Nigel P. Davies

Selective arterial spin labeling (SASL): perfusion territory mapping of selected feeding arteries tagged using two-dimensional radiofrequency pulses.

To date, most perfusion magnetic resonance imaging (MRI) methods using arterial spin labeling (ASL) have employed slab‐selective inversion pulses or continuous labeling within a plane in order to obtain maps derived from all major blood vessels entering the brain. However, there is great potential for gaining additional information on the territories perfused by the major vessels if individual feeding arteries could be tagged. This study demonstrates noninvasive arterial perfusion territory maps obtained using two‐dimensional (2D) selective inversion pulses. This method is designated “selective ASL” (SASL). The SASL method was used to tag the major arteries below the circle of Willis. A combination of 2D selective tagging and multislice readout allows perfusion territories to be clearly visualized, with likely applications to cerebrovascular disease and stroke. Magn Reson Med 49:1133–1142, 2003.

Multi-centre reproducibility of diffusion MRI parameters for clinical sequences in the brain.

The purpose of this work was to assess the reproducibility of diffusion imaging, and in particular the apparent diffusion coefficient (ADC), intra‐voxel incoherent motion (IVIM) parameters and diffusion tensor imaging (DTI) parameters, across multiple centres using clinically available protocols with limited harmonization between sequences.

High resolution magic angle spinning 1H NMR of childhood brain and nervous system tumours

BackgroundBrain and nervous system tumours are the most common solid cancers in children. Molecular characterisation of these tumours is important for providing novel biomarkers of disease and identifying molecular pathways which may provide putative targets for new therapies. 1H magic angle spinning NMR spectroscopy (1H HR-MAS) is a powerful tool for determining metabolite profiles from small pieces of intact tissue and could potentially provide important molecular information.MethodsForty tissue samples from 29 children with glial and primitive neuro-ectodermal tumours were analysed using HR-MAS (600 MHz Varian gHX nanoprobe). Tumour spectra were fitted to a library of individual metabolite spectra to provide metabolite values. These values were then used in a two tailed t-test and multi-variate analysis employing a principal component analysis and a linear discriminant analysis. Classification accuracy was estimated using a leave-one-out analysis and B632+ bootstrapping.ResultsGlial tumours had significantly (two tailed t-test p < 0.05) higher creatine and glutamine and lower taurine, phosphoethanolamine, phosphorylcholine and choline compared with primitive neuro-ectodermal tumours. Classification accuracy was 90%. Medulloblastomas (n = 9) had significantly (two tailed t-test p < 0.05) higher creatine, glutamine, phosphorylcholine, glycine and scyllo-inositol than neuroblastomas (n = 7), classification accuracy was 94%. Supratentorial primitive neuro-ectodermal tumours had metabolite profiles in keeping with other primitive neuro-ectodermal tumours whilst ependymomas (n = 2) had metabolite profiles intermediate between pilocytic astrocytomas (n = 10) and primitive neuro-ectodermal tumours.ConclusionHR-MAS identified key differences in the metabolite profiles of childhood brain and nervous system improving the molecular characterisation of these tumours. Further investigation of the underlying molecular pathways is required to assess their potential as targets for new agents.

Accurate classification of childhood brain tumours by in vivo 1H MRS – A multi-centre study

AIMS To evaluate the accuracy of single-voxel Magnetic Resonance Spectroscopy ((1)H MRS) as a non-invasive diagnostic aid for paediatric brain tumours in a multi-national study. Our hypotheses are (1) that automated classification based on (1)H MRS provides an accurate non-invasive diagnosis in multi-centre datasets and (2) using a protocol which increases the metabolite information improves the diagnostic accuracy. METHODS Seventy-eight patients under 16 years old with histologically proven brain tumours from 10 international centres were investigated. Discrimination of 29 medulloblastomas, 11 ependymomas and 38 pilocytic astrocytomas (PILOAs) was evaluated. Single-voxel MRS was undertaken prior to diagnosis (1.5 T Point-Resolved Spectroscopy (PRESS), Proton Brain Exam (PROBE) or Stimulated Echo Acquisition Mode (STEAM), echo time (TE) 20-32 ms and 135-136 ms). MRS data were processed using two strategies, determination of metabolite concentrations using TARQUIN software and automatic feature extraction with Peak Integration (PI). Linear Discriminant Analysis (LDA) was applied to this data to produce diagnostic classifiers. An evaluation of the diagnostic accuracy was performed based on resampling to measure the Balanced Accuracy Rate (BAR). RESULTS The accuracy of the diagnostic classifiers for discriminating the three tumour types was found to be high (BAR 0.98) when a combination of TE was used. The combination of both TEs significantly improved the classification performance (p<0.01, Tukeys test) compared with the use of one TE alone. Other tumour types were classified accurately as glial or primitive neuroectodermal (BAR 1.00). CONCLUSION (1)H MRS has excellent accuracy for the non-invasive diagnosis of common childhood brain tumours particularly if the metabolite information is maximised and should become part of routine clinical assessment for these children.

A quantitative comparison of metabolite signals as detected by in vivo MRS with ex vivo1H HR-MAS for childhood brain tumours†

1H MRS provides a powerful method for investigating tumour metabolism by allowing the measurement of metabolites in vivo. Recently, the technique of 1H high‐resolution magic angle spinning (HR‐MAS) has been shown to produce high‐quality data, allowing the accurate measurement of many metabolites present in unprocessed biopsy tissue. The purpose of this study was to evaluate the agreement between the techniques of in vivo MRS and ex vivo HR‐MAS for investigating childhood brain tumours. Short‐TE (30 ms), single‐voxel, in vivo MRS was performed on 16 paediatric patients with brain tumours at 1.5 T. A frozen biopsy sample was available for each patient. HR‐MAS was performed on the biopsy samples, and metabolite quantities were determined from the MRS and HR‐MAS data using the LCModel™ and TARQUIN algorithms, respectively. Linear regression was performed on the metabolite quantities to asses the agreement between MRS and HR‐MAS. Eight of the 12 metabolite quantities were found to correlate significantly (P < 0.05). The four worst correlating metabolites were aspartate, scyllo‐inositol, glycerophosphocholine and N‐acetylaspartate, and, except for glycerophosphocholine, this error was reflected in their higher Cramer–Rao lower bounds (CRLBs), suggesting that low signal‐to‐noise was the greatest source of error for these metabolites. Glycerophosphocholine had a lower CRLB implying that interference with phosphocholine and choline was the most significant source of error. The generally good agreement observed between the two techniques suggests that both MRS and HR‐MAS can be used to reliably estimate metabolite quantities in brain tumour tissue and that tumour heterogeneity and metabolite degradation do not have an important effect on the HR‐MAS metabolite profile for the tumours investigated. HR‐MAS can be used to improve the analysis and understanding of MRS data. Copyright

MR spectroscopy-based brain metabolite profiling in propionic acidaemia: metabolic changes in the basal ganglia during acute decompensation and effect of liver transplantation

BackgroundPropionic acidaemia (PA) results from deficiency of Propionyl CoA carboxylase, the commonest form presenting in the neonatal period. Despite best current management, PA is associated with severe neurological sequelae, in particular movement disorders resulting from basal ganglia infarction, although the pathogenesis remains poorly understood. The role of liver transplantation remains controversial but may confer some neuro-protection. The present study utilises quantitative magnetic resonance spectroscopy (MRS) to investigate brain metabolite alterations in propionic acidaemia during metabolic stability and acute encephalopathic episodes.MethodsQuantitative MRS was used to evaluate brain metabolites in eight children with neonatal onset propionic acidaemia, with six elective studies acquired during metabolic stability and five studies during acute encephalopathic episodes. MRS studies were acquired concurrently with clinically indicated MR imaging studies at 1.5 Tesla. LCModel software was used to provide metabolite quantification. Comparison was made with a dataset of MRS metabolite concentrations from a cohort of children with normal appearing MR imaging.ResultsMRI findings confirm the vulnerability of basal ganglia to infarction during acute encephalopathy. We identified statistically significant decreases in basal ganglia glutamate+glutamine and N-Acetylaspartate, and increase in lactate, during encephalopathic episodes. In white matter lactate was significantly elevated but other metabolites not significantly altered. Metabolite data from two children who had received liver transplantation were not significantly different from the comparator group.ConclusionsThe metabolite alterations seen in propionic acidaemia in the basal ganglia during acute encephalopathy reflect loss of viable neurons, and a switch to anaerobic respiration. The decrease in glutamine + glutamate supports the hypothesis that they are consumed to replenish a compromised Krebs cycle and that this is a marker of compromised aerobic respiration within brain tissue. Thus there is a need for improved brain protective strategies during acute metabolic decompensations. MRS provides a non-invasive tool for which could be employed to evaluate novel treatments aimed at restoring basal ganglia homeostasis. The results from the liver transplantation sub-group supports the hypothesis that liver transplantation provides systemic metabolic stability by providing a hepatic pool of functional propionyl CoA carboxylase, thus preventing further acute decompensations which are associated with the risk of brain infarction.

Calibration of gradient propagation delays for accurate two-dimensional radiofrequency pulses.

Hardware‐related delays between the requested and actual start times of the gradient waveforms on each physical axis are of particular importance for multidimensional selective excitation in which the synchronization of gradient and radiofrequency (RF) waveforms is critical. A method is proposed for the accurate calibration of gradient propagation delays to optimize the spatial accuracy of 2D RF pulses, although the results may also be used to reduce artifacts in other MR techniques. The sensitivity of 2D RF pulses to uncorrected time shifts between the gradient and RF waveforms was exploited to calibrate accurately the propagation delays on each physical gradient axis. This was achieved using a technique that relates the effect of gradient delays in the component waveforms of a constant‐angular rate spiral k‐space trajectory 2D RF pulse to the spatial location of the subsequent excitation profile. Comparison was also made with a procedure based on a previously described k‐space plotting method, showing broad agreement, but with some discrepancies that illustrate the value of a self‐referenced correction method for multidimensional RF pulses. Magn Reson Med 53:231–236, 2005.

A comparative study of feature extraction and blind source separation of independent component analysis (ICA) on childhood brain tumour 1H magnetic resonance spectra

Independent component analysis (ICA) has the potential of determining automatically the metabolite signals which make up MR spectra. However, the realiability with which this is accomplished and the optimal approach for investigating in vivo MRS have not been determined. Furthermore, the properties of ICA in brain tumour MRS with respect to dataset size and data quality have not been systematically explored. The two common techniques for applying ICA, blind source separation (BSS) and feature extraction (FE) were examined in this study using simulated data and the findings confirmed on patient data. Short echo time (TE 30 ms), low and high field (1.5 and 3 T) in vivo brain tumour MR spectra of childhood astrocytoma, ependymoma and medulloblastoma were generated by using a quantum mechanical simulator with ten metabolite and lipid components. Patient data (TE 30 ms, 1.5 T) were acquired from children with brain tumours. ICA of simulated data shows that individual metabolite components can be extracted from a set of MRS data. The BSS method generates independent components with a closer correlation to the original metabolite and lipid components than the FE method when the number of spectra in the dataset is small. The experiments also show that stable results are achieved with 300 MRS at an SNR equal to 10. The FE method is relatively insensitive to different ranges of full width at half maximum (FWHM) (from 0 to 3 Hz), whereas the BSS method degrades on increasing the range of FWHM. The peak frequency variations do not affect the results within the range of ±0.08 ppm for the FE method, and ±0.05 ppm for the BSS method. When the methods were applied to the patient dataset, results consistent with the synthesized experiments were obtained. Copyright

The value of magnetic resonance spectroscopy in tumour imaging

Magnetic resonance (MR) imaging has a key role in the management of many childhood tumours. There is increasing interest in extending these investigations to MR techniques that give information on tumour biology in vivo . Magnetic resonance spectroscopy (MRS) is one such method and it provides information on tissue biochemistry. Promising results have been obtained from many preclinical and clinical studies, leading to an expectation that MRS will play a valuable clinical role. However, the role of MRS is not yet well defined and there is a paucity of data from multi-centre clinical trials. In this article we concentrate on MRS in paediatric oncology and provide some general guidance on current applications and outline areas that need to be developed further. Certain atomic nuclei (eg, 1H, 31P and 13C) possess a magnetic moment and when placed in a strong magnetic field will resonate at a particular radiofrequency that subtly depends upon the chemical environment. In MR spectroscopy, the frequencies and intensities of these resonances are measured and represented graphically in an MR spectrum. The most commonly available method clinically is 1H MRS, and the 1H spectrum is a biochemical profile of the small mobile metabolites and macromolecules present in the tissue. 1H MRS can be performed with a standard clinical MRI scanner as part of a conventional MRI investigation. An example 1H spectrum from normal brain is given in figure 1. The horizontal scale, in units of parts per million (ppm), represents signal frequency adjusted to be invariant to the strength of the magnetic field of the MR scanner. Each metabolite is identified by one or more peaks at specific ppm values with the areas under the peaks being proportional to the metabolite concentration. The main metabolites observed are N-acetyl aspartate (NAA), …

1H magnetic resonance spectroscopy in the diagnosis of paediatric low grade brain tumours

INTRODUCTION Low grade gliomas are the commonest brain tumours in children but present in a myriad of ways, each with its own treatment challenges. Conventional MRI scans play an important role in their management but have limited ability to identify likely clinical behaviour. The aim of this study is to investigate (1)H magnetic resonance spectroscopy (MRS) as a method for detecting differences between the various low grade gliomas and related tumours in children. PATIENTS AND METHODS Short echo time single voxel (1)H MRS at 1.5 or 3.0 T was performed prior to treatment on children with low grade brain tumours at two centres and five MR scanners, 69 cases had data which passed quality control. MRS data was processed using LCModel to give mean spectra and metabolite concentrations which were compared using T-tests, ANOVA, Receiver Operator Characteristic curves and logistic regression in SPSS. RESULTS Significant differences were found in concentrations of key metabolites between glioneuronal and glial tumours (T-test p<0.05) and between most of the individual histological subtypes of low grade gliomas. The discriminatory metabolites identified, such as choline and myoinositol, are known tumour biomarkers. In the set of pilocytic astrocytomas and unbiopsied optic pathway gliomas, significant differences (p<0.05, ANOVA) were found in metabolite profiles of tumours depending on location and patient neurofibromatosis type 1 status. Logistic regression analyses yielded equations which could be used to assess the probability of a tumour being of a specific type. CONCLUSIONS MRS can detect subtle differences between low grade brain tumours in children and should form part of the clinical assessment of these tumours.