3D Patient Specific Models Enhance Surgeon’s Understanding of Preoperative Anatomy in Liver Tumors

Abstract

Introduction: Liver surgery may be complex due to anatomical variants and anatomical disturbances by tumors. Preoperative planning is guided by cross-sectional imaging and the limitations of 2D imaging. Herein, we aimed to determine the impact of using 3D models on surgeons’ understanding of preoperative anatomy and surgical outcomes. Methods: Prospective single center study. Patients undergoing liver resection were included and classified based on diagnosis and by Lee et al complexity score. Preoperative cross-sectional imaging was used for the creation of 3D digital and printed models for each patient. A 5-point Likert scale survey was administered to surgeons to assess understanding of the patient anatomy. The survey was answered at two time points: before and after 3D liver model completion. Operative variables were recorded. Results: 30 patients were included, 13 (43.3%) were female and median age was 51 (IQR 32-65) years. 10 patients were living donors and 12 were diagnosed with primary liver cancer and 8 were diagnosed with metastatic disease. The most common planned procedures were right hepatectomy (44%) and right trisectionectomy (27%). Surgeons “understood” patients’ liver anatomy on 9, 3, and 5 cases before 3D education and increased to “completely understood” in 6 (p=0.7), 5 (p=0.2), and 9 (p=0.02) cases after 3D education in donor, metastatic disease, and primary liver cancer groups, respectively (Figure 1). Liver surgery complexity score, estimated blood loss, and length of stay were similar between groups. Conclusion: Patient specific 3D anatomic models improved clinical planning for the surgeon particularly in those with primary liver disease.