A Craniomaxillofacial Surgical Assistance Workstation for Enhanced Single-Stage Reconstruction Using Patient-Specific Implants.

BACKGROUND: Craniomaxillofacial reconstruction with patient-specific, customized craniofacial implants (CCIs) is ideal for skeletal defects involving areas of aesthetic concern-the non-weight-bearing facial skeleton, temporal skull, and/or frontal-forehead region. Results to date are superior to a variety of "off-the-shelf" materials, but require a protocol computed tomography scan and preexisting defect for computer-assisted design/computer-assisted manufacturing of the CCI. The authors developed a craniomaxillofacial surgical assistance workstation to address these challenges and intraoperatively guide CCI modification for an unknown defect size/shape. METHODS: First, the surgeon designed an oversized CCI based on his/her surgical plan. Intraoperatively, the surgeon resected the bone and digitized the resection using a navigation pointer. Next, a projector displayed the limits of the craniofacial bone defect onto the prefabricated, oversized CCI for the size modification process; the surgeon followed the projected trace to modify the implant. A cadaveric study compared the standard technique (n = 1) to the experimental technique (n = 5) using surgical time and implant fit. RESULTS: The technology reduced the time and effort needed to resize the oversized CCI by an order of magnitude as compared with the standard manual resizing process. Implant fit was consistently better for the computer-assisted case compared with the control by at least 30%, requiring only 5.17 minutes in the computer-assisted cases compared with 35 minutes for the control. CONCLUSION: This approach demonstrated improvement in surgical time and accuracy of CCI-based craniomaxillofacial reconstruction compared with previously reported methods. The craniomaxillofacial surgical assistance workstation will provide craniofacial surgeons a computer-assisted technology for effective and efficient single-stage reconstruction when exact craniofacial bone defect sizes are unknown.

Embedded clutter reduction and face detection algorithms for a visual prosthesis.

Retinal prosthetic devices can significantly and positively impact the ability of visually challenged individuals to live a more independent life. We describe a visual processing system which leverages image analysis techniques to produce visual patterns and allows the user to more effectively perceive their environment. These patterns are used to stimulate a retinal prosthesis to allow self guidance and a higher degree of autonomy for the affected individual. Specifically, we describe an image processing pipeline that allows for object and face localization in cluttered environments as well as various contrast enhancement strategies in the "implanted image." Finally, we describe a real-time implementation and deployment of this system on the Argus II platform. We believe that these advances can significantly improve the effectiveness of the next generation of retinal prostheses.

Computer-assisted single-stage cranioplasty.

Cranioplasty treats and repairs cranial defects with a custom craniofacial implant (CCI). Typically, surgeons know the defect size prior to surgery. Recent efforts consider single-stage cranioplasty-performing the bony resection and fixating the CCI in a single operation. This paper develops a computer-assisted technique to perform single-stage cranioplasty. Intraoperatively, the surgeon traces the bony resection. The outline of the bony cuts is projected on a preoperatively-designed CCI to guide the surgeon during the resizing. A cadaveric case study showed good fit with minimal gaps between the implant and remaining skull. Moreover, the procedure reduced the time to resize the implant by an order of magnitude compared to manual resizing without the use of the computer-assisted technique. This approach represents the next step in quickly, effectively, and robustly performing single-stage CCI to treat craniofacial defects.

Effects of tools inserted through snake-like surgical manipulators.

Snake-like manipulators with a large, open lumen can offer improved treatment alternatives for minimally-and less-invasive surgeries. In these procedures, surgeons use the manipulator to introduce and control flexible tools in the surgical environment. This paper describes a predictive algorithm for estimating manipulator configuration given tip position for nonconstant curvature, cable-driven manipulators using energy minimization. During experimental bending of the manipulator with and without a tool inserted in its lumen, images were recorded from an overhead camera in conjunction with actuation cable tension and length. To investigate the accuracy, the estimated manipulator configuration from the model and the ground-truth configuration measured from the image were compared. Additional analysis focused on the response differences for the manipulator with and without a tool inserted through the lumen. Results indicate that the energy minimization model predicts manipulator configuration with an error of 0.24 ± 0.22mm without tools in the lumen and 0.24 ± 0.19mm with tools in the lumen (no significant difference, p = 0.81). Moreover, tools did not introduce noticeable perturbations in the manipulator trajectory; however, there was an increase in requisite force required to reach a configuration. These results support the use of the proposed estimation method for calculating the shape of the manipulator with an tool inserted in its lumen when an accuracy range of at least 1mm is required.

Multiscale modeling of double-helical DNA and RNA: a unification through Lie groups.

Several different mechanical models of double-helical nucleic-acid structures that have been presented in the literature are reviewed here together with a new analysis method that provides a reconciliation between these disparate models. In all cases, terminology and basic results from the theory of Lie groups are used to describe rigid-body motions in a coordinate-free way, and when necessary, coordinates are introduced in a way in which simple equations result. We consider double-helical DNAs and RNAs which, in their unstressed referential state, have backbones that are either straight, slightly precurved, or bent by the action of a protein or other bound molecule. At the coarsest level, we consider worm-like chains with anisotropic bending stiffness. Then, we show how bi-rod models converge to this for sufficiently long filament lengths. At a finer level, we examine elastic networks of rigid bases and show how these relate to the coarser models. Finally, we show how results from molecular dynamics simulation at full atomic resolution (which is the finest scale considered here) and AFM experimental measurements (which is at the coarsest scale) relate to these models.

Promoting self-efficacy in minimally invasive surgery training.

Many surgeons continue to actively pursue surgical approaches that are less invasive for their patients. This pursuit requires the surgeon to adapt to new instruments, techniques, technologies, knowledge bases, visual perspectives, and motor skills, among other changes. The premise of this paper is that surgeons adopting minimally invasive approaches are particularly obligated to maintain an accurate perception of their own competencies and learning needs in these areas (ie, self-efficacy). The psychological literature on the topic of self-efficacy is vast and provides valuable information that can help assure that an individual develops and maintains accurate self-efficacy beliefs. The current paper briefly summarizes the practical implications of psychological research on self-efficacy for minimally invasive surgery training. Specific approaches to training and the provision of feedback are described in relation to potential types of discrepancies that may exist between perceived and actual efficacy.