TAToo: vision-based joint tracking of anatomy and tool for skull-base surgery.

PURPOSE: Tracking the 3D motion of the surgical tool and the patient anatomy is a fundamental requirement for computer-assisted skull-base surgery. The estimated motion can be used both for intra-operative guidance and for downstream skill analysis. Recovering such motion solely from surgical videos is desirable, as it is compliant with current clinical workflows and instrumentation. METHODS: We present Tracker of Anatomy and Tool (TAToo). TAToo jointly tracks the rigid 3D motion of the patient skull and surgical drill from stereo microscopic videos. TAToo estimates motion via an iterative optimization process in an end-to-end differentiable form. For robust tracking performance, TAToo adopts a probabilistic formulation and enforces geometric constraints on the object level. RESULTS: We validate TAToo on both simulation data, where ground truth motion is available, as well as on anthropomorphic phantom data, where optical tracking provides a strong baseline. We report sub-millimeter and millimeter inter-frame tracking accuracy for skull and drill, respectively, with rotation errors below [Formula: see text]. We further illustrate how TAToo may be used in a surgical navigation setting. CONCLUSIONS: We present TAToo, which simultaneously tracks the surgical tool and the patient anatomy in skull-base surgery. TAToo directly predicts the motion from surgical videos, without the need of any markers. Our results show that the performance of TAToo compares favorably to competing approaches. Future work will include fine-tuning of our depth network to reach a 1 mm clinical accuracy goal desired for surgical applications in the skull base.

Twin-S: a digital twin for skull base surgery.

PURPOSE: Digital twins are virtual replicas of real-world objects and processes, and they have potential applications in the field of surgical procedures, such as enhancing situational awareness. We introduce Twin-S, a digital twin framework designed specifically for skull base surgeries. METHODS: Twin-S is a novel framework that combines high-precision optical tracking and real-time simulation, making it possible to integrate it into image-guided interventions. To guarantee accurate representation, Twin-S employs calibration routines to ensure that the virtual model precisely reflects all real-world processes. Twin-S models and tracks key elements of skull base surgery, including surgical tools, patient anatomy, and surgical cameras. Importantly, Twin-S mirrors real-world drilling and updates the virtual model at frame rate of 28. RESULTS: Our evaluation of Twin-S demonstrates its accuracy, with an average error of 1.39 mm during the drilling process. Our study also highlights the benefits of Twin-S, such as its ability to provide augmented surgical views derived from the continuously updated virtual model, thus offering additional situational awareness to the surgeon. CONCLUSION: We present Twin-S, a digital twin environment for skull base surgery. Twin-S captures the real-world surgical progresses and updates the virtual model in real time through the use of modern tracking technologies. Future research that integrates vision-based techniques could further increase the accuracy of Twin-S.

A force-sensing surgical drill for real-time force feedback in robotic mastoidectomy.

PURPOSE: Robotic assistance in otologic surgery can reduce the task load of operating surgeons during the removal of bone around the critical structures in the lateral skull base. However, safe deployment into the anatomical passageways necessitates the development of advanced sensing capabilities to actively limit the interaction forces between the surgical tools and critical anatomy. METHODS: We introduce a surgical drill equipped with a force sensor that is capable of measuring accurate tool-tissue interaction forces to enable force control and feedback to surgeons. The design, calibration and validation of the force-sensing surgical drill mounted on a cooperatively controlled surgical robot are described in this work. RESULTS: The force measurements on the tip of the surgical drill are validated with raw-egg drilling experiments, where a force sensor mounted below the egg serves as ground truth. The average root mean square error for points and path drilling experiments is 41.7 (± 12.2) mN and 48.3 (± 13.7) mN, respectively. CONCLUSION: The force-sensing prototype measures forces with sub-millinewton resolution and the results demonstrate that the calibrated force-sensing drill generates accurate force measurements with minimal error compared to the measured drill forces. The development of such sensing capabilities is crucial for the safe use of robotic systems in a clinical context.

Design and Fabrication of a Fiber Bragg Grating Shape Sensor for Shape Reconstruction of a Continuum Manipulator.

Continuum dexterous manipulators (CDMs) are suitable for performing tasks in a constrained environment due to their high dexterity and maneuverability. Despite the inherent advantages of CDMs in minimally invasive surgery, real-time control of CDMs' shape during nonconstant curvature bending is still challenging. This study presents a novel approach for the design and fabrication of a large deflection fiber Bragg grating (FBG) shape sensor embedded within the lumens inside the walls of a CDM with a large instrument channel. The shape sensor consisted of two fibers, each with three FBG nodes. A shape-sensing model was introduced to reconstruct the centerline of the CDM based on FBG wavelengths. Different experiments, including shape sensor tests and CDM shape reconstruction tests, were conducted to assess the overall accuracy of the shape-sensing. The FBG sensor evaluation results revealed the linear curvature-wavelength relationship with the large curvature detection of 0.045 mm and a high wavelength shift of up to 5.50 nm at a 90° bending angle in both the bending directions. The CDM's shape reconstruction experiments in a free environment demonstrated the shape-tracking accuracy of 0.216 ± 0.126 mm for positive/negative deflections. Also, the CDM shape reconstruction error for three cases of bending with obstacles was observed to be 0.436 ± 0.370 mm for the proximal case, 0.485 ± 0.418 mm for the middle case, and 0.312 ± 0.261 mm for the distal case. This study indicates the adequate performance of the FBG sensor and the effectiveness of the model for tracking the shape of the large-deflection CDM with nonconstant-curvature bending for minimally invasive orthopedic applications.

Crystal Face Distributions and Surface Site Densities of Two Synthetic Goethites: Implications for Adsorption Capacities as a Function of Particle Size.

Two synthetic goethites of varying crystal size distributions were analyzed by BET, conventional TEM, cryo-TEM, atomic resolution STEM and HRTEM, and electron tomography in order to determine the effects of crystal size, shape, and atomic scale surface roughness on their adsorption capacities. The two samples were determined by BET to have very different site densities based on CrVI adsorption experiments. Model specific surface areas generated from TEM observations showed that, based on size and shape, there should be little difference in their adsorption capacities. Electron tomography revealed that both samples crystallized with an asymmetric {101} tablet habit. STEM and HRTEM images showed a significant increase in atomic-scale surface roughness of the larger goethite. This difference in roughness was quantified based on measurements of relative abundances of crystal faces {101} and {201} for the two goethites, and a reactive surface site density was calculated for each goethite. Singly coordinated sites on face {210} are 2.5 more dense than on face {101}, and the larger goethite showed an average total of 36% {210} as compared to 14% for the smaller goethite. This difference explains the considerably larger adsorption capacitiy of the larger goethite vs the smaller sample and points toward the necessity of knowing the atomic scale surface structure in predicting mineral adsorption processes.