Intelligent Systems
Note: This research group has relocated.

Soft Phantom for the Training of Renal Calculi Diagnostics and Lithotripsy

2019

Conference Paper

pf


Organ models are important for medical training and surgical planning. With the fast development of additive fabrication technologies, including 3D printing, the fabrication of 3D organ phantoms with precise anatomical features becomes possible. Here, we develop the first high-resolution kidney phantom based on soft material assembly, by combining 3D printing and polymer molding techniques. The phantom exhibits both the detailed anatomy of a human kidney and the elasticity of soft tissues. The phantom assembly can be separated into two parts on the coronal plane, thus large renal calculi are readily placed at any desired location of the calyx. With our sealing method, the assembled phantom withstands a hydraulic pressure that is four times the normal intrarenal pressure, thus it allows the simulation of medical procedures under realistic pressure conditions. The medical diagnostics of the renal calculi is performed by multiple imaging modalities, including X-ray, ultrasound imaging and endoscopy. The endoscopic lithotripsy is also successfully performed on the phantom. The use of a multifunctional soft phantom assembly thus shows great promise for the simulation of minimally invasive medical procedures under realistic conditions.

Author(s): Li., D. and Suarez-Ibarrola, R. and Choi, E. and Jeong, M. and Gratzke, C. and Miernik, A. and Fischer, P. and Qiu, T.
Year: 2019
Month: July
Day: 24

Department(s): Micro, Nano, and Molecular Systems
Bibtex Type: Conference Paper (conference)

Event Name: 41st Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC)
Event Place: Berlin

BibTex

@conference{Li2019,
  title = {Soft Phantom for the Training of Renal Calculi Diagnostics and  Lithotripsy},
  author = {Li., D. and Suarez-Ibarrola, R. and Choi, E. and Jeong, M. and Gratzke, C. and Miernik, A. and Fischer, P. and Qiu, T.},
  month = jul,
  year = {2019},
  doi = {},
  month_numeric = {7}
}