Journal of pediatric surgery · 2016
Computer-assisted surgery planning in children with complex liver tumors identifies variability of the classical Couinaud classification.
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Warmann Steven W, Schenk Andrea, Schaefer Juergen F, Ebinger Martin, Blumenstock Gunnar, Tsiflikas Ilias, Fuchs Joerg
Аннотация
BACKGROUND: In complex malignant pediatric liver tumors there is an ongoing discussion regarding surgical strategy; for example, primary organ transplantation versus extended resection in hepatoblastoma involving 3 or 4 sectors of the liver. We evaluated the possible role of computer-assisted surgery planning in children with complex hepatic tumors.
METHODS: Between May 2004 and March 2016, 24 Children with complex liver tumors underwent standard multislice helical CT scan or MRI scan at our institution. Imaging data were processed using the software assistant LiverAnalyzer (Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany). Results were provided as Portable Document Format (PDF) with embedded interactive 3-dimensional surface mesh models.
RESULTS: Median age of patients was 33months. Diagnoses were hepatoblastoma (n=14), sarcoma (n=3), benign parenchyma alteration (n=2), as well as hepatocellular carcinoma, rhabdoid tumor, focal nodular hyperplasia, hemangioendothelioma, or multiple hepatic metastases of a pancreas carcinoma (each n=1). Volumetry of liver segments identified remarkable variations and substantial aberrances from the Couinaud classification. Computer-assisted surgery planning was used to determine surgical strategies in 20/24 children; this was especially relevant in tumors affecting 3 or 4 liver sectors. Primary liver transplantation could be avoided in 12 of 14 hepaoblastoma patients who theoretically were candidates for this approach.
CONCLUSIONS: Computer-assisted surgery planning substantially contributed to the decision for surgical strategies in children with complex hepatic tumors. This tool possibly allows determination of specific surgical procedures such as extended surgical resection instead of primary transplantation in certain conditions.
METHODS: Between May 2004 and March 2016, 24 Children with complex liver tumors underwent standard multislice helical CT scan or MRI scan at our institution. Imaging data were processed using the software assistant LiverAnalyzer (Fraunhofer Institute for Medical Image Computing MEVIS, Bremen, Germany). Results were provided as Portable Document Format (PDF) with embedded interactive 3-dimensional surface mesh models.
RESULTS: Median age of patients was 33months. Diagnoses were hepatoblastoma (n=14), sarcoma (n=3), benign parenchyma alteration (n=2), as well as hepatocellular carcinoma, rhabdoid tumor, focal nodular hyperplasia, hemangioendothelioma, or multiple hepatic metastases of a pancreas carcinoma (each n=1). Volumetry of liver segments identified remarkable variations and substantial aberrances from the Couinaud classification. Computer-assisted surgery planning was used to determine surgical strategies in 20/24 children; this was especially relevant in tumors affecting 3 or 4 liver sectors. Primary liver transplantation could be avoided in 12 of 14 hepaoblastoma patients who theoretically were candidates for this approach.
CONCLUSIONS: Computer-assisted surgery planning substantially contributed to the decision for surgical strategies in children with complex hepatic tumors. This tool possibly allows determination of specific surgical procedures such as extended surgical resection instead of primary transplantation in certain conditions.