1 H MRS has great potential for the clinical investigation of childhood brain tumours, but the low incidence in, and difficulties of performing trials on, children have hampered progress in this area. Most studies have used a long-TE, thus limiting the metabolite information obtained, and multivariate analysis has been largely unexplored. Thirty-five children with untreated cerebellar tumours (18 medulloblastomas, 12 pilocytic astrocytomas and five ependymomas) were investigated using a single-voxel short-TE PRESS sequence on a 1.5 T scanner. Spectra were analysed using LCModel TM to yield metabolite profiles, and key metabolite assignments were verified by comparison with high-resolution magic-angle-spinning NMR of representative tumour biopsy samples. In addition to univariate metabolite comparisons, the use of multivariate classifiers was investigated. Principal component analysis was used for dimension reduction, and linear discriminant analysis was used for variable selection and classification. A bootstrap cross-validation method suitable for estimating the true performance of classifiers in small datasets was used. The discriminant function coefficients were stable and showed that medulloblastomas were characterised by high taurine, phosphocholine and glutamate and low glutamine, astrocytomas were distinguished by low creatine and high N-acetylaspartate, and ependymomas were differentiated by high myo-inositol and glycerophosphocholine. The same metabolite features were seen in NMR spectra of ex vivo samples. Successful classification was achieved for glial-cell (astrocytoma þ ependymoma) versus non-glial-cell (medulloblastoma) tumours, with a bootstrap 0.632 þ error, e B.632þ , of 5.3%. For astrocytoma vs medulloblastoma and astrocytoma vs medulloblastoma vs ependymoma classification, the e B.632þ was 6.9% and 7.1%, respectively. The study showed that 1 H MRS detects key differences in the metabolite profiles for the main types of childhood cerebellar tumours and that discriminant analysis of metabolite profiles is a promising tool for classification. The findings warrant confirmation by larger multi-centre studies.
ElsevierVicente Robledo, J.; Fuster Garcia, E.; Tortajada Velert, S.; García Gómez, JM.; Davies, N.; Natarajan, K.; Wilson, M.... (2013) Integration. Linear Discriminant Analysis 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 TE significantly improved the classification performance (p < 0.01, Tukeyʼs test) compared with the use of one TE alone. 3Other tumour types were classified accurately as glial or primitive neuroectodermal (BAR 1.00). 12 cases failed the inclusion criteria for QC mainly due to poor SNR. Conclusions Classification and evaluation 9The diagnostic classification problem of discriminating between EPEN, PILOA and MED, the three most common pediatric tumour types, is addressed in this study. Since EPEN and PILOA tumours can be found in brain locations other than the PF whereas MED are found only in the PF, training was undertaken twice, once using the tumour cases located in the PF and then with those in any brain location. Classifiers were designed and evaluated using features from Short-TE and Long-TE alone and a combination of both TEs, ShortTE+Long-TE. Our results were compared with those in previous studies [27][28][29][30].Based on the results of previous studies [15,20,26,29 Results Spectral featuresSeveral key features allow visual discrimination of PILOA, EPEN and MED. Figures 1 and 2 show the Short-TE and Long-TE mean spectra of the tumour types. Minimum differences are found between the mean spectra of the tumours in the PF and those in any location. All tumour spectra display an increase in Cho peak (3.2ppm) with respect to Cr peak (3.0ppm). NAA (2.0ppm) presents a less prominent peak in MED and EPEN compared with 10 PILOA. Elevation of macromolecules and lipids (0.9ppm and 1.3ppm) is observed in Short-TE. Regarding Long-TE, the inverted peak of Lac at 1.3ppm is distinguished in PILOA and EPEN but not in MED. Tables 2 and 3 show the metabolite concentrations estimated with TARQUIN in Short-TE and Long-TE for the three tumour types found in any brain location. The Kruskal-Wallis test for the analysis of the variance (α=0.05) was applied to determine the significant differences in metabolite concentrations of PILOA, EPEN and MED. Both Cho components, Glycerophosphocholine (GPC) and Phosphocholine (PCh) (p≤0.01) showed significant differences. Cr and Tau concentrations were significantly different in both TEs (p≤0.01). Univariate metabolite comparisonDifferences in the mI concentrations (p≤0.01) were significant in Short-TE.Macromolecules and lipids at 0.9, 1.3 and 2.0ppm (p≤0.05, p≤0.01 and p≤0.01, respectively) exhibited statistical differences in Short-TE MRS. Classification DiscussionThis is the first study of MRS as a non-invasive diagnostic aid in childhood brain tumo...
Children with isolated CM-I do not have a PFV smaller than normal, whereas children with both CM-I and syringomyelia have a PFV significantly smaller than normal. This result indicates that the two subgroups may represent different phenotypic expression or even a different pathogenesis.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.