Background: Vestibular symptoms can severely affect patients with vestibular schwannomas (VSs). Studies assessing vestibular symptoms beyond clinical routine assessment in patients with VS treated by stereotactic radiosurgery (SRS) are scarce. Therefore, we employed the standardized questionnaire Dizziness Handicap Inventory (DHI) to systematically evaluate vestibular symptoms prior to and after SRS. Methods: For this retrospective single center study, we included patients who received Cyberknife® SRS for newly diagnosed unilateral VS between 2012 and 2022, and who had a minimum of two follow-up (FU) visits. Besides clinical assessment, the presence and severeness of vestibular symptoms before and after treatment was recorded by using the DHI. Overall DHI symptom scores (1-100) were classified into four grades (0 = "none", 1 = "mild", 2 = "moderate" and 3 = "severe"). The results were correlated with tumor-, patient-, and treatment-related characteristics. Results: We analyzed 128 patients with a median age of 60 years (range: 20-82) and a median FU of 36 months (range: 11-106 months). The median tumor volume was 0.99 cm3 (range: 0.04-7.1 cm3). A median marginal dose of 13 Gy (range: 12-14 Gy) was administered. The crude rate of local tumor control was 99.2%. The mean DHI total score at last follow-up (LFU, 25.5 ± 24.7; range 0-92) was significantly lower than before SRS (29.4 ± 25.3; range:0-92, p = 0.026), which was reflected in a higher proportion of patients with DHI grade "none" and a lower proportion of patients with DHI grade "severe" at LFU. Chi-square tests showed a significant correlation of the DHI grades (DHI 0-1 vs. DHI 2-3) with the absence or presence of vestibular symptoms both before SRS (p < 0.001, CI 95%) and at LFU (p = 0.038). Conclusions: The DHI is a feasible and valid instrument for measuring vestibular symptoms after SRS. In addition, the DHI enables the quantification of symptoms and can therefore serve as an important tool for outcome assessment after SRS of VS. In the present cohort, DHI scores improved significantly during FU.

BACKGROUND:The normal tissue objective (NTO) is an inverse planning approach in radiosurgery, also available for the CyberKnife system. By employing a model function, it aims to achieve precise control over the global dose fall-off in healthy tissue. As a novel technique, NTO can serve as an alternative to the established method, which utilizes layered contours around the target to shape dose gradients and enhance conformity, referred to as Auto-shells in CyberKnife systems. PURPOSE:This study compares the dose distribution achieved with NTO and Auto-shells to evaluate their respective advantages in CyberKnife treatment planning. METHODS:A total of 45 patients with brain tumors-including 15 vestibular schwannomas, 15 meningiomas, and 15 metastases, all of whom had previously been treated using an Auto-shells-generated plan, were analyzed. For each case, an alternative NTO-based plan was generated and compared with its Auto-shells counterpart. Key treatment parameters-including nodes, beams, total monitor units (MU), treatment time, new conformity index (nCI), gradient index (GI), and dose exposure volumes to healthy brain tissue (V12Gy and V5Gy)-were evaluated. RESULTS:Both methods resulted in comparable plans across many indices. Significant differences were particularly in terms of healthy brain tissue dose exposure. With the NTO method, V12Gy and V5Gy were reduced by up to 14%, and in the case of meningiomas and metastases, the GI was reduced by up to 7%. The conformity, described by the nCI, was within 2%. No significant difference was observed in MU. CONCLUSION:NTO optimization presents a viable option to the Auto-shells method for CyberKnife treatment of brain tumors. By reducing healthy brain tissue exposure without increasing monitor units, it enhances dose-sparing efficiency. However, maintaining optimal conformity remains an important issue, highlighting the trade-offs between precision and tissue preservation.

High NA EUV lithography has become a reality. The high NA EUV scanner (EXE:5000) produces exposure fields of 26x16.5 mm2 which is twice smaller than standard fields on other scanners. For certain use cases (e.g. when a die is larger than the High NA field) stitching between two exposure fields might be required. Stitching of vertical lines across two exposure fields has already been demonstrated in several publications. In this publication, we pay attention to photomask related aspects of stitching which are multifold. We draw attention to the need for mask resolution enhancement which will enable advanced OPC at stitching. We will show stitching behavior on both Tantalum and low-n masks and demonstrate low-n absorber reflectivity suppression by means of sub-resolution gratings which is required for stitching. We explore the behavior of the exposure field black border (BB) edge and formulate recommendations for specifications on BB edge control as well as pattern placement and pattern fidelity at the black border. Finally, we conclude that the mask performance is a key enabler of High NA stitching.

Introduction: Photon-counting detector computed tomography (PCD-CT) represents the next generation of CT technology, offering enhanced capabilities for detecting the orientation of directional leads in deep brain stimulation (DBS). This study aims to refine PCD-CT-based lead orientation determination using an automated method applicable to devices from various manufacturers, addressing current methodological limitations and improving neurosurgical precision. Methods: An automated method was developed to ascertain the orientation of directional DBS leads using PCD-CT data and grayscale model fitting for devices from Boston Scientific, Medtronic, and Abbott. A phantom study was conducted to evaluate the precision and accuracy of this method, comparing it with the stripe artifact method across different lead alignments relative to the CT gantry axis. Results: Except for the Medtronic Sensight™ lead, where detection was occasionally unfeasible if aligned normal to the z-axis of the CT gantry, a clinically very unlikely alignment, the lead orientation could be automatically determined regardless of its position. The accuracy and precision of this automated method was comparable to those of the stripe artifact method. Conclusion: PCD-CT enables the automatic determination of lead orientation from leading manufacturers with an accuracy comparable to the stripe artifact method, and it offers the added benefit of being independent of the clinically occurring orientation of the head and, consequently, the lead relative to the CT gantry axis.

Introduction: With recent advancements in deep brain stimulation (DBS), directional leads featuring segmented contacts have been introduced, allowing for targeted stimulation of specific brain regions. Given that manufacturers employ diverse markers for lead orientation, our investigation focuses on the adaptability of the 2017 techniques proposed by the Cologne research group for lead orientation determination. Methods: We tailored the two separate 2D and 3D X-ray-based techniques published in 2017 and originally developed for C-shaped markers, to the dual-marker of the Medtronic SenSight™ lead. In a retrospective patient study, we evaluated their feasibility and consistency by comparing the degree of agreement between the two methods. Results: The Bland-Altman plot showed favorable concordance without any noticeable systematic errors. The mean difference was 0.79°, with limits of agreement spanning from 21.4° to −19.8°. The algorithms demonstrated high reliability, evidenced by an intraclass correlation coefficient of 0.99 (p < 0.001). Conclusion: The 2D and 3D algorithms, initially formulated for discerning the circular orientation of a C-shaped marker, were adapted to the marker of the Medtronic SenSight™ lead. Statistical analyses revealed a significant level of agreement between the two methods. Our findings highlight the adaptability of these algorithms to different markers, achievable through both low-dose intraoperative 2D X-ray imaging and standard CT imaging.

Purpose: In robotic stereotactic radiosurgery (SRS), optimal selection of collimators from a set of fixed cones must be determined manually by trial and error. A unique and uniformly scaled metric to characterize plan quality could help identify Pareto-efficient treatment plans. Methods: The concept of dose-area product (DAP) was used to define a measure (DAP(ratio)) of the targeting efficiency of a set of beams by relating the integral DAP of the beams to the mean dose achieved in the target volume. In a retrospective study of five clinical cases of brain metastases with representative target volumes (range: 0.5-5.68 ml) and 121 treatment plans with all possible collimator choices, the DAP(ratio) was determined along with other plan metrics (conformity index CI, gradient index R50%, treatment time, total number of monitor units TotalMU, radiotoxicity index f12, and energy efficiency index eta 50%), and the respective Spearman's rank correlation coefficients were calculated. The ability of DAP(ratio) to determine Pareto efficiency for collimator selection at DAP(ratio) < 1 and DAP(ratio) < 0.9 was tested using scatter plots. Results: The DAP(ratio) for all plans was on average 0.95 +/- 0.13 (range: 0.61-1.31). Only the variance of the DAP(ratio) was strongly dependent on the number of collimators. For each target, there was a strong or very strong correlation of DAP(ratio) with all other metrics of plan quality. Only for R50% and eta 50% was there a moderate correlation with DAP(ratio) for the plans of all targets combined, as R50% and eta 50% strongly depended on target size. Optimal treatment plans with CI, R50%, f12, and eta 50% close to 1 were clearly associated with DAP(ratio) < 1, and plans with DAP(ratio) < 0.9 were even superior, but at the cost of longer treatment times and higher total monitor units. Conclusions: The newly defined DAP(ratio) has been demonstrated to be a metric that characterizes the target efficiency of a set of beams in robotic SRS in one single and uniformly scaled number. A DAP(ratio) < 1 indicates Pareto efficiency. The trade-off between plan quality on the one hand and short treatment time or low total monitor units on the other hand is also represented by DAP(ratio).

OPC model accuracy is an important contributor to the EPE budget in the latest lithography nodes. The overall OPC accuracy depends on accurate calibration of the sub-models capturing mask, optical, resist and etch effects. The advent of high-NA (0.55) EUV lithography with anamorphic imaging has further increased the emphasis on accurate aerial image model calibration for computational lithography. In this paper, we study the feasibility of using direct aerial image measurements with the ZEISS AIMS EUV tool for improving OPC model accuracy as well as accurate metrology of mask pattern variability, which are both relevant to EPE budgeting.

In this paper, we study the feasibility of direct aerial image measurements with the ZEISS AIMS® EUV tool for quantification of mask effects that impact EPE budget and OPC model accuracy. We demonstrate the application of aerial image metrology for OPC model calibration, pattern shift detection, quantitative mask metrology and for Optical process window characterization.

Edge placement error (EPE) analysis, which combines pattern variation data from single litho-process steps with overlay data from subsequent litho-process steps, has been well established as a key methodology to characterize the performance of complex semiconductor manufacturing processes. As critical dimensions shrink in new semiconductor technologies, process margins become tighter, and characterizing and monitoring EPE budgets becomes more important than ever to assess and maintain in-line process performance and yield. In this paper, we present SEM image contour-based EPE analysis and budget generation for a BEOL multi-patterning (LELE) layer. SEM contour analysis was previously shown to be a suitable method for pattern variability characterization, with the capability to capture not only pattern size, but also shape and local stochastic placement variations, and to provide statistical overlay margin estimates between separate device layers. In the current work, we also show that for a LELE process, contour analysis provides local overlay measurements and all inputs needed to generate the complete EPE budget breakdown. Multiple wafers from a device in production were provided after processing the second etch step of a metal layer LELE process. We acquire large field-of-view SEM images with a high-throughput e-beam tool (HMI eP5), sampled within die, across exposure field and across wafer in order to enable analysis of variability into global and local components. Pattern contours are extracted from individual SEM images, and contours are ‘stacked’ to identify specific locations of largest variability or smallest margin. While the images contain patterns from both processing steps, these can be uniquely distinguished after die-to-database alignment and labeled by mask ID, here 1st and 2nd litho-etch layers, respectively. In addition to size, shape and stochastic placement variations, we perform center-of-gravity analysis between patterns on the 1st and 2nd litho-etch layers. The latter reveals local on-device overlay variations that can be mapped across the measured wafers. The contour analysis therefore provides all information required for a thorough EPE budget breakdown, i.e. global CDU and local CDU for the most critical cutline locations, as well as overlay. Figure 1 shows the breakdown for one particular point of interest. We perform EPE budget analysis for multiple wafers, which can highlight wafer-to-wafer variations. This is a first step toward process monitoring, which would not only highlight process drifts, but also distinguish main contributors in order to aid in trouble shooting. KEYWORDS: pattern variability, pattern fidelity, contour analysis, edge placement error, holistic lithography, SEM metrology

In this case report, the authors describe the first case of a glioependymal cyst of the brainstem managed by robot-assisted, stereotactic, cysto-ventricular shunting. Glioependymal cysts are rare congenital cystic lesions that are thought to form by displacement of ependymal cells during the embryonal period. Glioependymal cysts have been reported in a variety of different locations within the central nervous system. However, glioependymal cysts of the brainstem have only been described once before. Here, we report the case of a 53-year-old man who was referred to our department due to hemiparesis, hemihypesthesia, and hemidysesthesia, as well as facial and abducens nerve palsy. A large pontine glioependymal cyst was confirmed via magnetic resonance imaging (MRI) scans. The cyst was subsequently decompressed by connecting the cyst with the fourth ventricle via robot-assisted stereotactic shunt placement. In the postoperative course, the patient made a quick recovery and did not report any permanent neurologic deficits.

Directional deep brain stimulation (DBS) leads are now widely used, but the orientation of directional leads needs to be taken into account when relating DBS to neuroanatomy. Methods that can reliably and unambiguously determine the orientation of directional DBS leads are needed. In this study, we provide an enhanced algorithm that determines the orientation of directional DBS leads from postoperative CT scans. To resolve the ambiguity of symmetric CT artifacts, which in the past, limited the orientation detection to two possible solutions, we retrospectively evaluated four different methods in 150 Cartesia™ directional leads, for which the true solution was known from additional X-ray images. The method based on shifts of the center of mass (COM) of the directional marker compared to its expected geometric center correctly resolved the ambiguity in 100% of cases. In conclusion, the DiODe v2 algorithm provides an open-source, fully automated solution for determining the orientation of directional DBS leads.

With the adoption of extreme ultraviolet (EUV) lithography for high volume production in the advanced wafer manufacturing fab, defects resulting from stochastic effects could be one of major yield killers and draw increasing interest from the industry. In this paper, we will present a flow, including stochastic edge placement error (SEPE) model calibration, pattern recognition and hot spot ranking from defect probability, to detect potential hot spot in the chip design. The prediction result shows a good match with the wafer inspection. HMI eP5 massive metrology and contour analysis were used to extract wafer statistical edge placement distribution data.

BACKGROUND The employment of the O-arm for intraoperative localization of deep brain stimulation (DBS) leads has been shown to be feasible and effective. However, partial volume artifacts impede the determination of individual electrode contacts and thus allow only an indirect approximation of each contact's localization. OBJECTIVE To reduce the partial volume artifacts by means of high-resolution (HiRes) reconstruction of O-arm data and thus allow more accurate predictions with regard to the positioning and orientation of individual DBS contacts. METHODS Following intraoperative flat-panel computed tomography, the O-arm raw data were reconstructed with a resolution of 0.2 mm × 0.2 mm × 0.2 mm. The geometric integrity of HiRes reconstructions was assessed via landmark transformation. Using a phantom, resolutions of both reconstruction modalities were then evaluated by means of the modulation transfer function (MTF). Finally, directional and nondirectional leads were compared visually to analyze the delineation of individual electrode contacts. RESULTS With a mean accuracy of 0.56 mm ± 0.12 mm, geometric integrity remained intact during HiRes reconstruction. Analysis of HiRes reconstruction resolution yielded a 47.7% increase of the 10% MTF in comparison to conventional postprocessing. Reduction of partial volume artifacts yielded strong contrasts of electrode compartments and allowed direct identification of individual contacts as well as localization of the X-ray marker on directional leads. CONCLUSION HiRes reconstruction of O-arm data allows an effective reduction of partial volume artifacts to such an extent that a delineation of individual contacts across single DBS leads is possible without requiring increases in radiation dose.

Der Status epilepticus ist durch nicht sistierende bzw. in kurzen Abständen wiederkehrende epileptische Anfälle charakterisiert, mit einer hohen Mortalität und Letalität assoziiert und stellt eine der häufigsten Erkrankungen auf neurologischen Intensivstationen dar. Reversible Diffusionsstörungen wurden bislang nur selten beschrieben, können sich jedoch im periiktal durchgeführten cMRT in bilateral symmetrischen Signalanhebungen des Rindenbandes äussern, die differentialdiagnostisch die Frage aufwerfen, ob es sich um die strukturelle Ursache oder eine Folge der epileptischen Aktivität handelt. Drei typische Patienten mit Epilepsie-bedingtem Status epilepticus und reversiblen Diffusionsstörungen im cMRT und die in Betracht kommenden Differentialdiagnosen werden vorgestellt.

Over the past few years, patterning edge placement error (EPE), which combines information on variability of pattern sizes and placement between adjacent device layers, has been established as the key metric for patterning budget generation and holistic patterning control. More recently, the emergence of high-throughput SEM tools that provide inspection and large-volume CD metrology capabilities has enabled unprecedented statistical analysis of on-product pattern variability. In the current paper we address edge placement budget generation as well as potential for improved patterning control for an HVM use case at the 28nm litho node. Edge placement and possible related defect mechanisms arise most critically at the contact layer, where contact hole patterning and EPE, with respect to both underlying gate and active layers need to be well controlled. At the 28nm node and for automotive applications, variability control within 5-sigma, i.e. to failure rates below 1 ppm, is generally required to ensure device reliability. To support generation of an EPE budget by wafer data that captures inter and intra-field components, including local stochastic variations, we use a high-throughput, large field-of-view SEM tool from Hermes Microvision, at all three process layers of interest, as well as YieldStar metrology for overlay characterization. The large volume of data being made available -tens of millions of individual CD measurements- allows mapping out the low-probability ends of variability distributions and detecting non-Gaussian ‘fat tails’ indicative of defect rates that would be underestimated by 3-sigma estimates. Data analysis includes decomposing the total pattern variations into sources of variability, such as global CDU, mask variations and local stochastics. In addition to established CD metrology, we apply novel SEM image based analysis of repetitive patterns in SRAM arrays to generate 2-dimensional process variability bands, including estimates of pattern placement. This approach allows to investigate in detail the probabilistic interaction between active, gate and contact layers.

Objectives Despite its efficacy in tremor-suppression, the ventral intermediate thalamic (VIM) nucleus has largely been neglected in deep brain stimulation (DBS) for tremor-dominant Parkinson's disease (tdPD). The employment of a parietal approach, however, allows stimulation of VIM and subthalamic nucleus (STN) using one trajectory only and thus constitutes a promising alternative to existing strategies. In the present study, we investigate safety and efficacy of combined lead implantation and stimulation of STN and VIM using a parietal approach. Materials and Methods Retrospective analysis of five patients with tdPD was performed who underwent DBS using a parietal approach. Changes in symptom severity, disease-specific health-related quality of life and l-dopa equivalent doses (LED) were evaluated over a total time course of 12 months. Results DBS within both targets yielded significant improvement of parkinsonian symptoms (median: 40.0%, p = 0.04) in the first 6 months of continuous stimulation and remained stable thereafter (median improvement at 12 months: 43.2%, p = 0.07). Sustained improvement of tremor (median at 6 months: 100.0%, p = 0.04; median at 12 months 83.3%, p = 0.04) and quality of life scores (median at 6 months: 29.8%, p = 0.04; median at 12 months: 32.6%, p = 0.04) was noted throughout the follow-up period. No significant change of LEDs was observed by the end of follow-up (median decrease: 2.2%, p = 0.89). Conclusions Simultaneous DBS of VIM and STN using one trajectory is safe, yielding good control of parkinsonian tremors. Further studies, however, are necessary to determine whether a parietal trajectory affords better control over tremor symptoms than established strategies and hence justifies the potential risks associated with the alternative approach.

We present an experimental study of pattern variability and defectivity, based on a large data set with more than 112 million SEM measurements from an HMI high-throughput e-beam tool. The test case is a 10nm node SRAM via array patterned with a DUV immersion LELE process, where we see a variation in mean size and litho sensitivities between different unique via patterns that leads to a seemingly qualitative differences in defectivity. The large available data volume enables further analysis to reliably distinguish global and local CDU variations, including a breakdown into local systematics and stochastics. A closer inspection of the tail end of the distributions and estimation of defect probabilities concludes that there is a common defect mechanism and defect threshold despite the observed differences of specific pattern characteristics. We expect that the analysis methodology can be applied for defect probability modeling as well as general process qualification in the future.

Traditionally, the performance of a lithography or patterning step is described by its mean size and the spread at a 3 sigma probability. Recent papers by Bristol, Brunner and others have shown this is insufficient to describe the process capability in EUV lithography. To address this challenge, an enormous increase of sampling CD (critical dimension) values is needed to describe the actual distribution on the wafer. We will show how we can address this by leveraging the HMI eP5 e-Beam system to acquire a set of CDs of previously unknown size. We will further show that extended sampling leads to better understanding of this phenomena, as we can probe full distribution behavior even on a limited number of repeated exposures on a wafer.

Background/Aims: Technological advancements had a serious impact on the evolution of robotic systems in stereotactic neurosurgery over the last three decades and may turn robot-assisted stereotactic neurosurgery into a sophisticated alternative to purely mechanical guiding devices. Objectives: To compare robot-assisted and conventional frame-based deep brain stimulation (DBS) surgery with regard to accuracy, precision, reliability, duration of surgery, intraoperative imaging quality, safety and maintenance using a standardized setup. Methods: Retrospective evaluation of 80 consecutive patients was performed who underwent DBS surgery using either a frame-based mechanical stereotactic guiding device (n = 40) or a stereotactic robot (ROSA Brain, MedTech, Montpellier, France) (n = 40). Results: The mean accuracy of robot-assisted and conventional lead implantation was 0.76 mm (SD: 0.37 mm, range: 0.17–1.52 mm) and 1.11 mm (SD: 0.59 mm, range: 0.10–2.90 mm), respectively. We observed a statistically significant difference in accuracy (p < 0.001) when comparing lateral deviations between both modalities. Furthermore, a statistical significance was observed when investigating the proportion of values exceeding 2.00 mm between both groups (p = 0.013). In 8.75% (n = 7) of conventionally implanted leads, lateral deviations were greater than 2.0 mm. With a maximum value of 1.52 mm, this threshold was never reached during robot-guided DBS. The mean duration of DBS surgery could be reduced significantly (p < 0.001) when comparing robot-guided DBS (mean: 325.1 ± 81.6 min) to conventional lead implantation (mean: 394.8 ± 66.6 min). Conclusions: Robot-assisted DBS was shown to be superior to conventional lead implantation with respect to accuracy, precision and operation time. Improved quality control, continuous intraoperative monitoring and less manual adjustment likely contribute to the robotic system’s reliability allowing high accuracy during lead implantation despite limited experience. Hence, robot-assisted lead implantation can be considered an appropriate and reliable alternative to purely mechanical devices.

We present an experimental study of pattern variability and defectivity, based on a large data set with >112 million critical dimension (CD) and via area measurements from a Hermes Microvision Inc. (HMI) high-throughput e-beam tool. The test case is a 10-nm node static random-access memory via array patterned with a deep ultraviolet immersion litho-etch-litho-etch process, where we see a variation in mean size and litho sensitivities between different unique via patterns that leads to significant differences in defectivity. The large data volume made available by high-throughput inspection capability of the HMI eP5 tool enables analysis to reliably distinguish global and local CD uniformity variations, including a breakdown into local systematics and stochastics. From a closer inspection of the tail end of the distributions and estimation of defect probabilities, we conclude that there is a common defect mechanism and defect threshold despite the observed differences of specific pattern characteristics. In addition, we studied wafer fingerprints for both global CD uniformity (GCDU) and local CD uniformity (LCDU), including stochastics. We used LCDU and GCDU wafer maps to identify correlations between those parameters and defect count. We expect that the analysis methodology presented can be applied for defect probability modeling as well as general process qualification in the future. (C) 2018 Society of Photo-Optical Instrumentation Engineers (SPIE)