Published in:
01-05-2012
Early Experience for the Robotic Duodenum-preserving Pancreatic Head Resection
Published in: World Journal of Surgery | Issue 5/2012
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Background
The duodenum-preserving pancreatic head resection (DPPHR) has been accepted as a valid surgical alternative to more extensive standard resections for the treatment of benign and low malignant tumors at the head of the pancreas. In this article, a new minimally invasive operation, the robot-assisted laparoscopic technique, is introduced for this procedure.
Methods
From March 2010 to Dec 2010, four patients (three women and one man), with a mean age of 42.3 years (range: 21–62 years), underwent robot-assisted laparoscopic DPPHR at the Hepato-Bilio-Pancreatic Surgical Department of Rui Jin Hospital in Shanghai, China. The preoperative symptoms include two cases of repeated upper abdominal pain, one case with no obvious preoperative symptoms, and one case of repeated hypoglycemia. The da Vinci Surgical System was used to perform the main steps of the operation. All patients underwent a pancreaticogastrostomy for pancreaticoenteric reconstruction to the distal stump.
Results
All four surgeries were successfully performed. There were no deaths. The mean operative time was 298.8 (270–335) min, average blood loss was 425 ml (range: 100–600 ml). The mean postoperative hospital stay was 26.8 days (range: 20–30 days). The one patient with an islet cell tumor has had normal blood glucose levels since the operation, and the other three patients have had no hyperglycemia. Three of the patients developed a pancreatic fistula that was cured by conservative treatment.
Conclusions
The robotic surgical system is technically fully capable of performing the complex DPPHR procedure with an acceptable range of surgical complications. It breaks through the bottleneck of the traditional laparoscopic technology and expands the range of its applications. However, this new technology is still at an exploratory stage, and the long-term effect remains to be validated by additional clinical data.