4.4 Article

Physical Models of Renal Malignancies Using Standard Cross-sectional Imaging and 3-Dimensional Printers: A Pilot Study

Journal

UROLOGY
Volume 84, Issue 2, Pages 268-272

Publisher

ELSEVIER SCIENCE INC
DOI: 10.1016/j.urology.2014.03.042

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OBJECTIVE To construct high-fidelity, patient customized, physical, 3-dimensional (3D) models of renal units with enhancing renal lesions identified on cross-sectional imaging, which may aid patients, trainees, and clinicians in their comprehension, characterization, localization, and extirpation of suspicious renal masses. METHODS Specialized software was used to import patient's diagnostic computerized tomography cross-sectional imaging into 3D printers and create physical 3D models of renal units with enhancing in situ lesions. Patients and trainees had the opportunity to manipulate the individualized model before surgical resection. Sterolithography additive manufacturing, a technique in which an ultraviolet laser is used to cure a photosensitive resin in sequential horizontally oriented layers, was used to build the models (Medical Modeling Inc., Golden, CO). Normal renal parenchyma was printed with a clear translucent resin, and red translucent resin delineated suspicious lesions. Renal vasculature and the proximal collecting system were printed in some models. RESULTS We constructed 5 physical models of renal units with suspected malignancies before surgery. All patients successfully underwent partial nephrectomy (4 robotic and 1 open). Average ischemia time was 21 minutes, nephrometry score was 6.8, and all margins were negative. Anecdotally, patients, their families, and trainees consistently stated that the models enhanced their comprehension of the renal tumor in relation to surrounding normal renal parenchyma and hilar structures and improved understanding of the goals of the surgery. CONCLUSION Preoperative physical 3D models using available printing techniques can be constructed and may potentially influence both patients' and trainees' understanding of renal malignancies. (C) 2014 Elsevier Inc.

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