Monitoring kidney and renal cyst volumes applying MR approaches on a rapamycin treated mouse model of ADPKD

Object  The aim of our study was to determine total cystic volume in a mouse model of PKD using MR imaging to monitor therapeutic effects in vivo. Materials and methods  We imaged eight female pcy-mice in two groups: four belonged to an untreated control group and four were treated with the anticystic agent rapamycin, which has proven to be effective in reducing cystogenesis in animal models. The mice were imaged using a 9.4 Tesla animal scanner. MRI measurements were taken at six time points during the therapy. Total renal volumes and total cyst volumes were calculated using a thresholding approach. Results  During the course of the treatment, the total cyst volume increased significantly faster than the total renal volume in the untreated group, indicating that growth of the total renal volume in the untreated group was primarily due to the growth of the cysts, rather than the parenchyma. The measured total renal volume in the control (placebo) group was significantly higher than the volume in the treated group. Conclusion  Using MRI, we were able to monitor the cystic volume in a mouse model of PKD to assess the therapeutic effect of anticystic treatment.     

Magnetic resonance image denoising using nonlocal maximum likelihood paradigm in DCT‐framework

The data acquired by magnetic resonance (MR) imaging system are inherently degraded by noise that has its origin in the thermal Brownian motion of electrons. Denoising can enhance the quality (by improving the SNR) of the acquired MR image, which is important for both visual analysis and other post processing operations. Recent works on maximum likelihood (ML) based denoising shows that ML methods are very effective in denoising MR images and has an edge over the other state‐of‐the‐art methods for MRI denoising. Among the ML based approaches, the Nonlocal maximum likelihood (NLML) method is commonly used. In the conventional NLML method, the samples for the ML estimation of the unknown true pixel are chosen in a nonlocal fashion based on the intensity similarity of the pixel neighborhoods. Euclidean distance is generally used to measure this similarity. It has been recently shown that computing similarity measure is more robust in discrete cosine transform (DCT) subspace, compared with Euclidean image subspace. Motivated by this observation, we integrated DCT into NLML to produce an improved MRI filtration process. Other than improving the SNR, the time complexity of the conventional NLML can also be significantly reduced through the proposed approach. On synthetic MR brain image, an average improvement of 5% in PSNR and 86%reduction in execution time is achieved with a search window size of 91 × 91 after incorporating the improvements in the existing NLML method. On an experimental kiwi fruit image an improvement of 10% in PSNR is achieved. We did experiments on both simulated and real data sets to validate and to demonstrate the effectiveness of the proposed method. © 2015 Wiley Periodicals, Inc. Int J Imaging Syst Technol, 25, 256–264, 2015     

Dendrimer as nanocarrier for drug delivery

Dendrimers are novel three dimensional, hyperbranched globular nanopolymeric architectures. Attractive features like nanoscopic size, narrow polydispersity index, excellent control over molecular structure, availability of multiple functional groups at the periphery and cavities in the interior distinguish them amongst the available polymers. Applications of dendrimers in a large variety of fields have been explored. Drug delivery scientists are especially enthusiastic about possible utility of dendrimers as drug delivery tool. Terminal functionalities provide a platform for conjugation of the drug and targeting moieties. In addition, these peripheral functional groups can be employed to tailor-make the properties of dendrimers, enhancing their versatility. The present review highlights the contribution of dendrimers in the field of nanotechnology with intent to aid the researchers in exploring dendrimers in the field of drug delivery.     

High-Resolution NMR and Magnetic Resonance Imaging (MRI) Studies on Fresh and Frozen Cod ( Gadus morhua) and Haddock (Melanogrammus aeglefinus)

Changes in the fish muscle from cod ( Gadus morhua ) and haddock ( Melanogrammus aeglefinus ) were investigated by high-resolution NMR and magnetic resonance imaging (MRI). Water- and salt-soluble extracts from fish stored at −20°C and −30°C were analysed by high-resolution proton NMR and enabled the identification of metabolites including trimethylamine oxide, trimethylamine (TMA) and dimethylamine. It was not possible to detect formaldehyde by NMR either in the stored fish samples or in spiked water or salt extracts even at high levels of formaldehyde addition, probably due to polymerisation. Systematic and controlled storage trials indicated the presence of dimethylamine at around 9 months for samples stored at −20°C, whereas no changes were detected at the control storage temperature of −30°C. A comparison of cod and haddock fillets stored for 1 year at −20 and −30°C confirmed the production of dimethylamine only in cod stored at −20°C. It was interesting to note that ‘fresh’ cod and haddock samples purchased from a local supermarket showed high levels of TMA indicating a breakdown of trimethylamine oxide to TMA by bacteria. TMA was not detected in the fish fillets especially obtained for the storage trials. MRI of fresh cod and fish stored at −8 and −30°C indicated that the fish half stored at −8°C exhibited dense lines or arches which are indicative of gaps in the tissue due to possible breakdown of the connective tissue. The images of fish stored at −30°C did not indicate any differences compared with the fresh fish. MRI also showed the presence of frozen and unfrozen areas in the fish non-destructively.     

一种基于蚁群算法的Snake模型与MRI分割

Snake模型以其收敛快速、精确度可达到亚像素等优点,被广泛地应用于医学图像分割,但该模型依赖于初始曲线的选取,易于收敛到局部最优且难以达到凹陷区域。为此提出一种基于蚁群算法的Snake模型,首先利用区域内灰度统计特征自动进行Snake初始化,然后在Snake演化过程中加入一向心力,使其能进入凹陷区域,最后用蚁群算法对演化结果进行优化,使其收敛到全局最优,获得最终的分割结果。实验结果表明,改进的模型在MRI分割中可以得到较好的分割结果。     

A Novel Yolk–Shell Fe3O4@ Mesoporous Carbon Nanoparticle as an Effective Tumor-Targeting Nanocarrier for Improvement of Chemotherapy and Photothermal Therapy

Owing to their good stability and high photothermal conversion efficiency, the development of carbon-based nanoparticles has been intensively investigated, while the limitation of unsatisfactory cellular internalization impedes their further clinical application. Herein, we report a novel strategy for fabrication of Fe₃O₄ yolk–shell mesoporous carbon nanocarriers (Fe₃O₄@hmC) with monodispersity and uniform size, which presented significantly higher cell membrane adsorption and cellular uptake properties in comparison with common solid silica-supported mesoporous carbon nanoparticles with core–shell structure. Moreover, the MRI performance of this novel Fe-based nanoparticle could facilitate precise tumor diagnosis. More importantly, after DOX loading (Fe₃O₄@hmC-DOX), owing to synergistic effect of chemo–phototherapy, this therapeutic agent exhibited predominant tumor cell ablation capability under 808 nm NIR laser irradiation, both in vitro and in vivo. Our work has laid a solid foundation for therapeutics with hollowed carbon shell for solid tumor diagnosis and therapy in clinical trials.     

MRI图像的基于窄带的递进多分区C-V分割方法

提出了递进的基于窄带的多分区C-V方法,并对多幅医学脑部MRI图像进行了分割实验。由于该递进方法分为多个阶段,每阶段只需一个水平集函数,并且在每一阶段应用窄带区域,即只处理窄带区域中的点,从而使计算量大大减少。实验结果证明本算法是有效的,在提高计算速度的同时,可大大改进复杂几何结构的分割效果。     

多模态影像学检查在诊断早期强直性脊柱炎骶髂关节疾病中的效果

目的:探究在早期强直性脊柱炎骶髂关节疾病诊断中不同放射影像学检查方法的应用效果.方法:抽取2018年5月-2020年1月本院收治的早期强直性脊柱炎骶髂关节疾病患者65例作为研究对象,所有患者均开展X线、CT、MRI影像学检查,对比三种不同影像学检查方法的检出率、影像学特征.结果:X线、CT、MRI检出率分别为38.46...     

A deep supervised approach for ischemic lesion segmentation from multimodal MRI using Fully Convolutional Network

The principle restorative step in the treatment of ischemic stroke depends on how fast the lesion is delineated from the Magnetic Resonance Imaging (MRI) images. This will serve as a vital aid to estimate the extent of damage caused to the brain cells. However, manual delineation of the lesion is time-consuming and it is subjected to intra-observer and inter-observer variability. Most of the existing methods for ischemic lesion segmentation rely on extracting handcrafted features followed by application of a machine learning algorithm. Identifying such features demand multi-domain expertise in Neuro-radiology as well as Image processing. This can be accomplished by learning the features automatically using Convolutional Neural Network (CNN). To perform segmentation, the spatial arrangement of pixel needs to be preserved in addition to learning local features of an image. Hence, a deep supervised Fully Convolutional Network (FCN) is presented in this work to segment the ischemic lesion. The highlight of this research is the application of Leaky Rectified Linear Unit activation in the last two layers of the network for a precise reconstruction of the ischemic lesion. By doing so, the network was able to learn additional features which are not considered in the existing U-Net architecture. Also, an extensive analysis was conducted in this research to select optimal hyper-parameters for training the FCN. A mean segmentation accuracy of 0.70 has been achieved from the experiments conducted on ISLES 2015 dataset. Experimental observations show that our proposed FCN method is 10% better than the existing works in terms of Dice Coefficient.     

Tissue-Specific Ferritin- and GFP-Based Genetic Vectors Visualize Neurons by MRI in the Intact and Post-Ischemic Rat Brain

(1) Background: Neurogenesis is considered to be a potential brain repair mechanism and is enhanced in stroke. It is difficult to reconstruct the neurogenesis process only from the histological sections taken from different animals at different stages of brain damage and restoration. Study of neurogenesis would greatly benefit from development of tissue-specific visualization probes. (2) Purpose: The study aimed to explore if overexpression of ferritin, a nontoxic iron-binding protein, under a doublecortin promoter can be used for non-invasive visualization of neurogenesis using magnetic resonance imaging (MRI). (3) Methods: Ferritin heavy chain (FerrH) was expressed in the adeno-associated viral backbone (AAV) under the doublecortin promoter (pDCX), specific for young neurons, in the viral construct AAV-pDCX-FerrH. Expression of the enhanced green fluorescent protein (eGFP) was used as an expression control (AAV-pDCX-eGFP). The viral vectors or phosphate-buffered saline (PBS) were injected intracerebrally into 18 adult male Sprague–Dawley rats. Three days before injection, rats underwent transient middle-cerebral-artery occlusion or sham operation. Animals were subjected to In vivo MRI study before surgery and on days 7, 14, 21, and 28 days after injection using a Bruker BioSpec 11.7 T scanner. Brain sections obtained on day 28 after injection were immunostained for ferritin, young (DCX) and mature (NeuN) neurons, and activated microglia/macrophages (CD68). Additionally, RT-PCR was performed to confirm ferritin expression. (4) Results: T2* images in post-ischemic brains of animals injected with AAV-pDCX-FerrH showed two distinct zones of MRI signal hypointensity in the ipsilesioned hemisphere starting from 14 days after viral injection—in the ischemic lesion and near the lateral ventricle and subventricular zone (SVZ). In sham-operated animals, only one zone of hypointensity near the lateral ventricle and SVZ was revealed. Immunochemistry showed that ferritin-expressing cells in ischemic lesions were macrophages (88.1%), while ferritin-expressing cells near the lateral ventricle in animals both after ischemia and sham operation were mostly mature (55.7% and 61.8%, respectively) and young (30.6% and 7.1%, respectively) neurons. RT-PCR confirmed upregulated expression of ferritin in the caudoputamen and corpus callosum. Surprisingly, in animals injected with AAV-pDCX-eGFP we similarly observed two zones of hypointensity on T2* images. Cellular studies also showed the presence of mature (81.5%) and young neurons (6.1%) near the lateral ventricle in both postischemic and sham-operated animals, while macrophages in ischemic lesions were ferritin-positive (98.2%). (5) Conclusion: Ferritin overexpression induced by injection of AAV-pDCX-FerrH was detected by MRI using T2*-weighted images, which was confirmed by immunochemistry showing ferritin in young and mature neurons. Expression of eGFP also caused a comparable reduced MR signal intensity in T2*-weighted images. Additional studies are needed to investigate the potential and tissue-specific features of the use of eGFP and ferritin expression in MRI studies.