Thresholding in correlation analyses of magnetic resonance functional neuroimaging

The definition of objective and effective thresholds in MRI of human brain function is a crucial step in the analysis of paradigm-related activations. This paper introduces a user-independent and robust procedure that calculates statistical parametric maps based on correlation coefficients. Thresholds are introduced as p values and defined with respect to the physiologic noise distribution of the individual maps. Experimental examples from the human visual and motor system rely on dynamic acquisitions of gradient-echo echo-planar images (2.0 T, TR = 2000 ms, 96 × 128 matrix) with blood oxygenation level-dependent contrast. The results demonstrate the disadvantages of thresholding with fixed correlation coefficients. In contrast, taking the individual noise into account allows for a derivation of p values and a reliable identification of highly significant activation centers. An adequate delineation of the spatial extent of activation may be achieved by adding directly neighboring pixels provided their correlation coefficients comply with a second lower p value threshold.     

A rat brain protein expression map including cytosolic and enriched mitochondrial and microsomal fractions

Proteomics is a powerful tool to screen brain protein expression but the methodology is hampered by low abundance of proteins or compartmentalization or overload of high-abundance proteins. It was therefore the aim of the study to determine the expression of brain proteins by using enriched cellular subfractions and pre-electrophoretic chromatographical separation of brain homogenates. We used two-dimensional electrophoresis with subsequent matrix-assisted laser desorption/ionization (MALDI) detection and characterization of brain proteins. Subfractionation into cytosolic, mitochondrial and microsomal compartments was performed by ultracentrifugation. Pre-electrophoretic fractionation of the cytosolic fractions was carried out by ion exchange column chromatography. We detected and identified a large series of 437 proteins in rat brain and have shown proteins specific for the individual subcellular compartments. These proteins included housekeeping, signaling, cytoskeletal, intermediary metabolism, antioxidant proteins on the one and neuron and synaptosomal specific proteins on the other hand. Using fractionations of brain homogenates we were able to improve the power of the method on forming the basis for brain protein expressional studies and providing a reference map as a powerful tool for the neuroscientist.     

Treatment-related central nervous system toxicity: MR imaging evaluation with CT and clinical correlation

Thirteen patients with abnormal brain MR scans attributable to treatment-induced injury were retrospectively reviewed. All patients were treated with radiation therapy and 62% received chemotherapy. Five patients were graded as having severe white matter (WM) changes, four had moderate WM changes, and four had mild WM changes. CT was generally equivalent to MR in evaluation of severe and moderate WM abnormalities, whereas MR was superior to CT in detection of mild WM abnormalities. In general, the severity of changes depicted by MR/CT correlated with the extent of neurologic dysfunction. The most severe changes were seen in those patients treated with combination irradiation and chemotherapy.     

脑脓肿42例诊治分析

目的：总结42例脑脓肿诊治经验及效果.方法：对42例脑脓肿病人15例施立体定向置管抽吸引流术,12例钻孔脓肿穿刺置管引流术,15例脑脓肿切除术..结果：治愈40例,重残1例,死亡1例.结论：CT引导立体定向穿刺置管抽吸引流术手术损伤小,操作简便,定位精确,安全可靠.     

Development of T2-relaxation values in regional brain sites during adolescence

Brain tissue changes accompany multiple neurodegenerative and developmental conditions in adolescents. Complex processes that occur in the developing brain with disease can be evaluated accurately only against normal aging processes. Normal developmental changes in different brain areas alter tissue water content, which can be assessed by magnetic resonance (MR) T2 relaxometry. We acquired proton-density (PD) and T2-weighted images from 31 subjects (mean age±S.D., 17.4±4.9 years; 18 male), using a 3.0-T MR imaging scanner. Voxel-by-voxel T2-relaxation values were calculated, and whole-brain T2-relaxation maps constructed and normalized to a common space template. We created a set of regions of interest (ROIs) over cortical gray and white matter, basal ganglia, amygdala, thalamic, hypothalamic, pontine and cerebellar sites, with sizes of ROIs varying from 12 to 243 mm³; regional T2-relaxation values were determined from these ROIs and normalized T2-relaxation maps. Correlations between R2 (1/T2) values in these sites and age were assessed with Pearson's correlation procedures, and gender differences in regional T2-relaxation values were evaluated with independent-samples t tests. Several brain regions, but not all, showed principally positive correlations between R2 values and age; negative correlations emerged in the cerebellar peduncles. No significant differences in T2-relaxation values emerged between males and females for those areas, except for the mid pons and left occipital white matter; males showed higher T2-relaxation values over females. The findings indicate that T2-relaxation values vary with development between brain structures, and emphasize the need to correct for such age-related effects during any determination of potential changes from control values.     

Unsupervised MRI segmentation of brain tissues using a local linear model and level set

Real-world magnetic resonance imaging of the brain is affected by intensity nonuniformity (INU) phenomena which makes it difficult to fully automate the segmentation process. This difficult task is accomplished in this work by using a new method with two original features: (1) each brain tissue class is locally modeled using a local linear region representative, which allows us to account for the INU in an implicit way and to more accurately position the region's boundaries; and (2) the region models are embedded in the level set framework, so that the spatial coherence of the segmentation can be controlled in a natural way. Our new method has been tested on the ground-truthed Internet Brain Segmentation Repository (IBSR) database and gave promising results, with Tanimoto indexes ranging from 0.61 to 0.79 for the classification of the white matter and from 0.72 to 0.84 for the gray matter. To our knowledge, this is the first time a region-based level set model has been used to perform the segmentation of real-world MRI brain scans with convincing results.     

Quantitative combination of volumetric MR imaging and MR spectroscopy data for the discrimination of meningiomas from metastatic brain tumors by means of pattern recognition

The analysis of information derived from magnetic resonance imaging (MRI) and spectroscopy (MRS) has been identified as an important indicator for discriminating among different brain pathologies. The purpose of this study was to investigate the efficiency of the combination of textural MRI features and MRS metabolite ratios by means of a pattern recognition system in the task of discriminating between meningiomas and metastatic brain tumors. The data set consisted of 40 brain MR image series and their corresponding spectral data obtained from patients with verified tumors. The pattern recognition system was designed employing the support vector machines classifier with radial basis function kernel; the system was evaluated using an external cross validation process to render results indicative of the generalization performance to “unknown” cases. The combination of MR textural and spectroscopic features resulted in 92.15% overall accuracy in discriminating meningiomas from metastatic brain tumors. The fusion of the information derived from MRI and MRS data might be helpful in providing clinicians a useful second opinion tool for accurate characterization of brain tumors.     

Differentiation between intra-axial metastatic tumor progression and radiation injury following fractionated radiation therapy or stereotactic radiosurgery using MR spectroscopy, perfusion MR imaging or volume progression modeling

Objective

To determine the accuracy of magnetic resonance spectroscopy (MRS), perfusion MR imaging (MRP), or volume modeling in distinguishing tumor progression from radiation injury following radiotherapy for brain metastasis.

Methods

Twenty-six patients with 33 intra-axial metastatic lesions who underwent MRS (n=41) with or without MRP (n=32) after cranial irradiation were retrospectively studied. The final diagnosis was based on histopathology (n=4) or magnetic resonance imaging (MRI) follow-up with clinical correlation (n=29). Cho/Cr (choline/creatinine), Cho/NAA (choline/N-acetylaspartate), Cho/nCho (choline/contralateral normal brain choline) ratios were retrospectively calculated for the multi-voxel MRS. Relative cerebral blood volume (rCBV), relative peak height (rPH) and percentage of signal-intensity recovery (PSR) were also retrospectively derived for the MRPs. Tumor volumes were determined using manual segmentation method and analyzed using different volume progression modeling. Different ratios or models were tested and plotted on the receiver operating characteristic curve (ROC), with their performances quantified as area under the ROC curve (AUC). MRI follow-up time was calculated from the date of initial radiotherapy until the last MRI or the last MRI before surgical diagnosis.

Results

Median MRI follow-up was 16 months (range: 2-33). Thirty percent of lesions (n=10) were determined to be radiation injury; 70% (n=23) were determined to be tumor progression. For the MRS, Cho/nCho had the best performance (AUC of 0.612), and Cho/nCho >1.2 had 33% sensitivity and 100% specificity in predicting tumor progression. For the MRP, rCBV had the best performance (AUC of 0.802), and rCBV >2 had 56% sensitivity and 100% specificity. The best volume model was percent increase (AUC of 0.891); 65% tumor volume increase had 100% sensitivity and 80% specificity.

Conclusion

Cho/nCho of MRS, rCBV of MRP, and percent increase of MRI volume modeling provide the best discrimination of intra-axial metastatic tumor progression from radiation injury for their respective modalities. Cho/nCho and rCBV appear to have high specificities but low sensitivities. In contrast, percent volume increase of 65% can be a highly sensitive and moderately specific predictor for tumor progression after radiotherapy. Future incorporation of 65% volume increase as a pretest selection criterion may compensate for the low sensitivities of MRS and MRP.     

Recent advances in clinical microdialysis

Clinical microdialysis (MD) is a minimally invasive sampling technique that offers selective in-vivo measurement of free, active drug or biomolecule concentrations in human tissues and organs. From a regulatory perspective, MD can thus be seen as a suitable scientific tool that meets regulatory requirements for the study of tissue distribution or bioequivalence during drug development. From a clinical perspective, the use of MD in different applications has shown the potential to rationalize drug-dosing regimens and to influence clinical decision-making, although validation and correlation of MD-derived results with clinical response are required to promote routine clinical use of the technique. From an analytical perspective, highly sensitive analytical systems have increasingly become available for MD-sample analysis, and these have further improved the quality and the power of MD-derived information. Given the constant development in recent years, MD data might become an important part of new drug submissions and clinical treatment algorithms, and might positively influence patient benefit in the future.