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Differences in Microsurgical Techniques Between the Microscope and the Endoscope — A Practical Instruction of 5 Years Experience

  • T. P. Szymula von Richter
  • M. Sawaizumi
  • Y. Iwahira
  • K. Onishi
  • Y. Maruyama
Part of the Update in Plastic Surgery book series (UPDATEPLASTIC)

Abstract

“Reconstructive microsurgery has reached three decades of sohd development. Technological advances in the microscope, micro instruments and microsuture materials have revolutionised surgical practice, leading to rapid development in micromanipulation with spin off in endoscopy and minimally invasive surgery. There is an ever widening clinical apphcation of free tissue transplant in reconstructive microsurgery.” The aim of the following article is to crystalhse the accumulated knowledge of the technique, emphasising in particular the idea of endoscopy and microsurgery. Since 1994, the following data were critically reviewed including existing and newly developed concepts as well as current and new innovative techniques. The results of this review may determine the direction in which reconstructive microsurgery will head in the next millennium. The following article contains experimental data that were presented in the proceedings of the 12th Symposium of the International Society of Reconstructive Microsurgery held in Singapore in 1996 as “technique of endoscopic microsurgical anastomoses of arteries, veins, lymphatic vessels and nerves” and “models for learning the technique of microsurgical anastomosis of blood and lymphatic vessels and nerves through the endoscope”. In the late 70’s models for learning microsurgical anastomoses through the microscope and loupes were described. Since Alexis Carreh around 1900, investigations in microvascular surgery created ideas for its use in reconstructive surgery.

Keywords

Lymphatic Vessel Free Flap Microsurgical Technique Abstract Book Free Flap Reconstruction 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Wien 2001

Authors and Affiliations

  • T. P. Szymula von Richter
  • M. Sawaizumi
  • Y. Iwahira
  • K. Onishi
  • Y. Maruyama

There are no affiliations available

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