Evaluation of 3D-printed silicone phantoms with controllable MRI signal properties

Abstract

3D printing technology is widely used for creating magnetic resonance imaging (MRI) phantoms, mimicking tissue, and contrast levels found in real patients. Traditionally, 3D-printed structures were filled with gels containing contrast agents. Recently, studies have shown that some 3D-printed materials can be directly used to create MRI phantoms. However, each material typically produces a unique MRI signal, requiring specific materials for desired contrasts, or a single material can produce various contrasts, but these often do not match the properties of different soft tissues. In this study, we aimed to investigate MRI signal properties of 3D-printed phantoms made of silicone in MRI. We determined the MRI relaxation times of extrusion silicone 3D-printed phantoms from different materials with different infill densities and correlated them with the reference values in soft tissues. We also evaluated the performance of our approach using realistic tumor phantoms. A reproducibility analysis as well as longitudinal stability analysis was also performed. The experimental results showed that the 3D-printed silicone phantoms could achieve MRI signal properties with good correspondence to a range of soft tissues and organs (T1 relaxation time range from 850.8 to 1113.3 ms and T2 relaxation time range from 22.6 to 140.7 ms). Our results demonstrated good stability of the T1 and T2 values over time and also good agreement for the replicas compared to the original samples, confirming the reproducibility of the printed materials. A good agreement was observed between the MRI signal property in tumor phantoms and the reference values of invasive ductal carcinoma of the breast in patients.

Keywords

3D printing / Adjustable contrast / MRI / Silicone phantoms

Funding

This work was supported by ACMIT - Austrian Center for Medical Innovation and Technology, which is funded within the scope of the COMET program and funded by Austrian BMVIT and BMWFW and the governments of Lower Austria and Tyrol. This work was also supported by the Provincial Government of Lower Austria (Land Niederösterreich) under grant assignment number WST3-F2- 528983/005-2018.

Conflict of interest

The authors declare they have no competing interests.