7 research outputs found

    Motion Induced Phase Shifts in MR: Acceleration Effects in Quantitative Flow Measurements—A Reconsideration

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    Magnetic resonance phase difference techniques are commonly used to study flow velocities in the human body. Acceleration is often present, either in the form of pulsatile flow, or in the form of convective acceleration. Questions have arisen about the exact time point at which the velocity is encoded, and also about the sensitivity to (convective) acceleration and higher order motion derivatives. It has become common practice to interpret the net phase shifts measured with a phase difference velocity technique as being the velocity at a certain (Taylor) expansion time point, chosen somewhere between the RF excitation and the echo readout. However, phase shifts are developed over the duration of the encoding magnetic field gradient wave form, and should therefore be interpreted as a more or less time‐averaged velocity. It will be shown that the phase shift as measured with a phase difference velocity technique represents the velocity at the “gravity” center of the encoding bipolar gradient (difference) function, without acceleration contribution. Any attempt to interpret the measured phase shift in terms of velocity on any other time point than the gradient gravity point will automatically introduce acceleration sensitivity

    Assessment of flow in the right human coronary artery by magnetic resonance phase contrast velocity measurement: Effects of cardiac and respiratory motion

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    Flow in the human right coronary artery was determined using magnetic resonance phase contrast velocity quantification. Two methods were applied to reduce respiratory motion: imaging during breath holding, which is fast, and retrospective respiratory gating, which has a high temporal resolution (32 ms) in the cardiac cycle. Vessel cross-sectional area, through-plane velocity, and volume flow were determined in six healthy subjects. In-plane vessel displacement during the cardiac cycle, caused by cardiac contraction, was about 2-4 mm within a time frame of 32 ms in systole and early diastole. The motion resulted in blurring of images obtained during breath holding caused by the large acquisition time window (126 ms) within the cardiac cycle. Therefore, only with a high temporal resolution correct velocity images over the entire cardiac cycle could be obtained. The time- and cross- sectionally averaged velocity was 7 ± 2 cm/s, and the volume flow was 30 ± 10 ml/min

    Nontriggered magnetic resonance velocity measurement of the time‐average of pulsatile velocity

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    The feasibility of the determination of the time‐average of pulsatile velocity obtained via a nontriggered magnetic resonance (MR) acquisition is studied. The advantage of this method, in comparison with a triggered acquisition, is a considerable reduction (≈15×) in acquisition time. However, pul‐satility causes image artifacts, known as ghosts, and the Fourier transform technique required for the imaging procedure accomplishes time‐averaging of the complex MR signal. Both effects can result in errors in the velocity determined. Calculations show that these errors depend on the velocity time function and the acquisition parameters. In vivo comparison of triggered and nontriggered MR velocity measurements in the femoral artery of volunteers (n = 7) shows larger statistical and systematic errors in the latter, which depend on the excitation angle. Therefore, this nontriggered average velocity measurement is only useful as a fast and rough estimation of the time‐averaged velocity

    In Vivo Validation of Magnetic Resonance Blood Volume Flow Measurements with Limited Spatial Resolution in Small Vessels

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    The accuracy of magnetic resonance phase contrast volume flow measurements in small blood vessels is expected to be smaller than in large vessels, because of partial volume effects at the vessel boundary. Accuracy was validated in the dog femoral artery, diameter 3.5 ± 0.7 mm, using an ultrasonic transit‐time flowmeter (TT). The number of pixels per vessel diameter (ND) ranged from 1.6 to 4.8. The vessel cross‐section was determined using a threshold in the magnitude image. Between the two methods the correlation coefficient was 0.95 (range 10–200 ml/min). The proportional difference (PD), (QTT – QMR/1/2(QTT + QMR), was 0.8%, showing no systematic difference between the methods. The PDs standard deviation was 27%, and 19% for flow rates above 30 ml/min. Only a significant decrease of the PDs variance was found at the highest ND values, suggesting other sources of error than partial volume effects. It is concluded that with an ND value of about 3, accurate blood volume flow rates can be determined

    Mri of coronary arteries: 2d breath-hold vs 3d respiratory-gated acquisition

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    Objective: Respiratory motion degrades MR images of the coronary arteries. The purpose of this study was to assess and compare two methods of reducing the effects of respiration in coronary artery MRI. Single-slice 2D imaging with breath-holding and a respiratory-gated 3D technique were used. Materials and Methods: A comparison was made in 10 normal subjects between a 2D multiple breath-holding approach and a 3D technique with and without retrospective respiratory gating in imaging the coronary arteries. Results: Respiratory gating improved the image quality in 76% of the 3D images. Both the 2D and the 3D approaches were capable of visualizing the proximal parts of the coronary arteries, with comparable vessel length and diameter. The image quality was somewhat better for images obtained by breath-holding in 83% of the vessels, probably due to less blurring by remnant respiratory motion and higher inflow contrast. Conclusion: The 2D breath-holding approach reveals a better image quality. However, the 3D respiratory-gated acquisition is less operator dependent, faster, and less strenuous for patients

    LAB-Secretome: a genome-scale comparative analysis of the predicted extracellular and surface-associated proteins of Lactic Acid Bacteria.

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    Explaining International IT Application Leadership: Health IT

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