Technique of robotic left hepatectomy : how we approach it View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

2019-04

AUTHORS

Iswanto Sucandy, Aviad Gravetz, Sharona Ross, Alexander Rosemurgy

ABSTRACT

Minimally invasive technique has been adopted as the standard of care in many surgical fields within general surgery. Hepatobiliary surgery, however, is lacking behind due to the complex nature of the operation and concerns of major bleeding. Several centers suggested that inherent limitations of conventional laparoscopy precludes its wide adoption. Robotic technique provides solutions to these limitations. In this study, we report our standardized technique of robotic left hepatectomy. We discuss aspects of robotic hepatectomy and describe our standardized approach for robotic left hepatectomy. A video is attached to this article. A 76-year-old man with a 4.5 cm biopsy-proven hepatocellular carcinoma was taken to the operating room for a robotic left hepatectomy. His past medical and surgical history was only consistent with hypertension and diabetes. Robotic extrahepatic glissonian pedicle approach was applied to gain inflow control. Left hepatic artery and portal vein were individually dissected and isolated prior to division. An intraoperative robotic ultrasound was utilized to ensure negative resection margins. Left hepatic vein was transected intrahepatically using a laparoscopic Endo GIA stapler. Segment 2,3, and part of 4 were removed. Operative time was 180 min without intraoperative complications. Estimated blood loss was less than 50 cc. The patient was discharged home on postoperative day 3. The use of robotic technology during complex hepatic resections such as left hepatectomy is safe and feasible. This approach provides an alternative technique in minimally invasive liver surgery. More... »

PAGES

201-207

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s11701-018-0890-6

DOI

http://dx.doi.org/10.1007/s11701-018-0890-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1109784651

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/30406886


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