Assignment of the 2.03 ppm resonance in in vivo 1H MRS of human brain tumour cystic fluid: contribution of macromolecules

Contribution of macromolecules to brain 1 H MR spectra: Experts' consensus recommendations

Proton MR spectra of the brain, especially those measured at short and intermediate echo times, contain signals from mobile macromolecules (MM). A description of the main MM is provided in this consensus paper. These broad peaks of MM underlie the narrower peaks of metabolites and often complicate their quantification but they also may have potential importance as biomarkers in specific diseases. Thus, separation of broad MM signals from low molecular weight metabolites enables accurate determination of metabolite concentrations and is of primary interest in many studies. Other studies attempt to understand the origin of the MM spectrum, to decompose it into individual spectral regions or peaks and to use the components of the MM spectrum as markers of various physiological or pathological conditions in biomedical research or clinical practice. The aim of this consensus paper is to provide an overview and some recommendations on how to handle the MM signals in different types of studies together with a list of open issues in the field, which are all summarized at the end of the paper.

Robust Conditional Independence maps of single-voxel Magnetic Resonance Spectra to elucidate associations between brain tumours and metabolites

The aim of the paper is two-fold. First, we show that structure finding with the PC algorithm can be inherently unstable and requires further operational constraints in order to consistently obtain models that are faithful to the data. We propose a methodology to stabilise the structure finding process, minimising both false positive and false negative error rates. This is demonstrated with synthetic data. Second, to apply the proposed structure finding methodology to a data set comprising single-voxel Magnetic Resonance Spectra of normal brain and three classes of brain tumours, to elucidate the associations between brain tumour types and a range of observed metabolites that are known to be relevant for their characterisation. The data set is bootstrapped in order to maximise the robustness of feature selection for nominated target variables. Specifically, Conditional Independence maps (CI-maps) built from the data and their derived Bayesian networks have been used. A Directed Acyclic Graph (DAG) is built from CI-maps, being a major challenge the minimization of errors in the graph structure. This work presents empirical evidence on how to reduce false positive errors via the False Discovery Rate, and how to identify appropriate parameter settings to improve the False Negative Reduction. In addition, several node ordering policies are investigated that transform the graph into a DAG. The obtained results show that ordering nodes by strength of mutual information can recover a representative DAG in a reasonable time, although a more accurate graph can be recovered using a random order of samples at the expense of increasing the computation time.

Metabolomics of Therapy Response in Preclinical Glioblastoma: A Multi-Slice MRSI-Based Volumetric Analysis for Noninvasive Assessment of Temozolomide Treatment

Glioblastoma (GBM) is the most common aggressive primary brain tumor in adults, with a short survival time even after aggressive therapy. Non-invasive surrogate biomarkers of therapy response may be relevant for improving patient survival. Previous work produced such biomarkers in preclinical GBM using semi-supervised source extraction and single-slice Magnetic Resonance Spectroscopic Imaging (MRSI). Nevertheless, GBMs are heterogeneous and single-slice studies could prevent obtaining relevant information. The purpose of this work was to evaluate whether a multi-slice MRSI approach, acquiring consecutive grids across the tumor, is feasible for preclinical models and may produce additional insight into therapy response. Nosological images were analyzed pixel-by-pixel and a relative responding volume, the Tumor Responding Index (TRI), was defined to quantify response. Heterogeneous response levels were observed and treated animals were ascribed to three arbitrary predefined groups: high response (HR, n = 2), TRI = 68.2 ± 2.8%, intermediate response (IR, n = 6), TRI = 41.1 ± 4.2% and low response (LR, n = 2), TRI = 13.4 ± 14.3%, producing therapy response categorization which had not been fully registered in single-slice studies. Results agreed with the multi-slice approach being feasible and producing an inverse correlation between TRI and Ki67 immunostaining. Additionally, ca. 7-day oscillations of TRI were observed, suggesting that host immune system activation in response to treatment could contribute to the responding patterns detected.

Delayed post-traumatic fronto-ethmoidal sinus mucocele evaluated with short and long TE MR spectroscopy

Mucoceles are slow-growing, benign, expansile, mucoid-filled masses developing after obstruction of the sinus ostium. Late post-traumatic mucoceles are relatively rare entities and the literature is limited to single case reports. We describe an unusual case of post-traumatic fronto-ethmoidal mucocele, evaluated with computed tomography (CT), magnetic resonance imaging (MRI) and proton MR-spectroscopy ((1)H-MRS). As a contribution to the diagnostic work-up of the mucocele, (1)H-MRS demonstrates a dominant peak at 2.0 ppm at long echo time (TE) and an additional component at 3.8 ppm at short TE due to mucus glycoprotein compounds of the mucocele.

Neuroenteric cysts of the brain-comprehensive magnetic resonance imaging

Neuroenteric cysts are developmental cysts that should be differentiated from other, more common non-neoplastic cysts as well as cystic neoplasms. While these lesions may have varied imaging findings, T1 hyperintense prepontine lesion due to mucinous/proteinaceous content is characteristic. Location and imaging characteristics aid in formulating the correct diagnosis of neuroepithelial/neuroenteric cysts. Magnetic resonance spectroscopy (MRS) has the specific finding of N-Acetyl Aspartate (NAA)-like peak at 2.02 ppm which is not seen in other cystic lesions. In this study, we aim to discuss the imaging findings of these lesions on conventional and advanced MRI findings and provide radiologic-pathologic correlation. We also briefly describe the pathogenesis, embryology and radiological differential diagnoses of these cysts.

Assessment of a 1H high-resolution magic angle spinning NMR spectroscopy procedure for free sugars quantification in intact plant tissue

In most plants, sucrose is the primary product of photosynthesis, the transport form of assimilated carbon, and also one of the main factors determining sweetness in fresh fruits. Traditional methods for sugar quantification (mainly sucrose, glucose and fructose) require obtaining crude plant extracts, which sometimes involve substantial sample manipulation, making the process time-consuming and increasing the risk of sample degradation. Here, we describe and validate a fast method to determine sugar content in intact plant tissue by using high-resolution magic angle spinning nuclear magnetic resonance spectroscopy (HR-MAS NMR). The HR-MAS NMR method was used for quantifying sucrose, glucose and fructose in mesocarp tissues from melon fruits (Cucumis melo var. reticulatus and Cucumis melo var. cantalupensis). The resulting sugar content varied among individual melons, ranging from 1.4 to 7.3 g of sucrose, 0.4-2.5 g of glucose; and 0.73-2.83 g of fructose (values per 100 g fw). These values were in agreement with those described in the literature for melon fruit tissue, and no significant differences were found when comparing them with those obtained using the traditional, enzymatic procedure, on melon tissue extracts. The HR-MAS NMR method offers a fast (usually <30 min) and sensitive method for sugar quantification in intact plant tissues, it requires a small amount of tissue (typically 50 mg fw) and avoids the interferences and risks associated with obtaining plant extracts. Furthermore, this method might also allow the quantification of additional metabolites detectable in the plant tissue NMR spectrum.

Apparent T(2) relaxation times of lipid and macromolecules: a study of high-grade tumor spectra

PURPOSE

To determine T(2) relaxation times of lipid and macromolecules (Lip/MMs) observed by (1)H magnetic resonance spectroscopy ((1)H MRS) of metastases (MET) and glioblastomas (GBM), so that they may be better characterized.

MATERIALS AND METHODS

(1)H spectra were acquired at multiple echo times from brain lesions using point-resolved spectroscopy sequence (PRESS) at TE = 30 msec either with metabolite-nulling (six GBM and 11 MET), or without metabolite-nulling (four MET and one mucocele). All lesions were previously untreated and had subsequent histopathological classification.

RESULTS

The T(2) of the 1.3-ppm Lip/MM peak was concentration-dependent, but at high concentrations it was significantly different (P = 0.015) between GBM (42 +/- 6 msec) and MET (63 +/- 18 msec). The broad 2.05-ppm and 0.09-ppm Lip/MM peaks had similar T(2)s in MET and GBM. The T(2) of the narrow 2.05-ppm Lip/MM peak sometimes observed had a T(2) of 100 +/- 17 msec in MET and 75 msec in the mucocele.

CONCLUSION

We observed significantly higher T(2) of the 1.3-ppm Lip/MM peak in MET compared with GBM at high 1.3-ppm proton concentrations, in agreement with a higher 1.3/0.9-ppm peak ratio found in MET. The relatively long T(2) of the 2.05-ppm Lip/MM peak sometimes observed in MET may cause it to be confused with N-acetyl aspartate (NAA).

Perturbation of mouse glioma MRS pattern by induced acute hyperglycemia

(1)H MRS is evolving into an invaluable tool for brain tumor classification in humans based on pattern recognition analysis, but there is still room for improvement. Here we propose a new approach: to challenge tumor metabolism in vivo by a defined perturbation, and study the induced changes in MRS pattern. For this we recorded single voxel (1)H MR spectra from mice bearing a stereotactically induced GL261 grade IV brain glioma during a period of induced acute hyperglycemia. A total of 29 C57BL/6 mice were used. Single voxel spectra were acquired at 7 T with point resolved spectroscopy and TE of 12, 30 and 136 ms. Tumors were induced by stereotactic injection of 10(5) GL261cells in 17 mice. Hyperglycemia (up to 338 +/- 36 mg/dL glucose in the blood) was induced by intraperitoneal bolus injection. Maximal increases in glucose resonances of up to 2.4-fold were recorded from tumors in vivo. Our observations are in agreement with extracellular accumulation of glucose, which may suggest that glucose transport and/or metabolism are working close to their maximum capacity in GL261 tumors. The significant and specific MRS pattern changes observed when comparing euglycemia and hyperglycemia may be of use for future pattern-recognition studies of animal and human brain tumors by enhancing MRS-based discrimination between tumor types and grades.

Bagging linear sparse Bayesian learning models for variable selection in cancer diagnosis

This paper investigates variable selection (VS) and classification for biomedical datasets with a small sample size and a very high input dimension. The sequential sparse Bayesian learning methods with linear bases are used as the basic VS algorithm. Selected variables are fed to the kernel-based probabilistic classifiers: Bayesian least squares support vector machines (BayLS-SVMs) and relevance vector machines (RVMs). We employ the bagging techniques for both VS and model building in order to improve the reliability of the selected variables and the predictive performance. This modeling strategy is applied to real-life medical classification problems, including two binary cancer diagnosis problems based on microarray data and a brain tumor multiclass classification problem using spectra acquired via magnetic resonance spectroscopy. The work is experimentally compared to other VS methods. It is shown that the use of bagging can improve the reliability and stability of both VS and model prediction.

Analysis of the changes in the 1H NMR spectral pattern of perchloric acid extracts of C6 cells with growth

The aim of this work was to identify spectral markers of cell proliferation that could be of use in clinical MRS. Cultured C6 ATCC rat glioma cells were used as models for this purpose and metabolites were extracted with perchloric acid at three different growth curve stages: log, confluence and post-confluence. 1D and 2D in vitro(1)H NMR spectra were recorded at 9.4 T. Statistically significant changes in myo-inositol and glutamine concentrations between log phase and post-confluence were found when normalized to the creatine ratio. The myo-inositol/creatine ratio was 2.76 +/- 0.82 at log phase increasing to 7.43 +/- 1.34 at post-confluence, while the glutamine/creatine ratio decreased from 0.22 +/- 0.03 to 0.10 +/- 0.02. No significant differences were recorded for other metabolites investigated. The fact that both myo-inositol and glutamine are detectable by in vivo MRS at clinical fields makes their changes relevant as potential astrocytic tumour proliferation rate markers in clinical MRS.

A multi-centre, web-accessible and quality control-checked database of in vivo MR spectra of brain tumour patients

OBJECTIVE

To describe an Internet-accessible database that contains validated in vivo MR spectra and clinical data of brain tumour patients.

MATERIALS AND METHODS

All data from patients entering the INTERPRET project (International Network for Pattern Recognition of Tumours Using Magnetic Resonance, <http://azizu.uab.es/INTERPRET>) were stored in a web-accessible database (iDB) and selected using its query functionality. Criteria for selection were that the case had a single voxel (SV) short-echo (20-32 ms) 1.5 T spectrum acquired from a nodular region of the tumour, that the voxel had been positioned in the same region as where subsequent biopsy was obtained, that the short-echo spectrum had not been discarded because of acquisition artefacts or other reasons, and that a histopathological diagnosis was agreed among a committee of neuropathologists. When the spectra were obtained from normal volunteers or were of abscesses or clinically proven metastases, biopsy was not required.

RESULTS

A subset of 304 cases (22 normal volunteers and 282 tumour patients) was obtained. These cases were migrated to another similar database (validated-DB).

CONCLUSION

The validated-DB complies with ethics regulations and represents the population studied. It is accessible by neuroradiologists willing to use information provided by MRS to help in the non-invasive diagnosis of brain tumours.