ABSTRACT
Introduction: Preoperative three-dimensional (3D) reconstruction using sectional imaging is increasingly used in challenging pediatric cases to aid in surgical planning. Many case series have described various teams' experiences, discussing feasibility and realism, while emphasizing the technological potential for children. Nonetheless, general knowledge on this topic remains limited compared to the broader research landscape. The aim of this review was to explore the current devices and new opportunities provided by preoperative Computed Tomography (CT) scans or Magnetic Resonance Imaging (MRI). Methods: A systematic review was conducted to screen pediatric cases of abdominal and pelvic tumors with preoperative 3D reconstruction published between 2000 and 2023. Discussion: Surgical planning was facilitated through virtual reconstruction or 3D printing. Virtual reconstruction of complex tumors enables precise delineation of solid masses, formulation of dissection plans, and suggests dedicated vessel ligation, optimizing tissue preservation. Vascular mapping is particularly relevant for liver surgery, large neuroblastoma with imaging-defined risk factors (IDRFs), and tumors encasing major vessels, such as complex median retroperitoneal malignant masses. 3D printing can facilitate specific tissue preservation, now accessible with minimally invasive procedures like partial nephrectomy. The latest advancements enable neural plexus reconstruction to guide surgical nerve sparing, for example, hypogastric nerve modelling, typically adjacent to large pelvic tumors. New insights will soon incorporate nerve plexus images into anatomical segmentation reconstructions, facilitated by non-irradiating imaging modalities like MRI. Conclusion: Although not yet published in pediatric surgical procedures, the next anticipated advancement is augmented reality, enhancing real-time intraoperative guidance: the surgeon will use a robotic console overlaying functional and anatomical data onto a magnified surgical field, enhancing robotic precision in confined spaces.
