AR visualizations in laparoscopy: surgeon preferences and depth assessment of vascular anatomy.

Introduction: This study compares five augmented reality (AR) vasculature visualization techniques in a mixed-reality laparoscopy simulator with 50 medical professionals and analyzes their impact on the surgeon. Material and methods: ​​The different visualization techniques' abilities to convey depth were measured using the participant's accuracy in an objective depth sorting task. Demographic data and subjective measures, such as the preference of each AR visualization technique and potential application areas, were collected with questionnaires. Results: Despite measuring differences in objective measurements across the visualization techniques, they were not statistically significant. In the subjective measures, however, 55% of the participants rated visualization technique II, 'Opaque with single-color Fresnel highlights', as their favorite. Participants felt that AR could be useful for various surgeries, especially complex surgeries (100%). Almost all participants agreed that AR could potentially improve surgical parameters, such as patient safety (88%), complication rate (84%), and identifying risk structures (96%). Conclusions: More studies are needed on the effect of different visualizations on task performance, as well as more sophisticated and effective visualization techniques for the operating room. With the findings of this study, we encourage the development of new study setups to advance surgical AR.

Phantom study on surgical performance in augmented reality laparoscopy.

PURPOSE: Only a few studies have evaluated Augmented Reality (AR) in in vivo simulations compared to traditional laparoscopy; further research is especially needed regarding the most effective AR visualization technique. This pilot study aims to determine, under controlled conditions on a 3D-printed phantom, whether an AR laparoscope improves surgical outcomes over conventional laparoscopy without augmentation. METHODS: We selected six surgical residents at a similar level of training and had them perform a laparoscopic task. The participants repeated the experiment three times, using different 3D phantoms and visualizations: Floating AR, Occlusion AR, and without any AR visualization (Control). Surgical performance was determined using objective measurements. Subjective measures, such as task load and potential application areas, were collected with questionnaires. RESULTS: Differences in operative time, total touching time, and SurgTLX scores showed no statistical significance ([Formula: see text]). However, when assessing the invasiveness of the simulated intervention, the comparison revealed a statistically significant difference ([Formula: see text]). Participants felt AR could be useful for various surgeries, especially for liver, sigmoid, and pancreatic resections (100%). Almost all participants agreed that AR could potentially lead to improved surgical parameters, such as operative time (83%), complication rate (83%), and identifying risk structures (83%). CONCLUSION: According to our results, AR may have great potential in visceral surgery and based on the objective measures of the study, may improve surgeons' performance in terms of an atraumatic approach. In this pilot study, participants consistently took more time to complete the task, had more contact with the vascular tree, were significantly more invasive, and scored higher on the SurgTLX survey than with AR.

Local Shape Preserving Deformations for Augmented Reality Assisted Laparoscopic Surgery.

Image registration is a commonly required task in computer assisted surgical procedures. Existing registration methods in laparoscopic navigation systems suffer from several constraints, such as lack of deformation compensation. The proposed algorithm aims to provide the surgeons with updated navigational information about the deep-seated anatomy, which considers the continuous deformations in the operating environment. We extended an initial rigid registration to a shape-preserving deformable registration pathway by incorporating user interaction and an iterative mesh editing scheme which preserves local details. The proposed deformable registration workflow was tested with phantom and animal trial datasets. A qualitative evaluation based on expert feedback demonstrated satisfactory outcome, and an commensurate execution efficiency was achieved. The improvements offered by the method, couples with its relatively easy implementation, makes it an attractive method for adoption in future pre-clinical and clinical applications of augmented reality assisted surgeries.

Shear Wave Elastography Reveals a High Prevalence of NAFLD-related Fibrosis even in Type 1 Diabetes.

BACKGROUND: The association between type 2 diabetes mellitus (T2DM) and advanced stages of non-alcoholic fatty liver disease is well known. Some studies indicate a relevant prevalence also in type 1 diabetes mellitus (T1DM), but so far there is only limited data. OBJECTIVE: To determine the prevalence of non-alcoholic fatty liver disease (NAFLD)-related liver fibrosis in individuals with T1DM and compare to those with type 2 diabetes. METHODS: Diabetic patients from a single diabetes care centre were screened for liver fibrosis by sonographic shear wave elastography (SWE). In addition, all patients received laboratory evaluation including non-alcoholic fatty liver fibrosis score and Fibrosis-4 Index. RESULTS: Three hundred and forty patients were included in the study, of these, 310 received SWE. Overall 254 patients (93 with type 1 and 161 with type 2 diabetes) had reliable measurements and were included in the final analysis. In patients with type 1 diabetes, the prevalence of NAFLD-related liver fibrosis was 16-21%, depending on the method of detection. Significant liver fibrosis was observed in 30-46% of patients with type 2 diabetes. CONCLUSIONS: Our data revealed an unexpectedly high prevalence of NAFLD-related liver fibrosis in patients with type 1 diabetes. To our knowledge, this is one of the first studies using SWE to diagnose advanced NAFLD in type 1 diabetes in a non-preselected cohort. Considering the findings of our study, regular screening for hepatic complications must be recommended for all diabetic patients, even for those with type 1 diabetes.

Pose-Dependent Weights and Domain Randomization for Fully Automatic X-Ray to CT Registration.

Fully automatic X-ray to CT registration requires a solid initialization to provide an initial alignment within the capture range of existing intensity-based registrations. This work addresses that need by providing a novel automatic initialization, which enables end to end registration. First, a neural network is trained once to detect a set of anatomical landmarks on simulated X-rays. A domain randomization scheme is proposed to enable the network to overcome the challenge of being trained purely on simulated data and run inference on real X-rays. Then, for each patient CT, a fully-automatic patient-specific landmark extraction scheme is used. It is based on backprojecting and clustering the previously trained network's predictions on a set of simulated X-rays. Next, the network is retrained to detect the new landmarks. Finally the combination of network and 3D landmark locations is used to compute the initialization using a perspective-n-point algorithm. During the computation of the pose, a weighting scheme is introduced to incorporate the confidence of the network in detecting the landmarks. The algorithm is evaluated on the pelvis using both real and simulated x-rays. The mean (± standard deviation) target registration error in millimetres is 4.1 ± 4.3 for simulated X-rays with a success rate of 92% and 4.2 ± 3.9 for real X-rays with a success rate of 86.8%, where a success is defined as a translation error of less than 30 mm .

Automatic intraoperative optical coherence tomography positioning.

PURPOSE: Intraoperative optical coherence tomography (iOCT) was recently introduced as a new modality for ophthalmic surgeries. It provides real-time cross-sectional information at a very high resolution. However, properly positioning the scan location during surgery is cumbersome and time-consuming, as a surgeon needs both his hands for surgery. The goal of the present study is to present a method to automatically position an iOCT scan on an anatomy of interest in the context of anterior segment surgeries. METHODS: First, a voice recognition algorithm using a context-free grammar is used to obtain the desired pose from the surgeon. Then, the limbus circle is detected in the microscope image and the iOCT scan is placed accordingly in the X-Y plane. Next, an iOCT sweep in Z direction is conducted and the scan is placed to centre the topmost structure. Finally, the position is fine-tuned using semantic segmentation and a rule-based system. RESULTS: The logic to position the scan location on various anatomies was evaluated on ex vivo porcine eyes (10 eyes for corneal apex and 7 eyes for cornea, sclera and iris). The mean euclidean distances (± standard deviation) was 76.7 (± 59.2) pixels and 0.298 (± 0.229) mm. The mean execution time (± standard deviation) in seconds for the four anatomies was 15 (± 1.2). The scans have a size of 1024 by 1024 pixels. The method was implemented on a Carl Zeiss OPMI LUMERA 700 with RESCAN 700. CONCLUSION: The present study introduces a method to fully automatically position an iOCT scanner. Providing the possibility of changing the OCT scan location via voice commands removes the burden of manual device manipulation from surgeons. This in turn allows them to keep their focus on the surgical task at hand and therefore increase the acceptance of iOCT in the operating room.

High-resolution detection of Brownian motion for quantitative optical tweezers experiments.

We have developed an in situ method to calibrate optical tweezers experiments and simultaneously measure the size of the trapped particle or the viscosity of the surrounding fluid. The positional fluctuations of the trapped particle are recorded with a high-bandwidth photodetector. We compute the mean-square displacement, as well as the velocity autocorrelation function of the sphere, and compare it to the theory of Brownian motion including hydrodynamic memory effects. A careful measurement and analysis of the time scales characterizing the dynamics of the harmonically bound sphere fluctuating in a viscous medium directly yields all relevant parameters. Finally, we test the method for different optical trap strengths, with different bead sizes and in different fluids, and we find excellent agreement with the values provided by the manufacturers. The proposed approach overcomes the most commonly encountered limitations in precision when analyzing the power spectrum of position fluctuations in the region around the corner frequency. These low frequencies are usually prone to errors due to drift, limitations in the detection, and trap linearity as well as short acquisition times resulting in poor statistics. Furthermore, the strategy can be generalized to Brownian motion in more complex environments, provided the adequate theories are available.

Resonances arising from hydrodynamic memory in Brownian motion.

Observation of the Brownian motion of a small probe interacting with its environment provides one of the main strategies for characterizing soft matter. Essentially, two counteracting forces govern the motion of the Brownian particle. First, the particle is driven by rapid collisions with the surrounding solvent molecules, referred to as thermal noise. Second, the friction between the particle and the viscous solvent damps its motion. Conventionally, the thermal force is assumed to be random and characterized by a Gaussian white noise spectrum. The friction is assumed to be given by the Stokes drag, suggesting that motion is overdamped at long times in particle tracking experiments, when inertia becomes negligible. However, as the particle receives momentum from the fluctuating fluid molecules, it also displaces the fluid in its immediate vicinity. The entrained fluid acts back on the particle and gives rise to long-range correlations. This hydrodynamic 'memory' translates to thermal forces, which have a coloured, that is, non-white, noise spectrum. One hundred years after Perrin's pioneering experiments on Brownian motion, direct experimental observation of this colour is still elusive. Here we measure the spectrum of thermal noise by confining the Brownian fluctuations of a microsphere in a strong optical trap. We show that hydrodynamic correlations result in a resonant peak in the power spectral density of the sphere's positional fluctuations, in strong contrast to overdamped systems. Furthermore, we demonstrate different strategies to achieve peak amplification. By analogy with microcantilever-based sensors, our results reveal that the particle-fluid-trap system can be considered a nanomechanical resonator in which the intrinsic hydrodynamic backflow enhances resonance. Therefore, instead of being treated as a disturbance, details in thermal noise could be exploited for the development of new types of sensor and particle-based assay in lab-on-a-chip applications.