Blood flow quantification in dialysis access using digital subtraction angiography: A retrospective study

Angiography-based hemodynamic features predict recurrent ischemic events after angioplasty and stenting of intracranial vertebrobasilar atherosclerotic stenosis

OBJECTIVES

To assess the predictive value of hemodynamic features for stroke relapse in patients with intracranial vertebrobasilar atherosclerotic stenosis treated with percutaneous transluminal angioplasty and stenting (PTAS) using quantitative digital subtraction angiography (q-DSA).

METHODS

In this retrospective longitudinal study, patients with intracranial vertebrobasilar atherosclerotic stenosis and who underwent PTAS treatment between January 2012 and May 2020 were enrolled. The q-DSA assessment was performed before and after PTAS. ROIs 1-4 were placed along the vertebral artery, proximal and distal basilar artery, and posterior cerebral artery; ROIs 5-8 were in 5 mm and 10 mm proximal and distal to the lesion, respectively. Relative time to peak (rTTP) was defined as the difference in TTP between ROIs. Cox regression analyses were performed to determine risk factors for recurrent stroke.

RESULTS

A total of 137 patients (mean age, 62 years ± 10 [standard deviation], 83.2% males) were included, and 26 (19.0%) patients had stroke relapse during follow-up (median time of 42.6 months [interquartile range, 19.7-60.7]). Preprocedural rTTP4-1 (adjusted hazard ratio (HR) = 2.270; 95% CI 1.371-3.758; p = 0.001) and preprocedural rTTP8-5 (adjusted HR = 0.240; 95% CI 0.088-0.658; p = 0.006) were independently associated with the recurrent stroke. These hemodynamic parameters provided an incremental prognostic value for stroke relapse (AUC, 0.817 [0.704-0.931]; the net reclassification index, 0.431 [0.057-0.625]; and the integrated discrimination index, 0.140 [0.035-0.292]).

CONCLUSIONS

In patients with intracranial vertebrobasilar atherosclerosis treated with PTAS, preprocedural prolonged TTP of the target vessel and shortened trans-stenotic TTP difference were associated with stroke relapse. Q-DSA-defined hemodynamic parameters provided incremental predictive value over conventional parameters for stroke recurrence.

CLINICAL RELEVANCE STATEMENT

Quantitative DSA analysis enables intuitive observation and semi-quantitative evaluation of peri-therapeutic cerebral blood flow. More importantly, quantitative DSA-defined hemodynamic parameters have the potential for risk stratification of patients with intracranial atherosclerotic stenosis.

KEY POINTS

Semi-quantitative angiography-based parameters can reflect pre- and postprocedural subtle changes in blood flow in patients with intracranial atherosclerotic stenosis. Although angioplasty procedures can significantly improve blood flow status, patients with more restricted baseline blood flow still show a higher risk of stroke recurrence. Angiography-based hemodynamic features possess prognostic value and can serve as clinical markers to assess stroke risk of patients with intracranial atherosclerotic stenosis.

Comparison of algorithms for estimating blood flow velocities in cerebral arteries based on the transport information of contrast agent: An in silico study

While many algorithms have been proposed to estimate blood flow velocities based on the transport information of contrast agent acquired by digital subtraction angiography (DSA), most relevant studies focused on a single vessel, leaving a question open as to whether the algorithms would be suitable for estimating blood flow velocities in arterial systems with complex topological structures. In this study, a one-dimensional (1-D) modeling method was developed to simulate the transport of contrast agent in cerebral arterial networks with various anatomical variations or having occlusive disease, thereby generating an in silico database for examining the accuracies of some typical algorithms (i.e., time-of-center of gravity (TCG), shifted least-squares (SLS), and cross correlation (CC) algorithms) that estimate blood flow velocity based on the concentration-time curves (CTCs) of contrast agent. The results showed that the TCG algorithm had the best performance in estimating blood flow velocities in most cerebral arteries, with the accuracy being only mildly affected by anatomical variations of the cerebral arterial network. Nevertheless, the presence of a stenosis of moderate to high severity in the internal carotid artery could considerably impair the accuracy of the TCG algorithm in estimating blood flow velocities in some cerebral arteries where the transport of contrast agent was disturbed by strong collateral flows. In summary, the study suggests that the TCG algorithm may offer a promising means for estimating blood flow velocities based on CTCs of contrast agent monitored in cerebral arteries, provided that the shapes of CTCs are not highly distorted by collateral flows.

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.

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.