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Tracks & Trails

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Hunter Phillips
Hunter Phillips

Download File KSN Part 6-10 PDF File With Full ...


One of two approaches may be used to determine severity of valvular stenosis with PC-CMR. The first is to serially obtain in-plane two-dimensional velocity-encoded cine acquisitions to identify the direction of the peak velocity, and then prescribe through-plane acquisitions perpendicular to the jet direction to obtain the peak velocity. This works well when there is one predominant stenotic jet (Figs. 6 and 7, Additional file 1A-D), but fares less well in the setting of multiple jets. The other approach involves velocity encoding in multiple directions over a volume that encompasses one or more stenotic jets emanating from the valve. This may not be feasible due long acquisition times and limited availability of post-processing tools to extract the peak velocity. In practice, the former approach is most often used, recognizing that without meticulous prescriptions to identify the plane of highest velocity one may easily underestimate stenosis severity. Also, most current clinical systems use segmented techniques that yield average velocities over multiple cardiac cycles. Newer approaches to real-time velocity encoded cine imaging are preferred when available to capture beat-to-beat variation [107, 142].




Download File KSN Part 6-10 PDF file with full ...



Aortic Stenosis. a Systolic frame from a balanced SSFP cine CMR acquisition in the left ventricular outflow tract plane shows a turbulent jet emanating from a thickened aortic valve suggesting significant stenosis. b Short axis view at the level of the aortic valve demonstrates a bicuspid valve en face with calcification of the anterior leaflet as well as at the commissural junctions. c Phase contrast image at mid-systole with VENC setting of 250 cm/s shows extensive aliasing, suggesting the peak velocity is considerably higher than 2.5 m/s. d Repeat phase contrast acquisition at the same location and point in the cardiac cycle with VENC increased to 450 cm/s eliminates aliasing, allowing for accurate quantification of peak velocity across this stenotic valve. See also Additional file 1


Other causes of shunt flow include anomalous pulmonary venous drainage [169], patent ductus arteriosus (Fig. 10, Additional file 3), aortopulmonary collaterals (APCs) [170] and iatrogenic shunts, such as those used to palliate cyanotic heart disease. Reliance on Qp:Qs to detect and quantify shunt flow should occur in the setting of several caveats. First, advanced pulmonary hypertension may blunt left-to-right shunting (Eisenmenger physiology), particularly in the presence of a large, long-standing intracardiac defect (Fig. 11, Additional file 4). Small shunts such as those seen with intermittent flow across a patent foramen ovale may not produce significant changes from normal in Qp:Qs, and borderline abnormal Qp:Qs results should prompt a search for other evidence before inferring presence of a shunt.


Ventricular Septal Defect. End-diastolic (a) and end-systolic (b) frames of a horizontal long-axis cine CMR acquisition demonstrate a large ventricular septal defect (VSD) of the basal half of the interventricular septum. In-plane PC-CMR showed no appreciable flow across this long-standing, restrictive VSD (Additional file 4). Through-plane PC-CMR with regions of interest (dotted circles) encircling the aortic valve (c,d) and pulmonic valve (e,f) allowed calculation of Qp:Qs that yielded a value close to 1:1, consistent with Eisenmenger physiology or advanced pulmonary hypertension limiting flow across even a large defect


The governing equations that describe the flow of fluid through a prescribed geometry are the Navier-Stokes equations. Numerically solving these equations using CFD models yields the velocity field. In general, although more general approaches have been pursued, analysis of flow in vascular structures is performed with two simplifying assumptions, namely that blood can be considered to be Newtonian and that the vessel walls are rigid. Although CFD methods have been used in application to idealized representations of vascular geometry, their greatest value comes in the calculation of velocity fields on a patient-specific basis [203, 206, 207]. In order to achieve this goal, the CFD model requires accurate boundary conditions [208]. For a vascular segment of interest, the required boundary conditions are both geometric, namely a full description of the luminal surface over that segment, and physiologic, describing all time-varying flow contributions into and out of the segment of interest. CMR is the radiologic imaging modality that is best suited for defining the boundary conditions. There are a variety of MRA methods for delineating the vascular lumen, including time-of-flight MRA, contrast-enhanced MRA, and phase contrast MRA [209]. Although other modalities such as Rotational Catheter Angiography, or Multi-Detector CTA have better spatial resolution than these MR angiographic methods [210], MR is the only modality that can, in addition, provide the profile of flow velocities across the flow lumen through the cardiac cycle. Although Doppler Ultrasound has unmatched spatial and temporal resolution, it is not able to simultaneously detect for example transverse velocity components at the same time as axial velocity components, which limits its ability to estimate the velocity profile across the vessel lumen [211]. 041b061a72


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