Recent advances in 4DFlow MRI (Phase Contrast MRA) acquisition and reconstruction enable high resolution exams to be obtained in practical imaging times. 4DFlow MRI provides images of vascular morphology and quantitative measurements of blood velocity throughout a 3D imaging volume. Hemodynamic parameters such as flow volume, relative wall shear stress, streamlines, vorticity and pressure gradients can be derived from the velocity data. The combination of anatomic vessel wall imaging, lumen visualization and physiologic data derived from accelerated 4DFlow MRI augments the characterization of intracranial arterial stenosis, aneurysms, vascular malformations and dural sinus pathology. This review provides an update for clinicians interested in 4DFlow MRI of the brain.
Noncontrast PCASL-MRA with 3D radial acquisition is a potential tool for the detection and characterization of intracranial AV shunts with a sensitivity and specificity equivalent or higher than routine clinical MRA.
Objective
Time resolved contrast enhanced magnetic resonance angiography (TR CEMRA) is commonly used to non-invasively characterize vascular malformations. However, the spatial and temporal resolution of current methods often compromises the clinical value of the exams. Constrained reconstruction is a temporal spatial correlation strategy that exploits the relative sparsity of vessels in space to dramatically reduce the amount of data required to generate fast high resolution TR CEMRA studies. In this report we use a novel temporal spatial acceleration method termed HYPRFLow to diagnose and classify dural arteriovenous fistulas (DAVFs). Our hypothesis is that HYPRFLow images are of adequate diagnostic image quality to delineate the arterial and venous components of DAVFs and allow correct classification using the Cognard system.
Subjects and Methods
8 patients with known DAVFs underwent HYPRFlow imaging with isotropic resolution of 0.68 mm and temporal resolution of 0.75 s and 3D Time of Flight MRA (3DTOF). 3DTOF images and HYPRFLow images were evaluated by 2 readers and scored for arterial anatomic image quality. DSA was available for comparison in seven subjects and for these patients each DAVF was classified according to the Cognard system using HYPRFlow and DSA exams. DSA was considered the reference exam or gold standard.
Results
HYPRFlow imaging classification was concordant with DSA in all but one case. There was no difference in the arterial image quality scores between HYPRFlow and 3DTOF MRA (95% CI). Arterial to venous separation was rated excellent (n=3), good (n=4) or poor (n=1)and arteriovenous shunting was easily appreciated. Undersampling artifacts were reduced by using a low pass filter and did not interfere with the diagnostic quality of the exams.
Conclusion
HYPRFlow is a novel acquisition and reconstruction technique that exploits the relative sparsity of intracranial vessels in space to increase temporal and spatial resolution and provides accurate delineation of DAVF vasculature.
Chronic pain is associated with several disease conditions. The inadequacy of current analgesics to treat chronic pain is the result of a lack of understanding of the mechanisms that mediate pain. RNA interference has emerged in recent years as a new way to evaluate the roles of molecules involved in the pain response. Selective knockout of proteins has proven to be a powerful technique for target validation, but has been limited as a potential therapeutic due to short-lived responses induced by RNAi. The short responses of RNAi illustrate the need for better delivery techniques, which is being addressed by current work to induce RNAi through the cell’s natural mechanisms. In order to gain a better understanding of chronic pain, it will be necessary to evaluate the pain molecules that are expressed as part of an injury induced pain response, which can be modeled by contusion spinal cord injury. RNAi will prove to be an important technique in this work. The present minireview will summarize the work that has been done using RNAi in vivo to study pain and discuss future directions for the use of RNAi to study chronic pain.
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