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A Moreno-Torres

Publications and source records attributed to A Moreno-Torres.

5 recordsLinked to original sources
PubMed2004

Brain tumor classification based on long echo proton MRS signals.

There has been a growing research interest in brain tumor classification based on proton magnetic resonance spectroscopy (1H MRS) signals. Four research centers within the EU funded INTERPRET project have acquired a significant number of long echo 1H MRS signals for brain tumor classification. In this paper, we present an objective comparison of several classification techniques applied to the discrimination of four types of brain tumors: meningiomas, glioblastomas, astrocytomas grade II and metastases. Linear and non-linear classifiers are compared: linear discriminant analysis (LDA), support vector machines (SVM) and least squares SVM (LS-SVM) with a linear kernel as linear techniques and LS-SVM with a radial basis function (RBF) kernel as a non-linear technique. Kernel-based methods can perform well in processing high dimensional data. This motivates the inclusion of SVM and LS-SVM in this study. The analysis includes optimal input variable selection, (hyper-) parameter estimation, followed by performance evaluation. The classification performance is evaluated over 200 stratified random samplings of the dataset into training and test sets. Receiver operating characteristic (ROC) curve analysis measures the performance of binary classification, while for multiclass classification, we consider the accuracy as performance measure. Based on the complete magnitude spectra, automated binary classifiers are able to reach an area under the ROC curve (AUC) of more than 0.9 except for the hard case glioblastomas versus metastases. Although, based on the available long echo 1H MRS data, we did not find any statistically significant difference between the performances of LDA and the kernel-based methods, the latter have the strength that no dimensionality reduction is required to obtain such a high performance.

Artificial Intelligence↗
PubMed2004

Classification of brain tumours using short echo time 1H MR spectra.

The purpose was to objectively compare the application of several techniques and the use of several input features for brain tumour classification using Magnetic Resonance Spectroscopy (MRS). Short echo time 1H MRS signals from patients with glioblastomas (n = 87), meningiomas (n = 57), metastases (n = 39), and astrocytomas grade II (n = 22) were provided by six centres in the European Union funded INTERPRET project. Linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel and LS-SVM with radial basis function kernel were applied and evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic curve (AUC) was used to measure the performance of binary classifiers, while the percentage of correct classifications was used to evaluate the multiclass classifiers. The influence of several factors on the classification performance has been tested: L2- vs. water normalization, magnitude vs. real spectra and baseline correction. The effect of input feature reduction was also investigated by using only the selected frequency regions containing the most discriminatory information, and peak integrated values. Using L2-normalized complete spectra the automated binary classifiers reached a mean test AUC of more than 0.95, except for glioblastomas vs. metastases. Similar results were obtained for all classification techniques and input features except for water normalized spectra, where classification performance was lower. This indicates that data acquisition and processing can be simplified for classification purposes, excluding the need for separate water signal acquisition, baseline correction or phasing.

Brain Chemistry↗
PubMed2002

Tricarboxylic acid cycle of glia in the in vivo human brain.

In the brain, acetate is exclusively oxidized by glia. To determine the contribution of glial metabolism to the tricarboxylic acid cycle (TCA), 1-(13)C-acetate was infused in six studies in three normal adult subjects and -one epileptic receiving valproic acid for seizure control. Ten grams of 99% 1-(13)C labeled acetate were infused intravenously as a 3.3% w/v solution over 60 min, during which in vivo 13C MR spectra of the brain were acquired. As expected, 13C label rapidly enriched cerebral bicarbonate, glutamate and glutamine C5. The mean rate of acetate oxidation calculated from steady-state 13C enrichment of bicarbonate in fasted normal subjects was 0.13 +/- 0.03 micromol/g/min (n=4), approximately 20% of the total cerebral TCA cycle rate.

Acetates↗
PubMed2001

[1-13C]glucose MRS in chronic hepatic encephalopathy in man.

[1-13C]-labeled glucose was infused intravenously in a single dose of 0.2 g/kg body weight over 15 min in six patients with chronic hepatic encephalopathy, and three controls. Serial 13C MR spectra of the brain were acquired. Patients exhibited the following characteristics relative to normal controls: 1) Cerebral glutamine concentration was increased (12.6 +/- 3.8 vs. 6.5 +/- 1.9 mmol/kg, P < 0.006) and glutamate was reduced (8.2 +/- 1.0 vs. 9.9 +/- 0.6 mmol/kg, P < 0.02). 2) 13C incorporation into glutamate C4 and C2 positions was reduced in patients (80 min after start of infusion C4: 0.43 +/- 0.09 vs. 0.84 +/- 0.15 mmol/kg, P < 0.001; C2: 0.20 +/- 0.03 vs. 0.45 +/- 0.07 mmol/kg, P < 0.0001). 3) 13C incorporation into bicarbonate was delayed (90 +/- 21 vs. 40 +/- 10 min, P < 0.003), and the time interval between detection of glutamate C4 and C2 labeling was longer in patients (22 +/- 8 vs. 12 +/- 3 min, P < 0.03). 4) Glutamate C2 turnover time was reduced in chronic hepatic encephalopathy (17.1 +/- 6.8 vs. 49.6 +/- 8.7 min, P < 0.0002). 5) 13C accumulation into glutamine C2 relative to its substrate glutamate C2 increased progressively with the severity of clinical symptoms (r = 0.96, P < 0.01). These data indicate disturbed neurotransmitter glutamate/glutamine cycling and reduced glucose oxidation in chronic hepatic encephalopathy. [1-13C] glucose MRS provides novel insights into disease progression and the pathophysiology of chronic hepatic encephalopathy.

Aged↗