364 research outputs found

    Evaluation of left ventricular torsion by cardiovascular magnetic resonance

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    Recently there has been considerable interest in LV torsion and its relationship with symptomatic and pre-symptomatic disease processes. Torsion gives useful additional information about myocardial tissue performance in both systolic and diastolic function. CMR assessment of LV torsion is simply and efficiently performed. However, there is currently a wide variation in the reporting of torsional motion and the procedures used for its calculation. For example, torsion has been presented as twist (degrees), twist per length (degrees/mm), shear angle (degrees), and shear strain (dimensionless). This paper reviews current clinical applications and shows how torsion can give insights into LV mechanics and the influence of LV geometry and myocyte fiber architecture on cardiac function. Finally, it provides recommendations for CMR measurement protocols, attempts to stimulate standardization of torsion calculation, and suggests areas of useful future research

    Gas Concentration Measurements in Underground Waste Storage Tanks

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    Currently over 100 underground tanks at the Hanford facility in eastern Washington state are being used to store high-level radioactive waste. With plans for a long-term nuclear-waste repository in Nevada in place (though not yet approved), one promising use for these underground storage tanks is as a temporary waystation for waste destined for the Nevada repository. However, without a reasonable understanding of the chemical reactions going on within the tanks, transporting waste in and out of the tanks has been deemed to be unsafe. One hazard associated with such storage mechanisms is explosion of flammable gases produced within the tank. Within many of the storage tanks is a sludge layer. This layer, which is a mixture of liquid and solids, contains most of the radioactive material. Radioactive decay and its associated heat can produce several flammable materials within this layer. Two components of particular concern are hydrogen (H2) and nitrous oxide (N2O), since they are highly volatile in the gaseous phase. Though the tanks have either forced or natural convection systems to vent these gases, the possibility of an explosion still exists. Measurements of these gases are taken in several ways. Continuous measurements are taken in the headspace, which is the layer between the tank ceiling and the liquid (supernatant) or sludge layer below. In tanks where a supernatant layer sits atop the sludge layer, there are often rollovers or gas release events (GREs), where a large chunk of sludge, after attaining a certain void fraction, becomes buoyant, rising through the supernatant and releasing its associated gas composition to the headspace. Such changes trigger a sensor, and thus measurements are also taken at that time. Lastly, a retained gas sample (RGS) can be taken from either the supernatant or sludge layer. Such a core sample is quite expensive, but can yield crucial data about the way gases are being produced in the sludge and convected through the supernatant. Unfortunately, the measurements from these three populations do not seem to match. In particular, the ratio r = [N2O]/[H2] varies from population to population. r also varies from tank to tank, but this can more readily be explained in terms of the waste composition of each tank. Since H2 is more volatile than N2O (and since there are more sources of oxygen in the headspace), lower values of r correspond to more hazardous situations. This variance in r is troubling, since we need to be able to explain why certain values of r are lower (and hence more dangerous) in certain areas of the tank. In this report we examine the data from three tanks. We first verify that the differences in r among populations is significant. We then postulate several mechanisms which could explain such a difference

    Model-based Analysis of Cardiac Motion from Tagged MRI Data

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    We develop a new method for analyzing the motion of the left ventricle (LV) of a heart from tagged MRI data. Our technique is based on the development of a new class of physics-based deformable models whose parameters are functions allowing the definition of new parameterized primitives and parameterized deformations. These parameter functions improve the accuracy of shape description through the use of a few intuitive parameters such as functional twisting. Furthermore, these parameters require no complex post-processing in order to be used by a physician. Using a physics-based approach, we convert these geometric models into deformable models that deform due to forces exerted from the datapoints and conform to the given dataset. We present experiments involving the extraction of shape and motion of the LV from MRI-SPAMM data based on a few parameter functions. Furthermore, by plotting the variations over time of the extracted model parameters from normal and abnormal heart data we are able to characterize quantitatively their differences

    Current and Future Role of Artificial Intelligence in Cardiac Imaging

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    Cardiovascular disease remains the most common cause of morbidity and mortality worldwide, and thus an important focus for medical research and medical imaging. Despite continuous advances in cardiac imaging modalities, including echocardiography, cardiovascular magnetic resonance and cardiac computed tomography, the heart remains a challenging organ to image, in particular due to its perpetual motion. Other challenges faced by cardiac imaging include respiratory motion, complex geometry of the ventricles and atria, variability in imaging conditions and protocols, oblique orientation of the heart with respect to the body, and the small size of some of the cardiac structures, including the coronary arteries, trabeculae and papillary muscles

    Development of a method for the measurement of primary cilia length in 3D

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    BACKGROUND: Primary cilia length is an important measure of cell and tissue function. While accurate length measurements can be calculated from cells in 2D culture, measurements in tissue or 3D culture are inherently difficult due to optical distortions. This study uses a novel combination of image processing techniques to rectify optical distortions and accurately measure cilia length from 3D images. METHODS: Point spread functions and experimental resolutions were calculated from subresolution microspheres embedded in 3D agarose gels for both wide-field fluorescence and confocal laser scanning microscopes. The degree of axial smearing and spherical aberration was calculated from xy:xz diameter ratios of 3D image data sets of 4 μm microspheres that had undergone deconvolution and/or Gaussian blurring. Custom-made 18 and 50 μm fluorescent microfibers were also used as calibration objects to test the suitability of processed image sets for 3D skeletonization. Microfiber length in 2D was first measured to establish an original population mean. Fibers were then embedded in 3D agarose gels to act as ciliary models. 3D image sets of microfibers underwent deconvolution and Gaussian blurring. Length measurements within 1 standard deviation of the original 2D population mean were deemed accurate. Finally, the combined method of deconvolution, Gaussian blurring and skeletonization was compared to previously published methods using images of immunofluorescently labeled renal and chondrocyte primary cilia. RESULTS: Deconvolution significantly improved contrast and resolution but did not restore the xy:xz diameter ratio (0.80). Only the additional step of Gaussian blurring equalized xy and xz resolutions and yielded a diameter ratio of 1.02. Following image processing, skeletonization successfully estimated microfiber boundaries and allowed reliable and repeatable measurement of fiber lengths in 3D. We also found that the previously published method of calculating length from 2D maximum projection images significantly underestimated ciliary length. CONCLUSIONS: This study used commercial and public domain image processing software to rectify a long-standing problem of 3D microscopy. We have shown that a combination of deconvolution and Gaussian blurring rectifies optical distortions inherent in 3D images and allows accurate skeletonization and length measurement of microfibers and primary cilia that are bent or curved in 3D space

    Feasibility of single breath-hold left ventricular function with 3 Tesla TSENSE acquisition and 3D modeling analysis

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    <p>Abstract</p> <p>Background</p> <p>A single breath-hold evaluation of ventricular function would allow assessment in cases where scan time or patient tolerance is limited. Spatiotemporal acceleration techniques such as TSENSE decrease cardiovascular MR acquisition time, but standard slice summation analysis requires enough short axis slices to cover the left ventricle (LV). By reducing the number of short axis slices, incorporating long axis slices, and applying a 3D model based analysis, it may be possible to obtain accurate LV mass and volumes. We evaluated LV volume, mass and ejection fraction at 3.0T using a 3D modeling analysis in 9 patients with a history of myocardial infarction and one healthy volunteer. Acquisition consisted of a standard short axis SSFP stack and a 15 heart-beat single breath-hold six slice multi-planar (4 short and 2 long axis) TSENSE SSFP protocol with an acceleration factor of <it>R </it>= 4.</p> <p>Results</p> <p>Differences (standard minus accelerated protocol mean ± s.d.) and coefficients of variation (s.d. of differences as a percentage of the average estimate) were 7.5 ± 9.6 mL and 6% for end-diastolic volume (p = 0.035), 0.4 ± 5.1 mL and 7% for end-systolic volume (p = NS), 7.1 ± 8.1 mL and 9% for stroke volume (p = 0.022), 2.2 ± 2.8% and 5% for ejection fraction (p = 0.035), and -7.1 ± 6.2 g and 4% for LV mass (p = 0.005), respectively. Intra- and inter-observer errors were similar for both protocols (p = NS for all measures).</p> <p>Conclusion</p> <p>These results suggest that clinically useful estimates of LV function can be obtained in a TSENSE accelerated single breath-hold reduced slice acquisition at 3T using 3D modeling analysis techniques.</p

    Aortic valve stenotic area calculation from phase contrast cardiovascular magnetic resonance: the importance of short echo time

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    <p>Abstract</p> <p>Background</p> <p>Cardiovascular magnetic resonance (CMR) can potentially quantify aortic valve area (AVA) in aortic stenosis (AS) using a single-slice phase contrast (PC) acquisition at valve level: AVA = aortic flow/aortic velocity-time integral (VTI). However, CMR has been shown to underestimate aortic flow in turbulent high velocity jets, due to intra-voxel dephasing. This study investigated the effect of decreasing intra-voxel dephasing by reducing the echo time (TE) on AVA estimates in patients with AS.</p> <p>Method</p> <p>15 patients with moderate or severe AS, were studied with three different TEs (2.8 ms/2.0 ms/1.5 ms), in the main pulmonary artery (MPA), left ventricular outflow tract (LVOT) and 0 cm/1 cm/2.5 cm above the aortic valve (AoV). PC estimates of stroke volume (SV) were compared with CMR left ventricular SV measurements and PC peak velocity, VTI and AVA were compared with Doppler echocardiography. CMR estimates of AVA obtained by direct planimetry from cine acquisitions were also compared with the echoAVA.</p> <p>Results</p> <p>With a TE of 2.8 ms, the mean PC SV was similar to the ventricular SV at the MPA, LVOT and AoV<sub>0 cm </sub>(by Bland-Altman analysis bias ± 1.96 SD, 1.3 ± 20.2 mL/-6.8 ± 21.9 mL/6.5 ± 50.7 mL respectively), but was significantly lower at AoV<sub>1 </sub>and AoV<sub>2.5 </sub>(-29.3 ± 31.2 mL/-21.1 ± 35.7 mL). PC peak velocity and VTI underestimated Doppler echo estimates by approximately 10% with only moderate agreement. Shortening the TE from 2.8 to 1.5 msec improved the agreement between ventricular SV and PC SV at AoV<sub>0 cm </sub>(6.5 ± 50.7 mL vs 1.5 ± 37.9 mL respectively) but did not satisfactorily improve the PC SV estimate at AoV<sub>1 cm </sub>and AoV<sub>2.5 cm</sub>. Agreement of CMR AVA with echoAVA was improved at TE 1.5 ms (0.00 ± 0.39 cm<sup>2</sup>) versus TE 2.8 (0.11 ± 0.81 cm<sup>2</sup>). The CMR method which agreed best with echoAVA was direct planimetry (-0.03 cm<sup>2 </sup>± 0.24 cm<sup>2</sup>).</p> <p>Conclusion</p> <p>Agreement of CMR AVA at the aortic valve level with echo AVA improves with a reduced TE of 1.5 ms. However, flow measurements in the aorta (AoV 1 and 2.5) are underestimated and 95% limits of agreement remain large. Further improvements or novel, more robust techniques are needed in the CMR PC technique in the assessment of AS severity in patients with moderate to severe aortic stenosis.</p
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