Comparison and calibration of a real-time virtual stenting algorithm using Finite Element Analysis and Genetic Algorithms

In this paper, we perform a comparative analysis between two computational methods for virtual stent deployment: a novel fast virtual stenting method, which is based on a spring-mass model, is compared with detailed finite element analysis in a sequence of in silico experiments. Given the results of the initial comparison, we present a way to optimise the fast method by calibrating a set of parameters with the help of a genetic algorithm, which utilises the outcomes of the finite element analysis as a learning reference. As a result of the calibration phase, we were able to substantially reduce the force measure discrepancy between the two methods and validate the fast stenting method by assessing the differences in the final device configurations.

Towards Predicting Patient-Specific Flow-Diverter Treatment Outcomes for Bifurcation Aneurysms: From Implantation Rehearsal to Virtual Angiograms

Despite accounting for the majority of all cerebral aneurysm cases, bifurcation aneurysms present many challenges to standard endovascular treatment techniques. This study examines the treatment of bifurcation aneurysms endovascularly with flow-diverting stents and presents an integrative computational modeling suite allowing for rehearsing all aspects of the treatment. Six bifurcation aneurysms are virtually treated with 70% porosity flow-diverters. Substantial reduction (>50%) in aneurysm inflow due to device deployment is predicted in addition to reductions in peak and average aneurysm wall shear stress to values considered physiologically normal. The subsequent impact of flow-diverter deployment on daughter vessels that are jailed by the device is investigated further, with a number of simulations conducted with increased outlet pressure conditions at jailed vessels. Increased outlet pressures at jailed daughter vessels are found to have little effect on device-induced aneurysm inflow reduction, but large variation (13–86%) is seen in the resulting reduction in daughter vessel flow rate. Finally, we propose a potentially powerful approach for validation of such models, by introducing an angiographic contrast model, with contrast transport modeled both before and after virtual treatment. Virtual angiograms and contrast residence curves are created, which offer unique clinical relevance and the potential for future in vivo verification of simulated results.

Personalizing flow-diverter intervention for cerebral aneurysms: from computational hemodynamics to biochemical modeling

This paper presents the computational modeling of a variety of flow-diverting stents, deployed in a number of patient-specific aneurysm geometries. We consider virtual device deployment and hemodynamics as well as thrombus formation, with the scope to assess pre-operatively the efficacy of specific devices in treating particular aneurysms. An algorithm based on a linear and torsional spring analogy is developed for the fast virtual deployment of stents and similar minimally invasive devices in patient-specific vessel geometries. The virtual deployment algorithm is used to accurately deploy a total of four stent designs in three aneurysm geometries. A variety of different flow-diverting stent designs, representing the commercially available and the entirely novel, are presented, varying in both mesh design and porosity. Transient computational hemodynamics simulations are performed on multiple patient-specific geometries to predict the reduction in aneurysm inflow after the deployment of each device. Further, a thrombosis initiation and growth model is implemented, coupled with the hemodynamic computations. Hemodynamic simulations show large variations in flow reduction between devices and across different aneurysm geometries. The industry standard of flow-diverters with 70% porosity, assumed to offer the best compromise in flexibility and flow reduction, is challenged in at least one aneurysm geometry.

Content analysis of the use of fantasy, challenge, and curiosity in school-based nutrition education programs

The objective of this research was to document the extent to which elements of fantasy, curiosity, and challenge are used in existing nutrition education materials. A content analysis of 30 nutrition education curricula designed for elementary and middle-school grades was conducted. Print curricula, computer software, videotapes, and puppet shows were included in the sample. The use of challenge, curiosity, and fantasy, as defined in the Theory of Intrinsically Motivating Instruction (TIMI), was assessed in each curriculum. Approximately half of the curricula included elements of challenge, curiosity, or fantasy. All of the nonprint curricula and 30% of the print curricula incorporated these characteristics. Curiosity was most frequently used in these curricula, followed by fantasy and then challenge. The TIMI provided a useful theory to examine the instructional approaches frequently used in school-based nutrition education programs. Nutritionists may apply concepts from the TIMI to the design of future curricula so that these programs are interesting and entertaining for their target audience.