalitis had ¹ H MRS metabolite concentration alterations versus control dogs. These changes included mild to moderate decreases in N-acetyl aspartate and creatine peaks, and mild increases in glutamate/glutamine peaks. No lactate or lipid signal was detected in any dog. Myoinositol and choline signals did not differ between affected and control dogs. In conclusion, findings supported the use of ¹ H MRS as an adjunctive imaging method for dogs with suspected tick-borne encephalitis and inconclusive conventional MRI findings.

Multiparametric MR Imaging in the Assessment of Brain Tumors

Functional MR imaging methods make possible the quantification of dynamic physiologic processes that occur in the brain. Moreover, the use of these advanced imaging techniques in the setting of oncologic treatment of the brain is widely accepted and has found worldwide routine clinical use.

A systematic pipeline for the objective comparison of whole-brain spectroscopic MRI with histology in biopsy specimens from grade III glioma

The diagnosis, prognosis, and management of patients with gliomas are largely dictated by the pathological analysis of tissue biopsied from a selected region within the lesion. However, the heterogeneous and infiltrative nature of gliomas make it difficult to identify the optimal region for biopsy with conventional magnetic resonance imaging (MRI). This is particularly true for low-grade gliomas, which are often nonenhancing tumors. To improve the management of patients with such tumors, neuro-oncology requires an imaging modality that can specifically identify a tumor's most anaplastic/aggressive region(s) for biopsy targeting. The addition of metabolic mapping using spectroscopic MRI (sMRI) to supplement conventional MRI could improve biopsy targeting and, ultimately, diagnostic accuracy. Here, we describe a pipeline for the integration of state-of-the-art, high-resolution, whole-brain 3-dimensional sMRI maps into a stereotactic neuronavigation system for guiding biopsies in gliomas with nonenhancing components. We also outline a machine-learning method for automated histological analysis that generates normalized, quantitative metrics describing tumor infiltration in immunohistochemically stained tissue specimens. As a proof of concept, we describe the combination of these 2 techniques in a small cohort of patients with grade 3 glioma. With this work, we aim to present a systematic pipeline to stimulate histopathological image validation of advanced MRI techniques, such as sMRI.

Whole-brain spectroscopic MRI biomarkers identify infiltrating margins in glioblastoma patients

BACKGROUND

The standard of care for glioblastoma (GBM) is maximal safe resection followed by radiation therapy with chemotherapy. Currently, contrast-enhanced MRI is used to define primary treatment volumes for surgery and radiation therapy. However, enhancement does not identify the tumor entirely, resulting in limited local control. Proton spectroscopic MRI (sMRI), a method reporting endogenous metabolism, may better define the tumor margin. Here, we develop a whole-brain sMRI pipeline and validate sMRI metrics with quantitative measures of tumor infiltration.

METHODS

Whole-brain sMRI metabolite maps were coregistered with surgical planning MRI and imported into a neuronavigation system to guide tissue sampling in GBM patients receiving 5-aminolevulinic acid fluorescence-guided surgery. Samples were collected from regions with metabolic abnormalities in a biopsy-like fashion before bulk resection. Tissue fluorescence was measured ex vivo using a hand-held spectrometer. Tissue samples were immunostained for Sox2 and analyzed to quantify the density of staining cells using a novel digital pathology image analysis tool. Correlations among sMRI markers, Sox2 density, and ex vivo fluorescence were evaluated.

RESULTS

Spectroscopic MRI biomarkers exhibit significant correlations with Sox2-positive cell density and ex vivo fluorescence. The choline to N-acetylaspartate ratio showed significant associations with each quantitative marker (Pearson's ρ = 0.82, P < .001 and ρ = 0.36, P < .0001, respectively). Clinically, sMRI metabolic abnormalities predated contrast enhancement at sites of tumor recurrence and exhibited an inverse relationship with progression-free survival.

CONCLUSIONS

As it identifies tumor infiltration and regions at high risk for recurrence, sMRI could complement conventional MRI to improve local control in GBM patients.

Imaging of the Posttherapeutic Brain

This review covers important topics relating to the imaging evaluation of glioblastoma multiforme after therapy. An overview of the Macdonald and Response Assessment in Neuro-Oncology criteria as well as important questions and limitations regarding their use are provided. Pseudoprogression and pseudoresponse as well as the use of advanced magnetic resonance imaging techniques such as perfusion, diffusion, and spectroscopy in the evaluation of the posttherapeutic brain are also reviewed.

Multimodality Brain Tumor Imaging: MR Imaging, PET, and PET/MR Imaging

Standard MR imaging and CT are routinely used for anatomic diagnosis in brain tumors. Pretherapy planning and posttreatment response assessments rely heavily on gadolinium-enhanced MR imaging. Advanced MR imaging techniques and PET imaging offer physiologic, metabolic, or functional information about tumor biology that goes beyond the diagnostic yield of standard anatomic imaging. With the advent of combined PET/MR imaging scanners, we are entering an era wherein the relationships among different elements of tumor metabolism can be simultaneously explored through multimodality MR imaging and PET imaging. The purpose of this review is to provide a practical and clinically relevant overview of current anatomic and physiologic imaging of brain tumors as a foundation for further investigations, with a primary focus on MR imaging and PET techniques that have demonstrated utility in the current care of brain tumor patients.

High Resolution Imaging of Viscoelastic Properties of Intracranial Tumours by Multi-Frequency Magnetic Resonance Elastography

PURPOSE

In recent years Magnetic Resonance Elastography (MRE) emerged into a clinically applicable imaging technique. It has been shown that MRE is capable of measuring global changes of the viscoelastic properties of cerebral tissue. The purpose of our study was to evaluate a spatially resolved three-dimensional multi-frequent MRE (3DMMRE) for assessment of the viscoelastic properties of intracranial tumours.

METHODS

A total of 27 patients (63 ± 13 years) were included. All examinations were performed on a 3.0 T scanner, using a modified phase-contrast echo planar imaging sequence. We used 7 vibration frequencies in the low acoustic range with a temporal resolution of 8 dynamics per wave cycle. Post-processing included multi-frequency dual elasto-visco (MDEV) inversion to generate high-resolution maps of the magnitude |G*| and the phase angle φ of the complex valued shear modulus.

RESULTS

The tumour entities included in this study were: glioblastoma (n = 11), anaplastic astrocytoma (n = 3), meningioma (n = 7), cerebral metastasis (n = 5) and intracerebral abscess formation (n = 1). Primary brain tumours and cerebral metastases were not distinguishable in terms of |G*| and φ. Glioblastoma presented the largest range of |G*| values and a trend was delineable that glioblastoma were slightly softer than WHO grade III tumours. In terms of φ, meningiomas were clearly distinguishable from all other entities.

CONCLUSIONS

In this pilot study, while analysing the viscoelastic constants of various intracranial tumour entities with an improved spatial resolution, it was possible to characterize intracranial tumours by their mechanical properties. We were able to clearly delineate meningiomas from intraaxial tumours, while for the latter group an overlap remains in viscoelastic terms.

Error decomposition for parallel imaging reconstruction using modulation-domain representation of undersampled data

This paper presents a quantitative approach to evaluating and optimizing parallel imaging reconstruction for a clinical requirement. By introducing a "modulation domain representation" for undersampled data, the presented approach decomposes parallel imaging reconstruction error into multiple error components that can be grouped into three categories: image fidelity error, residue aliasing artifacts, and amplified noise. It is experimentally found that these error components have different image-space patterns that compromise imaging quality in different fashions. An error function may be defined as the weighted summation of these error components. By choosing a set of weighting coefficients that can quantify desirable image quality, parallel imaging may be optimized for a clinical requirement. It is found that error decomposition model may improve clinical utility of parallel imaging, providing an application-oriented approach to clinical parallel imaging.

Perspectives of 3 T magnetic resonance imaging in radiosurgical treatment planning

The introduction of 3 T magnetic resonance imaging (MRI) scanners for neuro-oncological diagnostics showed a general improvement of image quality, especially in terms of the detection and differentiation of intracranial tumors. Among the advantages of 3 T scanners compared to 1.5 T scanners are the possibility of higher spatial image resolution or shorter investigation times and the availability of functional imaging in sufficient quality. Consequently, the use of 3 T MRI for radiosurgery planning is highly desired. Functional MRI techniques (perfusion-weighted imaging, dynamic contrast-enhanced MRI, MR spectroscopy, diffusion-weighted imaging, and diffusion tensor imaging) available at 3 T scanners provide not only better detection and differentiation but also significantly better delineation of intracranial tumors, which is a crucial feature for successful radiosurgical treatment planning. The use of multimodal morphological and functional MRI methods allows identification of the biologically most active parts of the tumors with consecutive changes in therapy planning. On the other hand, there are increased geometric distortions on MRI scans obtained at 3 T compared to 1.5 T, which makes their use limited for now. However, the newest studies show an acceptable degree of geometric distortion on the 3 T planning images using special imaging protocols, while additional investigations on this issue are needed to find the optimal technical solution.

The effect of paramagnetic contrast in choline peak in patients with glioblastoma multiforme might not be significant

BACKGROUND AND PURPOSE

(1)H-MR spectroscopy is a useful tool in brain tumor evaluation. A critical point in obtaining representative spectra is the correct voxel positioning, which can be more accurate after Gd administration. Some experimental data suggested that Gd could cause Cho signal loss. Our aim was to evaluate the effect of Gd in the Cho peak area and width in patients with GBM.

MATERIALS AND METHODS

We performed multivoxel (1)H-MR spectroscopy before and after Gd administration in 18 patients with GBM. Quantification of Cho peak area and width in each voxel was completed, and the Cho mean and maximum values before and after Gd injection were calculated in the tumor and contralateral hemisphere. Choline peak area and width values obtained before and after contrast were compared, considering as separate entities enhancing and nonenhancing tumoral voxels and the contralateral hemisphere.

RESULTS

No statistically significant differences were found for the Cho peak area mean values in the tumoral voxels or contralaterally (P > .05). A tendency for an increase in the Cho peak width mean value was found in the tumoral enhancing voxels (P = .055). A statistically significant decrease was found for the mean value of the maximum Cho peak area in enhancing tumoral voxels (P = .020). No significant differences were found in the nonenhancing tumoral voxels or contralaterally (P > .05).

CONCLUSIONS

The injection of Gd before performing (1)H-MR spectroscopy might not significantly affect the Cho peak area in patients with GBM. The paramagnetic contrast seems to cause a different effect, depending on Gd enhancement.

MR imaging of neoplastic central nervous system lesions: review and recommendations for current practice

MR imaging is the preferred technique for the diagnosis, treatment planning, and monitoring of patients with neoplastic CNS lesions. Conventional MR imaging, with gadolinium-based contrast enhancement, is increasingly combined with advanced, functional MR imaging techniques to offer morphologic, metabolic, and physiologic information. This article provides updated recommendations to neuroradiologists, neuro-oncologists, neurosurgeons, and radiation oncologists on the practical applications of MR imaging of neoplastic CNS lesions in adults, with particular focus on gliomas, based on a review of the clinical trial evidence and personal experiences shared at a recent international meeting of experts in neuroradiology, neuro-oncology, neurosurgery, and radio-oncology.

Treatment monitoring in gliomas: comparison of dynamic susceptibility-weighted contrast-enhanced and spectroscopic MRI techniques for identifying treatment failure

OBJECTIVE

To evaluate whether dynamic susceptibility-weighted contrast-enhanced (DSC), dynamic contrast-enhanced (DCE), and proton spectroscopic imaging ((1)H-MRSI) can identify progression and predict treatment failure during follow-up before tumor size changes, contrast agent uptake, or when new lesions become obvious. The aim was also to find out which of the aforementioned techniques had the best diagnostic performance compared with each other and standard magnetic resonance imaging (MRI).

MATERIALS AND METHODS

Thirty-seven patients with gliomas (21 women, 16 men; mean age at inclusion, 48 ± 14 years [standard deviation]) were assessed prospectively by (1)H-MRSI (point-resolved spectroscopy), DCE, and DSC perfusion MRI, each after a single dose of gadobenate dimeglumine during follow-up. Histology was available in all cases (resection, N = 18; biopsy, N = 19). All patients with low-grade gliomas (n = 20) did not receive any radio- or chemotherapy after partial resection (n = 7) or biopsy (n = 13), whereas 17 patients with high-grade gliomas had received adjuvant radiotherapy immediately after surgery. Tumor progression (progressive disease, PD) was defined as increase in longest glioma diameter by at least 20% (Response Evaluation Criteria in Solid Tumors), appearance of new lesions, or new contrast-enhancement. DSC, DCE, and MRSI image analyses comprised a detailed semiquantitative region of interest (ROI) analysis of the different parameters. Wilcoxon signed-rank test, Wilcoxon rank sum test, and Cox regression were used for statistical analysis.

RESULTS

The median follow-up time was 607 days. Twenty patients showed PD (54%), 8 of 20 with low-grade (40%) and 12 of 17 with high-grade gliomas (71%). In PD, significant positive differences between log2-transformed ROI ratios at the last measurement in comparison to the first measurement (baseline) could be detected for tumor blood flow (P < 0.006) and volume (P < 0.001) derived from DSC and for maximum choline within tumor tissue (P = 0.0029) and Cho/Cr (P = 0.032) but not choline/N-acetyl-aspartate (P = 0.37) derived from MRSI. In contrast, these parameters were not significantly higher at last measurement in stable disease. Also, the differences between last value and baseline were significantly different between PD and stable disease for tumor blood flow (P < 0.004) and volume (P < 0.002) as well as for maximum choline within tumor tissue (P = 0.0011). The best prognostic parameter for PD at Cox analysis was time-dependent difference to baseline of log2 of relative regional cerebral blood flow normalized on gray matter (hazard ratio, 2.67; 95% confidence interval, 1.25-6.08; P = 0.01), while a prognostic value of MRS parameters could not be demonstrated.

CONCLUSION

DSC perfusion imaging can identify progression and can predict treatment failure during follow-up of gliomas with the best diagnostic performance.

Clinical pitfalls related to short and long echo times in cerebral MR spectroscopy

MR-spectroscopy (MRS) is a multiparameter diagnostic tool and modification of each parameter results in spectrum morphology changes. In particular, changing the echo time (TE) represents a useful tool to highlight different diagnostic elements, but also has significant impact on the spectrum morphology. Diagnostic errors can result if the role of TE is not properly considered. This article reviews the four most common TE-related pitfalls of MRS interpretation. Clinical practical methods to avoid such pitfalls are also suggested.

Imaging of brain tumors: MR spectroscopy and metabolic imaging

The utility of magnetic resonance spectroscopy (MRS) in diagnosis and evaluation of treatment response to human brain tumors has been widely documented. The role of MRS in tumor classification, tumors versus nonneoplastic lesions, prediction of survival, treatment planning, monitoring of therapy, and post-therapy evaluation is discussed. This article delineates the need for standardization and further study in order for MRS to become widely used as a routine clinical tool.

Advanced Contrast-Enhanced MR Imaging of the CNS

One of the most frequent uses of magnetic resonance imaging (MRI) since its introduction has been in the assessment of the CNS for neoplasm. In recent years there has been a substantial improvement in the MR protocol for tumors that includes the use of functional imaging techniques. As shown in multiple experimental and clinical studies an optimized use of high quality contrast media and the introduction of these functional MRI methods has improved the detection and delineation of CNS tumors. This results not only in more confident diagnoses, but also in a substantially improved differential diagnostic process. The article reviews and summarizes the technical advances in functional techniques and their impact on the assessment of cerebral pathologies, namely brain tumors, and gives practical information on how to optimize sequence parameters to achieve the optimal tissue and pathology contrast.

N-Acetyl peak in MR spectra of intracranial metastatic mucinous adenocarcinomas

Absence of N-acetylaspartate (NAA) is one important diagnostic criterion of MR spectroscopy (MRS) that may suggest that an intracranial mass lesion is a metastasis. We report two cases of histopathology-confirmed intracranial metastatic mucinous adenocarcinoma, which predominantly showed a large metabolite peak at 2.0 ppm, mimicking an NAA peak of normal brain tissue. This finding could be of help in the interpretation of MRS in cases of intracranial enhancing mass lesions, metastases or gliomas.

Measurements of diagnostic examination performance using quantitative apparent diffusion coefficient and proton MR spectroscopic imaging in the preoperative evaluation of tumor grade in cerebral gliomas

PURPOSE

Tumor grading is very important both in treatment decision and evaluation of prognosis. While tissue samples are obtained as part of most therapeutic approaches, factors that may result in inaccurate grading due to sampling error (namely, heterogeneity in tissue sampling, as well as tumor-grade heterogeneity within the same tumor specimen), have led to a desire to use imaging better to ascertain tumor grade. The purpose in our study was to evaluate the sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), area under the curve (AUC), and accuracy of diffusion-weighted MR imaging (DWI), proton MR spectroscopic imaging (MRSI) or both in grading primary cerebral gliomas.

MATERIALS AND METHODS

We performed conventional MR imaging (MR), DWI, and MRSI in 74 patients with newly diagnosed brain gliomas: 59 patients had histologically verified high-grade gliomas: 37 glioblastomas multiform (GBM) and 22 anaplastic astrocytomas (AA), and 15 patients had low-grade gliomas. Apparent diffusion coefficient (ADC) values of tumor and peritumoral edema, and ADC ratios (ADC in tumor or peritumoral edema to ADC of contralateral white matter, as well as ADC in tumor to ADC in peritumoral edema) were determined from three regions of interest. The average of the mean, maximum, and minimum for ADC variables was calculated for each patient. The metabolite ratios of Cho/Cr and Cho/NAA at intermediate TE were assessed from spectral maps in the solid portion of tumor, peritumoral edema and contralateral normal-appearing white matter. Tumor grade determined with the two methods was then compared with that from histopathologic grading. Logistic regression and receiver operating characteristic (ROC) curve analysis were performed to determine optimum thresholds for tumor grading. Measures of diagnostic examination performance, such as sensitivity, specificity, PPV, NPV, AUC, and accuracy for identifying high-grade gliomas were also calculated.

RESULTS

Statistical analysis demonstrated a threshold minimum ADC tumor value of 1.07 to provide sensitivity, specificity, PPV, and NPV of 79.7%, 60.0%, 88.7%, and 42.9% respectively, in determining high-grade gliomas. Threshold values of 1.35 and 1.78 for peritumoral Cho/Cr and Cho/NAA metabolite ratios resulted in sensitivity, specificity, PPV, and NPV of 83.3%, 85.1%, 41.7%, 97.6%, and 100%, 57.4%, 23.1% and 100% respectively for determining high-grade gliomas. Significant differences were noted in the ADC tumor values and ratios, peritumoral Cho/Cr and Cho/NAA metabolite ratios, and tumoral Cho/NAA ratio between low- and high-grade gliomas. The combination of mean ADC tumor value, maximum ADC tumor ratio, peritumoral Cho/Cr and Cho/NAA metabolite ratios resulted in sensitivity, specificity, PPV, and NPV of 91.5%, 100%, 100% and 60% respectively.

CONCLUSION

Combining DWI and MRSI increases the accuracy of preoperative imaging in the determination of glioma grade. MRSI had superior diagnostic performance in predicting glioma grade compared with DWI alone. The predictive values are helpful in the clinical decision-making process to evaluate the histologic grade of tumors, and provide a means of guiding treatment.

Advanced imaging techniques in brain tumors

Perfusion, permeability and magnetic resonance spectroscopy (MRS) are now widely used in the research and clinical settings. In the clinical setting, qualitative, semi-quantitative and quantitative approaches such as review of color-coded maps to region of interest analysis and analysis of signal intensity curves are being applied in practice. There are several pitfalls with all of these approaches. Some of these shortcomings are reviewed, such as the relative low sensitivity of metabolite ratios from MRS and the effect of leakage on the appearance of color-coded maps from dynamic susceptibility contrast (DSC) magnetic resonance (MR) perfusion imaging and what correction and normalization methods can be applied. Combining and applying these different imaging techniques in a multi-parametric algorithmic fashion in the clinical setting can be shown to increase diagnostic specificity and confidence.

Surgical anatomy and functional connectivity of the limbic system

OBJECT

The goal in this study was to highlight the potential of currently available imaging techniques for surgical planning of procedures in and around the limbic system.

METHODS

The authors review traditional and newer imaging techniques as applied to neurosurgical planning. Today MR imaging techniques play a preponderant role. The various applications of functional techniques such as diffusion weighted, diffusion tensor, perfusion, and functional MR imaging methods are discussed.

RESULTS

In addition to the high-resolution studies of anatomy that can be acquired, especially at higher field strengths (>or= 3 T), MR imaging now also offers the possibility of acquiring functional, metabolic, hemodynamic, and molecular information on normal and pathological brain processes.

CONCLUSIONS

The knowledge obtained using the various imaging techniques contributes substantially to understanding the disease processes in a way that drastically improves surgical planning.

Quantitative imaging biomarkers in neuro-oncology

Conventional structural imaging provides limited information on tumor characterization and prognosis. Advances in neurosurgical techniques, radiotherapy planning and novel drug treatments for brain tumors have generated increasing need for reproducible, noninvasive, quantitative imaging biomarkers. This Review considers the role of physiological MRI and PET molecular imaging in understanding metabolic processes associated with tumor growth, blood flow and ultrastructure. We address the utility of various techniques in distinguishing between tumors and non-neoplastic processes, in tumor grading, in defining anatomical relationships between tumor and eloquent brain regions and in determining the biological substrates of treatment response. Much of the evidence is derived from limited case series in individual centers. Despite their 'added value', the effect of these techniques as an adjunct to structural imaging in clinical research and practice remains limited.

MRI for identification of progression in brain tumors: from morphology to function

For monitoring of brain tumors, it is crucial to identify progression or treatment failure early during follow-up to change treatment schemes and, thereby, optimize patient outcome. In the past years, several areas within the field of magnetic resonance (MR) have seen considerable advances: modern contrast media, advanced morphologic approaches and several functional techniques, for example, in the visualization of tumor perfusion or tumor cell metabolism. This review presents these recent advances by introducing the different techniques and outlining their benefit for identification of progression in brain tumors, with a focus on gliomas, metastases and meningiomas. After radiotherapy, MR spectroscopy helps to more accurately discriminate between radiation necrosis and glioma progression. In low-grade gliomas, perfusion MR techniques enable a more sensitive detection of anaplastic transformation than conventional MRI. Modern contrast media, as well as diffusion tensor imaging, allow for an improved tumor delineation and assessment of tumor extension. We will also highlight the biological background of these techniques, their applicability and current limitations. In conclusion, modern MRI techniques have been developed that are on the doorstep to be integrated in clinical routine.

Low Grade Gliomas. Can We Predict Tumour Behaviour from Imaging Features?

Low grade gliomas (WHO grade II) are diffuse, infiltrative glial tumours of the brain. The low grade glioma group includes a number of entities, namely diffuse astrocytoma, oligodendroglioma and oligoastrocytoma. This group of the low-grade gliomas share certain common issues of behaviour, clinical assessment and management. Even though these tumours are termed low grade they are not to be considered “benign”: untreated they are invariably fatal. They may remain “stable” for many years and hence a “watch and wait” treatment policy is often adopted. Unfortunately some tumours progress more rapidly than others with dedifferentiation into high grade tumours which become rapidly fatal. Based on standard imaging criteria it has been difficult to predict which of these low grade gliomas will progress more rapidly. Treatment decisions would benefit from some prediction as to which tumours are likely to progress more rapidly than others. This review will discuss some of the imaging features that may help to predict which low grade gliomas will progress more rapidly than others. Such imaging features include the rate of growth on serial imaging; the morphological features that parallel genetic markers; the assessment and change of tumour vascular status as assessed by MR perfusion imaging and tumour characteristics on PET and MR spectroscopy.

Neurosurgical implications of mannitol accumulation within a meningioma and its peritumoral region demonstrated by magnetic resonance spectroscopy: case report

Mannitol is widely considered the hyperosmolar therapy of choice in routine neurosurgical practice for the reduction of intracranial pressure (ICP). The authors present a unique case of a patient with a large meningioma treated with mannitol, in which mannitol accumulation within the tumor and its surrounding parenchyma was shown using in vivo magnetic resonance spectroscopy (MRS). This rare appearance of mannitol on MRS was characterized by a wide-based peak at 3.8 ppm, which remained detectable several hours after the last dose. These findings provide the first in vivo evidence in support of the prevailing theory that mannitol leakage into the peritumoral edematous region may contribute to rebound increases in ICP and suggest that this phenomenon has the potential to occur in extraaxial tumors. Judicious use of mannitol in the setting of elevated ICP due to tumor may be indicated to avoid potentially deleterious side effects caused by its accumulation.

Central nervous system lymphoma characterization by diffusion-weighted imaging and MR spectroscopy

PURPOSE

The characterization and differentiation of central nervous system (CNS) lymphoma has important diagnostic, therapeutic, and prognostic significance. The purpose of this study is to characterize the diffusion-weighted imaging (DWI) and MR spectroscopic (MRS) findings in CNS lymphoma.

MATERIALS AND METHODS

Twenty consecutive patients (male [n= 12], female [n= 8]) with histopathologically proven CNS lymphoma were retrospectively evaluated during this study from July 2005 to April 2007. Patients included immunocompromised (n= 9) and immunocompetent (n= 11) individuals. MR Imaging (pretreatment n= 13), pre- and post-treatment (n= 7) included DWI (n= 20) (b = 1000s/mm2) and ADC (apparent diffusion coefficient) maps of all patients. MRS was performed (n= 10) with PRESS (point-resolved spectroscopy) sequence (multivoxel n= 8, single voxel n= 2) with a TE of 144 msec. All patients were histopathologically confirmed to have lymphoma by biopsy.

RESULTS

Areas of restricted diffusion were observed in 90 % (n= 18/20) on pretreatment scans. The diffusion restriction was variable on post-treatment scans. Median metabolite ratios in 10 patients were Cho/Cr- 2.12, NAA/Cho - .49, and NAA/Cr - 1.64. Presence of lactate or lipid was noted in 90 % (n= 9/10). Sites of lesion location were subcortical white matter (n= 6), basal ganglia (n= 4), corpus callosum (n= 3), extra-axial space including cavernous sinus (n= 5), cerebellum (n= 1), and lateral ventricle (n= 1).

CONCLUSION

Restricted diffusion is a consistent imaging finding in CNS lymphoma in immunocompetent patients. Spectroscopy is helpful in initial imaging diagnosis and post-treatment surveillance. These lesions are usually paraventricular in location. MR imaging appearances differ among immunocompetent and immunosuppressed individuals in most cases.

The use of magnetic resonance imaging to noninvasively detect genetic signatures in oligodendroglioma

BACKGROUND

Some patients with low-grade glioma have extraordinarily long survival times; current, early treatment does not prolong their lives. For this reason, therapies that sometimes have neurologic side effects are often deferred intentionally.

METHODS

In a study of oligodendrogliomas, we used a quantitative method of MR analysis based on the S-transform to investigate whether codeletion of chromosomes 1p and 19q, a marker of good prognosis, could be predicted accurately by measuring image texture.

RESULTS

Differences in texture were seen between tumors with codeletion of chromosomes 1p and 19q and those with intact 1p and 19q alleles on contrast-enhanced T1-weighted and T2-weighted MR images. Quantitative MR texture on T2 images predicted codeletion of chromosomes 1p and 19q with high sensitivity and specificity.

CONCLUSIONS

This new method of MR image interpretation may have the potential to augment the diagnostic assessment of patients with suspected low-grade glioma.

MR-Spektroskopie bei Hirntumoren

MRT allows the anatomical visualization of intracerebral space-occupying lesions, and when magnetic resonance spectroscopy (MRS) is used in routine clinical practice it can give more information and be helpful in the diagnosis of such lesions. In MRS with long echo times for nerve tissue there are five metabolites that are particularly significant: N-acetyl aspartate (NAA), creatine, choline, lactate, and lipids. NAA levels are lowered in the presence of intracerebral tumors. Creatine is lowered in situations of hypermetabolic metabolism and elevated in hypometabolic conditions, but remains constant in many pathologic states and can be used as a reliable reference value. With malignant tumors there are usually elevated choline concentrations, reflecting increased membrane synthesis and a higher cell turnover. The lactate level rises following a switch in metabolism from aerobic to anaerobic glycolysis, and this is frequently observed in the presence of malignant tumors. The occurrence of lipid peaks in a tumor spectrum suggests the presence of tissue necroses or metastases. There are typical constellations that are seen on MRS for individual tumors, which are discussed in detail in the present paper.

Evaluation of intraaxial enhancing brain tumors on magnetic resonance imaging: intraindividual crossover comparison of gadobenate dimeglumine and gadopentetate dimeglumine for visualization and assessment, and implications for surgical intervention

Object

The goal in this article was to compare 0.1 mmol/kg doses of gadobenate dimeglumine (Gd-BOPTA) and gadopentetate dimeglumine, also known as gadolinium diethylenetriamine pentaacetic acid (Gd-DTPA), for enhanced magnetic resonance (MR) imaging of intraaxial brain tumors.

Methods

Eighty-four patients with either intraaxial glioma (47 patients) or metastasis (37 patients) underwent two MR imaging examinations at 1.5 tesla, one with Gd-BOPTA as the contrast agent and the other with Gd-DTPA. The interval between fully randomized contrast medium administrations was 2 to 7 days. The T1-weighted spin echo and T2-weighted fast spin echo images were acquired before administration of contrast agents and T1-weighted spin echo images were obtained after the agents were administered. Acquisition parameters and postinjection acquisition times were identical for the two examinations in each patient. Three experienced readers working in a fully blinded fashion independently evaluated all images for degree and quality of available information (lesion contrast enhancement, lesion border delineation, definition of disease extent, visualization of the lesion's internal structures, global diagnostic preference) and quantitative enhancement (that is, the extent of lesion enhancement after contrast agent administration compared with that seen before its administration [hereafter referred to as percent enhancement], lesion/brain ratio, and contrast/noise ratio). Differences were tested with the Wilcoxon signed-rank test. Reader agreement was assessed using kappa statistics.

Significantly better diagnostic information/imaging performance (p < 0.0001, all readers) was obtained with Gd-BOPTA for all visualization end points. Global preference for images obtained with Gd-BOPTA was expressed for 42 (50%), 52 (61.9%), and 56 (66.7%) of 84 patients (readers 1, 2, and 3, respectively) compared with images obtained with Gd-DTPA contrast in four (4.8%), six (7.1%), and three (3.6%) of 84 patients. Similar differences were noted for all other visualization end points. Significantly greater quantitative contrast enhancement (p < 0.04) was noted after administration of Gd-BOPTA. Reader agreement was good (κ > 0.4).

Conclusions

Lesion visualization, delineation, definition, and contrast enhancement are significantly better after administration of 0.1 mmol/kg Gd-BOPTA, potentially allowing better surgical planning and follow up and improved disease management.

Contrast-enhanced magnetic resonance imaging of central nervous system tumors: agents, mechanisms, and applications

Brain tumors are one of the most common neoplasms in young adults and are associated with a high mortality and disability rate. Magnetic resonance imaging (MRI) is widely accepted to be the most sensitive imaging modality in the assessment of cerebral neoplasms. Because the detection, characterization, and exact delineation of brain tumors require a high lesion contrast that depends on the signal of the lesion in relation to the surrounding tissue, contrast media is given routinely. Anatomical and functional, contrast agent-based MRI techniques allow for a better differential diagnosis, grading, and especially therapy decision, planing, and follow-up. In this article, the basics of contrast enhancement of brain tumors will be reviewed. The underlying pathology of a disrupted blood-brain barrier and drug influences will be discussed. An overview of the currently available contrast media and the influences of dosage, field strength, and application on the tumor tissue contrast will be given. Challenging, contrast-enhanced, functional imaging techniques, such as perfusion MRI and dynamic contrast-enhanced MRI, are presented both from the technical side and the clinical experience in the assessment of brain tumors. The advantages over conventional, anatomical MRI techniques will be discussed as well as possible pitfalls and drawbacks.

Development of a cone-shape phantom for multi-voxel MR spectroscopy

The purpose of this study was to develop a cone-shape phantom for multi-voxel magnetic resonance spectroscopy (MRS) and to evaluate MR spectra using the cone-shape phantom we developed in this study. A cone-shape MRS phantom was developed with a combination of cone-shape vials. The cylindrical main body was made of acrylic resin and the cone-shape vials were fabricated from poly-ethylene cones. Each cone of the phantom was filled with various metabolite materials. 1.5T GE and 3T Philips systems were used for the single voxel spectroscopy (SVS) as well as for the multi-voxel spectroscopy (MVS). Identification and quantification of the metabolite materials in the cone-shape phantom were done by the SAGE post-program. The MR images and spectra of the cone-shape phantom were obtained from the assigned slice position. The high order shimming control provided enhanced resolution in the SVS and MVS. The area and amplitude were proportional to the metabolite volume in the voxel. The present study demonstrated that the cone-shape phantom was useful for the metabolite quantification. Thus, we propose that the cone-shape phantom can be used for the evaluation of quality control of the MR spectra obtained from SVS and MVS.

Perfusion MR imaging and proton MR spectroscopic imaging in differentiating necrotizing cerebritis from glioblastoma multiforme

We describe a lesion with the magnetic resonance imaging (MRI) characteristics of a glioblastoma mutiforme and demonstrate how perfusion MRI and proton MR spectroscopic imaging can be used to differentiate necrotizing cerebritis from what appeared to be a high-grade glioma. A 43-year-old woman presented to her physician complaining of progressive visual disturbance and headache for several weeks. Conventional MRI demonstrated a parietal peripherally enhancing mass with central necrosis and moderate to severe surrounding T2 hyperintensity, suggesting an infiltrating high-grade glioma. However, advanced imaging, including dynamic susceptibility contrast MRI (DSC MRI) and magnetic resonance spectroscopic imaging (MRSI), suggested a nonneoplastic lesion. The DSC MRI data demonstrated no hyperperfusion within the lesion and surrounding T2 signal abnormality, and the MRSI data showed overall decrease in metabolites in this region, except for lactate. Because of the aggressive appearance to the lesion and the patients' worsening symptoms, a biopsy was performed. The pathologic diagnosis was necrotizing cerebritis. After the commencement of steroid therapy, imaging findings and patient symptoms improved. This report will review the utility of advanced imaging for differentiating inflammatory from neoplastic appearing lesions on conventional imaging.

Natural linewidth chemical shift imaging (NL-CSI)

The discrete Fourier transform (FT) is a conventional method for spatial reconstruction of chemical shifting imaging (CSI) data. Due to point spread function (PSF) effects, FT reconstruction leads to intervoxel signal leakage (Gibbs ringing). Spectral localization by imaging (SLIM) reconstruction was previously proposed to overcome this intervoxel signal contamination. However, the existence of magnetic field inhomogeneities creates an additional source of intervoxel signal leakage. It is demonstrated herein that even small field inhomogeneities substantially amplify intervoxel signal leakage in both FT and SLIM reconstruction approaches. A new CSI data acquisition strategy and reconstruction algorithm (natural linewidth (NL) CSI) is presented that eliminates effects of magnetic field inhomogeneity-induced intervoxel signal leakage and intravoxel phase dispersion on acquired data. The approach is based on acquired CSI data, high-resolution images, and magnetic field maps. The data are reconstructed based on the imaged object structure (as in the SLIM approach) and a reconstruction matrix that takes into account the inhomogeneous field distribution inside anatomically homogeneous compartments. Phantom and in vivo results show that the new method allows field inhomogeneity effects from the acquired MR signal to be removed so that the signal decay is determined only by the "natural" R2 relaxation rate constant (hence the term "natural linewidth" CSI).

MR-Perfusions- und spektroskopische Bildgebung bei WHO-Grad-II-Astrozytomen

BACKGROUND

This study evaluates whether MR perfusion imaging and spectroscopic imaging (MRSI) can depict anaplastic areas in WHO grade II astrocytomas, whether these areas are co-localized, and whether the prognosis can be better predicted.

MATERIAL AND METHODS

Fifteen patients (nine female, six male, aged 42+/-14 years) with WHO grade II astrocytomas but without preceding radio- or chemotherapy were examined every 3 months with MR perfusion imaging and MRSI (mean follow-up 18 months). Using a region of interest analysis, the regional relative cerebral blood volume (rrCBV) and blood flow (rrCBF) were measured in tumor tissue. In the same areas, choline/creatine (Cho/Cr) and choline/N-acetyl-aspartate (Cho/NAA) ratios were quantified.

RESULTS

During follow-up, nine patients had stable disease. In six patients, the tumor showed progression and contrast-enhancement. The progressing tumors had already had higher perfusion (rrCBF 2.1+/-1.4; rrCBV 1.9+/-1.1) parameters than the stable astrocytomas (rrCBF 1.2+/-0.6, p=0.01; rrCBV 1.4+/-0.8, p=0.05) at first examination. However, the Cho/NAA and Cho/Cr ratios only tended to be higher than in stable astrocytomas (Cho/NAA 2.4+/-1.0 vs. 2.0+/-1.5, p=0.23; Cho/Cr 1.7+/-0.6 vs. 1.4+/-0.5, p=0.06). In all six progressing tumors, areas of maximum perfusion and maximum Cho/NAA and Cho/Cr ratio were co-localized. During follow-up, contrast-enhancement was observed in these areas.

CONCLUSIONS

MR perfusion imaging can depict anaplastic areas in WHO grade II astrocytomas earlier than conventional MRI and thus enables a better prediction of prognosis.