Purpose: Three-dimensional printing (3DP) has been used increasingly in medicine over the past several years for various applications such as surgical planning, trainee education, and patient education. 3DP allows for the creation of comprehensive patient-specific models or models with complex geometries that otherwise may not be achievable. Although many different printing materials are available for 3DP, most materials are hard plastics or based on powders which generally have very short transverse relaxation time (<1ms), therefore are not readily visualized using conventional MRI techniques. The purpose of this study was to use an UTE MRI sequence to visualize a 3DP anatomic model with complex geometry and evaluate the volume accuracy of the MRI acquisition method.
Methods: A patient-specific 3DP renal mass model was created from volumetric medical imaging data using binder jetting (CJP 660 Pro, 3D Systems). The printed model was immersed in saline water and scanned at 3T using a dual-echo ultrashort TE sequence with isotropic (0.6mm)3 spatial resolution and TR/TE1/TE2/FA=7.8ms/50μs/2.2ms/7°. 3D MR datasets from two echoes were subtracted to improve contrast before model segmentation. MR images were evaluated for image quality and the accuracy of the MR technique was evaluated.
Results: The first echo with TE=50μs had positive MR signal from the 3DP model, while the second echo had negligible MR signal with TE=2.2ms. High positive contrast between 3DP model and background was achieved after image subtraction, leading to easy 3DP model segmentation. Renal mass volumes were 82523.12mm2,79247.75mm3, 75906.68mm3 for the 3D printed design from the patient-specific imaging data, the MRI of the model, and the CT of the model respectively, with DICE correlation coefficients of 0.98 for the MRI and 0.96 for the CT.
Conclusion: 3D dual-echo UTE MRI can be utilized to generate positive MR contrast images from 3DP anatomic models to accurately determine geometrical volume.
Funding Support, Disclosures, and Conflict of Interest: Funding Support: In-kind Support, 3D Systems Healthcare Disclosures and Conflict of Interest: Consultant, GE Healthcare In-kind Support, 3D Systems Healthcare In-kind Support, Stratasys Speaker, Ultimaker