Optimal Target Point Research Articles

Динамика маркеров ангиогенеза у пациентов с облитерирующим атеросклерозом после оперативного лечения

INTRODUCTION: The processes of regulation of blood circulation in any organism are in constant dynamic interaction due to the systems of pro- and anti-angiogenesis. The main proangiogenic factors include HIF1a, VEGF, PDGF. Depending on the concentration of these factors in the blood serum, it is possible to make an assumption about the activity of the angiogenesis system in the patient and assess the degree of its activity. AIM: To evaluate the activity of neoangiogenesis in the postoperative period in patients with obliterating atherosclerosis of the arteries of the lower extremities. MATERIALS AND METHODS: The study included data from 40 patients with obliterating atherosclerosis, who had a clinic picture of critical ischemia of the lower extremities, who underwent direct open revascularization operations. The content of HIF1a, VEGF and PDGF was evaluated in the pre- and early postoperative periods, and further during 1 year of monitoring. RESULTS: The HIF1a index from the initial 0.52 ng/ml in the early postoperative period decreased to 0.381 ng/ml (decrease by 27%, p = 0.004), in 1 month and 6 months of monitoring its concentration practically did not change (0.41 ng/ml in 1 month (p = 0.004), 0.398 ng/ml by 6 months (p = 0.003)), and the tendency to recovery was outlined only by 1 year of monitoring (0.495 ng/ml). The concentration of VEGF was initially 728 pg/ml, the decrease in its concentration was observed more smoothly and reached a minimum by 1 month of monitoring (552.2 pg/ml for 5–7 days and 480.7 pg/ml by 1 month (p = 0.025)). Further, during the monitoring, the concentration of VEGF increased by 6 months (529.8 pg/ml) and by 1 year of monitoring (515 pg/ml). Initially PDGF was 3563.8 pg/ml, and the most marked decrease in its concentration to 2922.5 pg/ml was observed already on the 5th–7th days after surgery (p = 0.043). Then the concentration of PDGF increased by 1 month of monitoring (3254.3 pg/ml) and remained at the same level (3270 pg/ml by 1 year), still not reaching the initial preoperative values. CONCLUSION: The maximum decrease in the concentration of proangiogenic factors was detected in the early postoperative period, which indicates a low activity of angiogenesis in this time interval and is the optimal time target point for the use of therapeutic angiogenesis techniques.

An Improved Algorithm for Complete Coverage Path Planning Based on Biologically Inspired Neural Network

Complete coverage path planning (CCPP) requires the mobile robots to traverse every part of the workspace, which is one of the major challenges in cleaning robots and many other robotic systems. The biologically inspired neural network (BINN) algorithm has been extensively applied in path planning, recently. In this paper, a new CCPP strategy with biologically inspired neural network is proposed. The planned path of cleaning robot is not only determined by the dynamic neural activities, but also by the distribution of obstacles in the environmental map. By distinguishing the connectivity between different areas of the environmental map, and using the proposed path backtracking algorithm, the improved CCPP algorithm can autonomously plan a collision-free path and reduce the path repetition ratio. Besides, an improved dynamic deadlock escape algorithm is presented to select the optimal escape target point. The simulation results show that the proposed CCPP algorithm without any templates or learning procedures is able to generate an orderly path in both known and unknown environment.

System Delays and Target Points: An Analysis of the ST-elevation MI Response Programme in a Single Centre

Background: The goal in the treatment of ST-elevation MI (STEMI) is prompt revascularisation. This study aims to assess system delays and identify optimal target points within each step of the response program. Methods: This study included adults aged >19 years enrolled in the acute MI (AMI) registry due to STEMI and treated with emergency percutaneous coronary intervention (PCI) between January 2019 and June 2021. Door-to-balloon times and STEMI diagnosis-to-wire cross times were divided into Met and Unmet groups, and time frames were compared using the Mann–Whitney U-test. For time frames with no significant difference, the median of the Met group was adopted, whereas, for significantly different time frames, the optimal target points were chosen from the highest percentages of Met if the value was less than or equal to the target point and Unmet if the value was greater than the target point. ORs with 95% CIs from binary logistic regression were calculated to predict the Met status. Results: In all, 113 participants were analysed. Significant delays were observed in ECG to paging (p≤0.034), cardiology fellow on duty (CFOD) arrival to STEMI diagnosis (p=0.008), STEMI diagnosis to consent (p≤0.001), consent to cath lab (p≤0.001) and cath lab to puncture (p=0.003). The optimal targets in minutes were as follows: door to ECG (≤9 median), ECG to paging (≤1, OR 2.19, p=0.069), paging to CFOD arrival (≤2 median), CFOD arrival to STEMI diagnosis (≤3, OR 2.15, p=0.086), STEMI diagnosis to consent (≤10, OR 7.57, p≤0.001), consent to cath lab (≤24, OR 15.38, p≤0.001), cath lab to puncture (≤12, OR 2.68, p≤0.043). Conclusion: In a developing country and during the COVID-19 pandemic, the most significant delays in our STEMI programme occurred in obtaining consent for emergency PCI and transferring patients to the cath lab. Optimal target points for each time frame can provide concrete objectives that may increase the likelihood of achieving door-to-balloon time and STEMI diagnosis to wire cross goals.

Global path guided vehicle obstacle avoidance path planning with artificial potential field method

AbstractAn artificial potential field method based on global path guidance (G‐APF) is proposed for target unreachability and local minima problems of the conventional artificial potential field (APF) method in complex environments with dynamic obstacles. First, for the target unreachability problem, the global path attraction is added to the APF; second, an obstacle detection optimisation method is proposed and the optimal virtual target point is selected by setting the evaluation function to improve the local minima problem; finally, based on the obstacle detection optimisation method, the gravitational and repulsive processes are improved so that the path can pass through the narrow channel smoothly and remain collision‐free. Experiments show that the method optimises 40.8% of the total path corners, reduces 81.8% of the number of path oscillations, and shortens 4.3% of the path length in Map 1. It can be applied to the vehicle obstacle avoidance path planning problem in complex environments with dynamic obstacles.

System delays and target points: analysis of STEMI response program a single center

Abstract Funding Acknowledgements Type of funding sources: None. Introduction STEMI carries the highest risk among the AMI and the mortality is influenced by many factors. Hospital delays are the most easily audited and should be analyzed and improved. Methodology Participants were adults aged > 19 years enrolled in the AMI registry due to STEMI and treated with emergency PCI from January 2019 to June 2021. The door-to-balloon times and STEMI diagnosis-to-wire cross times were divided into Met and Unmet groups and time frames were compared using the Mann Whitney U test. For time frames with no significant difference, the median of the Met group was adopted while in time frames with a significant difference, the optimal target points were chosen from the highest percentages of Met if ≤ and Unmet if > the target point. Odds ratio (OR) with 95% confidence intervals from binary logistic regression were done to predict the Met status. Results A total of 113 participants were analyzed. Significant delays were seen in ECG-Paging (p=<0.034), CFOD arrival-to-STEMI diagnosis (p=0.008), STEMI diagnosis-to-consent (p= <0.001), consent-to-Cath lab (p=<0.001) and Cath lab-to-puncture (p=0.003). The optimal targets in minutes: Door-ECG (median 9), ECG-Paging (≤1/>, 56.67%, 62.65%, OR 2.19, p=0.069), paging-to-CFOD arrival (median <2), CFOD arrival-to-STEMI diagnosis ( ≤/>3, 66.67%, 51.81% OR 2.15, p=0.086), STEMI diagnosis-to-consent (≤/>10, 78.26%, 67.78%, OR 7.57, p=<0.001), consent-to-Cath lab (≤/>24, 73.91%, 67.78%, OR 15.38, p=<0.001), Cath lab-to-puncture (≤/>12, 65.22%, 58.89%, OR 2.68, p=<0.043). Conclusion In a developing country and during the COVID-19 pandemic, the most significant delays of our STEMI program occurred in obtaining consent for emergency percutaneous coronary intervention and transferring the patient to the catheterization laboratory. Optimal target points for every time frame can provide concrete objectives that may increase the chance of achieving the door-to-balloon and STEMI diagnosis-to-wire cross goals.

Hierarchical framework for mobile robots to effectively and autonomously explore unknown environments

Achieving efficient and safe autonomous exploration in unknown environments is an urgent challenge to be overcome in the field of robotics. Existing exploration methods based on random and greedy strategies cannot ensure that the robot moves to the unknown area as much as possible, and the exploration efficiency is not high. In addition, because the robot is located in an unknown environment, the robot cannot obtain enough information to process the surrounding environment and cannot guarantee absolute safety. To improve the efficiency and safety of exploring unknown environments, we propose an autonomous exploration motion planning framework that is divided into the exploration and obstacle avoidance levels. The two levels are independent and interconnected. The exploration level finds the optimal frontier target point in the global scope based on the forward filtering angle and cost function, attracting the robot to move to the unknown area as much as possible, and improving the exploration efficiency; the obstacle avoidance level establishes a scenario-speed conversion mechanism, and the target point and obstacle information are weighed to realise dynamic motion planning and completes obstacle avoidance control, and ensures the safety of exploration. Experiments in different simulation scenarios and real environments verify the superiority of the method. Results show that our method is superior to the existing methods.

Autonomous Exploration of Mobile Robots via Deep Reinforcement Learning Based on Spatiotemporal Information on Graph

In this paper, we address the problem of autonomous exploration in unknown environments for ground mobile robots with deep reinforcement learning (DRL). To effectively explore unknown environments, we construct an exploration graph considering historical trajectories, frontier waypoints, landmarks, and obstacles. Meanwhile, to take full advantage of the spatiotemporal feature and historical information in the autonomous exploration task, we propose a novel network called Spatiotemporal Neural Network on Graph (Graph-STNN). Specifically, the proposed Graph-STNN extracts the spatial feature using graph convolutional network (GCN) and the temporal feature using temporal convolutional network (TCN). Then, gated recurrent unit (GRU) is performed to synthesize the spatial feature, the temporal feature, and the historical state information into the current state feature. Combined with DRL, our Graph-STNN helps estimation of the optimal target point through extracted hybrid features. The simulation experiment shows that our approach is more effective than the GCN-based approach and the information entropy-based approach. Moreover, Graph-STNN also performs better generalization ability than GCN-based, information entropy-based, and random methods. Finally, we validate our approach on the simulation platform Stage with the actual robot model.

Image-Guided Transcranial Doppler Ultrasound for Monitoring Posthemorrhagic Vasospasms of Infratentorial Arteries: A Feasibility Study

A considerable number of patients with subarachnoid hemorrhage (SAH) develop vasospasms of the infratentorial arteries. Transcranial Doppler sonography (TCD) is used to screen for vasospasm. In this study, we used a technical modification that combines TCD with an image guidance device that the operator can use to navigate to the ultrasonic window and to predefined intracranial vascular targets. Our aim was to analyze the feasibility, spatial precision, and spatial reproducibility of serial image-guided TCD of infratentorial and-for comparison-supratentorial arteries in the clinical setting of monitoring for vasospasm after SAH. The study included 10 SAH patients, who each received 5 serial image-guided TCD examinations. Using computed tomography angiography data, trajectories to the infratentorial and supratentorial cerebral arteries were planned and loaded into an image guidance device tracking the Doppler probe. As a measure of spatial precision and spatial reproducibility, we analyzed the distances between the positions of preplanned vascular targets and optimal Doppler signals. The mean distance between preplanned and optimal target points was 4.8 ± 2.1 mm (first exam), indicating high spatial precision. The spatial precision decreased with increasing depth of the vascular target. In all patients, image-guided TCD detected all predefined supratentorial and infratentorial vascular segments. There were no significant changes in spatial precision in serial exams, indicating high reproducibility. Image-guided TCD is feasible for supratentorial and infratentorial arteries. It shows high spatial precision and reproducibility. This study provides a basis for future clinical studies on image-guided TCD for post-SAH vasospasm screening.

Model Predictive Sliding Control for Finite-Time Three-Axis Spacecraft Attitude Tracking

This paper deals with the robust optimal three-axis attitude tracking problem of spacecrafts. To this aim, the exceptional features of two advanced control approaches, i.e., nonlinear terminal sliding mode control (TSMC) and linear model predictive control (MPC), are combined in a compound double layer structure. The proposed approach addresses the global stability and robust attitude tracking of near-polar orbit spacecrafts actuated by a set of reaction wheels and subject to unknown disturbances, uncertainties, and actuators’ saturation. The TSMC controller is designed to guarantee the robust three-axis attitude tracking goal in the presence of disturbances and uncertainties provided that proper target points are available. The next part of the compound controller takes the advantages of the MPC technique (i.e., preknown attitude maneuvers and constraints) into account to provide the required optimal target points for the lower level TSMC controller. Despite the fact that the spacecraft has nonlinear nature, we have analytically derived conditions under which the actuators’ constraints satisfaction is guaranteed a priori . Finally, a set of simulation results are provided to illustrate the effectiveness and performance of the proposed method.

P31 Optimising trajectories in computer assisted planning for cranial laser interstitial thermal therapy: a machine learning approach

ObjectivesOptimal trajectory planning for cranial laser interstitial thermal therapy (cLITT) in drug resistant focal mesial temporal lobe epilepsy (MTLE).DesignA composite ablation score of ablated AHC minus ablated PHG volumes were calculated and normalised. Random forest and linear regression were implemented to predict composite ablation scores and determine the optimal entry and target point combinations to maximize this.SubjectsTen patients with hippocampal sclerosis were included.MethodsComputer Assisted Planning (CAP) cLITT trajectories were generated using entry regions that include the inferior occipital gyri (IOG), middle occipital gyri (MOG), inferior temporal gyri (ITG) and middle temporal gyri (MTG). Target points were varied by sequential erosions and transformations of the centroid of the amygdala. In total 760 trajectory combinations were generated per patient and ablation volumes were calculated based on a conservative 15 mm maximum ablation diameter.ResultsLinear regression was superior to random forest predictions. Linear regression indicated that maximal composite ablation scores were associated with entry points that clustered around the junction of the IOG, MOG and MTG. The optimal target point was a translation of the centroid of the amygdala anteriorly and medially.ConclusionsMachine learning techniques accurately predict composite ablation scores with linear regression outperforming the random forest approach. Optimal CAP entry points for cLITT maximize ablation of the AHC and spare the PHG.

Finger-vein pattern restoration with Direction-Variance-Boundary Constraint Search

Finger-vein verification is an emerging biometrics technology. Its first task is extracting finger-vein patterns. Although existing algorithms can extract most finger-vein patterns robustly, some branch of these patterns always breaks, which leads to adverse effects for features extraction and matching. In this paper, a Direction-Variance-Boundary Constraint Search (DVBCS) model is presented to restore the broken finger-vein patterns. At the beginning, endpoints of broken finger-vein branches are located. Then, a direction constraint for searching candidate point set is demonstrated. Following the second stage, an optimal target point is selected from the candidate point set according to a minimum within-cluster variance criterion. Eventually, the boundary constraint and variance constraint are introduced as the termination conditions. Experimental results illustrate that, while maintaining low segmentation error, the proposed method can restore above 10% lost target points. Moreover, the equal error rate of finger-vein recognition is reduced from 0.57% to 0.29% when using the proposed method to restore finger-vein patterns.

Mean reverting financial leverage: theory and evidence from Pakistan

Grounding concepts of the two competing theories of capital structure (trade-off theory, pecking order theory) are quite opposite to each other. Trade-off theory claims that there is an optimal (target) capital structure and firms try to achieve that optimal (target) point. Whereas pecking order theory argues that there is no optimal (target) capital structure but the firms follow a specific pattern of financing. Using the two competing theoretic frameworks, this study applies Fisher-type panel unit root test to an unbalanced panel data of 13 115 firm-year observations of nonfinancial firms listed on Karachi Stock Exchange Pakistan spread over 38 years (1973–2010). Overall panel test results, for short-term, long-term, as well as total leverage support trade-off financing behaviour while individual firm results do not. Individual firm results show that only 16% of the firms have short-term target, 25% of the firms have long-term target and 12% of the firms have total target leverage ratio. Further, industry results explain that most of the industries do have target leverage ratios and classification of data into profitable and lossmaking firm-year observations explains that profitable firms clearly follow trade-off financing behaviour while the results for lossmaking firms do not support trade-off financing behaviour. Our study indicates that it is important for the government to ensure policies to develop well-balanced financial markets and to improve accountability systems.

Fast optimal aggregate point search for a merged set on road networks

Aggregate nearest neighbor query, which returns an optimal target point that minimizes the aggregate distance for a given query point set, is one of the most important operations in spatial databases and their application domains. This paper addresses the problem of finding the aggregate nearest neighbor for a merged set that consists of the given query point set and multiple points needed to be selected from a candidate set, which we name as merged aggregate nearest neighbor(MANN) query. This paper proposes two algorithms to process MANN query on road networks when aggregate function is max. Then, we extend the algorithms to support other aggregate functions (e.g., sum). Extensive experiments are conducted to examine the behaviors of the solutions in terms of five parameters affecting the performance. The overall experiments show that our strategies to minimize the response time are effective.

Single training session for first time pelvic C-clamp users: Correct pin placement and frame assembly

BackgroundUnstable pelvic fractures with associated haemodynamic instability are major contributors of mortality and morbidity after blunt trauma. The pelvic C-clamp is one of the methods for emergency skeletal stabilization for pelvic ring injuries with posterior instability. The application of this device is taught on courses, but it is seldom used. The safety and efficiency of C-clamp application by trained first time users is unknown. We hypothesised that the pelvic C-clamp cannot be safely positioned on a training model after one training session. Methods and materialsA theoretical and a practical session on the application of the pelvic C-clamp was held within an interval of 11.2±4.4. Twenty-seven participants of various levels of training were assessed on accuracy and efficacy of the application of the pelvic C-clamp was applied to a pelvic model (Pelvic Trainer™). Results70.4% of all participants were able to place both pins inside the safe zone, whilst 81.5% of all pins were positioned safe. 18.5% were considered to be in unsafe position. The distance to optimal target point was 9.6±7.8mm on the left (injured) hemipelvis and 8.7±7.8mm on the right (uninjured). The time needed for assembly was 99.7±39.7s, for placement it averaged at 133.9±74s. ConclusionsThe majority of pins were placed into the safe zone on a training model within 4min after one training session. 18.5% dangerous pin placement within 11 days of the training requires careful consideration (risk/benefit) in the context of a critically injured dying patient.

Optimal Targets for the Bank Shot in Men's Basketball

The purpose of this study was to gain an understanding of the bank shot and ultimately determine the optimal target points on the backboard for the bank shot in men’s basketball. The study used over one million three-dimensional simulations of basketball trajectories. Four launch variables were studied: launch height, launch speed, launch angle, and aim angle. The shooter’s statistical characteristics were prescribed to yield a 70 percent free throw when launching the ball seven feet above the ground with 3 Hz of back spin. We found that the shooter can select a bank shot over a direct shot with as much as a 20 percent advantage. The distribution over the court of preferences of the bank shot over the direct shot was determined. It was also shown that there is an aim line on the backboard independent of the shooter’s location on the court. We also found that at 3.326 inches behind the backboard, there exists a vertical axis that aids in finding the optimal target point on the backboard. The optimal target point is the crossing of the vertical axis and the aim line that is in the shooter’s line of sight.

Feature Preserving Mesh Simplification Using Feature Sensitive Metric

We present a new method for feature preserving mesh simplification based on feature sensitive (FS) metric. Previous quadric error based approach is extended to a high-dimensional FS space so as to measure the geometric distance together with normal deviation. As the normal direction of a surface point is uniquely determined by the position in Euclidian space, we employ a two-step linear optimization scheme to efficiently derive the constrained optimal target point. We demonstrate that our algorithm can preserve features more precisely under the global geometric properties, and can naturally retain more triangular patches on the feature regions without special feature detection procedure during the simplification process. Taking the advantage of the blow-up phenomenon in FS space, we design an error weight that can produce more suitable results. We also show that Hausdorff distance is markedly reduced during FS simplification

Tremor entrainment by patterned low-frequency stimulation

High-frequency test stimulation for tremor suppression is a standard procedure for functional target localization during deep brain stimulation. This method does not work in cases where tremor vanishes intraoperatively, for example, due to general anaesthesia or due to an insertional effect. To overcome this difficulty, we developed a stimulation technique that effectively evokes tremor in a well-defined and quantifiable manner. For this, we used patterned low-frequency stimulation (PLFS), i.e. brief high-frequency pulse trains administered at pulse rates similar to neurons' preferred burst frequency. Unlike periodic single-pulse stimulation, PLFS enables one to convey effective and considerably greater integral charge densities without violation of safety requirements. In a computational investigation of an oscillatory neuronal network temporarily rendered inactive, we found that PLFS evokes synchronized activity, phase locked to the stimulus. While a stronger increase in the amount of synchrony in the neuronal population requires higher stimulus intensities, the portion of synchronously active neurons nevertheless becomes strongly phase locked to PLFS already at weak stimulus intensities. The phase entrainment effect of PLFS turned out to be robust against variations in the stimulation frequency, whereas enhancement of synchrony required precisely tuned stimulation frequencies. We applied PLFS to a patient with spinocerebellar ataxia type 2 (SCA2) with pronounced tremor that disappeared intraoperatively under general anaesthesia. In accordance with our computational results, PLFS evoked tremor, phase locked to the stimulus. In particular, weak PLFS caused low-amplitude, but strongly phase-locked tremor. PLFS test stimulations provided the only functional information about target localization. Optimal target point selection was confirmed by excellent post-operative tremor suppression.

Identification of the optimal cortical target point for extracranial–intracranial bypass surgery in patients with hemodynamic cerebrovascular insufficiency

The objective of this report is to describe a new approach to identify the optimal cortical target point for extracranial-intracranial (EC-IC) bypass surgery, to reliably find suitable recipient vessels for the anastomosis. Thirty consecutive patients (17 men and 13 women; mean age 54.6 +/- 11.79 years [+/- standard deviation]) with hemodynamic cerebrovascular insufficiency due to stenoocclusive arterial disease underwent EC-IC bypass surgery. The end of the Sylvian fissure was identified preoperatively using a specially designed template and external landmarks. At surgery, a 3-cm trephination was made, centered over the target point as determined by the template. The number, diameter, and length of the exposed cortical arteries were assessed using photographs and indocyanine green (ICG) angiograms. At least 1 recipient artery appropriate for anastomosis (>or= 1 mm) was found in every craniectomy. The mean number of suitable recipient arteries per craniotomy was 2.09 +/- 0.87, the mean diameter was 1.28 +/- 0.24 mm, and the mean length 10.83 +/- 4.87 mm. Bypass patency was confirmed by intraoperative ICG angiography, postoperative computed tomography angiography, and digital subtraction angiography, and reached 100%. Performing a 3-cm craniectomy over the described target point, reliably allows access to suitable recipient arteries for EC-IC bypass surgery.

What is the Optimal Angle of Needle Insertion in Korean Young Adult Male during Paramedian Spinal Puncture? A Radiological Study

Background: The object of this study is to offer the optimal angle of needle insertion during L3-L4 paramedian approach using simple X-ray. Methods: Twenty-five male patients were enrolled for this study. After placing a radio-opaque material (RO) on the point 1cm lateral and 1cm caudad to inferior edge of L3 spinous process in the sitting-flexion position, simple AP X-ray films in erect position and lateral films in sitting-flexion position were taken. The distance from RO (I) to the midline of vertebral column was measured on the AP film. On the lateral film, the optimal target point (T) was determined. When the real RO (I) appeared on lateral film, the point was named I'. The line perpendicular to the line tangential to skin on I' was drawn to the vertebral body. When another line perpendicular to that line was drawn from the target point (T), the two lines meet perpendicularly at the point C. Two triangles can be formed three-dimensionally with T, I', C and T, I, C. Medial insertion angle (, angle I-C-I') and cephalad insertion angle (, angle T-I-C) were calculated. Results: The mean angle of was 10.7 2.3 and was 13.9 5.0. The insertion based on the calculated angles was successfully achieved at the first trial in 24 patients and at the second in 1 patient. Conclusions: Spinal anesthesia with L3-L4 paramedian approach can be successfully performed using calculated angles measured by simple X-rays.

Computer-aided placement of deep brain stimulators: from planningto intraoperative guidance

In current practice, optimal placement of deep-brain stimulators (DBSs) used to treat movement disorders in patients with Parkinson's disease and essential tremor is an iterative procedure. A target is chosen preoperatively based on anatomical landmarks identified on magnetic resonance images. This point is used as an initial position that is refined intraoperatively using both microelectrode recordings and macrostimulation. In this paper, we report on our current progress toward developing a system for the computer-assisted preoperative selection of target points and for the intraoperative adjustment of these points. The system consists of a deformable atlas of optimal target points that can be used to select automatically the preoperative target, of an electrophysiological atlas, and of an intraoperative interface. Results we have obtained show that automatic prediction of target points is an achievable goal. Our results also indicate that electrophysiological information could be used to resolve structures not visible in anatomic images, thus improving both preoperative and intraoperative guidance. Our intraoperative system has reached the stage of a working prototype and we compare targeting accuracy as well as the number of paths needed to reach the targets with our system and with the method in current clinical use.