Feasibility of non-contrast-enhanced magnetic resonance angiography for imaging upper extremity vasculature prior to vascular access creation.

OBJECTIVES: Preoperative mapping of arterial and venous anatomy helps to prevent postoperative complications after vascular access creation. The use of gadolinium in contrast-enhanced (CE) magnetic resonance angiography (MRA) has been linked to nephrogenic systemic fibrosis in patients with end-stage renal disease (ESRD). The purpose of this study was to evaluate non-contrast-enhanced (NCE) MRA for assessment of upper extremity and central vasculature and to compare it with CE-MRA. METHODS: NCE and CE-MRA images were acquired in 10 healthy volunteers and 15 patients with ESRD. In each data set, two observers analysed 11 arterial and 16 venous segments with regard to image quality (0-4), presence of artefacts (0-2) and vessel-to-background ratio. RESULTS: More arterial segments were depicted using CE-MRA compared to NCE-MRA (99% vs. 96%, p = 0.001) with mean image quality of 3.80 vs. 2.68, (p < 0.001) and mean vessel-to-background ratio of 6.47 vs. 4.14 (p < 0.001). Ninety-one percent of the venous segments were portrayed using NCE-MRA vs. 80% using CE-MRA (p < 0.001). Mean image quality and vessel-to-background ratio were 2.41 vs. 2.21 (p = 0.140) and 5.13 vs. 3.88 (p < 0.001), respectively. CONCLUSIONS: Although arterial image quality and vessel-to-background ratios were lower, NCE-MRA is considered a feasible alternative to CE-MRA in patients with ESRD who need imaging of the upper extremity and central vasculature prior to dialysis access creation.

Assisting vascular access surgery planning for hemodialysis by using MR, image segmentation techniques, and computer simulations.

The surgical creation of a vascular access, used for hemodialysis treatment of renal patients, has considerable complication rates (30-50 %). Image-based computational modeling might assist the surgeon in planning by enhanced analysis of preoperative hemodynamics, and in the future might serve as platform for outcome prediction. The objective of this study is to investigate preoperative personalization of the computer model using magnetic resonance (MR). MR-angiography and MR-flow data were obtained for eight patients and eight volunteers. Blood vessels were extracted for model input by a segmentation algorithm. Windkessel elements were added at the ends to represent the peripheral beds. Monte Carlo-based calibration was used to estimate the most influential non-measurable parameters. The predicted flow waveforms were compared with the MR-flow measurements for framework evaluation. The vasculature of all subjects were segmented in on average <5 min. The Monte Carlo-calibrated simulations showed a deviation between measured and simulated flow waveforms of 9 and 10 % for volunteers and patients, respectively. The presented method accurately mimics the preoperative hemodynamic state. Furthermore, the surgeon can interactively explore the hemodynamics at any vascular tree position. This integration of measurements in a modeling approach can provide the surgeon with additional information for preoperative planning.

Importance of initial stress for abdominal aortic aneurysm wall motion: dynamic MRI validated finite element analysis.

Currently the transverse diameter is the primary decision criterion to assess rupture risk in patients with an abdominal aortic aneurysm (AAA). To obtain a measure for more patient-specific risk assessment, aneurysm wall stress, calculated using finite element analysis (FEA), has been evaluated in literature. In many cases, initial stress, present in the AAA wall during image acquisition, is not taken into account. In the current study the effect of initial stress incorporation (ISI) is determined by directly comparing wall displacements extracted from FEA and dynamic MRI. Ten patients with an aneurysm diameter >5.5 cm were scanned with cardiac triggered MRI. Semi-automatic segmentation of the AAA was performed on the diastolic phase. The segmented in-slice contours were propagated through the remaining cardiac phases using an active contour model as to track wall displacements on MRI. Consequently, FEA with and without ISI (no-ISI) was performed using the diastolic geometry with simultaneously measured intra-aneurysm pressure values as boundary condition. Contours extracted from FEA were compared with MRI contours at corresponding cardiac phases by distance and relative area differences. The wall displacements from FEA with ISI show significant better correspondence with wall motion from MRI data in comparison with the no-ISI FEA (deviation in wall displacement 1.7% vs. 12.4%; p<0.001). Based on these results it can be concluded that incorporation of initial stress significantly improves wall displacement accuracy of FEA and therefore it should be incorporated in future analyses.