3D-printed tissue-mimicking phantoms for medical imaging and computational validation applications

AJ Cloonan, D Shahmirzadi, RX Li… - 3D printing and …, 2014 - liebertpub.com
AJ Cloonan, D Shahmirzadi, RX Li, BJ Doyle, EE Konofagou, TM McGloughlin
3D printing and additive manufacturing, 2014liebertpub.com
Abdominal aortic aneurysm (AAA) is a permanent, irreversible dilation of the distal region of
the aorta. Recent efforts have focused on improved AAA screening and biomechanics-
based failure prediction. Idealized and patient-specific AAA phantoms are often employed to
validate numerical models and imaging modalities. To produce such phantoms, the
investment casting process is frequently used, reconstructing the 3D vessel geometry from
computed tomography patient scans. In this study the alternative use of 3D printing to …
Abstract
Abdominal aortic aneurysm (AAA) is a permanent, irreversible dilation of the distal region of the aorta. Recent efforts have focused on improved AAA screening and biomechanics-based failure prediction. Idealized and patient-specific AAA phantoms are often employed to validate numerical models and imaging modalities. To produce such phantoms, the investment casting process is frequently used, reconstructing the 3D vessel geometry from computed tomography patient scans. In this study the alternative use of 3D printing to produce phantoms is investigated. The mechanical properties of flexible 3D-printed materials are benchmarked against proven elastomers. We demonstrate the utility of this process with particular application to the emerging imaging modality of ultrasound-based pulse wave imaging, a noninvasive diagnostic methodology being developed to obtain regional vascular wall stiffness properties, differentiating normal and pathologic tissue in vivo. Phantom wall displacements under pulsatile loading conditions were observed, showing good correlation to fluid–structure interaction simulations and regions of peak wall stress predicted by finite element analysis. 3D-printed phantoms show a strong potential to improve medical imaging and computational analysis, potentially helping bridge the gap between experimental and clinical diagnostic tools.
Mary Ann Liebert
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