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Publication Detail
Design and Evaluation of Image Guidance Systems for RARP
Introduction: There is a strong appetite amongst laparoscopic surgeons for image guidance during the procedure. It seems intuitively obvious that providing the surgeon with additional information on the location of unseen anatomy can only improve patient outcomes. However, this is not necessarily the case. If the system gives information that is not relevant to the procedure it merely becomes a distraction. Similarly if the system has large alignment errors the information presented may be dangerously wrong. One danger is that image guidance systems can be developed on an ad-hoc basis based not on targeted clinical goals but on the technical expertise and research goals of the scientists and engineers involved. Such a system may or may not benefit the patient. However, there is a real danger, as discussed by [1], that such systems will be introduced into surgical practice without proper assessment. We present our minimalist image guidance system for robot assisted radical prostatectomy together with a design and evaluation framework built upwards from the desired clinical outcomes. Methods: Our image guidance system allows the surgeon to refer to pre-operative MRI images of the patient aligned to the visible anatomy. The MRI is aligned manually to the intra-operative scene using a wire-frame representation of the inner surface of the pubic arch. Figure 1 shows the alignment and the MRI overlay. Using this the surgeon is able to intuitively match anatomy shown in the MRI to its intra-operative location. The system is intended as a start point for the development of more sophisticated image guidance systems. By properly assessing the performance of this system it should be possible to target future development efforts. We have aligned our assessment with the framework for surgical innovation set out in [1]. Starting with a list of clinical goals, we have developed a list of system design goals, which are then linked to a set of measured and controlled system parameters. How well the system achieves the design goals is assessed using a post operative surgeon questionnaire. Results: We have measured the system accuracy and so far tested the system during 11 clinical cases. Despite having a very low accuracy (around 2cm) the system has scored highly when rated by the surgeons. Table 1 lists the desired clinical outcomes and the design goals. Conclusions: We present a simple image guidance system and a framework to evaluate its performance and the performance of comparable systems. Even a very rudimentary system, providing image guidance only for a limited range of static scenes has been very well received clinically.
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