3D printed aneurysm training before treatment: A case control retrospective study

Abstract

Background

Intracranial aneurysms are abnormal dilatations of arteries in the brain, often necessitating intricate endovascular interventions. Preoperative planning using 3D-printed models can enhance the understanding of complex aneurysm anatomy and improve treatment strategies. This study aims to evaluate the impact of patient-specific 3D-printed aneurysm models on procedural planning, treatment efficacy, and clinical outcomes.

Methods

We conducted a retrospective analysis of patients treated for non-ruptured intracranial aneurysms at our institution between 2021 and 2023. Nine patients underwent preoperative simulation using 3D-printed models, while 32 patients received standard care without simulation. The vascular models were created using 3D Slicer for segmentation and Meshmixer for model refinement. The simulations were performed on a biplane Allura system. Data on demographics, aneurysm characteristics, hospitalization duration, procedure times, treatment changes, and unused materials were collected and analyzed using SPSS software. Statistical significance was assessed with independent one-tail t-tests, with a p-value < 0.05 considered significant.

Results

The experimental group (nine patients) showed a trend towards reduced procedure times compared to the control group (126 ± 48 mins vs. 142 ± 68 mins, p = 0.253). There was no significant difference in mean hospitalization days between the groups (4 ± 0.9 days vs. 4 ± 1.7 days, p = 0.502). Interestingly, the treatment strategy was altered in four cases based on 3D simulation insights. The 3D simulation group also experienced fewer procedural complications (22.2 % vs. 31.2 %).

Conclusions

simulation using 3D-printed models shows potential in enhancing procedural planning and reducing complication rates in the treatment of intracranial aneurysms. While the study did not demonstrate statistically significant differences in procedure time and hospitalization days, the observed trends and changes in treatment strategies suggest that 3D printing technology can provide valuable insights for neurointerventionists. Further research with larger sample sizes and prospective designs is warranted to validate these findings and establish standardized protocols for integrating 3D printing into clinical practice.