Model-based blood flow quantification from rotational angiography

Interleaved x-ray imaging: A method for simultaneous acquisition of quantitative and diagnostic digital subtraction angiography

BACKGROUND

Flow altering angiographic procedures suffer from ill-defined, qualitative endpoints. Quantitative digital subtraction angiography (qDSA) is an emerging technology that aims to address this issue by providing intra-procedural blood velocity measurements from time-resolved, 2D angiograms. To date, qDSA has used 30 frame/s DSA imaging, which is associated with high radiation dose rate compared to clinical diagnostic DSA (up to 4 frame/s).

PURPOSE

The purpose of this study is to demonstrate an interleaved x-ray imaging method which decreases the radiation dose rate associated with high frame rate qDSA while simultaneously providing low frame rate diagnostic DSA images, enabling the acquisition of both datasets in a single image sequence with a single injection of contrast agent.

METHODS

Interleaved x-ray imaging combines low radiation dose image frames acquired at a high rate with high radiation dose image frames acquired at a low rate. The feasibility of this approach was evaluated on an x-ray system equipped with research prototype software for x-ray tube control. qDSA blood velocity quantification was evaluated in a flow phantom study for two lower dose interleaving protocols (LD1:3.7 ± 0.02 mGy / s $3.7 \pm 0.02\ {\mathrm{mGy}}/{\mathrm{s}}$ and LD2:1.7 ± 0.04 mGy / s $1.7 \pm 0.04{\mathrm{\ mGy}}/{\mathrm{s}}$ ) and one conventional (full dose) protocol (11.4 ± 0.04 mGy / s ) $11.4 \pm 0.04{\mathrm{\ mGy}}/{\mathrm{s}})$ . Dose was measured at the interventional reference point. Fluid velocities ranging from 24 to 45 cm/s were investigated. Gold standard velocities were measured using an ultrasound flow probe. Linear regression and Bland-Altman analysis were used to compare ultrasound and qDSA.

RESULTS

The LD1 and LD2 interleaved protocols resulted in dose rate reductions of -67.7% and -85.5%, compared to the full dose qDSA scan. For the full dose protocol, the Bland-Altman limits of agreement (LOA) between qDSA and ultrasound velocities were [0.7, 6.7] cm/s with a mean difference of 3.7 cm/s. The LD1 interleaved protocol results were similar (LOA: [0.3, 6.9] cm/s, bias: 3.6 cm/s). The LD2 interleaved protocol resulted in slightly larger LOA: [-2.5, 5.5] cm/s with a decrease in the bias: 1.5 cm/s. Linear regression analysis showed a strong correlation between ultrasound and qDSA derived velocities using the LD1 protocol, with aR 2 ${R}^2$ of0.96 $0.96$ , a slope of1.05 $1.05$ and an offset of1.9 $1.9$  cm/s. Similar values were also found for the LD2 protocol, with aR 2 ${R}^2$ of0.93 $0.93$ , a slope of0.98 $0.98$ and an offset of2.0 $2.0$  cm/s.

CONCLUSIONS

The interleaved method enables simultaneous acquisition of low-dose high-rate images for intra-procedural blood velocity quantification (qDSA) and high-dose low-rate images for vessel morphology evaluation (diagnostic DSA).

Motion-compensation approach for quantitative digital subtraction angiography and its effect on in-vivo blood velocity measurement

Purpose

Quantitative monitoring of flow-altering interventions has been proposed using algorithms that quantify blood velocity from time-resolved two-dimensional angiograms. These algorithms track the movement of contrast oscillations along a vessel centerline. Vessel motion may occur relative to a statically defined vessel centerline, corrupting the blood velocity measurement. We provide a method for motion-compensated blood velocity quantification.

Approach

The motion-compensation approach utilizes a vessel segmentation algorithm to perform frame-by-frame vessel registration and creates a dynamic vessel centerline that moves with the vasculature. Performance was evaluated in-vivo through comparison with manually annotated centerlines. The method was also compared to a previous uncompensated method using best- and worst-case static centerlines chosen to minimize and maximize centerline placement accuracy. Blood velocities determined through quantitative DSA (qDSA) analysis for each centerline type were compared through linear regression analysis.

Results

Centerline distance errors were 0.3 ± 0.1    mm relative to gold standard manual annotations. For the uncompensated approach, the best- and worst-case static centerlines had distance errors of 1.1 ± 0.6 and 2.9 ± 1.2    mm , respectively. Linear regression analysis found a high R -squared between qDSA-derived blood velocities using gold standard centerlines and motion-compensated centerlines (R 2 = 0.97 ) with a slope of 1.15 and a small offset of - 0.6    cm / s . The use of static centerlines resulted in low coefficients of determination for the best case (R 2 = 0.35 ) and worst-case (R 2 = 0.20 ) scenarios, with slopes close to zero.

Conclusions

In-vivo validation of motion-compensated qDSA analysis demonstrated improved velocity quantification accuracy in vessels with motion, addressing an important clinical limitation of the current qDSA algorithm.

Application of Digital Subtraction Angiography in Predicting the Outcomes of Intraoperative Hemorrhage of Juvenile Nasopharyngeal Angiofibroma

OBJECTIVE

Juvenile nasopharyngeal angiofibroma (JNA) is a very rare hemorrhagic vascular tumor that predominantly affects adolescent boys. The tumor is relatively large when detected, and the risk of intraoperative bleeding is high. We aimed to examine factors associated with intraoperative blood loss in JNA surgery.

METHODS

Thirteen patients with JNA who underwent surgery at the Jikei University Hospital between 2009 and 2020 were retrospectively reviewed, and factors associated with blood loss were examined by single regression analysis.

RESULTS

The mean age was 20.8 ± 7.7 years. Preoperative angiographic images were evaluated in 9 of the 13 cases. The 6 patients with the largest bleeding volumes, all had residual nutrient vessels from the internal carotid artery (ICA), with an average number of 2.5 vessels. The mean blood loss of patients with residual nutrient vessels from the ICA was 3037 ± 2568 mL. Single regression analysis of bleeding volume against the number of remaining nutrient vessels from the ICA and the total peak contrast density of nutrient vessels (Cmax) standardized by region of interest showed that the coefficient was positive (P < 0.05 for both), confirming a significant correlation between the 2, respectively.

CONCLUSIONS

The amount of bleeding significantly correlated with the number of remaining nutrient vessels from the ICA after preoperative embolization and with the total Cmax/region of interest. The ability to predict the amount of preoperative blood loss using this study will facilitate proposals for external incisions in patients with JNA.

Dispersion of Heterogeneous Medium in Pulsatile Blood Flow and Absolute Pulsatile Flow Velocity Quantification

Heterogeneous medium enhanced angiogr- ams are key diagnostic tools in clinical practice; the associated hemodynamic information is crucial for diagnosing cardiovascular diseases. However, the dynamics of such medium in physiological blood flow are poorly understood. Herein, we report a previously unnoticed dispersion pattern, which is a universal phenomenon, of a medium in pulsatile blood flow. We present a physical theory for studying the dispersion of a steadily injected heterogeneous medium into a thin tubular blood vessel in which the blood flow is pulsatile. In a thin tubular blood vessel, we demonstrate that variations of concentration associated with the heterogeneous medium obey a one-dimensional advection diffusion equation, and the diffusion has limited effect whenever a short vascular segment is considered. A distinct feature of the distribution of the medium in the axial distance-time plane is a "dilation-retraction" pattern. The time evolution signals at different axial positions exhibit distinct concentration waveforms. A numerical scheme is proposed for exploiting this information to estimate the pulsatile velocity. Artificial data are adopted to validate the scheme. Real X-ray angiography is also analyzed to support our theory and method. The theory is applicable whenever imaging protocols involve a heterogeneous medium in pulsatile flow.

Estimating Pulsatile Blood Flow Parameters from Digital Subtraction Angiography

Digital subtraction angiography (DSA) is the gold standard for diagnosing vascular diseases. Much attention had been attracted on estimating blood flow velocity from DSA data, and many techniques to compute the mean flow velocity had been proposed. In this paper, we present a physical model that demonstrates how the pulsatile flow can affect the dispersion of the contrast medium delivered into the blood vessel. Using empirical mode decomposition and angiographic data of 4 patients, we then showed it is feasible to compute pulsatile flow related parameters from routine interventional angiographic acquisitions.Clinical Relevance- This is the first attempt to present a physical model and corresponding method to estimate pulsatile flow related parameters from routine angiographic acquisitions, and has potential to be used for real-time diagnostic and therapeutic monitoring during interventional procedures.

Mathematical Models for Blood Flow Quantification in Dialysis Access Using Angiography: A Comparative Study

Blood flow rate in dialysis (vascular) access is the key parameter to examine patency and to evaluate the outcomes of various endovascular interve7ntions. While angiography is extensively used for dialysis access–salvage procedures, to date, there is no image-based blood flow measurement application commercially available in the angiography suite. We aim to calculate the blood flow rate in the dialysis access based on cine-angiographic and fluoroscopic image sequences. In this study, we discuss image-based methods to quantify access blood flow in a flow phantom model. Digital subtraction angiography (DSA) and fluoroscopy were used to acquire images at various sampling rates (DSA—3 and 6 frames/s, fluoroscopy—4 and 10 pulses/s). Flow rates were computed based on two bolus tracking algorithms, peak-to-peak and cross-correlation, and modeled with three curve-fitting functions, gamma variate, lagged normal, and polynomial, to correct errors with transit time measurement. Dye propagation distance and the cross-sectional area were calculated by analyzing the contrast enhancement in the vessel. The calculated flow rates were correlated versus an in-line flow sensor measurement. The cross-correlation algorithm with gamma-variate curve fitting had the best accuracy and least variability in both imaging modes. The absolute percent error (mean ± SEM) of flow quantification in the DSA mode at 6 frames/s was 21.4 ± 1.9%, and in the fluoroscopic mode at 10 pulses/s was 37.4 ± 3.6%. The radiation dose varied linearly with the sampling rate in both imaging modes and was substantially low to invoke any tissue reactions or stochastic effects. The cross-correlation algorithm and gamma-variate curve fitting for DSA acquisition at 6 frames/s had the best correlation with the flow sensor measurements. These findings will be helpful to develop a software-based vascular access flow measurement tool for the angiography suite and to optimize the imaging protocol amenable for computational flow applications.

Estimating blood flow velocity using time-resolved 3D angiography and a derived physical law of contrast media

OBJECTIVE

Four-dimensional (4D) digital subtraction angiography (DSA) offers a method for evaluating hemodynamics. It is, however, unclear how the delivered contrast medium interacts with the physiological blood flow, and how hemodynamic information may be inferred from the mixture of the contrast medium and blood. In this study, we present a theoretical explanation of contrast dynamics, and an accompanying algorithm for estimating blood flow velocity.

APPROACH

We retrospectively recruited 23 patients who underwent both 4D DSA and magnetic resonance (MR) phase-contrast imaging. The 4D DSA-reconstructed contrast dynamics were first studied for the internal carotid arteries. Using physical laws governing fluid motion within a curved tube, we showed that the reconstructed contrast dynamics obeyed a simple advection equation. We then proposed an algorithm for estimating the contrast dynamics using angiographic data, and subsequently estimated the axial blood flow velocity using an advection equation.

MAIN RESULTS

The estimated velocities were compared using three techniques: the Fourier technique, Lin's method, and MR phase contrast. Testing with noise-corrupted artificial data showed that the proposed algorithm was noise resistant. The velocities of 23 patients computed by 4D DSA using the proposed algorithm showed a moderate correlation with the MR phase contrast (r = 0.61), and good correlations with the other two techniques (r = 0.75 and r = 0.72).

SIGNIFICANCE

The proposed algorithm and has been applied to blood vessel segments with poor signal-to-noise ratios and axial lengths of less than 3 cm, and has a physical basis for computing axial flow velocities using an advection equation. The results of the proposed algorithm are consistent with existing methods.

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.

Geometrical force constraint method for vessel and x-ray angiogram simulation

This study proposes a novel geometrical force constraint method for 3-D vasculature modeling and angiographic image simulation. For this method, space filling force, gravitational force, and topological preserving force are proposed and combined for the optimization of the topology of the vascular structure. The surface covering force and surface adhesion force are constructed to drive the growth of the vasculature on any surface. According to the combination effects of the topological and surface adhering forces, a realistic vasculature can be effectively simulated on any surface. The image projection of the generated 3-D vascular structures is simulated according to the perspective projection and energy attenuation principles of X-rays. Finally, the simulated projection vasculature is fused with a predefined angiographic mask image to generate a realistic angiogram. The proposed method is evaluated on a CT image and three generally utilized surfaces. The results fully demonstrate the effectiveness and robustness of the proposed method.

Changes of time-attenuation curve blood flow parameters in patients with and without carotid stenosis

BACKGROUND AND PURPOSE

From the time-attenuation curves of DSA flow parameters, maximal intensity, maximal slope, and full width at half maximum of selected vascular points are defined. The study explores the reliability of defining the flow parameters by the time-attenuation curves of DSA.

MATERIALS AND METHODS

Seventy patients with unilateral carotid artery stenosis (group A) and 56 healthy controls (group B) were retrospectively enrolled. Fixed contrast injection protocols and DSA acquisition parameters were used with all patients. The M1, sigmoid sinus, and internal jugular vein on anteroposterior view DSA and the M2, parietal vein, and superior sagittal sinus on lateral view DSA were chosen as ROI targets for measuring flow parameters. The difference of time of maximal intensity between 2 target points was defined as the circulation time between the target points.

RESULTS

The maximal intensity difference of 2 selected points from the ICA to the M1, sigmoid sinus, internal jugular vein, M2, parietal vein, and superior sagittal sinus was significantly longer in group A than in group B. The maximum slope of M1, M2, and the superior sagittal sinus was significantly lower in group A than in group B. The full width at half maximum of M1 and M2 was significantly larger in group A than in group B. The maximal slope of M1 demonstrated the best diagnostic performance.

CONCLUSIONS

The maximal intensity difference of 2 selected points derived from DSA can be used as a definitive alternative flow parameter for intracranial circulation time measurement. Maximal slope and full width at half maximum complement the maximal intensity difference of 2 selected points in defining flow characteristics of healthy subjects and patients with carotid stenosis.

3D velocity field and flow profile reconstruction from arbitrarily sampled Doppler ultrasound data

With the need for adequate analysis of blood flow dynamics, different maging modalities have been developed to measure varying blood velocities over time. Due to its numerous advantages, Doppler ultrasound sonography remains one of the most widely used techniques in clinical routine, but requires additional preprocessing to recover 3D velocity information. Despite great progress in the last years, recent approaches do not jointly consider spatial and temporal variation in blood flow. In this work, we present a novel gating- and compounding-free method to simultaneously reconstruct a 3D velocity field and a temporal flow profile from arbitrarily sampled Doppler ultrasound measurements obtained from multiple directions. Based on a laminar flow assumption, a patch-wise B-spline formulation of blood velocity is coupled for the first time with a global waveform model acting as temporal regularization. We evaluated our method on three virtual phantom datasets, demonstrating robustness in terms of noise, angle between measurements and data sparsity, and applied it successfully to five real case datasets of carotid artery examination.

Quantification of internal carotid artery flow with digital subtraction angiography: validation of an optical flow approach with Doppler ultrasound

BACKGROUND AND PURPOSE

Digital subtraction angiography is the reference standard technique to evaluate intracranial vascular anatomy and used on the endovascular treatment of vascular diseases. A dedicated optical flow-based algorithm was applied to DSA to measure arterial flow. The first quantification results of internal carotid artery flow validated with Doppler sonography are reported.

MATERIALS AND METHODS

We included 22 consecutive patients who underwent endovascular procedures. To assess the sensitivity of the algorithm to contrast agent-blood mixing dynamics, we acquired high-frame DSA series (60 images/s) with different injection rates: 1.5 mL/s (n = 19), 2.0 mL/s (n = 18), and 3.0 mL/s (n = 13). 3D rotational angiography was used to extract the centerline of the vessel and the arterial section necessary for volume flow calculation. Optical flow was used to measure flow velocities in straight parts of the ICAs; these data were further compared with Doppler sonography data. DSA mean flow rates were linearly regressed on Doppler sonography measurements, and regression slope coefficient bias from value 1 was analyzed within the 95% confidence interval.

RESULTS

DSA mean flow rates measured with the optical flow approach significantly matched Doppler sonography measurements (slope regression coefficient, b = 0.83 ± 0.19, P = .05) for injection rate = 2.0 mL/s and circulating volumetric blood flow <6 mL/s. For injection rate = 1.5 mL/s, volumetric blood flow <3 mL/s correlated well with Doppler sonography (b = 0.67 ± 0.33, P = .05). Injection rate = 3.0 mL/s failed to provide DSA-optical flow measurements correlating with Doppler sonography because of the lack of measurable pulsatility.

CONCLUSIONS

A new model-free optical flow technique was tested reliably on the ICA. DSA-based blood flow velocity measurements were essentially validated with Doppler sonography whenever the conditions of measurable pulsatility were achieved (injection rates = 1.5 and 2.0 mL/s).

The influence of contrast agent injection on physiological flow in the circle of Willis

X-ray videodensitometry allows in vivo flow measurements from gradients in contrast agent concentration. However, the injection of contrast agent alters the flow to be measured. Here, the temporal, spatial, and inter-patient variability of the response to injection are examined. To this purpose, an injection is prescribed in the internal carotid in a 1D wave propagation model of the arterial circulation. Although the resulting effect of injection is constant over a cardiac cycle, the response does vary with the location within the cerebral circulation and the geometry of the circle of Willis. At the injection site, the injection partly suppresses the incoming blood flow, such that the distal flow is increased by approximately 10%. This corresponds to approximately 20% of the injection rate added to the blood flow during injection, depending on the vascular geometry. In the communicating arteries, the flow direction is reversed during injection. Since the measured flow is not equal to the physiological blood flow, the effect of injection should be taken into account when deriving the flow from travelling contrast agent.

Spatio-temporal data fusion for 3D+T image reconstruction in cerebral angiography

This paper provides a framework for generating high resolution time sequences of 3D images that show the dynamics of cerebral blood flow. These sequences have the potential to allow image feedback during medical procedures that facilitate the detection and observation of pathological abnormalities such as stenoses, aneurysms, and blood clots. The 3D time series is constructed by fusing a single static 3D model with two time sequences of 2D projections of the same imaged region. The fusion process utilizes a variational approach that constrains the volumes to have both smoothly varying regions separated by edges and sparse regions of nonzero support. The variational problem is solved using a modified version of the Gauss-Seidel algorithm that exploits the spatio-temporal structure of the angiography problem. The 3D time series results are visualized using time series of isosurfaces, synthetic X-rays from arbitrary perspectives or poses, and 3D surfaces that show arrival times of the contrasted blood front using color coding. The derived visualizations provide physicians with a previously unavailable wealth of information that can lead to safer procedures, including quicker localization of flow altering abnormalities such as blood clots, and lower procedural X-ray exposure. Quantitative SNR and other performance analysis of the algorithm on computational phantom data are also presented.