scholarly journals Functional MRI of the kidney: tools for translational studies of pathophysiology of renal disease

2006 ◽  
Vol 290 (5) ◽  
pp. F958-F974 ◽  
Author(s):  
Pottumarthi V. Prasad
Keyword(s):  
Animal Models ◽  
Renal Disease ◽  
Functional Mri ◽  
State Of The Art ◽  
Functional Information ◽  
Resonance Imaging ◽  
Ischemic Renal Disease ◽  
Translational Studies ◽  
Magnetic Resonance Imaging Mri ◽  
Do So

Magnetic resonance imaging (MRI) provides exquisite anatomic detail of various organs and is capable of providing additional functional information. This combination allows for comprehensive diagnostic evaluation of pathologies such as ischemic renal disease. Noninvasive MRI techniques could facilitate translation of many studies performed in controlled animal models using technologies that are invasive to humans. Such a translation is being recognized as essential because many proposed interventions and drugs that prove efficacious in animal models fail to do so in humans. In this article, we review the state-of-the-art functional MRI technique as applied to the kidneys.

scholarly journals Using magnetic resonance imaging in animal models to guide drug development in multiple sclerosis

2013 ◽  
Vol 20 (1) ◽  
pp. 3-11 ◽  
Author(s):  
Nabeela Nathoo ◽  
V Wee Yong ◽  
Jeff F Dunn
Keyword(s):  
Magnetic Resonance Imaging ◽  
Multiple Sclerosis ◽  
Clinical Trials ◽  
Magnetic Resonance ◽  
Animal Models ◽  
Mr Imaging ◽  
Preclinical Studies ◽  
Resonance Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
Potential Therapeutics

Major advances are taking place in the development of therapeutics for multiple sclerosis (MS), with a move past traditional immunomodulatory/immunosuppressive therapies toward medications aimed at promoting remyelination or neuroprotection. With an increase in diversity of MS therapies comes the need to assess the effectiveness of such therapies. Magnetic resonance imaging (MRI) is one of the main tools used to evaluate the effectiveness of MS therapeutics in clinical trials. As all new therapeutics for MS are tested in animal models first, it is logical that MRI be incorporated into preclinical studies assessing therapeutics. Here, we review key papers showing how MR imaging has been combined with a range of animal models to evaluate potential therapeutics for MS. We also advise on how to maximize the potential for incorporating MRI into preclinical studies evaluating possible therapeutics for MS, which should improve the likelihood of discovering new medications for the condition.

Magnetic resonance imaging of catalytically relevant processes

2019 ◽  
Vol 0 (0) ◽  
Author(s):  
Alexandra I. Svyatova ◽  
Kirill V. Kovtunov ◽  
Igor V. Koptyug
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
State Of The Art ◽  
Chemical Processes ◽  
Resonance Imaging ◽  
Heterogeneous Catalytic ◽  
Heterogeneous Catalytic Processes ◽  
Hyperpolarized Mri ◽  
Magnetic Resonance Imaging Mri ◽  
Low Sensitivity

Abstract The main aim of this article is to provide a state-of-the-art review of the magnetic resonance imaging (MRI) utilization in heterogeneous catalysis. MRI is capable to provide very useful information about both living and nonliving objects in a noninvasive way. The studies of an internal heterogeneous reactor structure by MRI help to understand the mass transport and chemical processes inside the working catalytic reactor that can significantly improve its efficiency. However, one of the serious disadvantages of MRI is low sensitivity, and this obstacle dramatically limits possible MRI application. Fortunately, there are hyperpolarization methods that eliminate this problem. Parahydrogen-induced polarization approach, for instance, can increase the nuclear magnetic resonance signal intensity by four to five orders of magnitude; moreover, the obtained polarization can be stored in long-lived spin states and then transferred into an observable signal in MRI. An in-depth account of the studies on both thermal and hyperpolarized MRI for the investigation of heterogeneous catalytic processes is provided in this review as part of the special issue emphasizing the research performed to date in Russia/USSR.

Concordance Between Transcranial Magnetic Stimulation and Functional Magnetic Resonance Imaging (MRI) Derived Localization of Language in a Clinical Cohort

2020 ◽  
Vol 35 (6) ◽  
pp. 363-379
Author(s):  
Katherine Schiller ◽  
Asim F. Choudhri ◽  
Tamekia Jones ◽  
Christen Holder ◽  
James W. Wheless ◽  
...  
Keyword(s):  
Functional Mri ◽  
Odds Ratio ◽  
Magnetic Stimulation ◽  
Diagnostic Odds Ratio ◽  
Functional Magnetic Resonance ◽  
Resonance Imaging ◽  
Clinical Cohort ◽  
Brodmann Areas ◽  
Magnetic Resonance Imaging Mri ◽  
Language Areas

Transcranial magnetic stimulation (TMS) is a newer noninvasive language mapping tool that is safe and well-tolerated by children. We examined the accuracy of TMS-derived language maps in a clinical cohort by comparing it against functional magnetic resonance imaging (MRI)–derived language map. The number of TMS-induced speech disruptions and the volume of activation during functional MRI tasks were localized to Brodmann areas for each modality in 40 patients with epilepsy or brain tumor. We examined the concordance between TMS- and functional MRI–derived language maps by deriving statistical performance metrics for TMS including sensitivity, specificity, accuracy, and diagnostic odds ratio. Brodmann areas 6, 44, and 9 in the frontal lobe and 22 and 40 in the temporal lobe were the most commonly identified language areas by both modalities. Overall accuracy of TMS compared to functional MRI in localizing language cortex was 71%, with a diagnostic odds ratio of 1.27 and higher sensitivity when identifying left hemisphere regions. TMS was more accurate in determining the dominant hemisphere for language with a diagnostic odds ratio of 6. This study is the first to examine the accuracy of the whole brain language map derived by TMS in the largest cohort examined to date. While this comparison against functional MRI confirmed that TMS reliably localizes cortical areas that are not essential for speech function, it demonstrated only slight concordance between TMS- and functional MRI–derived language areas. That the localization of specific language cortices by TMS demonstrated low accuracy reveals a potential need to use concordant tasks between the modalities and other avenues for further optimization of TMS parameters.

Neuroimaging Techniques and Their Application in the Spinal Cord

2016 ◽  
Vol 2 (4) ◽  
pp. 211-214
Author(s):  
Yong Hu
Keyword(s):  
Spinal Cord ◽  
Neural Function ◽  
Functional Information ◽  
Resonance Imaging ◽  
Spinal Disorders ◽  
Human Spinal Cord ◽  
Non Invasive ◽  
Conventional Mri ◽  
Magnetic Resonance Imaging Mri ◽  
Neuroimaging Techniques

Non-invasive neuroimaging plays a crucial role in the assessment of the human spinal cord, but it is quite challenging. Magnetic resonance imaging (MRI) is an important modality to obtain both high-resolution anatomical and functional information concerning the spinal cord. Besides conventional MRI, advanced MRI techniques could provide novel information about the microstructure and neural function of the spinal cord, thereby enhancing the understanding of spinal cord neurology and pathology of various spinal disorders.

scholarly journals Automated Multimodal image fusion for brain tumor detection

2021 ◽  
Vol 3 (1) ◽  
pp. 68-82
Author(s):  
Harpreet Kaur ◽  
◽  
Deepika Koundal ◽  
Virendar Kadyan ◽  
Navneet Kaur ◽  
...  
Keyword(s):  
Image Fusion ◽  
State Of The Art ◽  
Signal To Noise Ratio ◽  
Visual Image ◽  
Fusion Rule ◽  
Resonance Imaging ◽  
Signal To Noise ◽  
Multiple Images ◽  
Fused Image ◽  
Magnetic Resonance Imaging Mri

In medical domain, various multimodalities such as Computer tomography (CT) and Magnetic resonance imaging (MRI) are integrated into a resultant fused image. Image fusion (IF) is a method by which vital information can be preserved by extracting all important information from the multiple images into the resultant fused image. The analytical and visual image quality can be enhanced by the integration of different images. In this paper, a new algorithm has been proposed on the basis of guided filter with new fusion rule for the fusion of different imaging modalities such as MRI and Fluorodeoxyglucose images of brain for the detection of tumor. The performance of the proposed method has been evaluated and compared with state-of-the-art image fusion techniques using various qualitative as well as quantitative evaluation metrics. From the results, it has been observed that more information has achieved on edges and content visibility is also high as compared to the other techniques which makes it more suitable for real applications. The experimental results are evaluated on the basis of with-reference and without-references metric such as standard deviation, entropy, peak signal to noise ratio, mutual information etc.

scholarly journals Magnetic Resonance Imaging in Animal Models of Alzheimer’s Disease Amyloidosis

2021 ◽  
Author(s):  
Ruiqing Ni
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Animal Models ◽  
Amyloid Beta ◽  
High Field ◽  
Diffusion Tensor ◽  
Small Animal ◽  
Resonance Imaging ◽  
Magnetic Resonance Imaging Mri

Amyloid-beta plays an important role in the pathogenesis of Alzheimer’s disease. Aberrant amyloid-beta and tau accumulation induce neuroinflammation, cerebrovascular alterations, synaptic deficits, functional deficits, and neurodegeneration, leading to cognitive impairment. Animal models recapitulating the amyloid-beta pathology such as transgenic, knock-in mouse and rat models have facilitated the understanding of disease mechanisms and development of therapeutics targeting at amyloid-beta. There is a rapid advance in high-field MR in small animals. Versatile high-field magnetic resonance imaging (MRI) sequences such as diffusion tensor imaging, arterial spin labelling, resting-state functional MRI, anatomical MRI, MR spectroscopy as well as contrast agents have been developed for the applications in animal models. These tools have enabled high-resolution in vivo structural, functional, and molecular readouts with a whole brain field-of-view. MRI have been utilized to visualize non-invasively the amyloid-beta deposits, synaptic deficits, regional brain atrophy, impairment in white matter integrity, functional connectivity, cerebrovascular and glymphatic system in animal models of amyloidosis. Many of the readouts are translational in clinical MRI in the brain of patients with Alzheimer’s disease. In this review, we summarize the recent advance of using MRI for visualizing the pathophysiology in amyloidosis animal model. We discuss the outstanding challenges in brain imaging using MRI in small animal and propose future outlook in visualizing amyloid-beta-related alterations in brain of animal models.

QuadrupletNet: A Novel Local Descriptor for Brain Tumor Detection and Segmentation

2020 ◽  
Vol 10 (7) ◽  
pp. 1763-1768
Author(s):  
Jun Jiang ◽  
Jing Jin ◽  
Binluo Wang ◽  
Jinming Wang ◽  
Tiaojuan Ren ◽  
...  
Keyword(s):  
Brain Tumor ◽  
State Of The Art ◽  
Tumor Detection ◽  
Segmentation Method ◽  
Resonance Imaging ◽  
Brain Tumor Surgery ◽  
Local Descriptor ◽  
Mri Brain ◽  
Triplet Loss ◽  
Magnetic Resonance Imaging Mri

Brain tumor detection and segmentation from Magnetic Resonance Imaging (MRI) images is being one of the emerging fields in the biomedicine. A formidable undertaking in brain tumor surgery, medical care, treatment programme and quantitative assessment of MRI images is to precisely diagnose its location and extent. Recently, the convolutional neural network (CNN) based detection and segmentation method on brain tumor MRI images is being one of the emerging fields in the medical imaging as an automatic clinic treatment and evaluation solution. In this article, we put forward a brand new quadruplet loss in CNN framework, which achieves higher accuracy in brain tumor detection and segmentation than other pairwise loss and triplet loss methods. By applying the proposed quadruplet loss to the original L2Net CNN architecture leads to a more compact descriptor named QuadrupletNet. From our experiments, QuadrupletNet shows higher performance than other state-of-the-art loss functions e.g., the Triplet loss, as indicated in experiments on Multimodal Brain Tumor Image Segmentation (BRATS 2018) datasets, and on our own collected MRI brain tumor datasets (named MBTD).

Magnetic Resonance Imaging of the Brain in Children With Headache

2011 ◽  
Vol 50 (12) ◽  
pp. 1134-1139 ◽  
Author(s):  
Phillipp Fridolin Streibert ◽  
Werner Piroth ◽  
Michael Mansour ◽  
Patrick Haage ◽  
Thorsten Langer ◽  
...  
Keyword(s):  
Magnetic Resonance Imaging ◽  
Magnetic Resonance ◽  
Clinical Relevance ◽  
State Of The Art ◽  
Resonance Imaging ◽  
Magnetic Resonance Imaging Mri ◽  
The Brain

The aim of this study was to evaluate the frequency of abnormal findings in magnetic resonance imaging (MRI) in children with headache, the clinical relevance of these findings, and whether more sophisticated technologies also result in more relevant abnormal findings. The MRIs of 1004 children with age ranging from 1 to 17 years were retrospectively analyzed. Children who were investigated with established sequences (n = 419) were compared with those examined with state-of-the-art MRI acquisition technology (n = 585). In 216/1004 investigations, MRI was performed because of headache (74/216 with established sequences, 142/216 with state-of-the-art acquisition technology). In 114/216 (52.8%) patients with headache, the MRI was abnormal with relevant findings in 23/114 patients and findings without clinical relevance in 91/114 children. A higher incidence of abnormal findings than in previous reports was found but there was only limited clinical gain of information using modern sequences in children with headache.

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