Proton MR spectroscopy improves discrimination between tumor and pseudotumoral lesion in solid brain masses

Diagnostic algorithm for glioma grading using dynamic susceptibility contrast‑enhanced magnetic resonance perfusion and proton magnetic resonance spectroscopy

The present retrospective study aimed to investigate the diagnostic capacity of and design a diagnostic algorithm for dynamic susceptibility contrast-enhanced MRI (DSCE-MRI) and proton magnetic resonance spectroscopy (1H-MRS) in grading low-grade glioma (LGG) and high-grade glioma (HGG). This retrospective study enrolled 57 patients, of which 14 had LGG and 43 had HGG, five had World Health Organization grade 1, nine had grade 2, 20 had grade 3 and 23 had grade 4 glioma. All subjects underwent a standard 3T MRI brain tumor protocol with conventional MRI (cMRI) and advanced techniques, including DSCE-MRI and 1H-MRS. The associations of grade categorization with parameters in tumor and peritumor regions in the DSCE-MRI were examined, including tumor relative cerebral blood volume (TrCBV) and peripheral relative (Pr)CBV, as well as Tr and Pr cerebral blood flow (CBF) and 1H-MRS, including the creatine (Cr) and N-acetyl aspartate (NAA) ratios of choline (Cho), i.e. the TCho/NAA, PCho/NAA, TCho/Cr and PCho/Cr metabolite ratios. The data were compared using the Mann-Whitney U-test, independent samples t-test, Chi-square test, Fisher's exact test and receiver operating characteristic curve analyses. Decision tree analysis established an algorithm based on cutoffs for specified significant parameters. The PrCBF had the highest performance in the preoperative prediction of histological glioma grading, followed by the TrCBV, PrCBF, TrCBV, PCho/NAA, PCho/Cr, TCho/NAA and TCho/Cr. An algorithm based on TrCBV, PrCBF and TCho/Cr had a diagnostic accuracy of 100% for LGG and 90.7% for HGG and a misclassification risk of 7%. The cutoffs (sensitivity and specificity) were 2.48 (86 and 100%) for TrCBV, 1.26 (83.7 and 100%) for PrCBF and 3.18 (69.8 and 78.6%) for TCho/Cr. In conclusion, the diagnostic algorithm using TrCBV, PrCBF and TCho/Cr values, which were obtained from DSCE-MRI and 1H-MRS, increased diagnostic accuracy to 100% for LGGs and 90.7% for HGGs compared to previous studies using conventional MRI. This non-invasive advanced MRI diagnostic algorithm is recommended for clinical application for constructing preoperative strategies and prognosis of patients with glioma.

Diagnostic Accuracy of MR Spectroscopic Imaging and 18F-FET PET for Identifying Glioma: A Biopsy-Controlled Hybrid PET/MRI Study

Contrast-enhanced MRI is the method of choice for brain tumor diagnostics, despite its low specificity for tumor tissue. This study compared the contribution of MR spectroscopic imaging (MRSI) and amino acid PET to improve the detection of tumor tissue. Methods: In 30 untreated patients with suspected glioma, O-(2-[18F]fluoroethyl)-l-tyrosine (18F-FET) PET; 3-T MRSI with a short echo time; and fluid-attenuated inversion recovery, T2-weighted, and contrast-enhanced T1-weighted MRI were performed for stereotactic biopsy planning. Serial samples were taken along the needle trajectory, and their masks were projected to the preoperative imaging data. Each sample was individually evaluated neuropathologically. 18F-FET uptake and the MRSI signals choline (Cho), N-acetyl-aspartate (NAA), creatine, myoinositol, and derived ratios were evaluated for each sample and classified using logistic regression. The diagnostic accuracy was evaluated by receiver operating characteristic analysis. Results: On the basis of the neuropathologic evaluation of tissue from 88 stereotactic biopsies, supplemented with 18F-FET PET and MRSI metrics from 20 areas on the healthy-appearing contralateral hemisphere to balance the glioma/nonglioma groups, 18F-FET PET identified glioma with the highest accuracy (area under the receiver operating characteristic curve, 0.89; 95% CI, 0.81-0.93; threshold, 1.4 × background uptake). Among the MR spectroscopic metabolites, Cho/NAA normalized to normal brain tissue showed the highest diagnostic accuracy (area under the receiver operating characteristic curve, 0.81; 95% CI, 0.71-0.88; threshold, 2.2). The combination of 18F-FET PET and normalized Cho/NAA did not improve the diagnostic performance. Conclusion: MRI-based delineation of gliomas should preferably be supplemented by 18F-FET PET.

Accuracy of Proton Magnetic Resonance Spectroscopy in Distinguishing Neoplastic From Non-neoplastic Brain Lesions

OBJECTIVE

To evaluate the advantage of a combination of magnetic resonance spectroscopy (MRS) and magnetic resonance imaging (MRI) over MRI in the diagnosis of intracranial mass lesions to differentiate between neoplastic and non-neoplastic lesions and compare them with histopathology and clinical data as gold standard.

METHODOLOGY

This was a descriptive cross-sectional study conducted at the Department of Radiology, Apollo Hospital located in Jubilee Hills, Hyderabad. In the present study, a total of 60 patients of all ages with brain masses found through MRI with positive clinical symptoms, regardless of gender, were included. We also involved patients with non-brain cancers suspected of spreading to the brain.

RESULT

MRI identified 63% of lesions as neoplastic and 37% as non-neoplastic. Combining MRI and MRS increased accuracy, with 65% of the lesions diagnosed as neoplastic and 35% as non-neoplastic, demonstrating that MRS significantly enhances diagnostic precision compared to MRI alone.

CONCLUSION

 This study aimed to see how combining MRI and MRS helps diagnose brain masses, comparing with histopathology as the gold standard. MRI alone identified 63% as neoplastic, but MRI with MRS improved accuracy (65%). MRI sensitivity was 87.80%, but combined with MRS, it increased to 92.68%. Thus, the study concluded that the combination of MRI and MRS is more accurate than MRI alone.

Is pre-radiotherapy metabolic heterogeneity of glioblastoma predictive of progression-free survival?

BACKGROUND AND PURPOSE

All glioblastoma subtypes share the hallmark of aggressive invasion, meaning that it is crucial to identify their different components if we are to ensure effective treatment and improve survival. Proton MR spectroscopic imaging (MRSI) is a noninvasive technique that yields metabolic information and is able to identify pathological tissue with high accuracy. The aim of the present study was to identify clusters of metabolic heterogeneity, using a large MRSI dataset, and determine which of these clusters are predictive of progression-free survival (PFS).

MATERIALS AND METHODS

MRSI data of 180 patients acquired in a pre-radiotherapy examination were included in the prospective SPECTRO-GLIO trial. Eight features were extracted for each spectrum: Cho/NAA, NAA/Cr, Cho/Cr, Lac/NAA, and the ratio of each metabolite to the sum of all the metabolites. Clustering of data was performed using a mini-batch k-means algorithm. The Cox model and logrank test were used for PFS analysis.

RESULTS

Five clusters were identified as sharing similar metabolic information and being predictive of PFS. Two clusters revealed metabolic abnormalities. PFS was lower when Cluster 2 was the dominant cluster in patients' MRSI data. Among the metabolites, lactate (present in this cluster and in Cluster 5) was the most statistically significant predictor of poor outcome.

CONCLUSION

Results showed that pre-radiotherapy MRSI can be used to reveal tumor heterogeneity. Groups of spectra, which have the same metabolic information, reflect the different tissue components representative of tumor burden proliferation and hypoxia. Clusters with metabolic abnormalities and high lactate are predictive of PFS.

[A case of multiple sclerosis with a tumefactive lesion during long-term treatment with fingolimod, leading to decompressive craniotomy]

We report a 57-year-old man with multiple sclerosis since his 30s who was treated with fingolimod for 9 years. He developed left hemiparesis and consciousness disturbance. Brain MRI revealed a mass lesion in the right frontal lobe with gadolinium enhancement. Cerebrospinal fluid examination showed no pleocytosis. The lesion continued to expand after admission, and on the 9th day after admission, decompressive craniectomy and brain biopsy were performed. Brain pathology revealed demyelination in the lesion, leading to the diagnosis of a tumefactive demyelinating lesion. Corticosteroid therapy ameliorated the brain lesion, and we inducted natalizumab. Tumefactive demyelinating lesions requiring decompressive craniotomy are rare, and we report this case for the further accumulation of similar cases.

Imaging characterization of an adult H3 K27M-altered diffuse midline glioma of the medulla oblongata with a confounding steroid response

We report an uncommon, infratentorial localization of adult H3 K27M-altered diffuse midline glioma arising in a particularly rare site (medulla oblongata). In addition to this unusual presentation, the lesion exhibited a substantial contrast enhancement and size decrease after dexamethasone, generating diagnostic dilemmas. Histology, molecular details, advanced Magnetic Resonance imaging features and differential diagnoses are here described and discussed, as well as common misconceptions about steroid-sensitive mass lesions, and practical difficulties for clinicians involved in the process of making diagnosis.

Role of MRSI Major Metabolite Ratios in Differentiating Between Intracerebral Ring-Enhancing Neoplastic and Non-Neoplastic Lesions, High-Grade Gliomas and Metastases, and High-Grade and Low-Grade Gliomas

Introduction The purpose of this study was to determine whether multi-voxel magnetic resonance spectroscopic imaging (MRSI) can differentiate between intracranial neoplastic and non-neoplastic and between neoplastic ring-enhancing lesions (RELs) based on differences in major metabolite ratios in their enhancing and peri-enhancing regions. Methods In a prospective observational study involving patients with an intracerebral RELs, MRSI using the two-dimensional multi-voxel point-resolved spectroscopy (PRESS) chemical-shift imaging (CSI) sequence at an echo time (TE) of 135 milliseconds (ms) was performed on a total of 38 patients. Of 38 lesions, 23 (60.5%) were neoplastic and 15 (39.5%) were non-neoplastic. Of the 23 neoplastic lesions, 12 were high-grade gliomas (HGGs), seven were metastases, and four were low-grade gliomas (LGGs). Major metabolite ratios, i.e., choline-to-N-acetylaspartate (Cho/NAA), choline-to-creatine (Cho/Cr), and N-acetylaspartate-to-creatine (NAA/Cr), were calculated in the enhancing and peri-enhancing regions of the RELs. A Mann-Whitney U test was run to determine differences in metabolite ratios at different voxel locations between neoplastic versus non-neoplastic lesions, HGGs versus metastatic lesions, and HGGs versus LGGs. A receiver operating characteristic (ROC) curve analysis was performed to derive cut-off values for Cho/NAA and NAA/Cr ratios in the enhancing and peri-enhancing portions of the lesions. Results The sensitivity, specificity, positive predictive value, and negative predictive value for categorizing an REL in either neoplastic or non-neoplastic lesions using MRSI with magnetic resonance imaging (MRI) were 91.3%, 73.3%, 84%, and 84.6%, respectively. There was a statistically significant difference between Cho/NAA (p = 0.006) and NAA/Cr (p = 0.021) ratios in the enhancing region of 23 neoplastic and 15 non-neoplastic lesions. In the voxel placed in the peri-enhancing portions, the differences between Cho/Cr ratios were just significant (p = 0.047). A cut-off score of Cho/NAA >1.67 in the enhancing regions gave a sensitivity of 82.6% and specificity of 60%. The cut-off score for NAA/Cr of <0.80 in the enhancing regions showed a sensitivity and specificity of 60.9% and 86.7%, respectively. Of the 23 neoplastic lesions, 12 HGGs and seven metastases were differentiated using the Cho/NAA ratio in the peri-enhancing region with a cut-off value of 1.21, sensitivity of 100%, and specificity of 85%. A cut-off value of Cho/Cr ≥1.45 in the peri-enhancing regions showed a sensitivity of 83% and a specificity of 71.4%. For discriminating between 12 HGGs and four LGGs both from the 23 neoplastic REL group, using the cut-off score for Cho/NAA in the enhancing portions ≥4.16 showed a sensitivity of 0.75 and specificity of 100%. In the peri-enhancing regions, a cut-off score of ≥2.07 provided a sensitivity and specificity of 83% and 100%, respectively. Conclusion Conventional MRI sometimes poses a diagnostic challenge in distinguishing between neoplastic and non-neoplastic lesions and other neoplastic RELs. Interpreting MRSI findings by comparing the major metabolite ratios in the enhancing and peri-enhancing regions of these lesions may enable distinction between the two.

High Myoinositol on Proton MR Spectroscopy Could Be a Potential Signature of Papillary Tumors of the Pineal Region-Case Report of Two Patients

Papillary tumor of the pineal region (PTPR) is an uncommon entity in which a presurgical suspicion may be crucial for patient management. Maximal safe neurosurgical resection is of choice when PTPR is suspected, whereas non-surgical approaches can be considered in other tumors of the pineal region, such as pineocytoma or concrete subtypes of germ-cell tumors. In general terms, imaging features of tumors of the pineal region have been reported to be unspecific. Nevertheless, in this report, we describe two pathology-confirmed PTPRs in which presurgical proton MR spectroscopy demonstrated extremely high myoinositol, a pattern which drastically differs from that of other pineal tumors. We hypothesize that this high myoinositol may be related to PTPR’s known ependymal component, and that it could be used as a specific non-invasive diagnostic signature.

Emerging methods for prostate cancer imaging: evaluating cancer structure and metabolic alterations more clearly

Imaging plays a fundamental role in all aspects of the cancer management pathway. However, conventional imaging techniques are largely reliant on morphological and size descriptors that have well-known limitations, particularly when considering targeted-therapy response monitoring. Thus, new imaging methods have been developed to characterise cancer and are now routinely implemented, such as diffusion-weighted imaging, dynamic contrast enhancement, positron emission technology (PET) and magnetic resonance spectroscopy. However, despite the improvement these techniques have enabled, limitations still remain. Novel imaging methods are now emerging, intent on further interrogating cancers. These techniques are at different stages of maturity along the biomarker pathway and aim to further evaluate the cancer microstructure (vascular, extracellular and restricted diffusion for cytometry in tumours) magnetic resonance imaging (MRI), luminal water fraction imaging] as well as the metabolic alterations associated with cancers (novel PET tracers, hyperpolarised MRI). Finally, the use of machine learning has shown powerful potential applications. By using prostate cancer as an exemplar, this Review aims to showcase these potentially potent imaging techniques and what stage we are at in their application to conventional clinical practice.

Mapping of Metabolic Heterogeneity of Glioma Using MR-Spectroscopy

Simple Summary

Radiomics is a research field that integrates radiological and genetic information, but the application of the techniques that have been developed to this purpose have not been widely established in daily clinical practice. The purpose of our study is the development of a straightforward tool that can easily be used to preoperatively predict and correlate the metabolic signature of different CNS-lesions. Particularly in gliomas, we hope to integrate the molecular profile of these tumors into our prediction model. Our goal is to deliver an open-software tool with the intention of advancing the diagnostic work-up of gliomas to the latest standards.

Abstract

Proton magnetic resonance spectroscopy (¹H-MRS) delivers information about the non-invasive metabolic landscape of brain pathologies. ¹H-MRS is used in clinical setting in addition to MRI for diagnostic, prognostic and treatment response assessments, but the use of this radiological tool is not entirely widespread. The importance of developing automated analysis tools for ¹H-MRS lies in the possibility of a straightforward application and simplified interpretation of metabolic and genetic data that allow for incorporation into the daily practice of a broad audience. Here, we report a prospective clinical imaging trial (DRKS00019855) which aimed to develop a novel MR-spectroscopy-based algorithm for in-depth characterization of brain lesions and prediction of molecular traits. Dimensional reduction of metabolic profiles demonstrated distinct patterns throughout pathologies. We combined a deep autoencoder and multi-layer linear discriminant models for voxel-wise prediction of the molecular profile based on MRS imaging. Molecular subtypes were predicted by an overall accuracy of 91.2% using a classifier score. Our study indicates a first step into combining the metabolic and molecular traits of lesions for advancing the pre-operative diagnostic workup of brain tumors and improve personalized tumor treatment.

Differentiation of multiple sclerosis lesions and low-grade brain tumors on MRS data: machine learning approaches

Some multiple sclerosis (MS) lesions may have great similarities with neoplastic brain lesions in magnetic resonance (MR) imaging and thus wrong diagnoses may occur. In this study, differentiation of MS and low-grade brain tumors was performed with computer-aided diagnosis (CAD) methods by magnetic resonance spectroscopy (MRS) data. MRS data belonging to 51 MS and 39 low-grade brain tumor patients were obtained. The feature extraction from MRS data was performed by the help of peak integration (PI) and full spectra (FS) methods and the most significant features were identified. For the classification step, artificial neural network (ANN), support vector machine (SVM), and linear discriminant analysis (LDA) methods were used and the differentiation between MS and brain tumor was performed automatically. Examining the results, one can conclude that data which belong to MS and low-grade brain tumor cases were automatically differentiated from each other with the help of ANN with 100% accuracy, 100% sensitivity, and 100% specificity. Using of MR spectroscopy and artificial intelligence methods may be useful as a complementary imaging technique to MR imaging in the differentiation of MS lesions and low-grade brain tumors.

SPectroscOpic prediction of bRain Tumours (SPORT): study protocol of a prospective imaging trial

Background

The revised 2016 WHO-Classification of CNS-tumours now integrates molecular information of glial brain tumours for accurate diagnosis as well as for the development of targeted therapies. In this prospective study, our aim is to investigate the predictive value of MR-spectroscopy in order to establish a solid preoperative molecular stratification algorithm of these tumours. We will process a 1H MR-spectroscopy sequence within a radiomics analytics pipeline.

Methods

Patients treated at our institution with WHO-Grade II, III and IV gliomas will receive preoperative anatomical (T2- and T1-weighted imaging with and without contrast enhancement) and proton MR spectroscopy (MRS) by using chemical shift imaging (MRS) (5 × 5 × 15 mm³ voxel size). Tumour regions will be segmented and co-registered to corresponding spectroscopic voxels. Raw signals will be processed by a deep-learning approach for identifying patterns in metabolic data that provides information with respect to the histological diagnosis as well patient characteristics obtained and genomic data such as target sequencing and transcriptional data.

Discussion

By imaging the metabolic profile of a glioma using a customized chemical shift 1H MR spectroscopy sequence and by processing the metabolic profiles with a machine learning tool we intend to non-invasively uncover the genetic signature of gliomas. This work-up will support surgical and oncological decisions to improve personalized tumour treatment.

Trial registration

This study was initially registered under another name and was later retrospectively registered under the current name at the German Clinical Trials Register (DRKS) under DRKS00019855.

Anatomical and functional MR imaging to define tumoral boundaries and characterize lesions in neuro-oncology

Neuroimaging and especially MRI has emerged as a necessary imaging modality to detect, measure, characterize and monitor brain tumours. Advanced MRI sequences such as perfusion MRI, diffusion MRI and spectroscopy as well as new post-processing techniques such as automatic segmentation of tumours and radiomics play a crucial role in characterization and follow up of brain tumours. The purpose of this review is to provide an overview on anatomical and functional MRI use for brain tumours boundaries determination and tumour characterization in the specific context of radiotherapy. The usefulness of anatomical and functional MRI on particular challenges posed by radiotherapy such as pseudo progression and pseudo esponse and new treatment strategies such as dose painting is also described.

Diagnostic Value of Diffusion-weighted Magnetic Resonance (MR) Imaging, MR Perfusion, and MR Spectroscopy in Addition to Conventional MR Imaging in Intracranial Space-occupying Lesions

PURPOSE

Our aim was to determine the diagnostic performance of the combined usage of diffusion-weighted imaging (DWI), magnetic resonance spectroscopy (MRS) and perfusion MR (MRP) imaging for the differential diagnosis of benign and malignant intracranial lesions.

MATERIALS AND METHODS

A total of 30 patients with intracranial lesions who were prospectively evaluated with contrast-enhanced magnetic resonance imaging (MRI), DWI, MRS, and MRP were included in this study. The lesions were classified as benign and malignant according to the radiologic findings. All imaging data were compared with the histopathologic results and follow-up of the patients. We used the Pearson chi-square test and Fischer's exact t-test for statistical analysis.

RESULTS

For the differentiation of benign and malignant brain lesions, CBV and choline/creatine (Cho/Cr) ratio at short echo time (TE) had the highest sensitivity (87%-88%), Cho/N-acetyl aspartate (NAA) at short TE had the highest specificity (86%). DWI predicted 77% sensitivity, 75% specificity; MRP presented 91% sensitivity, 88% specificity; MRS yielded 77% sensitivity, 63% specificity. The combination of either DWI and MRS, MRP and MRS or DWI+MRS+MRP revealed 100% sensitivity, 100% specificity.

CONCLUSION

For the differentiation of benign and malignant brain lesions, the combination of DWI, MRS, and MRP predicted 100% sensitivity. Invasive procedures like transcranial biopsy were not required via the usage of these advanced MRI techniques.

Cancer metabolism in a snapshot: MRS(I)

The contribution of MRS(I) to the in vivo evaluation of cancer-metabolism-derived metrics, mostly since 2016, is reviewed here. Increased carbon consumption by tumour cells, which are highly glycolytic, is now being sampled by ¹³ C magnetic resonance spectroscopic imaging (MRSI) following the injection of hyperpolarized [1-¹³ C] pyruvate (Pyr). Hot-spots of, mostly, increased lactate dehydrogenase activity or flow between Pyr and lactate (Lac) have been seen with cancer progression in prostate (preclinical and in humans), brain and pancreas (both preclinical) tumours. Therapy response is usually signalled by decreased Lac/Pyr ¹³ C-labelled ratio with respect to untreated or non-responding tumour. For therapeutic agents inducing tumour hypoxia, the ¹³ C-labelled Lac/bicarbonate ratio may be a better metric than the Lac/Pyr ratio. ³¹ P MRSI may sample intracellular pH changes from brain tumours (acidification upon antiangiogenic treatment, basification at fast proliferation and relapse). The steady state tumour metabolome pattern is still in use for cancer evaluation. Metrics used for this range from quantification of single oncometabolites (such as 2-hydroxyglutarate in mutant IDH1 glial brain tumours) to selected metabolite ratios (such as total choline to N-acetylaspartate (plain ratio or CNI index)) or the whole ¹ H MRSI(I) pattern through pattern recognition analysis. These approaches have been applied to address different questions such as tumour subtype definition, following/predicting the response to therapy or defining better resection or radiosurgery limits.

Glioma Mimics: Magnetic Resonance Imaging Characteristics of Granulomas in Dogs

Granulomas can "mimic" gliomas on magnetic resonance imaging (MRI) in human patients. The goal of this retrospective study was to report canine brain granulomas that were consistent with glioma based upon MRI, report their histologic diagnosis, and identify MRI criteria that might be useful to distinguish granuloma from glioma. Ten granulomas, initially suspected to be glioma based on MRI, were ultimately diagnosed as granulomatous meningoencephalomyelitis (n = 5), infectious granulomas (n = 3) or other meningoencephalitis (n = 2). Age was 1.6-15.0 years and two dogs were brachycephalic breeds. MRI characteristics overlapping with glioma included intra-axial, heterogeneous, T2-weighted hyperintense, T1-weighted hypointense to isointense mass lesions with contrast-enhancement. Signals on fluid attenuation inversion recovery, gradient echo and diffusion weighted imaging also matched glioma. Peri-lesional edema and mass effect were toward the high end of findings reported for glioma. MRI characteristics that would be considered unusual for glioma included dural contact (n = 4), T2-hypointensity (n = 2), concomitant meningeal-enhancement (n = 9), and minor changes in the contralateral brain (n = 2). Cerebrospinal fluid analysis revealed albuminocytological dissociation or mild pleocytosis. These cases show that granulomas can "mimic" glioma on canine brain MRI. In individual cases, certain MRI findings may help increase the index of suspicion for granuloma. Lack of pronounced cerebrospinal fluid pleocytosis does not exclude granuloma. Signalment is very useful in the suspicion of glioma, and many of these dogs with granuloma were of ages and breeds in which glioma is less commonly seen.

Lack of choline elevation on proton magnetic resonance spectroscopy in grade I-III gliomas

Elevated levels of choline are generally emphasized as marker of increased cellularity and cell membrane turnover in gliomas. In this study, we investigated the incidence rate of lack of choline/creatine and choline/water elevation in a population of grade I-III gliomas. A cohort of 41 patients with histopathologically confirmed gliomas underwent multi-voxel proton magnetic resonance spectroscopy on a 3 T magnetic resonance system prior to treatment. Peak areas for choline and myoinositol were measured from all voxels that exhibited hyperintensity on fluid-attenuated inversion recovery images and were normalized to creatine and unsuppressed water from each voxel. The average metabolite/creatine and metabolite/water ratios from these voxels were then computed. Similarly, average metabolite ratios were computed from normal brain parenchyma. Gliomas were considered for lack of choline elevation when choline/creatine and choline/water ratios from neoplastic regions were less than those from normal brain parenchyma regions. Six of 41 (14.6%) grade I-III gliomas showed lack of elevation for choline/creatine and choline/water ratios compared to normal brain parenchyma. Four of these six gliomas also demonstrated elevated levels of myoinositol/creatine ratio. All other gliomas (n = 35) had elevated choline levels from neoplastic regions relative to normal parenchyma. The sensitivity of choline/creatine or choline/water in determining a grade I-III glioma was 85.4%. These findings suggest that a lack of choline/creatine or choline/water elevation may be seen in some gliomas and low choline levels should not prevent us from considering the possibility of a grade I-III glioma.

The value of magnetic resonance spectroscopy as a supplement to MRI of the brain in a clinical setting

BACKGROUND

There are different opinions of the clinical value of MRS of the brain. In selected materials MRS has demonstrated good results for characterisation of both neoplastic and non-neoplastic lesions. The aim of this study was to evaluate the supplemental value of MR spectroscopy (MRS) in a clinical setting.

MATERIAL AND METHODS

MRI and MRS were re-evaluated in 208 cases with a clinically indicated MRS (cases with uncertain or insufficient information on MRI) and a confirmed diagnosis. Both single voxel spectroscopy (SVS) and chemical shift imaging (CSI) were performed in 105 cases, only SVS or CSI in 54 and 49 cases, respectively. Diagnoses were grouped into categories: non-neoplastic disease, low-grade tumour, and high-grade tumour. The clinical value of MRS was considered very beneficial if it provided the correct category or location when MRI did not, beneficial if it ruled out suspected diseases or was more specific than MRI, inconsequential if it provided the same level of information, or misleading if it provided less or incorrect information.

RESULTS

There were 70 non-neoplastic lesions, 43 low-grade tumours, and 95 high-grade tumours. For MRI, the category was correct in 130 cases (62%), indeterminate in 39 cases (19%), and incorrect in 39 cases (19%). Supplemented with MRS, 134 cases (64%) were correct, 23 cases (11%) indeterminate, and 51 (25%) incorrect. Additional information from MRS was beneficial or very beneficial in 31 cases (15%) and misleading in 36 cases (17%).

CONCLUSION

In most cases MRS did not add to the diagnostic value of MRI. In selected cases, MRS may be a valuable supplement to MRI.

Glioma imaging in Europe: A survey of 220 centres and recommendations for best clinical practice

Objectives

At a European Society of Neuroradiology (ESNR) Annual Meeting 2015 workshop, commonalities in practice, current controversies and technical hurdles in glioma MRI were discussed. We aimed to formulate guidance on MRI of glioma and determine its feasibility, by seeking information on glioma imaging practices from the European Neuroradiology community.

Methods

Invitations to a structured survey were emailed to ESNR members (n=1,662) and associates (n=6,400), European national radiologists’ societies and distributed via social media.

Results

Responses were received from 220 institutions (59% academic). Conventional imaging protocols generally include T2w, T2-FLAIR, DWI, and pre- and post-contrast T1w. Perfusion MRI is used widely (85.5%), while spectroscopy seems reserved for specific indications. Reasons for omitting advanced imaging modalities include lack of facility/software, time constraints and no requests. Early postoperative MRI is routinely carried out by 74% within 24–72 h, but only 17% report a percent measure of resection. For follow-up, most sites (60%) issue qualitative reports, while 27% report an assessment according to the RANO criteria. A minority of sites use a reporting template (23%).

Conclusion

Clinical best practice recommendations for glioma imaging assessment are proposed and the current role of advanced MRI modalities in routine use is addressed.

Key Points

• We recommend the EORTC-NBTS protocol as the clinical standard glioma protocol.

• Perfusion MRI is recommended for diagnosis and follow-up of glioma.

• Use of advanced imaging could be promoted with increased education activities.

• Most response assessment is currently performed qualitatively.

• Reporting templates are not widely used, and could facilitate standardisation.

Electronic supplementary material

The online version of this article (10.1007/s00330-018-5314-5) contains supplementary material, which is available to authorized users.

Spatial Relationship of Glioma Volume Derived from 18F-FET PET and Volumetric MR Spectroscopy Imaging: A Hybrid PET/MRI Study

PET imaging of amino acid transport using O-(2-¹⁸F-fluoroethyl)-l-tyrosine (¹⁸F-FET) and proton MR spectroscopy (MRS) imaging of cell turnover measured by the ratio of choline to N-acetyl-aspartate (Cho/NAA) may provide additional information on tumor extent of cerebral gliomas compared with anatomic imaging; however, comparative studies are rare. Methods: In this prospective study, 41 patients (16 women, 25 men; mean age ± SD, 48 ± 14 y) with cerebral gliomas (World Health Organization [WHO] grade II: 10 [including 1 patient with 2 lesions], WHO III: 17, WHO IV: 13, without biopsy low-grade: 1, high-grade: 1) were investigated with a hybrid PET/MR scanner. Tumor extent, spatial overlap, and the distance between the corresponding centers of mass in ¹⁸F-FET PET and MRS imaging of Cho/NAA, determined by simultaneously acquired, 3-dimensional spatially resolved MRS imaging data, were compared. Results: The average tumor volumes for ¹⁸F-FET uptake and increased Cho/NAA were 19 ± 20 cm³ (mean ± SD) and 22 ± 24 cm³, respectively, with an overlap of 40% ± 25% and separation of the centers of mass by 9 ± 8 mm. None of the parameters showed a significant correlation with tumor grade. Conclusion:¹⁸F-FET uptake and increased Cho/NAA ratio are not always congruent and may represent different properties of glioma metabolism. The relationship to histologic tumor extent needs to be further analyzed.

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.

Accurate classification of brain gliomas by discriminate dictionary learning based on projective dictionary pair learning of proton magnetic resonance spectra

Proton magnetic resonance spectroscopy is a powerful noninvasive technique that complements the structural images of cMRI, which aids biomedical and clinical researches, by identifying and visualizing the compositions of various metabolites within the tissues of interest. However, accurate classification of proton magnetic resonance spectroscopy is still a challenging issue in clinics due to low signal-to-noise ratio, overlapping peaks of metabolites, and the presence of background macromolecules. This paper evaluates the performance of a discriminate dictionary learning classifiers based on projective dictionary pair learning method for brain gliomas proton magnetic resonance spectroscopy spectra classification task, and the result were compared with the sub-dictionary learning methods. The proton magnetic resonance spectroscopy data contain a total of 150 spectra (74 healthy, 23 grade II, 23 grade III, and 30 grade IV) from two databases. The datasets from both databases were first coupled together, followed by column normalization. The Kennard-Stone algorithm was used to split the datasets into its training and test sets. Performance comparison based on the overall accuracy, sensitivity, specificity, and precision was conducted. Based on the overall accuracy of our classification scheme, the dictionary pair learning method was found to outperform the sub-dictionary learning methods 97.78% compared with 68.89%, respectively. Copyright © 2016 John Wiley & Sons, Ltd.

Brain metabolic pattern analysis using a magnetic resonance spectra classification software in experimental stroke

Background

Magnetic resonance spectroscopy (MRS) provides non-invasive information about the metabolic pattern of the brain parenchyma in vivo. The SpectraClassifier software performs MRS pattern-recognition by determining the spectral features (metabolites) which can be used objectively to classify spectra. Our aim was to develop an Infarct Evolution Classifier and a Brain Regions Classifier in a rat model of focal ischemic stroke using SpectraClassifier.

Results

A total of 164 single-voxel proton spectra obtained with a 7 Tesla magnet at an echo time of 12 ms from non-infarcted parenchyma, subventricular zones and infarcted parenchyma were analyzed with SpectraClassifier (http://gabrmn.uab.es/?q=sc). The spectra corresponded to Sprague-Dawley rats (healthy rats, n = 7) and stroke rats at day 1 post-stroke (acute phase, n = 6 rats) and at days 7 ± 1 post-stroke (subacute phase, n = 14). In the Infarct Evolution Classifier, spectral features contributed by lactate + mobile lipids (1.33 ppm), total creatine (3.05 ppm) and mobile lipids (0.85 ppm) distinguished among non-infarcted parenchyma (100% sensitivity and 100% specificity), acute phase of infarct (100% sensitivity and 95% specificity) and subacute phase of infarct (78% sensitivity and 100% specificity). In the Brain Regions Classifier, spectral features contributed by myoinositol (3.62 ppm) and total creatine (3.04/3.05 ppm) distinguished among infarcted parenchyma (100% sensitivity and 98% specificity), non-infarcted parenchyma (84% sensitivity and 84% specificity) and subventricular zones (76% sensitivity and 93% specificity).

Conclusion

SpectraClassifier identified candidate biomarkers for infarct evolution (mobile lipids accumulation) and different brain regions (myoinositol content).

Electronic supplementary material

The online version of this article (doi:10.1186/s12868-016-0328-x) contains supplementary material, which is available to authorized users.

The Role of MRgLITT in Overcoming the Challenges in Managing Infield Recurrence After Radiation for Brain Metastasis

Radiation necrosis and tumor recurrence are common sequelae after radiation therapy for brain metastasis. The differentiation of radiation necrosis and recurrent brain metastases continues to remain a difficult task despite a number of diagnostic methods. Techniques including magnetic resonance imaging, diffusion-weighted imaging, nuclear studies, and the gold standard of biopsy have all been studied for their effectiveness in accurately diagnosing the postradiation condition. Various specific treatment options of the distinct pathologies are available with the general theory that recurrences require more immediate treatment whereas radiation necrosis can be observed until symptomatic before intervention. This further emphasizes the necessity to accurately diagnose the condition to start appropriate and effective treatment. Despite both pathologies being pathophysiologically distinct, controversies exist as to whether there should be a distinction made at all or if the two can be perceived as a single condition if treatment and presentation are similar enough. Furthermore, a single treatment option such as magnetic resonance–guided, laser-induced thermal therapy (MRgLITT) can be used, potentially eliminating the need to differentiate the 2 entities because it successfully treats both conditions while being minimally invasive.

Other noninfectious inflammatory disorders

Idiopathic inflammatory-demyelinating diseases (IIDDs) represent a broad spectrum of central nervous system (CNS) disorders, including monophasic, multiphasic, and progressive disorders that range from highly localized forms to multifocal or diffuse variants. In addition to the classic multiple sclerosis (MS) phenotypes, several MS variants have been described, which can be differentiated on the basis of severity, clinical course, and lesion distribution. Other forms of IIDD are now recognized as distinct entities and not MS variants, such as acute disseminated encephalomyelitis, and neuromyelitis optica spectrum disorders. The CNS can also be affected by a variety of inflammatory diseases. These include primary angiitis of the CNS (PACNS), a rare disorder specifically targeting the CNS vasculature, and various systemic conditions which, among other organs and systems, can also affect the CNS, such as systemic vasculitis and sarcoidosis. The diagnosis of PACNS is difficult, as this condition may be confused with reversible cerebral vasoconstriction syndrome (RCVS), a term comprising a group of conditions characterized by prolonged but reversible vasoconstriction of the cerebral arteries. Magnetic resonance imaging of the brain and spine is the radiologic technique of choice for diagnosing these disorders, and, together with the clinical and laboratory findings, enables a prompt and accurate diagnosis.

Classification of brain tumours from MR spectra: the INTERPRET collaboration and its outcomes

The INTERPRET project was a multicentre European collaboration, carried out from 2000 to 2002, which developed a decision-support system (DSS) for helping neuroradiologists with no experience of MRS to utilize spectroscopic data for the diagnosis and grading of human brain tumours. INTERPRET gathered a large collection of MR spectra of brain tumours and pseudo-tumoural lesions from seven centres. Consensus acquisition protocols, a standard processing pipeline and strict methods for quality control of the aquired data were put in place. Particular emphasis was placed on ensuring the diagnostic certainty of each case, for which all cases were evaluated by a clinical data validation committee. One outcome of the project is a database of 304 fully validated spectra from brain tumours, pseudotumoural lesions and normal brains, along with their associated images and clinical data, which remains available to the scientific and medical community. The second is the INTERPRET DSS, which has continued to be developed and clinically evaluated since the project ended. We also review here the results of the post-INTERPRET period. We evaluate the results of the studies with the INTERPRET database by other consortia or research groups. A summary of the clinical evaluations that have been performed on the post-INTERPRET DSS versions is also presented. Several have shown that diagnostic certainty can be improved for certain tumour types when the INTERPRET DSS is used in conjunction with conventional radiological image interpretation. About 30 papers concerned with the INTERPRET single-voxel dataset have so far been published. We discuss stengths and weaknesses of the DSS and the lessons learned. Finally we speculate on how the INTERPRET concept might be carried into the future.

Differential diagnosis of a vanishing brain space occupying lesion in a child

We describe clinical, diagnostic features and follow up of a patient with a vanishing brain lesion. A 14-year-old child admitted to the department of Neurology at September 2009 with a history of subacute onset of fever, anorexia, vomiting, blurring of vision and right hemiparesis since one month. Magnetic resonance imaging (MRI) of the brain revealed presence of intra-axial large mass (25 mm × 19 mm) in the left temporal lobe and the brainstem which showed hypointense signal in T1W and hyperintense signals in T2W and fluid attenuated inversion recovery (FLAIR) images and homogenously enhanced with gadolinium (Gd). It was surrounded by vasogenic edema with mass effect. Intravenous antibiotics, mannitol (2 g/12 h per 2 d) and dexamethasone (8 mg/12 h) were given to relief manifestations of increased intracranial pressure. Whole craniospinal radiotherapy (brain = 4000 CGy/20 settings per 4 wk; Spinal = 2600/13 settings per 3 wk) was given based on the high suspicion of neoplastic lesion (lymphoma or glioma). Marked clinical improvement (up to complete recovery) occurred within 15 d. Tapering of the steroid dose was done over the next 4 mo. Follow up with MRI after 3 mo showed small lesion in the left antero-medial temporal region with hypointense signal in T1W and hyperintense signals in T2W and FLAIR images but did not enhance with Gd. At August 2012, the patient developed recurrent generalized epilepsy. His electroencephalography showed the presence of left temporal focus of epileptic activity. MRI showed the same lesion as described in the follow up. The diffusion weighted images were normal. The seizures frequency was decreased with carbamazepine therapy (300 mg/12 h). At October 2014, single voxel proton (1H) MR spectroscopy (MRS) showed reduced N-acetyl-aspartate (NAA)/creatine (Cr), choline (Cho)/Cr, NAA/Cho ratios consistent with absence of a neoplasm and highly suggested presence of gliosis. A solitary brain mass in a child poses a considerable diagnostic difficulty. MRS provided valuable diagnostic differentiation between tumor and pseudotumor lesions.

Cerebral tumor or pseudotumor?

Pseudotumoral lesions are uncommon but important to identity lesions. They can occur during inflammatory diseases (systemic diseases, vasculitis, demyelinating diseases), infectious, and vascular diseases. Also, in a patient with a treated tumor, pseudo-progression and radionecrosis must be differentiated from the tumoral development. Diagnosis can be difficult on an MRI scan, but some MRI aspects in conventional sequences, diffusion, perfusion and spectroscopy can suggest the pseudotumoral origin of a lesion. Imaging must be interpreted according to the context, the clinic and the biology. The presence of associated intracranial lesions can orientate towards a systemic or infectious disease. A T2 hyposignal lesion suggests granulomatosis or histiocytosis, especially if a meningeal or hypothalamic-pituitary involvement is associated. Non-tumoral lesions are generally not hyperperfused. In the absence of a definitive diagnosis, the evolution of these lesions, whether under treatment or spontaneous, is fundamental.

Relative metabolite concentrations and ratios determined by use of 3-T region-specific proton magnetic resonance spectroscopy of the brain of healthy Beagles

OBJECTIVE

To determine relative concentrations of selected major brain tissue metabolites and their ratios and lobar variations by use of 3-T proton (hydrogen 1 [(1)H]) magnetic resonance spectroscopy (MRS) of the brain of healthy dogs.

ANIMALS

10 healthy Beagles.

PROCEDURES

3-T (1)H MRS at echo times of 144 and 35 milliseconds was performed on 5 transverse slices and 1 sagittal slice of representative brain lobe regions. Intravoxel parenchyma was classified as white matter, gray matter, or mixed (gray and white) and analyzed for relative concentrations (in arbitrary units) of N-acetylaspartate (NAA), choline, and creatine (ie, height at position of peak on MRS graph) as well as their ratios (NAA-to-choline, NAA-to-creatine, and choline-to-creatine ratios). Peak heights for metabolites were compared between echo times. Peak heights for metabolites and their ratios were correlated and evaluated among matter types. Yield was calculated as interpretable voxels divided by available lobar voxels.

RESULTS

Reference ranges of the metabolite concentration ratios were determined at an echo time of 35 milliseconds (NAA-to-choline ratio, 1.055 to 2.224; NAA-to-creatine ratio, 1.103 to 2.161; choline-to-creatine ratio, 0.759 to 1.332) and 144 milliseconds (NAA-to-choline ratio, 0.687 to 1.788; NAA-to-creatine ratio, 0.984 to 2.044; choline-to-creatine ratio, 0.828 to 1.853). Metabolite concentration ratios were greater in white matter than in gray matter. Voxel yields ranged from 43% for the temporal lobe to 100% for the thalamus.

CONCLUSIONS AND CLINICAL RELEVANCE

Metabolite concentrations and concentration ratios determined with 3-T (1)H MRS were not identical to those in humans and were determined for clinical and research investigations of canine brain disease.

Metabolic white matter diseases and the utility of MR spectroscopy

Magnetic resonance spectroscopy (MRS) can be useful as an adjuvant diagnostic tool to traditional MR imaging of the brain. MRS can provide both quantitative and qualitative information about white matter pathologic abnormality. It is important to interpret MRS in conjunction with other clinical factors including but not limited to additional diagnostic neuroimaging, history and physical examination findings, and genetics.

Proton magnetic resonance spectroscopy of periventricular white matter and hippocampus in obstructive sleep apnea patients

BACKGROUND

The purpose of this study was to diagnose the hypoxic impairment by Magnetic resonance spectroscopy (MRS), an advanced MR imaging technique, which could not be visualised by routine imaging methods in patients with obstructive sleep apnea (OSA).

MATERIAL/METHODS

20 OSA patients and 5 controls were included in this prospective research. MRS was performed on these 25 subjects to examine cerebral hypoxemia in specific regions (periventricular white matter and both hippocampi). Polysomnography was assumed as the gold standard. Statistical analysis was assessed by Mann-Whitney U test and Receiver operating characteristics (ROC) curve for NAA/Cho, NAA/Cr and Cho/Cr ratios.

RESULTS

In the periventricular white matter, NAA/Cho ratio in OSA patients was significantly lower than in the control group (p<0.05). There were no statistical differences between the OSA and the control group for NAA/Cho, NAA/Cr and Cho/Cr ratios for both hippocampal regions. Additionally, Cho/Cr ratio in the periventricular white matter region of OSA group was higher than in the control group (p<0.05).

CONCLUSIONS

Hypoxic impairment induced by repeated episodes of apnea leads to significant neuronal damage in OSA patients. MRS provides valuable information in the assessment of hypoxic ischemic impairment by revealing important metabolite ratios for the specific areas of the brain.

Utility of proton MR spectroscopy for differentiating typical and atypical primary central nervous system lymphomas from tumefactive demyelinating lesions

BACKGROUND AND PURPOSE

It may be challenging to differentiate primary CNS lymphomas, especially primary CNS lymphomas with atypical MR features, from tumefactive demyelinating lesions by the use of conventional MR. This study aimed to investigate the usefulness of (1)H-MR spectroscopy for making this discrimination.

MATERIALS AND METHODS

Forty-four patients with primary CNS lymphomas and 21 with tumefactive demyelinating lesions were enrolled. Single-voxel (TE = 144 ms) (1)H-MR spectroscopy scans with the use of the point-resolved spectroscopy sequence were retrospectively analyzed. The Cho/Cr and Cho/NAA area ratios were calculated. The lipid and/or lactate peak was visually categorized into 5 grades on the basis of comparison with the height of the Cr peak. The (1)H-MR spectroscopy findings were compared in all of the primary CNS lymphomas and the tumefactive demyelinating lesions and in the subgroup of atypical primary CNS lymphomas and tumefactive demyelinating lesions. The thresholds and added value of (1)H-MR spectroscopy to conventional MR were calculated by use of receiver operating characteristic curves.

RESULTS

Discrepancies between all of the primary CNS lymphomas and tumefactive demyelinating lesions were found in the Cho/Cr ratio (P = .000), Cho/NAA ratio (P = .000), and the lipid and/or lactate peak grade (P = .000). Lymphoma rather than tumefactive demyelinating lesions was suggested when the Cho/Cr ratio was >2.58, the Cho/NAA ratio was >1.73, and a high lipid and/or lactate peak grade (grade >3) was seen. Higher Cho/Cr ratios, Cho/NAA ratios, and lipid and/or lactate peak grades were found in atypical primary CNS lymphomas when compared with those of tumefactive demyelinating lesions. The area under the receiver operating characteristic curve of conventional MR was improved from 0.827 to 0.870 when Cho/NAA ratio was added in the uncertain cases.

CONCLUSIONS

(1)H-MR spectroscopy may be useful for differentiating primary CNS lymphomas from tumefactive demyelinating lesions. Cho/NAA ratio could provide added value to conventional MR imaging.

1H magnetic resonance spectroscopy in multiple sclerosis and related disorders

Proton magnetic resonance spectroscopy ((1)H-MRS) is an unconventional technique that allows noninvasive characterization of metabolic abnormalities in the central nervous system. (1)H-MRS provides important insights into the chemical-pathologic changes that occur in patients with multiple sclerosis (MS). In this review article we present the main brain and spinal cord (1)H-MRS features in MS, their diagnostic value in differentiating pseudotumoral demyelinating lesions from primary brain tumors, and their relationship with clinical variables. Last, some data related to the use of (1)H-MRS in therapeutic trials is presented.

Brain proton magnetic resonance spectroscopy: introduction and overview

Magnetic resonance (MR) spectroscopy offers a noninvasive means of assessing in vivo brain metabolites that shed light on cellular concentrations, cell function and dysfunction, cellular energetics, presence of ischemia, and presence of necrosis, among others. Studies obtained at higher field strengths are evolving toward sampling of smaller tissue volumes, greater signal-to-noise ratio, and higher metabolic spatial resolution. This article discusses the usefulness, from the clinical standpoint, of MR spectroscopy in various disorders. However, to be valid and significant the results of MR spectroscopy should always be correlated with their imaging counterparts.

Neurochemical correlates of cognitive dysfunction in patients with leukoaraiosis: a proton magnetic resonance spectroscopy study

OBJECTIVES

Leukoaraiosis (LA) is a common radiological finding in the elderly and may reflect cerebral small vessel disease (SVD). Although SVD has been identified as a major cause of vascular cognitive impairment or vascular dementia, the mechanisms for this association remain unclear. We therefore aimed to measure brain metabolites in LA using proton magnetic resonance spectroscopy ((1)H-MRS) as to determine the relationship between cognitive function and neurochemical white matter profile.

METHODS

We recruited 23 patients with LA and 23 age- and sex-matched healthy controls consecutively. Multi-voxel (1)H-MRS was performed with a volume of interest located in centrum semiovale that contained mainly white matter voxels. Three main ratios of N-acetyl aspartate (NAA)/Cr, choline (Cho)/Cr and NAA/Cho were obtained. Spearman rank correlation coefficients were calculated between the cognitive function and the measured metabolite ratios.

RESULTS

We found significantly lower levels of NAA/Cho and NAA/Cr ratios in lesioned white matter in patients with LA than healthy controls (P<0.05). The ratios of NAA/Cho and NAA/Cr in normal appearing white matter (NAWM) were higher than lesioned white matter and lower than controls, but this difference was not significant (P>0.05). There was a positive relationship between Mini-Mental State Examination (MMSE) and NAA/Cho in NAWM (r = 0.417, P = 0.048), and also a positive relationship between MMSE and NAA/Cr in lesioned white matter (r = 0.551, P = 0.006) in patients with LA. A positive relationship between the Z scores of the executive function and NAA/Cho in lesioned white matter (r = 0.557, P = 0.006) was also found.

CONCLUSION

The main finding of this study was a significant reduction in the ratios of NAA/Cr and NAA/Cho in lesioned white matter, which indicates a marker of neuronal loss or dysfunction in patients with LA, which was correlated with cognitive function. This relationship between cognitive function and metabolic changes suggests that (1)H-MRS can be explored as a marker for cognitive dysfunction in patients with LA.

The role of proton MR spectroscopy and apparent diffusion coefficient values in the diagnosis of malignant thyroid nodules: preliminary results

PURPOSE

Performance of proton magnetic resonance spectroscopy (H-MRS) and apparent diffusion coefficient (ADC) values in the diagnosis of malignant thyroid nodules.

METHOD

In a retrospective study with malignant nodules of 14 patients, H-MRS and diffusion-weighted MR imaging (DWI) were performed. Choline (Cho) peak, Cho/creatine (Cr) ratio, and ADC values of malignant nodules were correlated with the five benign nodules and four normal-appearing thyroid lobe parenchymata. The gold standard reference was fine needle aspiration biopsy and histopathology.

RESULTS

At echo time 40-144-ms acquisitions, average Cho/Cr ratio for the malignant nodules was 2.95±1.54-5.30±2.38, cutoff values were >0.805 and >1.225, and ADC values were 0.06±0.02.

CONCLUSION

H-MRS acquisitions, DWI, and ADC mapping give diagnostic data about the nature of the nodules.

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.

Neuroimaging findings in the initial phase of development of high grade cortical astrocytomas

OBJECTIVES

To describe the neuroradiological characteristics of a series of high grade cortical astrocytomas in the initial phase of development and their pattern of growth during a short time period.

MATERIAL AND METHODS

This was a retrospective observational study of the neuroradiological findings in six patients diagnosed with high grade astrocytoma. All presented with a new onset epileptic seizure and focal supratentorial cortical lesions. The diagnosis was established after a short period of clinical and radiological follow-up.

RESULTS

Magnetic resonance imaging (MRI) detected a small cortical lesion that was hyperintense in T2-weighted sequences in all six patients. This lesion showed slight or moderate enhancement after the administration of a contrast agent in five patients. All six patients underwent follow-up MRI within six months of the initial MRI examination (mean 79 days). Follow-up MRI showed marked growth of the lesions in all cases, and the histological diagnosis of high grade astrocytoma (glioblastoma in five patients and anaplastic oligoastrocytoma in one) was established after surgical debulking.

CONCLUSION

High grade astrocytomas originating in the supratentorial cortex can have an atypical neuroradiological presentation in the early stages. High grade astrocytoma should be included in the differential diagnosis of a cortical lesion that enhances slightly or moderately after the administration of contrast material in a patient with a new onset epileptic seizure.

Magnetic resonance spectroscopic detection of lactate is predictive of a poor prognosis in patients with diffuse intrinsic pontine glioma

Diffuse brainstem glioma has a poor prognosis, and there are few long-term survivors. We looked for clinical, conventional magnetic resonance (MR), and MR spectroscopic (MRS) findings predictive of the prognosis of patients with brainstem glioma. Our institutional review board approved this retrospective study of 23 patients with diffuse intrinsic pontine or diffuse medullary brainstem glioma treated during the period 2000-2009. To evaluate prognostic values, we performed a Kaplan-Meier survival analysis (log-rank test) that incorporated the patients' age and sex, symptom duration, the presence or absence of cranial nerve palsy, long tract sign, ataxia, and cysts, the chemotherapeutic regimen, Gd enhancement, longitudinal and cerebellar extension, basilar artery encasement, and MRS parameters. Of the 23 diffuse brainstem gliomas, 19 were located at the pons (ratio of male to female patients, 1.1:1). The mean age of the 23 patients was 15.9 years (range, 4-50 years); 16 were aged <20 years. The duration of overall survival was 19.7 months; in patients with diffuse intrinsic pontine glioma, it was 16.6 months, and in patients aged <20 years, it was 11.8 months. Clinical and conventional MR findings at presentation were not predictive of the prognosis in children with diffuse intrinsic pontine glioma. In addition, a patient age <20 years and the detection of lactate by MRS were poor prognostic factors. The MRS detection of lactate is a prognostic factor in patients with diffuse intrinsic pontine glioma. Additional studies of larger patient populations using other imaging modalities are needed.

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.