Fast nosologic imaging of the brain.

Magnetic resonance spectroscopic imaging (MRSI) provides information about the spatial metabolic heterogeneity of an organ in the human body. In this way, MRSI can be used to detect tissue regions with abnormal metabolism, e.g. tumor tissue. The main drawback of MRSI in clinical practice is that the analysis of the data requires a lot of expertise from the radiologists. In this article, we present an automatic method that assigns each voxel of a spectroscopic image of the brain to a histopathological class. The method is based on Canonical Correlation Analysis (CCA), which has recently been shown to be a robust technique for tissue typing. In CCA, the spectral as well as the spatial information about the voxel is used to assign it to a class. This has advantages over other methods that only use spectral information since histopathological classes are normally covering neighbouring voxels. In this paper, a new CCA-based method is introduced in which MRSI and MR imaging information is integrated. The performance of tissue typing is compared for CCA applied to the whole MR spectra and to sets of features obtained from the spectra. Tests on simulated and in vivo MRSI data show that the new method is very accurate in terms of classification and segmentation. The results also show the advantage of combining spectroscopic and imaging data.

The use of multivariate MR imaging intensities versus metabolic data from MR spectroscopic imaging for brain tumour classification.

This study investigated the value of information from both magnetic resonance imaging and magnetic resonance spectroscopic imaging (MRSI) to automated discrimination of brain tumours. The influence of imaging intensities and metabolic data was tested by comparing the use of MR spectra from MRSI, MR imaging intensities, peak integration values obtained from the MR spectra and a combination of the latter two. Three classification techniques were objectively compared: linear discriminant analysis, least squares support vector machines (LS-SVM) with a linear kernel as linear techniques and LS-SVM with radial basis function kernel as a nonlinear technique. Classifiers were evaluated over 100 stratified random splittings of the dataset into training and test sets. The area under the receiver operating characteristic (ROC) curve (AUC) was used as a global performance measure on test data. In general, all techniques obtained a high performance when using peak integration values with or without MR imaging intensities. For example for low- versus high-grade tumours, low- versus high-grade gliomas and gliomas versus meningiomas, the mean test AUC was higher than 0.91, 0.94, and 0.99, respectively, when both MR imaging intensities and peak integration values were used. The use of metabolic data from MRSI significantly improved automated classification of brain tumour types compared to the use of MR imaging intensities solely.

Characterization and validation of noninvasive oxygen tension measurements in human glioma xenografts by 19F-MR relaxometry.

PURPOSE: The aim of this study was to characterize and to validate noninvasive 19F-magnetic resonance relaxometry for the measurement of oxygen tensions in human glioma xenografts in nude mice. The following three questions were addressed: 1. When perfluorocarbon compounds (PFCs) are administrated intravenously, which tumor regions are assessed by 19F-MR relaxometry? 2. Are oxygen tension as detected by 19F-MR relaxometry (pO2/relaxo) comparable to Eppendorf O2-electrode measurements (pO2/electrode)? 3. Can 19F-MR relaxometry be used to detect oxygen tension changes in tumor tissue during carbogen breathing? METHODS AND MATERIALS: Slice-selective 19F-MR relaxometry was carried out with perfluoro-15-crown-5-ether as oxygen sensor. The PFC was injected i.v. 3 days before the 19F-MR experiments. Two datasets were acquired before and two after the start of carbogen breathing. The distribution of PFCs and necrotic areas were analyzed in 19F-Spin Echo (SE) density MR images and T2-weighted 1H-SE MR images, respectively. One day after the MR investigations, oxygen tensions were measured by oxygen electrodes in the same slice along two perpendicular tracks. These measurements were followed by (immuno)histochemical analysis of the 2D distribution of perfused microvessels, hypoxic cells, necrotic areas, and macrophages. RESULTS: The PFCs mainly became sequestered in perfused regions at the tumor periphery; thus, 19F-MR relaxometry probed mean oxygen tensions in these regions throughout the selected MR slice. In perfused regions of the tumor, mean PO2/relaxo values were comparable to mean PO2/electrode values, and varied from 0.03 to 9 mmHg. Median pO2/electrode values of both tracks were lower than mean pO2/relaxo values, because low pO2 electrode values that originate from hypoxic and necrotic areas were also included in calculations of median pO2/electrode values. After 8-min carbogen breathing, the average PO2/relaxo increase was 3.3 +/- 0.8 (SEM) mmHg and 2.1 +/- 0.6 (SEM) after 14 min breathing. CONCLUSIONS: We have demonstrated that PFCs mainly became sequestered in perfused regions of the tumor. Here, mean PO2/relaxo values were comparable to mean PO2electrode values. In these areas, carbogen breathing was found to increase the PO2/relaxo values significantly.

Automated correction of unwanted phase jumps in reference signals which corrupt MRSI spectra after eddy current correction.

A commonly applied step in the postprocessing of gradient localized proton MR spectroscopy, is correction for eddy current effects using the water signal as a reference. However, this method can degrade some of the metabolite signals, in particular if applied on proton MR spectroscopic imaging data. This artifact arises from the water reference signal in the presence of a second signal which resonates close to the main water resonance. The interference of both resonances will introduce jumps in the phase of the reference time domain signal. Using this phase for eddy current correction will result in a ringing artifact in the frequency domain of the metabolite signal over the whole frequency range. We propose a moving window correction algorithm, which screens the phase of reference signals and removes phase jumps in time domain caused by interference of signals from multiple spin systems. The phase jumps may be abrupt or gradually distributed over several time data points. Because the correction algorithm only corrects time data points which contain phase jumps, the phase is minimally disrupted. Furthermore, the algorithm is automated for large datasets, correcting only those water reference signals which are corrupted. After correction of the corrupted reference signals, normal eddy current correction may be performed. The algorithm is compared with a method which uses a low-pass filter and tested on simulated data as well as on in vivo proton spectroscopic imaging data from a healthy volunteer and from patients with a brain tumor.

Adenylate kinase 1 gene deletion disrupts muscle energetic economy despite metabolic rearrangement.

Efficient cellular energy homeostasis is a critical determinant of muscle performance, providing evolutionary advantages responsible for species survival. Phosphotransfer reactions, which couple ATP production and utilization, are thought to play a central role in this process. Here, we provide evidence that genetic disruption of AK1-catalyzed ss-phosphoryl transfer in mice decreases the potential of myofibers to sustain nucleotide ratios despite up-regulation of high-energy phosphoryl flux through glycolytic, guanylate and creatine kinase phosphotransfer pathways. A maintained contractile performance of AK1-deficient muscles was associated with higher ATP turnover rate and larger amounts of ATP consumed per contraction. Metabolic stress further aggravated the energetic cost in AK1(-/-) muscles. Thus, AK1-catalyzed phosphotransfer is essential in the maintenance of cellular energetic economy, enabling skeletal muscle to perform at the lowest metabolic cost.

Does the combination of magnetic resonance imaging and spectroscopic imaging improve the classification of brain tumours?

Magnetic Resonance Imaging (MRI) and magnetic resonance spectroscopic imaging (MRSI) play an important role in the noninvasive diagnosis of brain tumours. We investigate the use of both MRI and MRSI, separately and in combination with each other for classification of brain tissue types. Many clinically relevant classification problems are considered; for example healthy versus tumour tissues, low- versus high-grade tumours. Linear as well as nonlinear techniques are compared. The classification performance is evaluated by the area under the receiver operating characteristic (ROC) curve (AUC). In general, all techniques achieve a high performance, except when using MRI alone. For example, for low- versus high-grade tumours, low- versus high-grade gliomas, gliomas versus meningiomas, respectively a test AUC higher than 0.91, 0.93 and 0.98 is reached, when both MRI and MRSI data are used.

Effect of carbogen breathing on the physiological profile of human glioma xenografts.

The aim of this study was to evaluate the effect of carbogen breathing on the physiological profile of human glioma xenografts. Near infrared spectroscopy was used to investigate changes in oxy- and deoxyhemoglobin concentrations in tumor blood. Oxygen tension changes in tumor tissue were evaluated by (19)F-MR relaxometry, using perfluoro-15-crown-5-ether, and modifications of tumor blood perfusion (TBP) were analyzed by fast dynamic (1)H-MR imaging of Gd-DTPA uptake. Finally, changes of the bioenergetic status and pH of tumor cells were analyzed by (31)P-MRS. After 5 to 8 min of carbogen breathing, the average oxygen tension increase in tumor tissue was 4.6 +/- 1.3 mm Hg, which is in agreement with an increase of the oxyhemoglobin concentration in tumor blood (Delta[O(2)Hb] = 9. 2 +/- 3 microM). However, simultaneously the TBP was reduced, the bioenergetic status was diminished, and pH was decreased. As 100% O(2) breathing alone did not result in a detectable increase of oxyhemoglobin in tumor blood, the increase of the tumor oxygenation by carbogen appears to be mediated by its CO(2) content. This component may cause a nutrient-limited decrease of oxidative energy metabolism, indirectly via a steal-effect and/or by inhibition of the glycolytic rate resulting from tissue acidification. Magn Reson Med 42:490-499, 1999.