Abstract

BackgroundPediatric surgery patients often present with complex congenital anomalies or other conditions requiring deep understanding of their intricate anatomy. Commercial applications and services exist for the conversion of cross-sectional imaging data into three-dimensional (3D) models for education and preoperative planning. However, the associated costs and lack of familiarity may discourage their use in centers with limited resources. The purpose of this report is to present a low-cost, reproducible method for generating 3D images to visualize patient anatomy. MethodsDe-identified DICOM files were obtained from the hospital PACS system in preparation for assorted pediatric surgical procedures. Using open-source visualization software, variations in anatomic structures were examined using volume rendering and segmentation techniques. Images were further refined using available editing tools or artificial intelligence-assisted software extensions. ResultsUsing the described techniques we were able to obtain excellent visualization of desired structures and associated anatomic variations. Once structures were selected and modeled in 3D (segmentation), they could be exported as one of several 3D object file formats. These could then be retained for 3D printing, visualization in virtual reality, or as an anatomic reference during the perioperative period. Models may also be imported into commercial gaming engines for rendering under optimal lighting conditions and with enhanced detail. ConclusionPediatric surgeons are frequently tasked with the treatment of patients with complex and rare anomalies. Visualization and preoperative planning can be assisted by advanced imaging software at minimal to no cost, thereby facilitating enhanced understanding of these conditions in resource-limited environments. Level of EvidenceV, Case Series, Description of Technique.

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