Improved in vivo detection of cortical lesions in multiple sclerosis using double inversion recovery MR imaging at 3 Tesla

Objective: To investigate the impact of a higher magnetic field strength of 3 Tesla (T) on the detection rate of cortical lesions in multiple sclerosis (MS) patients, in particular using a dedicated double inversion recovery (DIR) pulse sequence. Methods: Thirty-four patients with clinically isolated syndromes or definite MS were included. All patients underwent magnetic resonance imaging (MRI) at 1.5 T and 3 T, including T2-weighted turbo spin echo (TSE), fluid-attenuated inversion recovery (FLAIR) and DIR sequences. All images were analysed for focal lesions categorised according to their anatomical location. Results: The total number of detected lesions was higher at 3 T across all pulse sequences. We observed significantly higher numbers of lesions involving the cortex at 3 T using a DIR sequence. DIR at 3 T showed 192% more pure intracortical (p<0.001) and 30% more mixed grey matter-white matter lesions (p=0.008). No significant increase in cortical lesions could be detected on the FLAIR and T2-weighted images. Using the T2-weighted and FLAIR sequences, significantly more lesions could be detected at 3 T in the infratentorial, periventricular and juxtacortical white matter. Conclusion: DIR brain MR imaging at 3 T substantially improves the sensitivity of the detection of cortical lesions compared with the standard magnetic field strength of 1.5 T. © European Society of Radiology 2009

The choice of feedstock for the biodiesel production with optimal physicochemical and low-temperature properties

The transesterification reaction of sunflower, mustard and linseed oil with ethyl alcohol was studied using potassium hydroxide as a catalyst. The physicochemical properties and low-temperature characteristics of the feedstock and obtained products were studied. The most preferred feedstock for the biodiesel fuel production had been determined

Dysembryoplastic Neuroepithelial Tumors: MR and CT Evaluation

PURPOSE: To evaluate dysembryoplastic neuroepithelial tumors (DNTs) on MR and CT studies and to compare DNT with other frequently encountered epileptogenic glioneuronal lesions. METH-ODS: We analyzed the MR images and CT scans of 16 patients who had complex partial epilepsy and DNT with respect to tumor location, size, CT density, MR signal intensity, mass effect, contrast enhancement, and heterogeneity, and compared these features with CT and MR findings in 51 cases of ganglioglioma and 33 cases of glioneuronal malformation. RESULTS: DNTs were located in the temporal lobe in 14 patients and in the frontal lobe in 2 patients. The cortex was involved in all cases and the subcortical white matter in 10 cases. Fifty percent of the tumors had poorly defined contours. On MR images, 14 DNTs had multiple cysts and 2 had single cysts. Contrast enhancement was observed in 6 DNTs, and mass effect was present in 9. CT scans disclosed moderately hypodense lesions in 7 patients and markedly hypodense cystic lesions in 6 patients. Two DNTs were calcified. Tumor hemorrhage with perifocal edema was observed in 1 case. Contrary to previous reports, slow but definite tumor growth was present during a 13-year period in 2 of 6 patients in whom serial CT or MR studies were obtained. CONCLUSION: A multicystic appearance on MR images is a characteristic feature of DNT and corresponds to its myxoid matrix and multinodular architecture. This feature is rare in gangliogliomas and glioneuronal malformations, and, as such, may help differentiate DNTs from these disorders

Visual shape and position sensing algorithm for a continuum robot

Continuum robots represent an actively developing and fast-growing technology in robotics. To successfully implement control and path planning of continuum robots it is important to develop an accurate three-dimensional shape and position sensing algorithm. In this paper, we propose an algorithm for the three-dimensional reconstruction of the continuum robot shape. The algorithm is performed during several steps. Initially, images from two cameras are processed by applying pre-processing and segmentation techniques. Then, the gradient descent method is applied to compare two-dimensional skeleton points of both masks. Having compared these points, it finds a skeleton of the robot in a threedimensional form. Additionally, the proposed algorithm is able to define key points using the distance from the robot base along the center line. The latter allows controlling the position of points of interest defined by a user. As a result, the developed algorithm achieved a relatively high level of accuracy and speed