Roel Hermans

Quantification of arterial flow using digital subtraction angiography.

PURPOSE In this paper, a method for the estimation of arterial hemodynamic flow from x-ray video densitometry data is proposed and validated using an in vitro setup. METHODS The method is based on the acquisition of three-dimensional rotational angiography and digital subtraction angiography sequences. A modest contrast injection rate (between 1 and 4 ml/s) leads to a contrast density that is modulated by the cardiac cycle, which can be measured in the x-ray signal. An optical flow based approach is used to estimate the blood flow velocities from the cyclic phases in the x-ray signal. RESULTS The authors have validated this method in vitro, and present three clinical cases. The in vitro experiments compared the x-ray video densitometry results with the gold standard delivered by a flow meter. Linear correlation analysis and regression fitting showed that the ideal slope of 1 and intercept of 0 were contained within the 95 percentile confidence interval. The results show that a frame rate higher than 50 Hz allows measuring flows in the range of 2 ml/s to 6 ml/s within an accuracy of 5%. CONCLUSIONS The in vitro and clinical results indicate that it is feasible to estimate blood flow in routine interventional procedures. The availability of an x-ray based method for quantitative flow estimation is particularly clinically useful for intra-cranial applications, where other methods, such as ultrasound Doppler, are not available.

Model-based blood flow quantification from rotational angiography

For assessment of cerebrovascular diseases, it is beneficial to obtain three-dimensional (3D) information on vessel morphology and haemodynamics. Rotational angiography is routinely used to determine the 3D geometry. In this paper, we propose a method to exploit the same acquisition to determine the blood flow waveform and the mean volumetric flow rate in the large cerebral arteries. The method uses a model of contrast agent dispersion to determine the flow parameters from the spatial and temporal progression of the contrast agent concentration, represented by a flow map. Furthermore, it overcomes artefacts due to the rotation (overlapping vessels and foreshortened vessels at some projection angles) of the C-arm using a reliability map. The method was validated on images from different phantom experiments. We analysed different properties of the flow quantification method, including the influence of noise and the influence of the length of the analysed blood vessel. In most cases, the relative error was between 5% and 10% for the volumetric mean flow rate and between 10% and 15% for the blood flow waveform. The manual interaction took at most one minute and the computational time for the flow quantification was between 4 and 20 min on a PC. From this, we conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions.

Phantom-based experimental validation of computational fluid dynamics simulations on cerebral aneurysms.

PURPOSE Recently, image-based computational fluid dynamics (CFD) simulation has been applied to investigate the hemodynamics inside human cerebral aneurysms. The knowledge of the computed three-dimensional flow fields is used for clinical risk assessment and treatment decision making. However, the reliability of the application specific CFD results has not been thoroughly validated yet. METHODS In this work, by exploiting a phantom aneurysm model, the authors therefore aim to prove the reliability of the CFD results obtained from simulations with sufficiently accurate input boundary conditions. To confirm the correlation between the CFD results and the reality, virtual angiograms are generated by the simulation pipeline and are quantitatively compared to the experimentally acquired angiograms. In addition, a parametric study has been carried out to systematically investigate the influence of the input parameters associated with the current measuring techniques on the flow patterns. RESULTS Qualitative and quantitative evaluations demonstrate good agreement between the simulated and the real flow dynamics. Discrepancies of less than 15% are found for the relative root mean square errors of time intensity curve comparisons from each selected characteristic position. The investigated input parameters show different influences on the simulation results, indicating the desired accuracy in the measurements. CONCLUSIONS This study provides a comprehensive validation method of CFD simulation for reproducing the real flow field in the cerebral aneurysm phantom under well controlled conditions. The reliability of the CFD is well confirmed. Through the parametric study, it is possible to assess the degree of validity of the associated CFD model based on the parameter values and their estimated accuracy range.

Experimental validation and sensitivity analysis for CFD simulations of cerebral aneurysms

In this work, by exploiting a phantom aneurysm model, we illustrate the correlation between experimental data and computational fluid dynamics (CFD) simulation results under well controlled conditions. This is difficult to achieve with clinical patient cases where several uncertainties are present. Quantitative measures are defined for CFD validation by virtual angiography. In addition, a parametric study has been carried out to systematically investigate the sensitivity of current measuring technique on the flow pattern.

Evaluation of model-based blood flow quantification from rotational angiography

For assessment of cerebrovascular diseases, it is beneficial to obtain three-dimensional (3D) information on vessel morphology and hemodynamics. Rotational angiography is routinely used to determine 3D geometry, and we recently outlined a method to estimate the blood flow waveform and mean volumetric flow rate from images acquired using rotational angiography. Our method uses a model of contrast agent dispersion to estimate the flow parameters from the spatial and temporal progression of the contrast agent concentration, represented by a flow map. Artifacts due to the rotation of the c-arm are overcome by using a reliability map. An attenuation calibration can be used to support our method, but it might not be available in clinical practice. In this paper, we analyze the influence of the attenuation calibration on our method. Furthermore, we concentrate on the validation of the proposed algorithm, with particular emphasis on the influence of parameters such as the length of the analyzed vessel segment, the frame rate of the acquisition, and the duration of the injection on accuracy. For the validation, rotational angiographic image sequences from a computer simulation and from a phantom experiment were used. With a mean error of about 10% for the mean volumetric flow rate and about 13% for the blood flow waveform from the phantom experiments, we conclude that the method has the potential to give quantitative estimates of blood flow parameters during cerebrovascular interventions which are accurate enough to be clinically useful.

Mean Aneurysm Flow Amplitude Ratio Comparison between DSA and CFD

The Mean Aneurysm Flow Amplitude ratio (MAFA-ratio) has been proposed to evaluate the efficacy of flow diverting stents during minimally invasive intracranial aneurysm treatment. A method has been described for calculating the MAFA-ratio on high frame-rate digital subtraction angiography (DSA) acquisitions using an optical flow algorithm. In this article we have generated computational fluid dynamics (CFD) simulations using six distinct aneurysms and computed the MAFA-ratios based on these data. Furthermore, the simulations have been used to create virtual angiograms, in order to calculate the MAFA-ratios using the DSA approach. An analysis of the MAFAratios generated by both methods shows that there is a monotone increasing relation between the DSA and CFD based ratios, albeit without a slope being identity. Overall, it can be concluded that the DSA-based ratio is a predictor for the magnitude of aneurysm flow reduction, i.e., for the efficacy of flow diverting stents.

Quantifying blood flowdivision at bifurcations from rotational angiography

For assessment of cerebrovascular diseases, it is beneficial to obtain information about the hemodynamics of the vessel system. Recently, we presented a method to quantify blood flow in a single blood vessel segment from rotational angiography. In this paper, we extend the method to bifurcations. A model- based method is proposed which estimates the mean flow, the waveform and the flow division at the bifurcation. The method is validated on experimental data using a phantom for a healthy and a stenosed carotid bifurcation. The average error for the estimate of the flow division was 8%.