High-Speed-Angiography (HSA) 1000 fps imaging was successfully used previously to visualize contrast media/blood flow in neurovascular anatomies. In this work we explore its usage in cardiovascular anatomies in a swine animal model. A 5 French catheter was guided into the right coronary artery of a swine, followed by the injection of iodine contrast through a computer-controlled injector at a controlled rate of 40 (ml/min). The injection process was captured using high-speed angiography at a rate of 1000 fps. The noise in the images was reduced using a custom-built machine-learning model consisting of long short-term memory networks. From the noise reduced images, velocity profiles of contrast/blood flow through the artery was calculated using Horn-Schunck optical flow (OF) method. From the high-speed coronary angiography (HSCA) images, the bolus of contrast could be visually tracked with ease as it traversed from the catheter tip through the artery. The imaging technique's high temporal resolution effectively minimized motion artifacts resulting from the heart's activity. The OF results of the contrast injection show velocities in the artery ranging from 20 – 40 cm/s. The results demonstrate the potential of 1000 fps HSCA in cardiovascular imaging. The combined high spatial and temporal resolution offered by this technique allows for the derivation of velocity profiles throughout the artery's structure, including regions distal and proximal to stenoses. This information can potentially be used to determine the need for stenoses treatment. Further investigations are warranted to expand our understanding of the applications of HSCA in cardiovascular research and clinical practice.
Understanding detailed hemodynamics is critical in the treatment of aneurysms and other vascular diseases; however, traditional Digital Subtraction Angiography (DSA) does not provide detailed quantitative flow information. Instead, 1000 fps High-Speed Angiography (HSA) can be used for high-temporal visualization and evaluation of detailed blood flow patterns and velocity distributions. In the treatment of aneurysms, flow diverter expansion and positioning play a critical role in affecting the hemodynamics and optimal patient outcomes. Patient-specific aneurysm phantom imaging was done with a CdTe photon-counting detector (Aries, Varex). Treatment was done with a Pipeline Flex Embolization Device on a 3D-printed fusiform aneurysm phantom. The untreated aneurysm and two treatment stent expansions and positions were imaged, and velocity calculations were generated using Optical Flow (OF). Pre- and post-treatment images were then compared between different HSA image sequences and evaluated using OF with different stent positions. Differences in flow patterns due to changes in stent placement characteristics were identified and quantified with OF velocimetry. The velocity results within the aneurysm post-treatment showed significant flow reduction. Differences in stent placement result in substantial changes in velocities. The peak velocities found in the aneurysm dome show a reduction with the widened stent placement compared to the narrowed placement and both are reduced compared to the untreated aneurysm. The stent placements were compared quantitatively with the adjusted widened stent clearly better diverting the flow away from the aneurysm with decreased velocity in the aneurysm dome compared to both the narrowed stent placement and the untreated aneurysm. Providing this information in-clinic can help improve treatment and patient outcomes.
Cerebral aneurysm (CA) rupture is one of the major causes of hemorrhagic stroke. During endovascular therapy (ET), neurointerventionalists rely on qualitative image sequences and do not have access to crucial quantitative hemodynamic information. Quantifying angiographic image sequences can provide vital information, but it is not possible to perform this in a controlled manner in vivo. Computational fluid dynamics (CFD) is a valuable tool capable of providing high fidelity quantitative data by replicating the blood flow physics within the cerebrovasculature. In this work, we use simulated angiograms (SA) to quantify the hemodynamic interaction with a clinically utilized contrast agent. SA enables extraction of time density curves (TDC) within the desired region of interest to analyze hemodynamic parameters such as time to peak (TTP) and mean transit time (MTT) within the aneurysm. We present on the quantification of several hemodynamic parameters of interest for multiple, clinically-relevant scenarios such as variable contrast injection duration and bolus volumes for 7 patient-specific CA geometries. Results indicate that utilizing these analyses provides valuable hemodynamic information relating vascular and aneurysm morphology, contrast flow conditions and injection variability. The injected contrast circulates for multiple cardiac cycles within the aneurysmal region, especially for larger aneurysms and tortuous vasculature. The SA approach enables determination of angiographic parameters for each scenario. Together, these have the potential to overcome the existing barriers in quantifying angiographic procedures in vitro or in vivo, and can provide clinically valuable hemodynamic insights for CA treatment.
Quantitative angiography (QAngio) may provide hemodynamic information during neurointerventional procedures through imaging biomarkers related to contrast flow. The standard clinical implementation of QAngio is limited by projection imaging: analysis of contrast motion within complex 3D geometries is restricted to 1-2 projection views, truncating the potential wealth of imaging biomarkers related to disease progression or efficacy of treatment. To understand the limitations of 2D biomarkers, we propose the use of in-silico contrast distributions to investigate the potential benefits of 3D-QAngio within the context of neurovascular hemodynamics. Ground-truth in-silico contrast distributions were generated in two patient-specific intracranial aneurysm models, accounting for the physical interactions of contrast media and blood. A short bolus of contrast was utilized to obtain full a wash-in/ wash-out cycle within the aneurysm ROI. Simulated angiograms mimicking clinical cone-beam CT (CBCT) acquisitions were then generated, and volumetric contrast distributions were reconstructed to analyze bulk contrast flow. The ground-truth 3D-CFD, reconstructed 3D-CBCT-DSA, and 2D-DSA projections were used to extract QAngio parameters related to contrast time dilution curves, such as area under the curve (AUC), peak height (PH), mean-transit-time (MTT), time-to-peak (TTP), and time to arrival (TTA). An initial comparison of quantitative flow parameters in both 2D and 3D, in a smaller and larger aneurysm, indicated that 3D-QAngio can provide a good description of bulk flow characteristics (TTA, TTP, MTT), but recovery of integral parameters (PH, AUC) aneurysms is limited. Nonetheless, incorporation of 3D-QAngio methods may provide additional insight into our understanding of abnormal vascular flow patterns.
Pathological changes in blood flow lead to altered hemodynamic forces, which are responsible for a number of conditions related to the remodeling and regeneration of the vasculature. More specifically, wall shear stress (WSS) has been shown to be a significant hemodynamic parameter with respect to aneurysm growth and rupture, as well as plaque activation leading to increased risk of stroke. In-vivo measurement of shear stress is difficult due to the stringent requirements on spatial resolution near the wall boundaries, as well as the deviation from the commonly assumed parabolic flow behavior at the wall. In this work, we propose an experimental method of in-vitro WSS calculations from high-temporal resolution velocity distributions, which are derived from 1000 fps high-speed angiography (HSA). The high-spatial and temporal resolution of our HSA detector makes such high-resolution velocity gradient measurements feasible. Presented here is the methodology for calculation of WSS in the imaging plane, as well as initial results for a variety of vascular geometries at physiologically realistic flow rates. Further, the effect of spatial resolution on the gradient calculation is explored using CFD-derived velocity data. Such angiographic-based analysis with HSA has the potential to provide critical hemodynamic feedback in an interventional setting, with the overarching objective of supporting clinical decision-making and improving patient outcomes.
Cerebral aneurysms (CA) affect nearly 6% of the US population and its rupture is one of the major causes of hemorrhagic stroke. Neurointerventionalists performing endovascular therapy (ET) to treat CA rely on qualitative image sequences obtained under fluoroscopy guidance alone, and do not have access to crucial quantitative information regarding blood flow before, during and after treatment – partially contributing to a failure rate of up to 30%. Computational fluid dynamics (CFD) is a powerful tool that can provide a wealth of quantitative data; however, CFD has found limited utility in the clinic due to the challenges in obtaining hemodynamic boundary conditions for each patient. In this work, we present a novel CFD-based simulated angiogram approach (SAA) that resolves the blood flow physics and interaction between blood and injected contrast agent to extract quantitative hemodynamic parameters which can be used to design real-time parametric imaging analysis. The SAA enables correlating contrast agent transport to the underlying hemodynamic conditions via time-density curves (TDC) obtained at several points in the region of interest. The ability of the TDC and the SAA to provide critical hemodynamic parameters in and around CA anatomies, such as washout and local flow changes is explored and presented. This provides invaluable quantitative data to the clinician at the time of intervention, since it incorporates the physics of blood flow and correlates the contrast transport to hemodynamic parameters quantitatively – thereby enabling the clinician to take informed decisions that improve treatment outcomes.
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