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Peripheral MRA with k-space Segmentation and Blood-Pool Contrast Agent

Rationale and Objectives

The purpose of this study was to perform high-resolution contrast-enhanced peripheral multistation magnetic resonance angiography using a new blood-pool contrast agent (gadofosveset trisodium; Vasovist) while suppressing venous signal by using an acquisition scheme with k-space segmentation.

Materials and Methods

Multistation peripheral magnetic resonance angiography with Vasovist was performed in 20 patients with known peripheral arterial occlusive disease. The k-space of the three-dimensional data sets was segmented such that the central parts were acquired during the first pass of the blood-pool agent, while the peripheral parts were acquired in the steady state. A third magnetic resonance angiographic data set acquired using the conventional technique served as comparison for venous overlay. Two radiologists blindly compared vessel sharpness, conspicuity, and venous contamination. Furthermore, a semiautomatic program to compare edge sharpness was used. Results were compared by means of Wilcoxon’s signed rank sum test.

Results

Comparison of vessel sharpness revealed statistically significant differences in favor of the fused data sets in all three stations. Arteries were depicted more sharply in the fused images and over longer parts, while veins were almost completely suppressed.

Conclusions

Peripheral contrast-enhanced magnetic resonance angiography with first-pass and steady-state k-space segmentation using a blood-pool contrast agent proved feasible and provided high-resolution data with sharp delineation of the arteries while reducing venous contamination.

Peripheral arterial occlusive disease (PAOD) is a significant cause of morbidity in the Western world and can lead to lower-extremity ischemia. Until recently, contrast-enhanced (CE) digital subtraction angiography had to be performed as reference standard. By now, three-dimensional (3D) CE magnetic resonance angiography (MRA) has been successfully applied to the peripheral vessels, leading to diagnostic images , and has been established as standard of reference for diagnostic evaluation of PAOD because of its noninvasiveness, its 3D nature encompassing multistation large fields of view, and its relatively good spatial resolution.

The timing and synchronization of the contrast agent with magnetic resonance data acquisition for peripheral CE MRA play a major role in acquiring high-signal arterial angiograms while simultaneously avoiding venous signal overlay.

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Materials and methods

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Technique

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Figure 1, Diagram illustrating data acquisition and k-space segmentation scheme for three-station peripheral run-off three-dimensional magnetic resonance angiography. During the first pass of the blood-pool contrast agent (line a ), only the central parts of k-space (15%) are acquired for each of the three stations, and the table is subsequently stepped to the next station toward the feet. Data acquisition times are given to 20, 20, and 23 seconds, respectively. Subsequent to data acquisition in this first pass of the contrast agent, data set I can be reconstructed, providing the low-resolution data set. During the steady state of the contrast agent (line b ), only the outer parts of k-space (85%) are acquired, starting at the calves (station 3) and subsequently moving toward the abdomen (station 1). Data acquisition times are 1 minute 44 seconds (calves), 1 minute 29 seconds (thighs), and 1 minute 33 seconds (abdomen). Following completion of steady-state data acquisition (line b ), the inner segments of k-space (15%) of line a are fused with the outer k-space segments of line b to reconstruct high-resolution data set II. Line c shows nonsegmented data acquisition of stations 1, 2, and 3 performed during the steady state of the blood-pool contrast agent for reconstruction of data set III. Data set III serves as a standard of reference for the evaluation of venous signal enhancement in the nonsegmented, conventional data acquisition scheme.

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Table 1

Imaging Parameters

Sequence Acquisition Time (seconds) Field of View, Head to Feet × Left to Right (mm 2 ) Acquired Voxel Size (mm 3 ) First pass Abdomen 20 500 × 344 0.8 × 2.0 × 2.0 Thighs 20 500 × 344 0.8 × 2.0 × 2.0 Calves 23 500 × 344 0.7 × 1.8 × 1.8 Fused data set Abdomen 93 500 × 344 0.8 × 0.8 × 0.8 Thighs 89 500 × 344 0.8 × 0.8 × 0.8 Calves 104 500 × 344 0.7 × 0.7 × 0.7 Steady state Abdomen 78 500 × 344 0.8 × 0.8 × 0.8 Thighs 78 500 × 344 0.8 × 0.8 × 0.8 Calves 107 500 × 344 0.7 × 0.7 × 0.7

Sequence parameters for all three stations and their first-pass and steady-state acquisitions. Sequence parameters that were identical for all acquisitions were flip angle (25°), bandwidth (490 Hz/pixel), repetition time (3.4 ms), echo time (1.3 ms), number of slices per slab (160), and generalized auto-calibrating partially parallel acquisition acceleration factor .

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Patients

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Image Evaluation

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Figure 2, Quantitative determination of vessel signal profile sharpness. This example schematically shows the determination of vessel sharpness on the popliteal artery (a) . A rectangular region of interest is drawn perpendicular to the course of the vessel segment under investigation (b) . This region of interest contains multiple signal profiles across the vessel. (c) Averaged vessel signal profiles out of the previously defined region of interest. The curve in the middle gives mean signal values; the curves above and below give the standard deviations. The edge detection program routine defines a baseline and two thresholds at 90% of signal maximum and 10% of signal maximum, respectively. The incline from background end (BE) to vessel start (VS) and from vessel end (VE) to background start (BS) gives a quantitative measure for the vessel sharpness and is averaged to one single mean. The higher the value, the sharper the vessel display.

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Statistical Analysis

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Results

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Figure 3, Magnetic resonance angiograms of data set I, the central k-space (a) ; data set II, the fused k-space (b) ; and data set III, the steady-state acquisition (c) . Looking at data set III, one can see how disturbing the venous overlay for image evaluation can be and how well the implemented k-space segmentation technique works (data set II).

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Image Quality

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Table 2

Results for Image Quality

Sequence Data Set I (First Pass) Data Set II (Fused Data Set)P Abdomen 2.5 2.9 <.01 Thighs 2.4 3.0 <.01 Calves 2.3 2.9 <.01

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Venous Overlay and Evaluation of Trace of Vessels and Minimal Vessel Size

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Figure 4, Comparison of the lower leg for data sets I (a) and II (b) . Images confirm the statistically significant higher sharpness of data set I (a) . Furthermore, vessels can be assessed in more detail and over longer ranges.

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Sharpness of Edges

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Discussion

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Conclusions

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