Proton NMR visible mobile lipid signals in sensitive and multidrug-resistant K562 cells are modulated by rafts

BACKGROUND: Most cancer cells are characterized by mobile lipids visible on proton NMR ((1)H-NMR), these being comprised mainly of methyl and methylene signals from lipid acyl chains. Erythroleukemia K562 cells show narrow signals at 1.3 and 0.9 ppm, corresponding to mobile lipids (methylene and methyl, respectively), which are reduced when K562 cells are multidrug resistant (MDR). While the significance of the mobile lipids is unknown, their subcellular localization is still a matter of debate and may lie in the membrane or the cytoplasm. In this study, we investigate the role of cholesterol in the generation of mobile lipid signals. RESULTS: The proportion of esterified cholesterol was found to be higher in K562-sensitive cells than in resistant cells, while the total cholesterol content was identical in both cell lines. Cholesterol extraction in the K562 wild type (K562wt) cell line and its MDR counterpart (K562adr), using methyl-β-cyclodextrin, was accompanied by a rise of mobile lipids in K562wt cells only. The absence of caveolae was checked by searching for the caveolin-1 protein in K562wt and K562adr cells. However, cholesterol was enriched in another membrane microdomain designated as "detergent-insoluble glycosphingomyelin complexes" or rafts. These microdomains were studied after extraction with triton X-100, a mild non-ionic detergent, revealing mobile lipid signals preserved only in the K562wt spectra. Moreover, following perturbation/disruption of these microdomains using sphingomyelinase, mobile lipids increased only in K562wt cells. CONCLUSION: These results suggest that cholesterol and sphingomyelin are involved in mobile lipid generation via microdomains of detergent-insoluble glycosphingomyelin complexes such as rafts. Increasing our knowledge of membrane microdomains in sensitive and resistant cell lines may open up new possibilities in resistance reversion

The impact of image dynamic range on texture classification of brain white matter

<p>Abstract</p> <p>Background</p> <p>The Greylevel Cooccurrence Matrix method (COM) is one of the most promising methods used in Texture Analysis of Magnetic Resonance Images. This method provides statistical information about the spatial distribution of greylevels in the image which can be used for classification of different tissue regions. Optimizing the size and complexity of the COM has the potential to enhance the reliability of Texture Analysis results. In this paper we investigate the effect of matrix size and calculation approach on the ability of COM to discriminate between peritumoral white matter and other white matter regions.</p> <p>Method</p> <p>MR images were obtained from patients with histologically confirmed brain glioblastoma using MRI at 3-T giving isotropic resolution of 1 mm³. Three Regions of Interest (ROI) were outlined in visually normal white matter on three image slices based on relative distance from the tumor: one peritumoral white matter region and two distant white matter regions on both hemispheres. Volumes of Interest (VOI) were composed from the three slices. Two different calculation approaches for COM were used: i) Classical approach (CCOM) on each individual ROI, and ii) Three Dimensional approach (3DCOM) calculated on VOIs. For, each calculation approach five dynamic ranges (number of greylevels N) were investigated (N = 16, 32, 64, 128, and 256).</p> <p>Results</p> <p>Classification showed that peritumoral white matter always represents a homogenous class, separate from other white matter, regardless of the value of N or the calculation approach used. The best test measures (sensitivity and specificity) for average CCOM were obtained for N = 128. These measures were also optimal for 3DCOM with N = 128, which additionally showed a balanced tradeoff between the measures.</p> <p>Conclusion</p> <p>We conclude that the dynamic range used for COM calculation significantly influences the classification results for identical samples. In order to obtain more reliable classification results with COM, the dynamic range must be optimized to avoid too small or sparse matrices. Larger dynamic ranges for COM calculations do not necessarily give better texture results; they might increase the computation costs and limit the method performance.</p

L'art du compromis socio-technique dans l'innovation hospitalière : le cas des systèmes de communication et d'archivage d'images médicales (PACS)

Dominique Boullier, Jacques D. de Certaines: The art of socio-technical compromise in hospital innovation: the case of Picture and Archiving Communication Systems (PACS). The history of certain pioneers in Picture and Archiving Communication Systems (PACS) provides useful information on the contradictory objectives and interests that are at play when innovations are introduced in the hospital environment. The Rennes project on which this paper is based was highly ambitious, and also generated extreme conflict during its development. The participants in the project were marginal vis-à-vis both the personnel in the radiology department and their industry partners, and it is not therefore surprising that no marketable product was produced. The main resuit was an increase in their power and notoriety within the hospital, which may, in itself, form a type of innovation, in which the technical considerations simply served as a lever for institutional change which, in turn, would lead to «technical» improvements. The authors propose indicators for evaluating technical choices adapted to medical imaging networks.Résumé. L'histoire de quelques pionniers des réseaux d'imagerie médicale est riche d'enseignements sur les objectifs et intérêts contradictoires qu'il faut associer lors d'une innovation à l'hôpital. Le projet rennais étudié fut l'un des plus ambitieux : les démentis furent aussi des plus sévères en cours de développement. Les positions marginales des acteurs du projet par rapport à la radiologie ordinaire et par rapport aux industriels ont rendu impossible tout passage à un produit de « marché ». Le résultat notable fut avant tout un gain de force et de notoriété au sein de l'hôpital. Mais n'est-ce pas là une forme possible d'innovation, la « technique » servant ici de levier au changement dit institutionnel pour entraîner de nouveaux changements dits techniques. Des indicateurs d'évaluation des choix techniques dans le cas de ces réseaux sont proposés.Dominique Boullier, Jacques D. de Certaines : El arte del compromiso socio-técnico en la innovaciôó hospitalaria : el caso de los sistemas de comunicación y de archivación de imágenes médicas (PACS). La historia de los pioneros de redes de archivación e imagen médica es rica en ensenanzas. Sobre todo cuando se trata de los objectivos e intereses muchas veces contradictorios que hay que conciliar cuando se promueve una innovación en el hospital. El proyecto estudiado (originario de Rennes) fué uno de los mas ambiciosos : sin embargo las fallas fueron muy severas en el curso del proyecto. Las posiciones marginales de los actores del proyecto con relación a la radiologia ordinaria y a los industriales hicieron imposible todo paso a un producto de « mercado ». El resultado mas notable fué una fuerza y una notoriedad mayor dentro del hospital. ¿ No es ésa una forma posible de innovación ?, la « técnologia » sirve aqui como palanca para el cambio llamado institucional afin de generar nuevos cambios llamados técnicos. Se proponen algunos indicadores de evaluación de las opciones técnicas en el caso de estas redes.Boullier Dominique, De Certaines Jacques D. L'art du compromis socio-technique dans l'innovation hospitalière : le cas des systèmes de communication et d'archivage d'images médicales (PACS). In: Sciences sociales et santé. Volume 10, n°3, 1992. pp. 75-103

MULTI-CENTER TRIAL WITH PROTOCOLS AND PROTOTYPE TEST OBJECTS FOR THE ASSESSMENT OF MRI EQUIPMENT

International audienc

Can Dynamic Contrast-Enhanced Magnetic Resonance Imaging Combined with Texture Analysis Differentiate Malignant Glioneuronal Tumors from Other Glioblastoma?

An interesting approach has been proposed to differentiate malignant glioneuronal tumors (MGNTs) as a subclass of the WHO grade III and IV malignant gliomas. MGNT histologically resemble any WHO grade III or IV glioma but have a different biological behavior, presenting a survival twice longer as WHO glioblastomas and a lower occurrence of metastases. However, neurofilament protein immunostaining was required for identification of MGNT. Using two complementary methods, dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) and texture analysis (MRI-TA) from the same acquisition process, the challenge is to in vivo identify MGNT and demonstrate that MRI postprocessing could contribute to a better typing and grading of glioblastoma. Results are obtained on a preliminary group of 19 patients a posteriori selected for a blind investigation of DCE T1-weighted and TA at 1.5 T. The optimal classification (0/11 misclassified MGNT) is obtained by combining the two methods, DCE-MRI and MRI-TA

Application of texture analysis to muscle MRI: 2 – technical recommendations

A goal of the multicenter European Cooperation in Science and Technology (COST) action MYO-MRI is to optimize Magnetic Resonance Imaging Texture Analysis (MRI-TA) methods for application in the study of muscle disease. This paper deals with recommendations on the optimal methodology to collect the MRI data, to analyse it via texture analysis and to make conclusions from the resultant texture parameter data. A full and detailed description is provided with respect to MR image quality control, sequence choice, image pre-processing, region of interest selection, texture analysis methods and data analysis. A series of conclusions are presented

Application of texture analysis to muscle MRI: 1- What kind of information should be expected from texture analysis?

International audienceSeveral previous clinical or preclinical studies using computerized texture analysis of MRImages have demonstrated much more clinical discrimination than visual image analysis bythe radiologist. In muscular dystrophy, a discriminating power has been already demonstratedwith various methods of texture analysis of magnetic resonance images (MRI-TA).Unfortunately, a scale gap exists between the spatial resolutions of histological and MRimages making a direct correlation impossible. Furthermore, the effect of the varioushistological modifications on the gray level of each pixel is complex and cannot be easilyanalyzed. Consequently, clinicians will not accept the use of MRI-TA in routine practice ifTA remains a “black box” without clinical correspondence at a tissue level. A goal thereforeof the multicenter European COST action MYO-MRI is to optimize MRI-TA methods inmuscular dystrophy and to elucidate the histological meaning of MRI textures