Fabio Procopio1, Matteo Cimino2, Luca Viganò1, Anna E Colombo3, Eloisa Franchi2, Guido Costa2, Matteo Donadon1, Daniele Del Fabbro2, Guido Torzilli4. 1. Division of Hepatobiliary and General Surgery, Department of Surgery, Humanitas Clinical and Research Center - IRCCS, Humanitas University, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Milan, Italy. 2. Division of Hepatobiliary and General Surgery, Department of Surgery, Humanitas Clinical and Research Center - IRCCS, Humanitas University, Rozzano, Milan, Italy. 3. Pathology Unit, Humanitas Research Hospital, Rozzano, Milan, Italy. 4. Division of Hepatobiliary and General Surgery, Department of Surgery, Humanitas Clinical and Research Center - IRCCS, Humanitas University, Rozzano, Milan, Italy; Department of Biomedical Sciences, Humanitas University, Milan, Italy. Electronic address: guido.torzilli@hunimed.eu.
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.
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.
Authors: Simone de Campos Vieira Abib; Chan Hon Chui; Sharon Cox; Abdelhafeez H Abdelhafeez; Israel Fernandez-Pineda; Ahmed Elgendy; Jonathan Karpelowsky; Pablo Lobos; Marc Wijnen; Jörg Fuchs; Andrea Hayes; Justin T Gerstle Journal: Ecancermedicalscience Date: 2022-02-17