Andrew C. Peet

A constrained least-squares approach to the automated quantitation of in vivo 1H magnetic resonance spectroscopy data

Totally Automatic Robust Quantitation in NMR (TARQUIN), a new method for the fully automatic analysis of short echo time in vivo 1H Magnetic resonance spectroscopy is presented. Analysis is performed in the time domain using non‐negative least squares, and a new method for applying soft constraints to signal amplitudes is used to improve fitting stability. Initial point truncation and Hankel singular value decomposition water removal are used to reduce baseline interference. Three methods were used to test performance. First, metabolite concentrations from six healthy volunteers at 3 T were compared with LCModel™. Second, a Monte‐Carlo simulation was performed and results were compared with LCModel™ to test the accuracy of the new method. Finally, the new algorithm was applied to 1956 spectra, acquired clinically at 1.5 T, to test robustness to noisy, abnormal, artifactual, and poorly shimmed spectra. Discrepancies of less than approximately 20% were found between the main metabolite concentrations determined by TARQUIN and LCModel™ from healthy volunteer data. The Monte‐Carlo simulation revealed that errors in metabolite concentration estimates were comparable with LCModel™. TARQUIN analyses were also found to be robust to clinical data of variable quality. In conclusion, TARQUIN has been shown to be an accurate and robust algorithm for the analysis of magnetic resonance spectroscopy data making it suitable for use in a clinical setting. Magn Reson Med, 2010.

On the Design of a Web-Based Decision Support System for Brain Tumour Diagnosis Using Distributed Agents

This paper introduces HealthAgents, an EC-funded research project to improve the classification of brain tumours through multi-agent decision support over a distributed network of local databases or data marts. HealthAgents will not only develop new pattern recognition methods for a distributed classification and analysis of in vivo MRS and ex vivo/in vitro HRMAS and DNA data, but also define a method to assess the quality and usability of a new candidate local database containing a set of new cases, based on a compatibility score

An algorithm for the automated quantitation of metabolites in in vitro NMR signals.

The quantitation of metabolite concentrations from in vitro NMR spectra is hampered by the sensitivity of peak positions to experimental conditions. The quantitation methods currently available are generally labor intensive and cannot readily be automated. Here, an algorithm is presented for the automatic time domain analysis of high‐resolution NMR spectra. The TARQUIN algorithm uses a set of basis functions obtained by quantum mechanical simulation using predetermined parameters. Each basis function is optimized by subdividing it into a set of signals from magnetically equivalent spins and varying the simulated chemical shifts of each of these groups to match the signal undergoing analysis. A novel approach to the standard multidimensional minimization problem is introduced based on evaluating the fit resulting from different permutations of possible chemical shifts, obtained from one‐dimensional searches. Results are presented from the analysis of 1H proton magic angle spinning spectra of cell lines illustrating the robustness of the method in a typical application. Simulation was used to investigate the biggest peak shifts that can be tolerated. Magn Reson Med, 2006.

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.

Non-invasive detection of glycine as a biomarker of malignancy in childhood brain tumours usingin-vivo1H MRS at 1.5 Tesla confirmed byex-vivohigh-resolution magic-angle spinning NMR

Management of brain tumours in children would benefit from improved non‐invasive diagnosis, characterisation and prognostic biomarkers. Metabolite profiles derived from in‐vivo MRS have been shown to provide such information. Studies indicate that using optimum a priori information on metabolite contents in the construction of linear combination (LC) models of MR spectra leads to improved metabolite profile estimation. Glycine (Gly) is usually neglected in such models due to strong overlap with myo‐inositol (mI) and a low concentration in normal brain. However, biological studies indicate that Gly is abundant in high‐grade brain tumours. This study aimed to investigate the quantitation of Gly in paediatric brain tumours using MRS analysed by LCModel™, and its potential as a non‐invasive biomarker of malignancy. Single‐voxel MRS was performed using PRESS (TR 1500 ms, TE 30 ms/135 ms) on a 1.5 T scanner. Forty‐seven cases (18 high grade (HG), 17 low grade (LG), 12 ungraded) were retrospectively selected if both short‐TE and long‐TE MRS (n = 33) or short‐TE MRS and high‐resolution magic‐angle spinning (HRMAS) of matched surgical samples (n = 15) were available. The inclusion of Gly in LCModel™ analyses led to significantly reduced fit residues for both short‐TE and long‐TE MRS (p < 0.05). The Gly concentrations estimated from short‐TE MRS were significantly correlated with the long‐TE values (R = 0.91, p < 0.001). The Gly concentration estimated by LCModel™ was significantly higher in HG versus LG tumours for both short‐TE (p < 1e‐6) and long‐TE (p = 0.003) MRS. This was consistent with the HRMAS results, which showed a significantly higher normalised Gly concentration in HG tumours (p < 0.05) and a significant correlation with the normalised Gly concentration measured from short‐TE in‐vivo MRS (p < 0.05). This study suggests that glycine can be reliably detected in paediatric brain tumours using in‐vivo MRS on standard clinical scanners and that it is a promising biomarker of tumour aggressiveness. Copyright

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.

Pediatric brain tumor cancer stem cells: cell cycle dynamics, DNA repair, and etoposide extrusion

Reliable model systems are needed to elucidate the role cancer stem cells (CSCs) play in pediatric brain tumor drug resistance. The majority of studies to date have focused on clinically distinct adult tumors and restricted tumor types. Here, the CSC component of 7 newly established primary pediatric cell lines (2 ependymomas, 2 medulloblastomas, 2 gliomas, and a CNS primitive neuroectodermal tumor) was thoroughly characterized. Comparison of DNA copy number with the original corresponding tumor demonstrated that genomic changes present in the original tumor, typical of that particular tumor type, were retained in culture. In each case, the CSC component was approximately 3–4-fold enriched in neurosphere culture compared with monolayer culture, and a higher capacity for multilineage differentiation was observed for neurosphere-derived cells. DNA content profiles of neurosphere-derived cells expressing the CSC marker nestin demonstrated the presence of cells in all phases of the cell cycle, indicating that not all CSCs are quiescent. Furthermore, neurosphere-derived cells demonstrated an increased resistance to etoposide compared with monolayer-derived cells, having lower initial DNA damage, potentially due to a combination of increased drug extrusion by ATP-binding cassette multidrug transporters and enhanced rates of DNA repair. Finally, orthotopic xenograft models reflecting the tumor of origin were established from these cell lines. In summary, these cell lines and the approach taken provide a robust model system that can be used to develop our understanding of the biology of CSCs in pediatric brain tumors and other cancer types and to preclinically test therapeutic 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

Functional imaging in adult and paediatric brain tumours

Imaging is a key component in the management of brain tumours, with MRI being the preferred modality for most clinical scenarios. However, although conventional MRI provides mainly structural information, such as tumour size and location, it leaves many important clinical questions, such as tumour type, aggressiveness and prognosis, unanswered. An increasing number of studies have shown that additional information can be obtained using functional imaging methods (which probe tissue properties), and that these techniques can give key information of clinical importance. These techniques include diffusion imaging, which can assess tissue structure, and perfusion imaging and magnetic resonance spectroscopy, which measures tissue metabolite profiles. Tumour metabolism can also be investigated using PET, with 18F-deoxyglucose being the most readily available tracer. This Review discusses these methods and the studies that have investigated their clinical use. A strong emphasis is placed on the measurement of quantitative parameters, which is a move away from the qualitative nature of conventional radiological reporting and presents major challenges, particularly for multicentre studies.