Perfusion imaging is the most applied modality for the assessment of acute stroke. Parameters such as Cerebral Blood Flow (CBF), Cerebral Blood volume (CBV) and Mean Transit Time (MTT) are used to distinguish the tissue infarct core and ischemic penumbra. Due to lack of standardization these parameters vary significantly between vendors and software even when provided with the same data set. There is a critical need to standardize the systems and make them more reliable. We have designed a uniform phantom to test and verify the perfusion systems. We implemented a flow loop with different flow rates (250, 300, 350 ml/min) and injected the same amount of contrast. The images of the phantom were acquired using a Digital Angiographic system. Since this phantom is uniform, projection images obtained using DSA is sufficient for initial validation. To validate the phantom we measured the contrast concentration at three regions of interest (arterial input, venous output, perfused area) and derived time density curves (TDC). We then calculated the maximum slope, area under the TDCs and flow. The maximum slope calculations were linearly increasing with increase in flow rate, the area under the curve decreases with increase in flow rate. There was 25% error between the calculated flow and measured flow. The derived TDCs were clinically relevant and the calculated flow, maximum slope and areas under the curve were sensitive to the measured flow. We have created a systematic way to calibrate existing perfusion systems and assess their reliability.

Digital Subtraction Angiography (DSA) is the main diagnostic tool for intracranial aneurysms (IA) flow-diverter (FD) assisted treatment. Based on qualitative contrast flow evaluation, interventionists decide on subsequent steps. We developed a novel fully Retrievable Asymmetric Flow-Diverter (RAFD) which allows controlled deployment, repositioning and detachment achieve optimal flow diversion. The device has a small low porosity or solid region which is placed such that it would achieve maximum aneurysmal in-jet flow deflection with minimum impairment to adjacent vessels. We tested the new RAFD using a flow-loop with an idealized and a patient specific IA phantom in carotid-relevant physiological conditions. We positioned the deflection region at three locations: distally, center and proximally to the aneurysm orifice and analyzed aneurysm dome flow using DSA derived maps for mean transit time (MTT) and bolus arrival times (BAT). Comparison between treated and untreated (control) maps quantified the RAFD positioning effect. Average MTT, related to contrast presence in the aneurysm dome increased, indicating flow decoupling between the aneurysm and parent artery. Maximum effect was observed in the center and proximal position (~75%) of aneurysm models depending on their geometry. BAT maps, correlated well with inflow jet direction and magnitude. Reduction and jet dispersion as high as about 50% was observed for various treatments. We demonstrated the use of DSA data to guide the placement of the RAFD and showed that optimum flow diversion within the aneurysm dome is feasible. This could lead to more effective and a safer IA treatment using FDs.

Purpose: To design a precise perfusion phantom mimicking capillaries of the brain vasculature which could be used to test various perfusion protocols and algorithms which generate perfusion maps. Methods: A perfusion phantom was designed in Solidworks and built using additive manufacturing. The phantom was an overall cylindrical shape of diameter and height 20mm and containing capillaries of 200μm or 300μm which were parallel and in contact making up the inside volume where flow was allowed. We created a flow loop using a peristaltic pump and contrast agent was injected manually. Digital Subtraction Angiographic images and low contrast images with cone beam CT were acquired after the contrast was injected. These images were analyzed by our own code in LabVIEW software and Time‐Density Curve, MTT and TTP was calculated. Results: Perfused area was visible in the cone beam CT images; however, individual capillaries were not distinguishable. The Time‐Density Curve acquired was accurate, sensitive and repeatable. The parameters MTT, and TTP offered by the phantom were very sensitive to slight changes in the TDC shape. Conclusion: We have created a robust calibrating model for evaluation of existing perfusion data analysis systems. This approach is extremely sensitive to changes in the flow due to the high temporal resolution and could be used as a golden standard to assist developers in calibrating and testing of imaging perfusion systems and software algorithms. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation

Purpose: The development of patient specific models for endovascular procedures using additive manufacturing. Methods: The work to be presented is composed of two parts: manufacturing and testing of patientspecific phantoms. Phantom manufacturing began with acquisition of 3D patient data and segmentation for the generation of a printable STL file. The models were printed using a Polyjet printer, Objet Eden260V. Once printed, the phantoms were cleaned of support material, and tested for geometric accuracy as compared to the original patient specific data. Imaging validation using x‐ray angiography and qualitative evaluation of mechanical properties were also performed during an endovascular image‐guided intervention. Several iterations of phantoms have been printed and tested, and optimal design parameters have been determined for a favorable manufactured output. Results: The most challenging aspect of phantom manufacturing, as experienced in both simple and complex phantoms, is the removal of support material. Cleaning support material from inside of vessels can be mechanically difficult due to tortuous designs, and must be performed delicately to prevent wall rupture. Phantoms required NaOH baths and high‐pressure washing to eliminate all support materials. Phantom accuracy testing showed size variations of 120μm, a very good agreement with the original design. Interventionists experienced similar back pressure from phantoms when testing mechanical behavior in simulated clinical procedures. Conclusion: This process can serve as a viable tool for procedures and devices, and present unique learning opportunities for the endovascular field as a whole. Supported by NIH Grant: 2R01EB002873 and an equipment grant from Toshiba Medical Systems Corporation