Prediction of remnant liver volume using 3D simulation software in patients undergoing R1vasc parenchyma-sparing hepatectomy for multiple bilobar colorectal liver metastases: reliability, clinical impact, and learning curve

HPB (Oxford). 2021 Jul;23(7):1084-1094. doi: 10.1016/j.hpb.2020.11.005. Epub 2021 Jan 19.

Abstract

Background: Assessment of the future liver remnant (FLR) is routinely performed before major hepatectomy. In R1-vascular one-stage hepatectomy (R1vasc-OSH), given the multiplanar dissection paths, the FLR is not easily predictable. Preoperative 3D-virtual casts may help. We evaluated the predictability of the FLR using the 3D-virtual cast in the R1vasc-OSH for multiple bilobar colorectal liver metastases (CLM).

Methods: Thirty consecutive patients with multiple bilobar CLMs scheduled for R1vasc-OSH were included. Predicted and real-FLRs were compared. Propensity score-matched analysis was used to determine the impact of 3D-virtual cast on postoperative complications.

Results: Median number of CLM and resection areas were 12 (4-33) and 3 (1-8). Median predicted-FLR was 899 ml (558-1157) and 60% (42-85), while for the real-FLR 915 ml (566-1777) and 63% (43-87). Median discrepancy between predicted and real-FLR was -0.6% (p = 0.504), indicating a slight tendency to underestimate the FLR. The difference was more evident in more than 12 CLMs (p = 0.013). A discrepancy was not evident according to the number of resection areas (p = 0.316). No mortality occurred. Patients in virtual-group had lower major complications compared to nonvirtual-group (0% vs 18%, p-value 0.014).

Conclusion: FLR estimation based on 3D-analysis is feasible, provides a safe surgery and represents a promising method in planning R1vasc-OSH for patients with multiple bilobar CLMs.

MeSH terms

  • Colorectal Neoplasms* / surgery
  • Hepatectomy / adverse effects
  • Humans
  • Learning Curve
  • Liver Neoplasms* / diagnostic imaging
  • Liver Neoplasms* / surgery
  • Portal Vein
  • Reproducibility of Results
  • Retrospective Studies
  • Software
  • Treatment Outcome