Target Error Research Articles

Evaluation of the Accuracy of 3D Printed Patient-Specific Brain Biopsy Guide Using 3D Volume Rendering Technique in Canine Cadavers

The objective of this study was to evaluate the accuracy of a CT-based, 3D-printed, patient-specific brain biopsy guide (3D-psBBG) through the application of a transfrontal approach in canine cadavers. A total of ten canine cadavers, with weights ranging from 4.36 to 14.4 kg, were subjected to preoperative CT scans to generate 3D skull models. Customized biopsy guides were created based on these models and manufactured using 3D printing technology. Twenty spinal needle insertions were performed, and the accuracy of needle placement was evaluated through both CT and 3D volume-rendering techniques. The mean needle placement error was 2.1 mm, with no significant differences observed between insertions targeting the fronto-olfactory and piriform lobes. The 3D volume-rendering method demonstrated superior accuracy compared to the CT method, with statistically significant differences in placement errors for both targets. The average time required for the design and manufacture of the guides was 249 min. These findings indicate the high accuracy and potential clinical application of CT-based 3D-psBBG for improving diagnostic outcomes in veterinary neurology.

Research on the Analysis and Optimization of Advertising Strategies on YouTube

The research presented in this paper investigates YouTube advertising and its problems and prospects with an emphasis on ad fatigue, ad-blocking tools, and targeting issues in digital advertising. The paper focuses on the aspects that might influence the effectiveness of YouTube ads based on the literature review and the case study of the YouTube channel Verdeliss. Some of the discoveries presented show that such factors as entertainment and informativeness are vital for capturing the audience’s attention, whereas ad irritation and targeting errors negatively impact the ads’ performance. Some of the strategies suggested are increasing the ad variety and relevance, refining targeting algorithms, and reducing the effects of ad blockers to enhance the return on investment (ROI) and user interaction. This study highlights the need to overcome these challenges to enhance digital advertising, especially on YouTube, so as to meet the users’ needs and firm goals. Based on these strategies, future research should endeavor to use empirical research to validate these strategies and other emerging methods of digital advertising in the dynamic online environment.

Analysis of the Grid Quantization for the Microwave Radar Coincidence Imaging Based on Basic Correlation Algorithm

In Microwave Radar Coincidence Imaging (MRCI), the imaging region is typically discretized into a fine grid. In other words, it assumes that the equivalent scatterers of the target are precisely located at the centers of these pre-discretized grids. However, this approach usually encounters the off-grid problem, which can significantly degrade the imaging performance. In this paper, to establish a criterion for grid quantization, the performance of the MRCI system related to the grid size and the distribution of imaging points is investigated. First, the discretization of the imaging scene is regarded as a random sampling problem, and the off-grid imaging model for MRCI is established. Then, the probability distribution function (PDF) of the imaging amplitude for a single point target is analyzed, and the mean first-order imaging error (MFE) for multiple point targets is derived based on the Basic Correlation Algorithm (BCA). Finally, the relationship between the grid quantization of the imaging area and the performance of the MRCI system is analyzed, providing a theoretical guidance for enhancing the performance of MRCI. The validity of the analyses is verified through simulation experiments.

In Vivo Feasibility Study: Evaluating Autonomous Data-Driven Robotic Needle Trajectory Correction in MRI-Guided Transperineal Procedures.

This study addresses the targeting challenges in MRI-guided transperineal needle placement for prostate cancer (PCa) diagnosis and treatment, a procedure where accuracy is crucial for effective outcomes. We introduce a parameter-agnostic trajectory correction approach incorporating a data-driven closed-loop strategy by radial displacement and an FBG-based shape sensing to enable autonomous needle steering. In an animal study designed to emulate clinical complexity and assess MRI compatibility through a PCa mock biopsy procedure, our approach demonstrated a significant improvement in targeting accuracy (p<0.05), with mean target error of only 2.2 ± 1.9 mm on first insertion attempts, without needle reinsertions. To the best of our knowledge, this work represents the first in vivo evaluation of robotic needle steering with FBG-sensor feedback, marking a significant step towards its clinical translation.

Eye-movement methodology reveals a shift in attention from threat to neutral stimuli with self-reported symptoms of social anxiety across children, adolescents and adults

ABSTRACT The current study used an eye-movement remote distractor paradigm (RDP) to examine the relationship between self-reported symptoms of social anxiety in children (9–11-year-olds), young adolescents (12–14-year-olds) and adults (18–43-year-olds) on saccade latencies to identify a target and saccadic errors to task irrelevant distractor (angry, neutral and happy faces). Distractors were presented simultaneously, either at the centre of the display, or at a contralateral parafoveal or peripheral location to the target. Symptoms of social anxiety in children were associated with increased saccade latencies in the presence of angry and neutral faces suggesting avoidance of these emotion expressions in this age group. Symptoms of social anxiety in adolescents and adults were respectively linked with longer latencies for neutral faces, indicating that neutral faces represent ambiguous and potentially negative stimuli for individuals with elevated social anxiety, and fit with research that has questioned the role of neutral faces as non-emotional control stimuli in attention research and anxiety.

Neyman-Pearson Multi-class Classification via Cost-sensitive Learning

Most existing classification methods aim to minimize the overall misclassification error rate. However, in applications such as loan default prediction, different types of errors can have varying consequences. To address this asymmetry issue, two popular paradigms have been developed: the Neyman-Pearson (NP) paradigm and the cost-sensitive (CS) paradigm. Previous studies on the NP paradigm have primarily focused on the binary case, while the multi-class NP problem poses a greater challenge due to its unknown feasibility. In this work, we tackle the multi-class NP problem by establishing a connection with the CS problem via strong duality and propose two algorithms. We extend the concept of NP oracle inequalities, crucial in binary classifications, to NP oracle properties in the multi-class context. Our algorithms satisfy these NP oracle properties under certain conditions. Furthermore, we develop practical algorithms to assess the feasibility and strong duality in multi-class NP problems, which can offer practitioners the landscape of a multi-class NP problem with various target error levels. Simulations and real data studies validate the effectiveness of our algorithms. To our knowledge, this is the first study to address the multi-class NP problem with theoretical guarantees. The proposed algorithms have been implemented in the R package npcs, which is available on CRAN.

Jaringan Saraf Tiruan (JST) Memprediksi Penjualan UMKM Kota Binjai dengan menggunakan Metode Backpropagation

The development of information technology that is currently developing serves to facilitate, accelerate, benefit and provide other alternatives for people who have businesses and have a big influence in the future. One of the things that is very influential is the sale of MSMEs. MSMEs are productive businesses owned by individuals or business entities that have met the criteria as micro businesses that have an important role in the economy because they provide employment, encourage local economic growth, and create innovation. MSMEs still face challenges such as limited access to financing, digital readiness, and marketing access that hinder the development of MSMEs. Therefore, it is necessary to take action to predict MSME sales in Binjai City using the backpropagation method so that later it can create new innovations and encourage community economic growth. Based on the process carried out using the backpropagation method, it can be seen that the value obtained has reached more than the predetermined target with a target value (t) of 0.26, learningrate 0.2, maximum epoch 10000 target error 0.01.

Self correction technique for amplitude and phase errors of underwater acoustic arrays based on variable decibel Bayesian inference

Abstract Direction of arrival (DOA) estimation of underwater targets is an important research direction in the field of underwater acoustic array signal processing. Due to factors such as assembly errors and component aging, amplitude and phase errors between each channel of the array are common, resulting in distortion of the array flow pattern matrix. At the same time, the non-uniform distribution of noise intensity at the positions of each array element further increases the difficulty of DOA for underwater targets. Based on the characteristics of sparse spatial distribution of underwater targets, this paper uses the flexibility of hyperparametric modeling to construct an array observation signal graph model. On this basis, the effects of amplitude and phase errors and non-uniform noise on the array model are added, and a comprehensive observation model with clear distribution types of amplitude and phase errors, signals, and noise is established. The variational Bayesian inference theory is used to obtain closed solutions of various variables and parameters, so as to achieve joint estimation of target azimuth and error parameters. Simulation results and sea trial data processing results show that the algorithm can achieve amplitude and phase error self correction while completing DOA estimation in the absence of prior information on the number of sources.

Robotic MR-guided high dose rate brachytherapy needle implantation in the prostate (ROBiNSon)—a proof-of-concept study

Objective. A robotic needle implant device for MR-guided high-dose-rate (HDR) prostate brachytherapy was developed. This study aimed to assess the feasibility and spatial accuracy of HDR brachytherapy using the robotic device, for a single intraprostatic target point. Approach. Five patients were treated from November 2019–June 2022 with the robot. The robot fits a 1.5 T MR scanner and the needle can be shifted and angulated. An intraprocedural MR scan was fused with the diagnostic MR and one preplanned needle position was selected for robotic insertion. The needle entry point and angles were set for a needle tip target point within the intraprostatic target volume. The needle was tapped stepwise towards the target point pneumatically. Final needle position was verified with MR, followed by plan optimization and dose delivery. Any remaining planned needles were inserted manually. Needle tip to geometrical target error (NTG-error) was defined as the deviation of the actual tip position relative to the predefined geometric target point, using MR-coordinates. Needle tip to treatment target error (NTT-error) was defined as the deviation of the actual tip position relative to the treatment target point, using fused MR-images pre- and post-needle implantation taking into account prostate deformation. Difference between NTT-error and NTG-error and fiducial marker shifts indicated prostate movement. For determining prostate deformation, the Jaccard index and prostate volumes were assessed. Main results. The robotic device was able to tap the needle to the planned depth for all patients. Mean robotic procedure duration was 142 min. NTG-error was 3.2 (range 1.1–6.7) mm and NTT-error 4.5 (range 2.6–9.6) mm. Marker displacements were smaller than 3 mm. No treatment-related acute toxicity was reported. Feasibility of needle placement within the prostate was considered adequate. Significance. MR-guided robotic needle insertion is feasible with a mean geometric accuracy of 3.2 mm and <3 mm prostate movement.

Detection of human movement by combining supervised machine learning and an embroidered textile capacitance sensor

This study contributes to respiratory pattern detection by introducing a fabric sensor utilizing capacitance measurement and a semi-supervised machine learning algorithm known as an AI-based autoencoder. The sensor, consisting of two embroidered electrodes composed of silver-coated conductive nylon filaments, leverages the body as a dielectric material. In the research, a garment-type respiratory sensor was employed to continuously monitor respiratory data during both static (standing) and dynamic (walking, brisk walking, running) actions. The sparse autoencoder algorithm was particularly employed for individual static and dynamic actions, effectively distinguishing respiratory patterns corresponding to various movements. In addition, the sparse autoencoder helps prevent overfitting, fundamentally minimizing errors between the compression and reconstruction of signals. The maximum number of epochs was set to 2000, and the target error was set at 0.005. All data were compared against the static walking as the training baseline. Ultimately, the root mean squared error (RMSE) between static postures averaged 0.1, while the RMSEs between dynamic actions of walking, brisk walking, and running were 0.61, 0.91, and 2.78, respectively. These results suggest that movement detection through error detection is practically feasible and possesses discernible capabilities.

Task-relevant visual feedback uncertainty attenuates visuomotor adaptation.

Motor adaptation is attenuated when sensory feedback about the movement is uncertain. Although this was initially shown for small visual errors, attenuation seems not to hold when visual errors are larger and the contributions of implicit adaptation are isolated with the error-clamp method, which makes visual feedback task-irrelevant. Here we ask whether adaptation to a similarly large perturbation is attenuated when task-relevant visual feedback is uncertain. In a first experiment, we tested participants on a 30° movement-contingent visuomotor rotation under both low (cursor) and high (cloud of moving dots) visual feedback uncertainty. In line with optimal integration, we found that the early increase in adaptation and final extent of adaptation were reduced with high feedback uncertainty. In a second experiment, we included several blocks of no-feedback trials during the perturbation block to quantify the contribution of implicit adaptation. Results showed that implicit adaptation was smaller with high compared to low feedback uncertainty throughout the perturbation block. The estimated contribution of explicit adaptation was overall small, particularly for high feedback uncertainty. Our results demonstrate an influence of task-relevant visual feedback, and the resulting target errors, on implicit adaptation. We show that our motor system is sensitive to the feedback it receives even for larger error sizes and accordingly adjusts its learning properties when our ability to achieve the task goal is affected.NEW & NOTEWORTHY Motor adaptation is linked to the estimation of our actions. Whereas uncertainty of task-irrelevant visual feedback appears not to influence implicit adaptation for errors beyond a certain size, here we tested whether this is still the case for task-relevant feedback. We show that implicit adaptation is attenuated when task-relevant visual feedback is uncertain, suggesting a dependency on the assessment of not just sensory prediction errors but also target errors.

Phantom-Enhanced High Mechanical Accuracy for Frame-Based Deep Brain Stimulation.

Deep brain stimulation (DBS) is a neurosurgical procedure that depends on high-accuracy targeting of structures to implant electrodes within the brain. The positioning of these electrodes in the brain determines the long-term efficacy of treating diseases such as Parkinson's disease, essential tremor, or dystonia.Misplaced electrodes in DBS can lead to poor efficacy and stimulation-induced side effects. Widespread targeting errors and variability have been published throughout the literature. As such,improvement in targeting accuracy is needed to enhance the quality of the procedures. A stereotactic phantom was utilized to test and adjust targeting before the surgical placement in the brain for 91 sequential electrodes.The tip of the microelectrode, the first rigid point in time, was measured and compared to the planned target.The technique utilized a to-target cannulawith an XY stage that allowed x-axis and y-axis adjustments and correction for inaccuracies relative to the phantom.A calculation was developed to convert anatomical angles (sagittal and coronal) provided by commercial planning stations to spherical angles to calculate points along a trajectory.Errorcalculations included each dimensional axis, Euclidean error, and radial error. Bends in the cannula and microelectrode were observed and corrected by referencing the phantom. All 91 first-pass tracks traversed the intended target, and three electrodes required a second mapping track beyond the first penetration due to neurophysiological and intraoperative testing. The results showed overall ultra-high (0-0.5 mm) to high (>0.5-1 mm) accuracy, an average Euclidean error of 0.66±0.30 mm, and a radial error of 0.45±0.28 mm with dimensional errors of less than 0.5 mm per axis. The utilization of a stereotactic phantom is an important tool to enhance the stereotactic targeting before insertion into the brain. This phantom technique yielded ultra-high to high accuracy in error calculations.Future methods and studies shouldfocus on error minimization to enhance these DBS mechanical accuracy and correlations with clinical outcomes.

Precise Motion Compensation of Multi-Rotor UAV-Borne SAR Based on Improved PTA

In recent years, with the miniaturization of high-precision position and orientation systems (POS), precise motion errors during SAR data collection can be calculated based on high-precision POS. However, compensating for these errors remains a significant challenge for multi-rotor UAV-borne SAR systems. Compared with large aircrafts, multi-rotor UAVs are lighter, slower, have more complex flight trajectories, and have larger squint angles, which result in significant differences in motion errors between building targets and ground targets. If the motion compensation is based on ground elevation, the motion error of the ground target will be fully compensated, but the building target will still have a large residual error; as a result, although the ground targets can be well-focused, the building targets may be severely defocused. Therefore, it is necessary to further compensate for the residual motion error of building targets based on the actual elevation on the SAR image. However, uncompensated errors will affect the time–frequency relationship; furthermore, the ω-k algorithm will further change these errors, resulting in errors in SAR images becoming even more complex and difficult to compensate for. To solve this problem, this paper proposes a novel improved precise topography and aperture-dependent (PTA) method that can precisely compensate for motion errors in the UAV-borne SAR system. After motion compensation and imaging processing based on ground elevation, a secondary focus is applied to defocused buildings. The improved PTA fully considers the coupling of the residual error with the time–frequency relationship and ω-k algorithm, and the precise errors in the two-dimensional frequency domain are determined through numerical calculations without any approximations. Simulation and actual data processing verify the effectiveness of the method, and the experimental results show that the proposed method in this paper is better than the traditional method.

Identifying fish and estimating abundance and swim velocities of migrating Pacific salmon using adaptive resolution imaging sonar in mobile surveys

Abstract Mobile acoustic sounding is an effective survey method for fish abundance residing or migrating in large riverine basins and marine areas. A long-standing challenge in acoustic fish surveys with conventional sonar is the uncertainty in identifying fish targets from acquired echo data. Identification errors of fish targets can significantly bias estimates of fish abundances and negatively impact the management of fisheries. In contrast to conventional sonar, adaptive resolution imaging sonar (ARIS), if deployed properly with appropriate settings, can yield high-quality images of fish targets. ARIS images acquired with adequate frame rates can form video recordings to allow for confident identification of fish targets from recorded morphological features, sizes, direction of movements, and speeds. In this paper, we present an approach of using ARIS sonar for mobile surveys of fish passage in a riverine environment. Applications of this approach are demonstrated for its practical values with results from an ARIS-based mobile survey of upstream migrating salmon at an acoustically challenging fish-counting site on the lower Fraser River in British Columbia, Canada.

Underwater Single-Photon 3D Reconstruction Algorithm Based on K-Nearest Neighbor.

The high sensitivity and picosecond time resolution of single-photon avalanche diodes (SPADs) can improve the operational range and imaging accuracy of underwater detection systems. When an underwater SPAD imaging system is used to detect targets, backward-scattering caused by particles in water often results in the poor quality of the reconstructed underwater image. Although methods such as simple pixel accumulation have been proven to be effective for time-photon histogram reconstruction, they perform unsatisfactorily in a highly scattering environment. Therefore, new reconstruction methods are necessary for underwater SPAD detection to obtain high-resolution images. In this paper, we propose an algorithm that reconstructs high-resolution depth profiles of underwater targets from a time-photon histogram by employing the K-nearest neighbor (KNN) to classify multiple targets and the background. The results contribute to the performance of pixel accumulation and depth estimation algorithms such as pixel cross-correlation and ManiPoP. We use public experimental data sets and underwater simulation data to verify the effectiveness of the proposed algorithm. The results of our algorithm show that the root mean square errors (RMSEs) of land targets and simulated underwater targets are reduced by 57.12% and 23.45%, respectively, achieving high-resolution single-photon depth profile reconstruction.

ПРОГНОЗИРОВАНИЕ ВРЕМЕНИ ТУШЕНИЯ ПОЖАРА КОМПОНЕНТОВ ПРОМЫШЛЕННЫХ ВЗРЫВЧАТЫХ ВЕЩЕСТВ ВОДНОГЕЛЕВЫМИ ОГНЕТУШАЩИМИ СОСТАВАМИ

. Using methods of regression analysis and neural network research, it was possible to preserve the physical properties of water-gene compositions and ensure a minimum time for extinguishing a fire in a model fire with components of industrial explosives. Neural network modeling was performed in the STATISTICA Application 10 program. The maximum discrepancy between the results of the neural network model and experimental data is 0,18 %. Regression analysis was performed in the REGRAN program. The maximum error in target results was 4,4 %. Analysis of experimental data and mathematical modeling results showed that the most significant properties of fire extinguishing agents based on hydrogels, providing minimal extinguishing time, are density and surface tension. The concentrations of the gelling agent were determined at which the water-gel composition acquires optimal physical properties for extinguishing a model outbreak of a component of an industrial explosive. Recommendations have been developed for creating hydrogel formulations with desired properties.

Initial United States experience with Medtronic Stealth Autoguide cranial robotic guidance platform.

Stereotactic techniques play an important role in neurosurgery. The development of a miniaturized cranial robot with an efficient workflow and accurate surgical execution is an important step in a broader application of these techniques. Herein, the authors describe their experience with the Medtronic Stealth Autoguide miniaturized cranial robot. A retrospective review of 75 cases from 2020 to 2022 was performed. The patients who had undergone surgery utilizing the Stealth Autoguide robot were analyzed for surgical indication and accuracy, operative time, and clinical outcome. The outcomes were defined as follows: for stereoelectroencephalography (SEEG), the electrode placement pattern that identified the seizure focus and did not require any revision or additional leads; for biopsy, the percentage of cases in which diagnostic tissue was obtained; and for laser interstitial thermal therapy (LITT), the percentage of cases in which laser fiber placement was adequate for ablation. Surgical complications were defined as any asymptomatic or symptomatic intracerebral hemorrhage, new neurological deficit, or need for electrode, laser fiber, or biopsy needle repositioning or revision. The Stealth Autoguide robot was utilized in 75 on-label cases, including 40 SEEG cases for seizure focus localization, 19 LITT cases, and 16 stereotactic biopsy cases. The mean real target error (RTE) at the entry was 1.48 ± 0.84 mm for biopsy, 1.36 ± 0.89 mm for Visualase laser fiber placement, and 1.24 ± 0.72 mm for SEEG. The mean RTE at the target was 1.56 ± 0.95 mm for biopsy needle placement, 1.42 ± 0.93 mm for Visualase laser fiber placement, and 1.31 ± 0.87 mm for SEEG electrode placement. The surgical time for unilateral SEEG cases took an average 52 minutes (average 6.5 mins/lead, average 8 electrodes). Bilateral SEEG cases took an average 105 minutes (average 7.5 mins/lead, average 14 electrodes). In the SEEG population, there were no revised or unsuccessful seizure localizations. For biopsy, diagnostic tissue was obtained in 100% of cases. For LITT, fiber placement was adequate for ablation in 100% of cases. There were no cases of symptomatic or asymptomatic intracerebral hemorrhage, and no cases required repositioning or replacement of the laser fiber, electrode, or biopsy needle. One patient experienced transient cranial nerve III palsy following laser ablation that resolved in 10 weeks. A failure of communication between the robotic platform and the Stealth Autoguide as a station required the cancellation of 1 procedure. The Medtronic Stealth Autoguide robot system is versatile across biopsy, SEEG, and laser ablation indications. Setup and surgical execution are efficient with a high degree of accuracy and consistency.

Accuracy of acetabular cup placement in total hip arthroplasty using an augmented reality navigation “pin-less” system: A pilot study

PurposeCurrently, there is limited information regarding the utilization of pin-less augmented reality (AR) assistance in total hip arthroplasty (THA). This preliminary study aimed to evaluate the precision of acetabular cup placement in THA utilizing the AR Navigation “Pin-less” System (Pin-less AR navigation, prototype). MethodsA total of 72 consecutive primary THAs in 58 patients were categorized into two groups: the Pin-less AR navigation group and the conventional group. All THAs were conducted via the direct anterior approach. First, the absolute value of difference between the intra-operative and post-operative angles (absolute difference) was calculated in the Pin-less AR navigation group. Second, the absolute value of error between the post-operative angles and the target angles (absolute target error) was assessed both in the Pin-less AR navigation group and the conventional group. ResultsThe absolute difference in inclination and anteversion angles was 2.2 ​± ​1.4° and 2.4 ​± ​1.5°, respectively. The absolute target error in the Pin-less AR navigation group versus the conventional group was 1.9 ​± ​1.5° versus 4.2 ​± ​2.7° in inclination (P ​< ​0.001) and 2.3 ​± ​1.5° versus 3.1 ​± ​2.1° in anteversion (P ​= ​0.092). The percentage of acetabular cups placed within ±5° from the target angles was significantly higher in the Pin-less AR navigation group (90.3%) compared with the conventional group (52.6%) (P ​< ​0.001). ConclusionsThis study demonstrates that Pin-less AR navigation yielded generally accurate acetabular cup positioning, surpassing the conventional method. Further research is warranted to thoroughly evaluate Pin-less AR navigation.

Microelectrode Recording During Deep Brain Stimulation Does Not Consistently Represent Lead Trajectory.

Long-term outcomes in deep brain stimulation (DBS) depend on accuracy of lead placement. Microelectrode recording (MER) is a long-used adjunct to leverage neurophysiological information to confirm satisfactory trajectory of implanted electrodes. The goal of this study was to evaluate the consistency in which electrodes are placed in sampled microelectrode trajectories. This is a retrospective study using intraoperative computed tomography to measure final electrode deviation from MER probe placement during the DBS insertion targeting subthalamic nucleus. Fifteen patients had 29 DBS leads placed using MER assistance. Radial distance between the probe and the lead were measured for each patient using intraoperative imaging. In addition, the preoperative target to final lead error was measured in 14 patients undergoing subthalamic nucleus implants without the use of MER and compared with the 15 patients in which MER was used as an adjunct. There was no significant difference in the mean radial target error (1.2 vs 1.0 mm, P = .156) when comparing the leads placed with or without MER assistance, respectively. The mean difference in final position of microelectrode compared with DBS lead was 0.9 ± 0.1 (range 0.4-2.0 mm). Of all MER-assisted electrodes placed, 44.8% (13) of electrode final positions radially deviated 1.0 mm or more from the MER probe. Electrode placement may deviate significantly from MER trajectories. Given the concern that physiological data may not be representative of the final electrode trajectory, surgeons should consider using intraoperative imaging or other adjunctive techniques during DBS to confirm accuracy and satisfactory trajectory of DBS leads.

Subthalamic deep brain stimulation in advanced Parkinson’s disease using the STarFix system

BackgroundDeep brain stimulation (DBS) is a well-established and highly effective treatment for patients with medically uncontrolled Parkinson’s disease (PD). This study presents the outcome of patients with PD after subthalamic deep brain stimulation (STN DBS) using the microtargeting the platform (MTP) stereotactic system (the STarFixSystem, FHC Inc., Bowdoin, Me., USA) for accurate localization of the target and precise placement of DBs electrodes. Patients were evaluated preoperatively and the follow up period was 1 year utilizing the Unified Parkinson’s Disease Rating Scale (UPDRS II and III) in on and off medication-stimulation conditions. It included 18 STN DBS procedures in 10 patients over a 2-year period. The technical features and the practical application of the STarFix system and the clinical outcome are reported. Also lead location analysis is done by doing postoperative CT to evaluate the clinical accuracy of the stereotactic system.ResultsThe mean age of PD patients was 67.7 years. Six patients were males (60%) and 4 patients were females (40%). The mean postoperative improvement in ADL was 83.47 ± 2.39 over Dopa therapy alone. The mean postoperative improvement in UPDRs motor score was 78.96 ± 7.74 over Dopa therapy alone. The STarFix system showed high accuracy with target error 1.89 mm (SD 0.8) without accounting for brain shift.ConclusionDeep brain stimulation (DBS) targeting the subthalamic nucleus (STN) offers fundamental benefits for patients with advanced Parkinson’s disease (PD). The usage of the STarFix system for implanting DBS electrodes in the STN provides an accurate, safe, and effective alternative to traditional stereotactic techniques. This approach simplifies the surgical procedure, boosts patient comfort, and minimizes the duration of the operation.Clinical trial registration ClinicalTrials.gov identifier: NCT03562403. Registered 19 June 2018, https://classic.clinicaltrials.gov/ct2/show/NCT03562403.