Title

Robot-Assisted Laparoscopic Prostatectomy: Surgical Technique

Keywords

Prostatic neoplasms prostatectomy; Robotics; Surgical procedures, operative

Abstract

Prostate tumours are among the most frequently diagnosed solid tumours in males (a total of 192,280 new cases in the USA in 2009); since the approval of the PSA test by the Food and Drug Administration in 1986, incidence has risen significantly, particularly in the '90s; furthermore the spread of the PSA test has led to an increased frequency of cancer diagnosis at the localised stage. The standard treatment for tumour of the prostate is retropubic radical prostatectomy (RRP) which however is not morbidity-free, e.g. intraoperative bleeding, urinary incontinence and erectile dysfunction. This is why the interest of the scientific community has turned increasingly to mini-invasive surgical procedures able to achieve the same oncological results as the open procedure, but which also reduce the impact of the treatment on these patients' quality of life. The first step in this direction was laparoscopic prostatectomy described by Schuessler in 1992 and standardised by Gaston in 1997. However, the technical difficulty inherent in this procedure has limited its more widespread use. In May 2000 Binder and Kramer published a report on the first robot-assisted prostatectomy (RARP) using the Da Vinci system (da Vinci TM, Intuitive Surgical, Sunnyvale, CA, USA). From the original experience, RARP, which exploits the advantages of an enlarged, three-dimensional view and the ability of the instruments to move with 7 degrees of freedom, the technique has spread enormously all over the world. At the time of writing, in the USA, RARP is the most common therapeutic option for the treatment of prostate tumour at localised stage. In the present study we describe the RARP technique proposed by dr. Vipul Patel, head of the Global Robotic Institute (Orlando Fl).

Publication Date

9-1-2010

Publication Title

Minerva Urologica e Nefrologica

Volume

62

Issue

3

Number of Pages

295-304

Document Type

Review

Personal Identifier

scopus

Socpus ID

78751686605 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/78751686605

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