Volumetric assessment of myocardial viability in rats using 3D double contrast enhanced T1 and T2-weighted MRI

Objective: Volumetric evaluation of the myocardial viability post-infarction in rats using 3D in vivo MR imaging at 7 T using injection of an extracellular paramagnetic contrast agent and intravascular superparamagnetic iron oxide nanoparticles in the same imaging session. Materials and methods: Five hours after induction of permanent myocardial infarction in rats (n=6), 3D in vivo T1- and T2-weighted MR Imaging was performed prior to and after Gd-DOTA injection (0.2 mmol/kg) and prior to and after nanoparticle injection (5 mg Fe/kg) to assess infarct size and myocardial viability. Results: 3D MR Imaging using a successive contrast agent injection showed a difference of infarct size after Gd-DOTA injection on T1-weighted images compared to the one measured on T2-weighted images after Gd-DOTA and nanoparticle injection. Conclusion: The use of 3D T1- and T2-weighted MR Imaging using a double contrast agents protocol made possible the accurate characterization of myocardial infarction volume and allowed the detection of myocardial viability post-infarction in rats     

完全开放式磁共振成像磁体的优化设计

采用完全开放式的磁体结构，可满足外科手术对磁共振成像系统的需求。文章基于一种完全开放式的磁体结构——单边磁体结构的初始结构设计理论，构建了一个由块状永磁体组成的单边成像磁体的初始结构，并进一步应用改进的遗传算法对磁体结构进行了优化设计。最终达到提高其目标区域磁场强度、改善磁场均匀度的目的。数值结果显示，本文提出的设计方法给出的设计方案能够在磁体结构外部的成像区域形成均匀并且强大的主磁场。     

Diagnosis of disc bulge and disc desiccation in lumbar MRI using concatenated shape and texture features with random forest classifier

Disc bulge and disc desiccation are the most common abnormalities occurring in the spine, which leads to severe low back pain. Despite computer-aided automatic abnormality diagnostic imaging systems are available still there is a need for betterment in diagnostic accuracy and in processing time. Image processing with combined imaging features like shape and texture has given better diagnostic ability when compared with processing with individual features. In the present study, the desiccated and bulged Intervertebral Discs (IVDs) are diagnosed automatically by combining shape features extracted using Histogram of Oriented Gradients (HOG) and texture feature extracted using novel Local Sub-Rhombus Binary Relation Pattern (LS-RBRP) techniques with Random Forest (RF) classifier. The performance analysis projects that the RF with HOG+LS-RBRP has an overall better accuracy of 94.7% when compared with HOG (87%) and LS-RBRP (90.2%) with RF classifier separately in categorizing the normal IVD, disc bulge and disc desiccation in the lumbar spine MRI.     

pH- and thermo-sensitive MTX-loaded magnetic nanocomposites: synthesis,characterization, and in vitro studies on A549 lung cancer cell and MR imaging

In the current study, we proposed a facile method for fabrication of multifunctional pH- and thermo-sensitive magnetic nanocomposites (MNCs) as a theranostic agent for using in targeted drug delivery and magnetic resonance imaging (MRI). To this end, we decorated Fe₃O₄ magnetic nanoparticles (MNPs) with N,N-dimethylaminoethyl methacrylate (DMAEMA) and N-isopropylacrylamide (NIPAAm), best known for their pH- and thermo-sensitive properties, respectively. We also conjugated mesoporous silica nanoparticles (MSNs) to polymer matrix acting as drug container to enhance the drug encapsulation efficacy. Methotroxate (MTX) as a model drug was successfully loaded in MNCs (M-MNCs) via surface adsorption onto MSNs and electrostatic interaction between drug and carrier. The pH- and temperature-triggered release of MTX was concluded through the evaluation of in vitro release at both physiological and simulated tumor tissue conditions. Based on in vitro cytotoxicity assay results, M-MNCs significantly revealed higher antitumor activity compared to free MTX. In vitro MR susceptibility experiment showed that M-MNCs relatively possessed high transverse relaxivity (r₂) of about 0.15?mM^?1·ms^?1 and a linear relationship between the transverse relaxation rate (R₂) and the Fe concentration in the M-MNCs was also demonstrated. Therefore, the designed MNCs can potentially become smart drug carrier, while they also can be promising MRI negative contrast agent.     

Catalase-imprinted Fe<Subscript>3</Subscript>O<Subscript>4</Subscript>/Fe@fibrous SiO<Subscript>2</Subscript>/polydopamine nanoparticles: An integrated nanoplatform of magnetic targeting,magnetic resonance imaging,and dual-mode cancer therapy

Recent advances in the research on the molecular mechanism of cell death and methods for preparation of nanomaterials make the integration of various therapeutic approaches,targeting,and imaging modes into a single nanoscale complex a new trend for the development of future nanotherapeutics.Hence,a novel ellipsoidal composite nanoplatform composed of a magnetic Fe3O4/Fe nanorod core (～120 nm) enwrapped by a catalase (CAT)-imprinted fibrous SiO2/ polydopamine (F-SiO2/PDA) shell with thickness 70 nm was prepared in this work.In vitro experiments showed that the Fe3O4/Fe@F-SiO2/PDA nanoparticles can selectively inhibit the bioactivity of CAT in tumor cells by the molecular imprinting technique.As a result,the H2O2 level in tumor cells was elevated dramatically.At the same time,the Fe3O4/Fe core released Fe ions to catalyze the conversion of H2O2 to ·OH in tumor cells.Eventually,the concentration of ·OH in tumor cells rapidly rose to a lethal level thus triggering apoptosis.Combined with the remarkable near-infrared light (NIR) photothermal effect of the CATimprinted PDA layer,the Fe3O4/Fe@F-SiO2/PDA nanoparticles can effectively kill MCF-7,HeLa,and 293T tumor cells but are not toxic to nontumor cells.Furthermore,these nanoparticles show good capacity for magnetic targeting and suitability for magnetic resonance imaging (MRI).Therefore,the integrated multifunctional nanoplatform opens up new possibilities for high-efficiency visual targeted nonchemo therapy for cancer.     

Online dynamic cardiac imaging based on the elastic-net model

Purpose: The purpose of this work was to develop an online dynamic cardiac MRI model to reconstruct image frames from partial acquisition of the Cartesian k-space data, which utilizes structural knowledge of consecutive image frames. Materials and methods: Using an elastic-net model, the proposed algorithm reconstructs dynamic images using both L₁ and L₂ norm operations. The L₁ norm enforces the sparsity of the frame difference, while the L₂ norm with motion-adaptive weights catches the internal structure of frame differences. Unlike other online methods such as the Kalman filter (KF) technique, the new model requires no assumption of Gaussian noise, and can faithfully reconstruct the dynamic images within a compressive sensing framework. Results: The proposed method was evaluated using simulated dynamic phantoms with 40 frames of images (128?×?128) and a cardiac MRI cine of 25 frames (256?×?256). Both results showed that the new model offered a better performance than the online KF method in depicting simulated phantom and cardiac dynamics. Conclusion: It is concluded that the proposed imaging model can be used to capture a large variety of objects in motion from highly under-sampled k-space data, and being particularly useful for improving temporal resolution of cardiac MRI.     

EEG‐based brain source localization using visual stimuli

Electroencephalography (EEG) is widely used in variety of research and clinical applications which includes the localization of active brain sources. Brain source localization provides useful information to understand the brain's behavior and cognitive analysis. Various source localization algorithms have been developed to determine the exact locations of the active brain sources due to which electromagnetic activity is generated in brain. These algorithms are based on digital filtering, 3D imaging, array signal processing and Bayesian approaches. According to the spatial resolution provided, the algorithms are categorized as either low resolution methods or high resolution methods. In this research study, EEG data is collected by providing visual stimulus to healthy subjects. FDM is used for head modelling to solve forward problem. The low‐resolution brain electromagnetic tomography (LORETA) and standardized LORETA (sLORETA) have been used as inverse modelling methods to localize the active regions in the brain during the stimulus provided. The results are produced in the form of MRI images. The tables are also provided to describe the intensity levels for estimated current level for the inverse methods used. The higher current value or intensity level shows the higher electromagnetic activity for a particular source at certain time instant. Thus, the results obtained demonstrate that standardized method which is based on second order Laplacian (sLORETA) in conjunction with finite difference method (FDM) as head modelling technique outperforms other methods in terms of source estimation as it has higher current level and thus, current density (J) for an area as compared to others.     

Evaluation of a power injection system in the 7‐Tesla MRI environment

The injection of contrast media enables the visualization of various pathologies through X‐ray, computed tomography, magnetic resonance imaging (MRI), or other medical imaging modalities. Safety and functionality of power injector systems must be evaluated at high magnetic fields (7‐Tesla). The purpose of this study was to evaluate MRI issues for a power injection system (OptiStar Elite MR Contrast Delivery System, Mallinckrodt Pharmaceuticals, Hazelwood, MO) at 7‐Tesla including magnetic field interaction and 31 injector performance tests. Additionally, effects of operation of the power injection system on MR images were evaluated through observation of image artifacts and signal to noise analysis. The components of the power injection system (powerhead, syringes) exhibited no translational attraction when close to 7‐Tesla MR system. Translational attraction was detected for the power supply, power control, and cables, therefore there is a requirement to maintain these components fixed outside of the 0.1000 Tesla line. 7‐Tesla MR scanning did not impact power injection performance. The power injection system produced no discernible image artifacts or degradation when the power controls and powerhead were positioned in the worst‐case position. The power injection system tested for MRI issues passed evaluation for safety and operation at 7‐Tesla and is labeled MR Conditional for use at 7‐T. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 50–55, 2015     

Residual U-Network for Breast Tumor Segmentation from Magnetic Resonance Images

Breast cancer positions as the most well-known threat and the main source of malignant growth-related morbidity and mortality throughout the world. It is apical of all new cancer incidences analyzed among females. Two features substantially influence the classification accuracy of malignancy and benignity in automated cancer diagnostics. These are the precision of tumor segmentation and appropriateness of extracted attributes required for the diagnosis. In this research, the authors have proposed a ResU-Net (Residual U-Network) model for breast tumor segmentation. The proposed methodology renders augmented, and precise identification of tumor regions and produces accurate breast tumor segmentation in contrast-enhanced MR images. Furthermore, the proposed framework also encompasses the residual network technique, which subsequently enhances the performance and displays the improved training process. Over and above, the performance of ResU-Net has experimentally been analyzed with conventional U-Net, FCN8, FCN32. Algorithm performance is evaluated in the form of dice coefficient and MIoU (Mean Intersection of Union), accuracy, loss, sensitivity, specificity, F1score. Experimental results show that ResU-Net achieved validation accuracy & dice coefficient value of 73.22% & 85.32% respectively on the Rider Breast MRI dataset and outperformed as compared to the other algorithms used in experimentation.