Magnetic resonance spectroscopy and imaging on fresh human brain tumor biopsies at microscopic resolution.

The metabolic composition and concentration knowledge provided by magnetic resonance spectroscopy (MRS) liquid and high-resolution magic angle spinning spectroscopy (HR-MAS) has a relevant impact in clinical practice during magnetic resonance imaging (MRI) monitoring of human tumors. In addition, the combination of morphological and chemical information by MRI and MRS has been particularly useful for diagnosis and prognosis of tumor evolution. MRI spatial resolution reachable in human beings is limited for safety reasons and the demanding necessary conditions are only applicable on experimental model animals. Nevertheless, MRS and MRI can be performed on human biopsies at high spatial resolution, enough to allow a direct correlation between the chemical information and the histological features observed in such biopsies. Although HR-MAS is nowadays a well-established technique for spectroscopic analysis of tumor biopsies, with this approach just a mean metabolic profile of the whole sample can be obtained and thus the high histological heterogeneity of some important tumors is mostly neglected. The value of metabolic HR-MAS data strongly depends on a wide statistical analysis and usually the microanatomical rationale for the correlation between histology and spectroscopy is lost. We present here a different approach for the combined use of MRI and MRS on fresh human brain tumor biopsies with native contrast. This approach has been designed to achieve high spatial (18 × 18 × 50 µm) and spectral (0.031 µL) resolution in order to obtain as much spatially detailed morphological and metabolical information as possible without any previous treatment that can alter the sample. The preservation of native tissue conditions can provide information that can be translated to in vivo studies and additionally opens the possibility of performing other techniques to obtain complementary information from the same sample.

Magnetic resonance microscopy contribution to interpret high-resolution magic angle spinning metabolomic data of human tumor tissue.

HRMAS NMR is considered a valuable technique to obtain detailed metabolic profile of unprocessed tissues. To properly interpret the HRMAS metabolomic results, detailed information of the actual state of the sample inside the rotor is needed. MRM (Magnetic Resonance Microscopy) was applied for obtaining structural and spatially localized metabolic information of the samples inside the HRMAS rotors. The tissue was observed stuck to the rotor wall under the effect of HRMAS spinning. MRM spectroscopy showed a transference of metabolites from the tissue to the medium. The sample shape and the metabolite transfer after HRMAS indicated that tissue had undergone alterations and it can not be strictly considered as intact. This must be considered when HRMAS is used for metabolic tissue characterization, and it is expected to be highly dependent on the manipulation of the sample. The localized spectroscopic information of MRM reveals the biochemical compartmentalization on tissue samples hidden in the HRMAS spectrum.

Compatibility between 3T 1H SV-MRS data and automatic brain tumour diagnosis support systems based on databases of 1.5T 1H SV-MRS spectra.

OBJECT: This study demonstrates that 3T SV-MRS data can be used with the currently available automatic brain tumour diagnostic classifiers which were trained on databases of 1.5T spectra. This will allow the existing large databases of 1.5T MRS data to be used for diagnostic classification of 3T spectra, and perhaps also the combination of 1.5T and 3T databases. MATERIALS AND METHODS: Brain tumour classifiers trained with 154 1.5T spectra to discriminate among high grade malignant tumours and common grade II glial tumours were evaluated with a subsequently-acquired set of 155 1.5T and 37 3T spectra. A similarity study between spectra and main brain tumour metabolite ratios for both field strengths (1.5T and 3T) was also performed. RESULTS: Our results showed that classifiers trained with 1.5T samples had similar accuracy for both test datasets (0.87 ± 0.03 for 1.5T and 0.88 ± 0.03 for 3.0T). Moreover, non-significant differences were observed with most metabolite ratios and spectral patterns. CONCLUSION: These results encourage the use of existing classifiers based on 1.5T datasets for diagnosis with 3T (1)H SV-MRS. The large 1.5T databases compiled throughout many years and the prediction models based on 1.5T acquisitions can therefore continue to be used with data from the new 3T instruments.

Metabolic profile of chronic liver disease by NMR spectroscopy of human biopsies.

Among the different processes occurring during the evolution of liver disease, fibrosis has a predominant role. Liver fibrosis mechanisms are fairly constant irrespective of the underlying etiology. Cirrhosis is the end-stage of this reaction. Metabolic profiles, which are affected by many physiological and pathological processes, may provide further insight into the metabolic consequences of this severe liver disease. The aim of this study was to demonstrate the applicability of 1H high resolution magic angle spinning (HR-MAS) NMR spectroscopy in the biochemical profile determination of human liver needle biopsy samples for the characterization of metabolic alterations related to the severity of liver disease. We recorded and analyzed HR-MAS spectra of 68 liver tissue samples obtained by needle biopsy from patients with chronic liver disease. Multivariate analysis was applied to these data to obtain discrimination patterns and to reveal relevant metabolites. The metabolic characterization of liver tissue from needle biopsies by HR-MAS NMR spectroscopy provided differential patterns for cirrhotic and non-cirrhotic chronic liver disease tissue. Metabolites closely related to the liver metabolism such as some fatty acids, glucose and amino acids show differences between the two groups. Phospholipid precursors, which have been previously correlated with hepatic lesions also show differences. Furthermore, the correlation between histologically assessed liver disease stages and the levels of the most discriminative metabolites show that liver dysfunction is present at the initial stages of chronic hepatic lesions. Overall, this work suggests that the additional information obtained by NMR metabolomics applied to needle biopsies of human liver may be useful for assessing metabolic alterations and liver dysfunction in chronic liver disease.

Metabolite identification in human liver needle biopsies by high-resolution magic angle spinning 1H NMR spectroscopy.

High-resolution magic angle spinning (HR-MAS) 1H NMR spectroscopy of intact human liver needle biopsies has not been previously reported. HR-MAS NMR spectra collected on 17 specimens with tissue amounts between approximately 0.5 and 12 mg showed very good spectral resolution and signal-to-noise ratios. One-dimensional 1H spectra revealed many intense signals corresponding to cellular metabolites. In addition, some high molecular weight metabolites, such as glycogen and mobile fatty acids, could be observed in some spectra. Resonance assignments for 22 metabolites were obtained by combining the analysis of three different types of 1D 1H spectral editing, such as T2 filtering or the nuclear Overhauser effect and 2D TOCSY and 13C-HSQC spectra. Biochemical stability of the liver tissue during up to 16 h of magic angle spinning at 277 K was studied. Biochemical trends corresponding to the different pathologies were observed, involving free fragments of lipids among other metabolites. NMR signal intensity ratios can be useful for discrimination among non-pathological, hepatitis C affected and cirrhotic liver tissues. Overall, this work demonstrates the applicability of HR-MAS NMR spectroscopy to the biochemical characterization of needle biopsies of the human liver.