4D-DSA: Development and Current Neurovascular Applications.

Originally described by Davis et al in 2013, 4D-Digital Subtraction Angiography (4D-DSA) has developed into a commercially available application of DSA in the angiography suite. 4D-DSA provides the user with 3D time-resolved images, allowing observation of a contrast bolus at any desired viewing angle through the vasculature and at any time point during the acquisition (any view at any time). 4D-DSA mitigates some limitations that are intrinsic to both 2D- and 3D-DSA images. The clinical applications for 4D-DSA include evaluations of AVMs and AVFs, intracranial aneurysms, and atherosclerotic occlusive disease. Recent advances in blood flow quantification using 4D-DSA indicate that these data provide both the velocity and geometric information necessary for the quantification of blood flow. In this review, we will discuss the development, acquisition, reconstruction, and current neurovascular applications of 4D-DSA volumes.

Optimizing the Quality of 4D-DSA Temporal Information.

BACKGROUND AND PURPOSE: Quantification of blood flow using a 4D-DSA would be useful in the diagnosis and treatment of cerebrovascular diseases. A protocol optimizing identification of density variations in the time-density curves of a 4D-DSA has not been defined. Our purpose was to determine the contrast injection protocol most likely to result in the optimal pulsatility signal strength. MATERIALS AND METHODS: Two 3D-printed patient-specific models were used and connected to a pulsatile pump and flow system, which delivered 250-260 mL/min to the model. Contrast medium (Isovue, 370 mg I/mL, 75% dilution) was injected through a 6F catheter positioned upstream from the inlet of the model. 4D-DSA acquisitions were performed for the following injection rates: 1.5, 2.0, 2.5, 3.0 and 3.5 mL/s for 8 seconds. To determine pulsatility, we analyzed the time-density curve at the inlets using the oscillation amplitude and a previously described numeric metric, the sideband ratio. Vascular geometry from 4D-DSA reconstructions was compared with ground truth and micro-CT measurements of the model. Dimensionless numbers that characterize hemodynamics, Reynolds and Craya-Curtet, were calculated for each injection rate. RESULTS: The strongest pulsatility signal occurred with the 2.5 mL/s injections. The largest oscillation amplitudes were found with 2.0- and 2.5-mL/s injections. Geometric accuracy was best preserved with injection rates of >1.5 mL/s. CONCLUSIONS: An injection rate of 2.5 mL/s provided the strongest pulsatility signal in the 4D-DSA time-density curve. Geometric accuracy was best preserved with injection rates above 1.5 mL/s. These results may be useful in future in vivo studies of blood flow quantification.

Quantification of Blood Velocity with 4D Digital Subtraction Angiography Using the Shifted Least-Squares Method.

BACKGROUND AND PURPOSE: 4D-DSA provides time-resolved 3D-DSA volumes with high temporal and spatial resolutions. The purpose of this study is to investigate a shifted least squares method to estimate the blood velocity from the 4D DSA images. Quantitative validation was performed using a flow phantom with an ultrasonic flow probe as ground truth. Quantification of blood velocity in human internal carotid arteries was compared with measurements generated from 3D phase-contrast MR imaging. MATERIALS AND METHODS: The centerlines of selected vascular segments and the time concentration curves of each voxel along the centerlines were determined from the 4D-DSA dataset. The temporal shift required to achieve a minimum difference between any point and other points along the centerline of a segment was calculated. The temporal shift as a function of centerline point position was fit to a straight line to generate the velocity. The proposed shifted least-squares method was first validated using a flow phantom study. Blood velocities were also estimated in the 14 ICAs of human subjects who had both 4D-DSA and phase-contrast MR imaging studies. Linear regression and correlation analysis were performed on both the phantom study and clinical study, respectively. RESULTS: Mean velocities of the flow phantom calculated from 4D-DSA matched very well with ultrasonic flow probe measurements with 11% relative root mean square error. Mean blood velocities of ICAs calculated from 4D-DSA correlated well with phase-contrast MR imaging measurements with Pearson correlation coefficient r = 0.835. CONCLUSIONS: The availability of 4D-DSA provides the opportunity to use the shifted least-squares method to estimate velocity in vessels within a 3D volume.

Comparison of vessel contrast measured with a scanning-beam digital x-ray system and an image intensifier/television system.

Vessel contrast was measured in the fluoroscopic images produced by a scanning-beam digital x-ray (SBDX) system and an image intensifier/television (II/TV) based system. The SBDX system electronically scans a series of pencil x-ray beams across the patient, each of which is directed at a distant small-area detector array. The reduction in detected scatter achieved with this geometry was expected to provide an increase in image contrast. Vessel contrast was evaluated from images of a phantom containing iodinated tubes. The vessels were inserted into an acrylic stack to provide a patient-mimicking scattering medium. Vessel diameter ranged from 0.3 to 3.1 mm. Images were acquired at 100 kVp with the SBDX and II/TV systems and averaged to reduce x-ray noise. The II/TV system was operated in the 6-in. image intensifier mode with an anti-scatter grid. The increase in contrast in the SBDX images, expressed as a ratio of the measured SBDX and II/TV contrasts, ranged from 1.63 to 1.79 for individual vessels. This agreed well with a prediction of the contrast improvement ratio for this experiment, based on measurements of the scatter fraction, object-plane line spread functions, and consideration of the source spectrum and detector absorption properties. The predicted contrast improvement ratio for SBDX relative to II/TV images was 1.62 to 1.77.