PURPOSE: Retroperitoneal sarcomas (RPS) present a surgical challenge due to their complex anatomical relationships to organs and vascular structures. In this limited case series, we reconstructed the tumour beds of four cases of RPS and their ex vivo specimens. METHODS: Four patients underwent surgical resection of their retroperitoneal sarcoma at our centre in 2023-2024. After completing the tumour resection, a smartphone was utilized to capture images of both the tumour bed and the resected specimen. Images were imported into 3D reconstruction programs, which used artificial intelligence (AI) to reconstruct the 3D model, available to explore from various angles and sizes by the surgical team. RESULTS: Four patients were treated at our centre: two left-sided and two right-sided RPS. Pathology was liposarcoma in two patients and leiomyosarcoma in the other two. After the resection was completed, a smartphone was used to create the 3D model. A total of nine models were created, five models of the tumour bed and four models of the ex vivo specimen. Fixed structures present in both the tumour bed and the resected specimen were labelled in both models to allow orientation. These included the ureteric stump, the divided peritoneal reflection and the divided renal pedicle. CONCLUSIONS: This technology has great potential for use in education, surgical quality control and other applications in surgical oncology.