Engineering a 3D human intracranial aneurysm model using liquid-assisted injection molding and tuned hydrogels

Endothelial Cell Transcription Modulation in Cerebral Aneurysms After Endovascular Flow Diversion

PURPOSE

Flow diverting stents (FDS) are used to treat cerebral aneurysms, by promoting thrombosis and occlusion of the aneurysm sac. However, retreatment is required in some cases, and the biologic basis behind treatment outcome is not known. The goal of this study was to understand how changes in hemodynamic flow after FDS placement affect aneurysmal endothelial cell (EC) activity.

METHODS

Three-dimensional models of patient-specific aneurysms were created to quantify the EC response to FDS placement. Computational fluid dynamic simulations were used to determine the hemodynamic impact of FDS. Two identical models were created for each patient; into one a FDS was inserted. Each model was then populated with human carotid ECs and subjected to patient-specific pulsatile flow for 24 h. ECs were isolated from aneurysm dome from each model and bulk RNA sequencing was performed.

RESULTS

Paired untreated and treated models were created for four patients. Aneurysm dome EC analysis revealed 366 (2.6%) significant gene changes between the untreated and FDS conditions, out of 13909 total expressed genes. Gene set enrichment analysis of the untreated models demonstrated enriched gene ontology terms related to cell adhesion, growth/tensile activity, cytoskeletal organization, and calcium ion binding. In the FDS models, enriched terms were related to cellular proliferation, ribosomal activity, RNA splicing, and protein folding.

CONCLUSION

Treatment of cerebral aneurysms with FDS induces significant EC gene transcription changes related to aneurysm hemodynamics in patient-specific in vitro 3D-printed models subjected to pulsatile flow. Further investigation is needed into the relationship between transcriptional change and treatment outcome.

Time-of-Flight MRA of Intracranial Aneurysms with Interval Surveillance, Clinical Segmentation and Annotations

Intracranial aneurysms (IAs) are present in 2-6% of the global population and can be catastrophic upon rupture with a mortality rate of 30-50%. IAs are commonly detected through time-of-flight magnetic resonance angiography (TOF-MRA), however, this data is rarely available for research and training purposes. The provision of imaging resources such as TOF-MRA images is imperative to develop new strategies for IA detection, rupture prediction, and surgical training. To support efforts in addressing data availability bottlenecks, we provide an open-access TOF-MRA dataset comprising 63 patients, of which 24 underwent interval surveillance imaging by TOF-MRA. Patient scans were evaluated by a neuroradiologist, providing aneurysm and vessel segmentations, clinical annotations, 3D models, in addition to 3D Slicer software environments containing all this data for each patient. This dataset is the first to provide interval surveillance imaging for supporting the understanding of IA growth and stability. This dataset will support computational and experimental research into IA dynamics and assist surgical and radiology training in IA treatment.

Comparison of Flow Behavior in Saccular Aneurysm Models Using Proper Orthogonal Decomposition

Aneurysms are abnormal ballooning of a blood vessel. Previous studies have shown presence of complex flow structures in aneurysms. The objective of this study was to quantify the flow features observed in two selected saccular aneurysm geometries over a range of inflow conditions using Proper Orthogonal Decomposition (POD). For this purpose, two rigid-wall saccular aneurysm models geometries were used (i.e., the bottleneck factor of 1 and 1.6), and the inflow conditions were varied using a peak Reynolds number (Rep) from 50 and 270 and Womersley number (α) from 2 and 5. The velocity flow field data for the studied aneurysm geometries were acquired using Particle Image Velocimetry (PIV). The average flow field from the PIV measurement showed that the model geometry and Rep have more significant impact on the average flow field than the variations in α. The POD results showed that the method was able to quantify the flow field characteristics between the two model geometries. The mode shapes obtained showed different spatial structures for each inflow scenarios and models. The POD energy results showed that more than 80% of the fluctuating kinetic energy were captured within five POD modes for BF=1.0 flow scenarios, while they were captured within ten modes for BF=1.6. The time varying coefficient results showed the complex interplay of POD modes at different inflow scenarios, highlighting important modes at different phases of the flow cycle. The low-order reconstruction results showed that the vortical structure either proceeded outward or stayed within the aneurysm, and this behavior was highly dependent on α, Rep, and model geometry that were not evident in average PIV results.