Optimizing cerebrovascular surgical and endovascular procedures in children via personalized 3D printing

Abstract

OBJECT Despite the availability of multiplanar imaging, understanding relational 3D anatomy for complex cerebrovascular lesions can be difficult. A 3D printed model allows for instantaneous visualization of lesional anatomy from all perspectives, with the added ability to simulate operative approaches with tactile feedback. The authors report their experience with customized 3D printed models of pediatric cerebrovascular lesions as an educational and clinical tool for patients, trainees, and physicians. METHODS Via an “in-house” 3D print service, magnetic resonance imaging (MRI) and computerized tomography (CT) studies of pediatric patients with arteriovenous malformations (AVMs) were processed with specialized software, and regions of interest were selected by the surgical/endovascular team. Multiple models for each patient were then printed on a 3D printer, with each construct designed to illustrate different aspects of the specific lesion. Intraoperative validation of model fidelity was performed using perioperative imaging, surgical filming, and post hoc analysis of models with intraoperative photography. RESULTS Four cases involving pediatric patients (ages 0–16 years) were studied for initial proof of principle. Three of the patients had AVMs and one had a vein of Galen malformation (VOGM). The VOGM was embolized successfully and the AVMs were resected without complication. In the AVM cases, intraprocedural imaging and photography were performed and verified millimeter-level fidelity of the models (n = 5, 98% concordance, range 94%–100% with average of < 2 mm variation in the largest AVM [6-cm diameter]). The use of 3D models was associated with a 30-minute reduction in operative time (12%) in 2 cases when they were compared with matched controls as a feasibility study. CONCLUSIONS Patient-specific 3D printed models of pediatric cerebrovascular conditions can be constructed with high fidelity. This proof-of-principle series demonstrates, for the first time, confirmation of model accuracy using intraprocedural assessment and potential benefit through shortened operative time.