PURPOSE: To provide unencumbered real-time ultrasound image guidance during robot-assisted laparoscopic radical prostatectomy (RALRP), we have developed a robotic transrectal ultrasound system (TRUS) that tracks the da Vinci instruments.
We describe our initial clinical experience with this system.
MATERIALS AND METHODS: After an evaluation in a canine model, twenty patients were enrolled in the study. During each procedure, first the TRUS was manually positioned using a brachytherapy stabilizer to provide good imaging of the prostate. Then, the TRUS was registered to the da Vinci robot by a previously validated procedure. Finally, automatic rotation of the TRUS was enabled, such that the TRUS imaging plane safely tracked the tip of the da Vinci instrument controlled by the surgeon, while real-time TRUS images were relayed to the surgeon at the da Vinci console. Tracking was activated during all critical stages of the surgery.
RESULTS: The TRUS was easy to setup and use, adding 7 (5-14) minutes to the procedure. It did not require an assistant or additional control devices. Qualitative feedback was acquired from the surgeons, who found TRUS useful in identifying the urethra while passing the dorsal venous complex suture, defining the prostate-bladder interface during bladder neck dissection, identifying the seminal vesicles and their location with respect to the rectal wall, and identifying the distal prostate boundary at the apex.
CONCLUSIONS: Real-time, registered robotic TRUS guidance with automatic instrument tracking during RALRP is feasible and potentially useful. The results justify further studies to establish whether the approach can improve procedure outcomes.
Written by:
Mohareri O, Ischia J, Black PC, Schneider C, Lobo J, Goldenberg L, Salcudean SE. Are you the author?
Department of Electrical and Computer Engineering, University of British Columbia; Department of Urological Sciences, University of British Columbia.
Reference: J Urol. 2014 Aug 20. pii: S0022-5347(14)04262-1.
doi: 10.1016/j.juro.2014.05.124
PubMed Abstract
PMID: 25150644