title: Anatomical dimensions using preoperative magnetic resonance imaging: impact on the learning curve of robot-assisted laparoscopic prostatectomy.
abstract: OBJECTIVE
  To evaluate the impact of anatomical dimensions as measured using preoperative magnetic resonance imaging on the outcomes of robot-assisted laparoscopic prostatectomy.
  
  
  METHODS
  We retrospectively reviewed 100 consecutive robot-assisted laparoscopic prostatectomy procedures that were carried out by a single surgeon at the Division of Urology, Department of Surgery, Tottori University Faculty of Medicine, Yonago, Japan. Preoperative clinical data and anatomical measurements, including the calculated prostate volume pelvic cavity index, were determined based on preoperative magnetic resonance imaging, and their effects on console time, estimated blood loss and surgical margin status were compared.
  
  
  RESULTS
  Body mass index, the prostate anteroposterior diameter, and the prostate volume-to-pelvic cavity index ratio were all significantly correlated with console time and estimated blood loss, based on a univariate analysis (P < 0.05). The prostate craniocaudal diameter, prostate transverse diameter and prostate volume also correlated with console time. However, based on the multiple linear regression analysis, only the prostate volume-to-pelvic cavity index ratio was found to be a significant predictor of console time and estimated blood loss. Furthermore, when the 100 total cases were divided into 50 early cases and 50 late cases, the prostate volume-to-pelvic cavity index ratio correlated with console time and estimated blood loss only in the early group, and not in the late group. In contrast, anatomical measurements had no significant effect on surgical margin status.
  
  
  CONCLUSIONS
  Magnetic resonance imaging can be a valuable adjunct to robot-assisted laparoscopic prostatectomy. Our data show that patients with larger prostates and narrow, deep pelvises might present more difficulty in robot-assisted laparoscopic prostatectomy procedures. However, the present data also show that this problem can be overcome by an experienced operator with improved surgical techniques.
authors.affiliation: Division of Urology, Department of Surgery, Tottori University Faculty of Medicine, Yonago, Japan.
authors.forename: Akihisa
authors.initials: A
authors.lastname: Yao
authors.forename: Hideto
authors.initials: H
authors.lastname: Iwamoto
authors.forename: Toshihiko
authors.initials: T
authors.lastname: Masago
authors.forename: Shuichi
authors.initials: S
authors.lastname: Morizane
authors.forename: Masashi
authors.initials: M
authors.lastname: Honda
authors.forename: Takehiro
authors.initials: T
authors.lastname: Sejima
authors.forename: Atsushi
authors.initials: A
authors.lastname: Takenaka
mesh_terms: D000368:Aged; D006801:Humans; D007564:Japan; D010535:Laparoscopy / Q000009:adverse effects / Q000379:methods*; D059032:Learning Curve; D008279:Magnetic Resonance Imaging / Q000379:methods*; D008297:Male; D008875:Middle Aged; D011467:Prostate / Q000473:pathology*; D011468:Prostatectomy / Q000009:adverse effects / Q000379:methods*; D011471:Prostatic Neoplasms / Q000473:pathology*; D012189:Retrospective Studies; D012371:Robotics / Q000379:methods*
keywords: learning curve; magnetic resonance imaging; pelvis; prostate cancer; robot-assisted laparoscopic radical prostatectomy