Evaluation of the Uncertainty Associated With the Young’s Modulus Measurement of 3-D-Printed Specimens for Intracranial Aneurysm Mock-Up Realization

Three-dimensional (3D)-printed vascular mock-ups are increasingly used in the study and treatment of intracranial aneurysms, providing patient-specific geometries for preoperative planning and surgical training. While previous research has primarily focused on anatomical fidelity, reproducing arterial mechanics is equally crucial for clinical relevance. However, the reliable quantification of uncertainty associated with elastic property measurements in soft, thin-walled 3D-printed specimens remains insufficiently addressed, and existing studies typically report only statistical dispersion without uncertainty analysis. This work presents a structured evaluation of the uncertainty in Young’s modulus (E) measurements in stereolithography (SLA)-printed specimens fabricated from Formlabs Elastic 50A resin. Cylindrical samples, representative of blood vessels’ shape, were printed in three orientations relative to the build plate, and rectangular and ring-shaped specimens were extracted for uniaxial tensile testing to assess the influence of specimen geometry on the uncertainty budget. This uncertainty budget was established in accordance with the GUM framework, using analytical uncertainty propagation and Monte Carlo simulations as a consistency check. Instrumentation uncertainty was primarily driven by dimensional measurements using a caliper, particularly for ring specimens, where the geometric correction factor introduced an additional contribution to the total uncertainty. Repeatability (intra-specimen) uncertainty (below 0.35% ofE) contributed far less to the overall budget, whereas reproducibility (inter-specimen) represented the dominant source of uncertainty (up to ~9% ofE). As a result, ring-shaped specimens exhibited higher uncertainty levels (~19% ofE) than rectangular specimens (~11% ofE), highlighting how specimen geometry and process variability affect the uncertainty budget associated with the mechanical validation of 3D-printed vascular phantoms.