Exploring the Feasibility of an Insourced 3D-Imaging Reconstruction: Preliminary Series with the Use of Synapse3D™ Software

Background/Objectives: To evaluate the feasibility and the learning curve of an insourced, clinician-performed three-dimensional (3D) image reconstruction workflow using Synapse3D™ software in a robotic urologic surgery setting. Methods: In this prospective single-centre case series, 20 consecutive patients scheduled for robotic kidney surgery were enrolled over a 30-day period. Three urology residents without prior experience in 3D reconstruction completed a structured two-day training programme including eight supervised practice reconstructions. Subsequently, each one reconstructed all 20 study cases independently. Reconstruction time was recorded for every reconstruction. After surgery, the two operating surgeons independently rated each model on a 5-point Likert scale for anatomical fidelity, defined as the correspondence between the model and the anatomy encountered intraoperatively. Results: All 60 reconstructions were completed successfully, with no failed reconstructions, no DICOM (Digital Imaging and Communications in Medicine) import errors and no software crashes; assistance from the manufacturer was never required. Mean reconstruction time was 19 min (range 11–29 min). Reconstruction time decreased by 0.63 min per case (95% CI 0.51–0.74; p < 0.001). Median time fell from 23 min in the first ten cases to 15 min in the last ten (p < 0.001), and the reduction was significant for each operator analysed separately. Anatomical fidelity was rated 4 (IQR 1) by both surgeons. The two surgeons rated overall system usability 3/5 and 5/5. Conclusions: Insourced 3D reconstruction with Synapse3D™ is technically feasible and is learned rapidly and reproducibly by urology residents after limited training.