Anecdotally, surgeons sometimes observe large errors when using image guidance in endonasal surgery. We hypothesize that one contributing factor is the possibility that operating room personnel might accidentally bump the optically tracked rigid body attached to the patient after registration has been performed. In this paper we explore the registration error at the skull base that can be induced by simulated bumping of the rigid body, and find that large errors can occur when simulated bumps are applied to the rigid body. To address this, we propose a new fixation method for the rigid body based on granular jamming (i.e. using particles like ground coffee). Our results show that our granular jamming fixation prototype reduces registration error by 28%-68% (depending on bump direction) in comparison to a standard Brainlab reference headband.
We present a novel robotic approach for the rapid, minimally invasive treatment of Intracerebral Hemorrhage (ICH), in which a hematoma or blood clot arises in the brain parenchyma. We present a custom image-guided robot system that delivers a steerable cannula into the lesion and aspirates it from the inside. The steerable cannula consists of an initial straight tube delivered in a manner similar to image-guided biopsy (and which uses a commercial image guidance system), followed by the sequential deployment of multiple individual precurved elastic tubes. Rather than deploying the tubes simultaneously, as has been done in nearly all prior studies, we deploy the tubes one at a time, using a compilation of their individual workspaces to reach desired points inside the lesion. This represents a new paradigm in active cannula research, defining a novel procedure-planning problem. A design that solves this problem can potentially save many lives by enabling brain decompression both more rapidly and less invasively than is possible through the traditional open surgery approach. Experimental results include a comparison of the simulated and actual workspaces of the prototype robot, and an accuracy evaluation of the system.
Preoperative image data can facilitate intrasurgical guidance by revealing interior features of opaque tissues, provided
image data can be accurately registered to the physical patient. Registration is challenging in organs that are deformable
and lack features suitable for use as alignment fiducials (e.g. liver, kidneys, etc.). However, provided intraoperative
sensing of surface contours can be accomplished, a variety of rigid and deformable 3D surface registration techniques
become applicable. In this paper, we evaluate the feasibility of conoscopic holography as a new method to sense organ
surface shape. We also describe potential advantages of conoscopic holography, including the promise of replacing open
surgery with a laparoscopic approach. Our feasibility study investigated use of a tracked off-the-shelf conoscopic
holography unit to perform a surface scans on several types of biological and synthetic phantom tissues. After first
exploring baseline accuracy and repeatability of distance measurements, we performed a number of surface scan
experiments on the phantom and ex vivo tissues with a variety of surface properties and shapes. These indicate that
conoscopic holography is capable of generating surface point clouds of at least comparable (and perhaps eventually
improved) accuracy in comparison to published experimental laser triangulation-based surface scanning results.