Electroanatomical mapping after cardiac radioablation for treatment of incessant electrical storm: a case report from the RAVENTA trial

BACKGROUND

Electroanatomical mapping (EAM)-guided stereotactic arrhythmia radioablation (STAR) is a novel noninvasive therapy option for patients with monomorphic ventricular tachycardia (VT) refractory to antiarrhythmic drugs and/or urgent catheter ablation (CA). Data on success rates in an emergency situation such as electrical storm (ES) are rare. We present a case of a patient with an initially very poor life expectancy after extensive myocardial infarction with therapy-resistant ES, not amendable for further antiarrhythmic drug therapy, implantable cardioverter-defibrillator implantation, or repeated CA who was introduced to the radiation oncology department for emergency STAR as a bail-out therapy.

METHODS

Target volume definition and transfer from EAM to CT were validated and quality assured with a semi-automatic, dedicated visualization tool (CARDIO-RT). Emergency STAR was performed with 25 Gy in the framework of the RAVENTA study. The VT burden gradually decreased after STAR; however, a second VT morphology occurred, which was successfully treated with EAM-guided CA 12 days after STAR.

RESULTS

The second EAM-guided CA showed areas of low voltage in the irradiated segments, indicating a precise targeting and early functional response to STAR. The patient remained free of any VT recurrence or any radiation-related toxicities and in good general condition during the recent follow-up of 18 months.

CONCLUSION

The case highlights the possible approach, caveats, difficulties, and prognosis of a patient severely affected by therapy-resistant VT in whom CA could not lead to VT suppression. Further studies of putative mechanisms of STAR in the acute and chronic phase of this novel therapy are warranted.

Radiosurgery for ventricular tachycardia (RAVENTA): interim analysis of a multicenter multiplatform feasibility trial

BACKGROUND

Single-session cardiac stereotactic radiation therapy (SBRT) has demonstrated promising results for patients with refractory ventricular tachycardia (VT). However, the full safety profile of this novel treatment remains unknown and very limited data from prospective clinical multicenter trials are available.

METHODS

The prospective multicenter multiplatform RAVENTA (radiosurgery for ventricular tachycardia) study assesses high-precision image-guided cardiac SBRT with 25 Gy delivered to the VT substrate determined by high-definition endocardial and/or epicardial electrophysiological mapping in patients with refractory VT ineligible for catheter ablation and an implanted cardioverter defibrillator (ICD). Primary endpoint is the feasibility of full-dose application and procedural safety (defined as an incidence of serious [grade ≥ 3] treatment-related complications ≤ 5% within 30 days after therapy). Secondary endpoints comprise VT burden, ICD interventions, treatment-related toxicity, and quality of life. We present the results of a protocol-defined interim analysis.

RESULTS

Between 10/2019 and 12/2021, a total of five patients were included at three university medical centers. In all cases, the treatment was carried out without complications. There were no serious potentially treatment-related adverse events and no deterioration of left ventricular ejection fraction upon echocardiography. Three patients had a decrease in VT episodes during follow-up. One patient underwent subsequent catheter ablation for a new VT with different morphology. One patient with local VT recurrence died 6 weeks after treatment in cardiogenic shock.

CONCLUSION

The interim analysis of the RAVENTA trial demonstrates early initial feasibility of this new treatment without serious complications within 30 days after treatment in five patients. Recruitment will continue as planned and the study has been expanded to further university medical centers.

TRIAL REGISTRATION NUMBER

NCT03867747 (clinicaltrials.gov). Registered March 8, 2019. Study start: October 1, 2019.

Quality assurance process within the RAdiosurgery for VENtricular TAchycardia (RAVENTA) trial for the fusion of electroanatomical mapping and radiotherapy planning imaging data in cardiac radioablation

A novel quality assurance process for electroanatomical mapping (EAM)-to-radiotherapy planning imaging (RTPI) target transport was assessed within the multi-center multi-platform framework of the RAdiosurgery for VENtricular TAchycardia (RAVENTA) trial. A stand-alone software (CARDIO-RT) was developed to enable platform independent registration of EAM and RTPI of the left ventricle (LV), based on pre-generated radiotherapy contours (RTC). LV-RTC were automatically segmented into the American-Heart-Association 17-segment-model and a manual 3D-3D method based on EAM 3D-geometry data and a semi-automated 2D-3D method based on EAM screenshot projections were developed. The quality of substrate transfer was evaluated in five clinical cases and the structural analyses showed substantial differences between manual target transfer and target transport using CARDIO-RT.

A step towards routine for stereotactic radioablation in refractory ventricular tachycardia – interim analysis on short term safety of the first prospective, multi-centre, multi-platform study RAVENTA

Background

Ventricular tachycardia (VT) is a potentially life-threatening heart rhythm disorder originating in heterogeneous conduction velocity in the ventricular myocardium, e.g. by scar formation in ischaemic or dilated cardiomyopathy. Current guideline-directed medical therapy comprises implantable cardioverter defibrillator (ICD), antiarrhythmic drugs, and endocardial/epicardial catheter ablation. There is a serious recurrence rate for example due to diffuse fibrosis, progress of disease, or insufficient ablation depth or volume.

In cases when Catheter ablation and antiarrhythmic medication failed to reduce VT burden, stereotactic body radiation therapy (SBRT) may become an additional treatment option. To date there have been several small retrospective case series and some single-centre prospective studies showing promising results.

Purpose

For the purpose of obtaining the authorization of a randomized trial, a feasibility study was designed. The primary objective is to demonstrate sufficient safety of cardiac SBRT for the non-invasive treatment of VT and whether the dose needed can be delivered while sparing sensitive surrounding structures (e.g. stomach, oesophagus, vena cava, coronary arteries, ICD). Secondarily, the effect on VT burden is reported.

Methods

The RAVENTA study (RAdiosurgery for VENtricular TAchycardias) is the first prospective, multicentre study on SBRT in patients suffering from refractory VTs worldwide. Patients were enrolled according to strict inclusion criteria. First, an electrophysiology study using a high definition mapping system was performed to identify the substrate (target region). In order to plan SBRT a planning computed tomography scan was obtained. Finally, a single dose of 25 Gy was administered to the target region. Neither sedation nor anaesthesia is necessary during SBRT.

Primary endpoint is feasibility defined as complete dose application and absence of severe (grade ≥3) treatment-related toxicity within 30 days of treatment. RAVENTA is powered to reject the hypothesis of 70% feasibility, if in fact feasibility is 95%. This is a pre-defined interim analysis with the aim of stopping early for futility.

Results

Between October 2019 and December 2021, the first 5 patients (characteristics shown in Table 1) could be enrolled and radiotherapy was delivered without major complications. Cardiac SBRT took on average 30 minutes. There was no treatment-related severe toxicity. Furthermore, we could not record any negative effect on functionality of the ICD: constant sensing amplitude and pacing capture threshold. In the short-term, patients showed a clear decrease in VT burden.

Conclusion

These preliminary data of the first multi-centre, multi-platform study on cardiac SBRT on refractory VT demonstrated sufficient short-term feasibility to continue the RAVENTA study. Meanwhile the study has been expanded to 6 centres in Germany.

Funding Acknowledgement

Type of funding sources: None.

Treatment Planning for Cardiac Radioablation: Multicenter Multiplatform Benchmarking for the XXX Trial

PURPOSE

Cardiac radioablation is a novel treatment option for patients with refractory ventricular tachycardia (VT) unsuitable for catheter ablation. The quality of treatment planning depends on dose specifications, platform capabilities, and experience of the treating staff. To harmonize the treatment planning, benchmarking of this process is necessary for multicenter clinical studies such as the XXX trial.

METHODS AND MATERIALS

Planning computed tomography data and consensus structures from three patients were sent to five academic centers for independent plan development using a variety of platforms and techniques with the XXX study protocol serving as guideline. Three-dimensional dose distributions and treatment plan details were collected and analyzed. In addition, an objective relative plan quality ranking system for VT treatments was established.

RESULTS

For each case, three coplanar volumetric modulated arc (VMAT) plans for C-arm linear accelerators (LINAC) and three non-coplanar treatment plans for robotic arm LINAC were generated. All plans were suitable for clinical applications with minor deviations from study guidelines in most centers. Eleven of 18 treatment plans showed maximal one minor deviation each for target and cardiac substructures. However, dose-volume histograms showed substantial differences: in one case, the PTV≥30Gy ranged from 0.0% to 79.9% and the RIVA V_14Gy ranged from 4.0% to 45.4%. Overall, the VMAT plans had steeper dose gradients in the high dose region, while the plans for the robotic arm LINAC had smaller low dose regions. Thereby, VMAT plans required only about half as many monitor units, resulting in shorter delivery times, possibly an important factor in treatment outcome.

CONCLUSIONS

Cardiac radioablation is feasible with robotic arm and C-arm LINAC systems with comparable plan quality. Although cross-center training and best practice guidelines have been provided, further recommendations, especially for cardiac substructures, and ranking of dose guidelines will be helpful to optimize cardiac radioablation outcomes.

Towards automated ultrasound imaging-robotic image acquisition in liver and prostate for long-term motion monitoring

Real-time volumetric (4D) ultrasound has shown high potential for diagnostic and therapy guidance tasks. One of the main drawbacks of ultrasound imaging to date is the reliance on manual probe positioning and the resulting user dependence. Robotic assistance could help overcome this issue and facilitate the acquisition of long-term image data to observe dynamic processesin vivoover time. The aim of this study is to assess the feasibility of robotic probe manipulation and organ motion quantification during extended imaging sessions. The system consists of a collaborative robot and a 4D ultrasound system providing real-time data access. Five healthy volunteers received liver and prostate scans during free breathing over 30 min. Initial probe placement was performed with real-time remote control with a predefined contact force of 10 N. During scan acquisition, the probe position was continuously adjusted to the body surface motion using impedance control. Ultrasound volumes, the pose of the end-effector and the estimated contact forces were recorded. For motion analysis, one anatomical landmark was manually annotated in a subset of ultrasound frames for each experiment. Probe contact was uninterrupted over the entire scan duration in all ten sessions. Organ drift and imaging artefacts were successfully compensated using remote control. The median contact force along the probe's longitudinal axis was 10.0 N with maximum values of 13.2 and 21.3 N for liver and prostate, respectively. Forces exceeding 11 N only occurred in 0.3% of the time. Probe and landmark motion were more pronounced in the liver, with median interquartile ranges of 1.5 and 9.6 mm, compared to 0.6 and 2.7 mm in the prostate. The results show that robotic ultrasound imaging with dynamic force control can be used for stable, long-term imaging of anatomical regions affected by motion. The system facilitates the acquisition of 4D image datain vivoover extended scanning periods for the first time and holds the potential to be used for motion monitoring for therapy guidance as well as diagnostic tasks.

Tumor-dose-rate variations during robotic radiosurgery of oligo and multiple brain metastases

Purpose

For step-and-shoot robotic stereotactic radiosurgery (SRS) the dose delivered over time, called local tumor-dose-rate (TDR), may strongly vary during treatment of multiple lesions. The authors sought to evaluate technical parameters influencing TDR and correlate TDR to clinical outcome.

Material and methods

A total of 23 patients with 162 oligo (1–3) and multiple (>3) brain metastases (OBM/MBM) treated in 33 SRS sessions were retrospectively analyzed. Median PTV were 0.11 cc (0.01–6.36 cc) and 0.50 cc (0.12–3.68 cc) for OBM and MBM, respectively. Prescription dose ranged from 16 to 20 Gy prescribed to the median 70% isodose line. The maximum dose-rate for planning target volume (PTV) percentage p in time span s during treatment (TDR_s,p) was calculated for various p and s based on treatment log files and in-house software.

Results

TDR_60min,98% was 0.30 Gy/min (0.23–0.87 Gy/min) for OBM and 0.22 Gy/min (0.12–0.63 Gy/min) for MBM, respectively, and increased by 0.03 Gy/min per prescribed Gy. TDR_60min,98% strongly correlated with treatment time (ρ = −0.717, p < 0.001), monitor units (MU) (ρ = −0.767, p < 0.001), number of beams (ρ = −0.755, p < 0.001) and beam directions (ρ = −0.685, p < 0.001) as well as lesions treated per collimator (ρ = −0.708, P < 0.001). Median overall survival (OS) was 20 months and 1‑ and 2‑year local control (LC) was 98.8% and 90.3%, respectively. LC did not correlate with any TDR, but tumor response (partial response [PR] or complete response [CR]) correlated with all TDR in univariate analysis (e.g., TDR_60min,98%: hazard ration [HR] = 0.974, confidence interval [CI] = 0.952–0.996, p = 0.019). In multivariate analysis only concomitant targeted therapy or immunotherapy and breast cancer tumor histology remained a significant factor for tumor response. Local grade ≥2 radiation-induced tissue reactions were noted in 26.3% (OBM) and 5.2% (MBM), respectively, mainly influenced by tumor volume (p < 0.001).

Conclusions

Large TDR variations are noted during MBM-SRS which mainly arise from prolonged treatment times. Clinically, low TDR corresponded with decreased local tumor responses, although the main influencing factor was concomitant medication.

Radiosurgery for ventricular tachycardia: preclinical and clinical evidence and study design for a German multi-center multi-platform feasibility trial (RAVENTA)

Background

Single-session high-dose stereotactic radiotherapy (radiosurgery) is a new treatment option for otherwise untreatable patients suffering from refractory ventricular tachycardia (VT). In the initial single-center case studies and feasibility trials, cardiac radiosurgery has led to significant reductions of VT burden with limited toxicities. However, the full safety profile remains largely unknown.

Methods/design

In this multi-center, multi-platform clinical feasibility trial which we plan is to assess the initial safety profile of radiosurgery for ventricular tachycardia (RAVENTA). High-precision image-guided single-session radiosurgery with 25 Gy will be delivered to the VT substrate determined by high-definition endocardial electrophysiological mapping. The primary endpoint is safety in terms of successful dose delivery without severe treatment-related side effects in the first 30 days after radiosurgery. Secondary endpoints are the assessment of VT burden, reduction of implantable cardioverter defibrillator (ICD) interventions [shock, anti-tachycardia pacing (ATP)], mid-term side effects and quality-of-life (QoL) in the first year after radiosurgery. The planned sample size is 20 patients with the goal of demonstrating safety and feasibility of cardiac radiosurgery in ≥ 70% of the patients. Quality assurance is provided by initial contouring and planning benchmark studies, joint multi-center treatment decisions, sequential patient safety evaluations, interim analyses, independent monitoring, and a dedicated data and safety monitoring board.

Discussion

RAVENTA will be the first study to provide the initial robust multi-center multi-platform prospective data on the therapeutic value of cardiac radiosurgery for ventricular tachycardia.

Trial registration number

NCT03867747 (clinicaltrials.gov). Registered March 8, 2019. The study was initiated on November 18th, 2019, and is currently recruiting patients.

Graphic abstract

Medical robotics simulation framework for application-specific optimal kinematics

Most kinematic structures in robot architectures for medical tasks are not optimal. Further, the workspace and payloads are often oversized which results in high product prices that are not suitable for a clinical technology transfer. To investigate optimal kinematic structures and configurations, we have developed an adaptive simulation framework with an associated workflow for requirement analyses, modelling and simulation of specific robot kinematics. The framework is used to build simple and cost effective medical robot designs and was evaluated in a tool manipulation task where medical instruments had to be positioned precisely and oriented on the patient's body. The model quality is measured based on the maximum workspace coverage according to a configurable scoring metric. The metric generalizes among different human body shapes that are based on anthropometric data from UMTRI Human Shape. This dexterity measure is used to analyze different kinematic structures in simulations using the open source simulation tool V-REP. Therefor we developed simulation and visualization procedures for medical tasks based on a patchwork of size-variant anatomical target regions that can be configured and selectively activated in a motion planning controller. In our evaluations we compared the dexterity scores of a commercial lightweight robot arm with 7 joints to optimized kinematic structures with 6, 7 and 8 joints. Compared to the commercial hardware, we achieved improvements of 59% when using an optimized 6- dimensional robot arm, 64% with the 7-dimensional arm and 96% with an 8-dimensional robot arm. Our results show that simpler robot designs can outperform the typically used commercial robot arms in medical applications where the maximum workspace coverage is essential. Our framework provides the basis for a fully automatic optimization tool of the robot parameters that can be applied to a large variety of problems.

Efficient Registration of High-Resolution Feature Enhanced Point Clouds

We present a novel framework for rigid point cloud registration. Our approach is based on the principles of mechanics and thermodynamics. We solve the registration problem by assuming point clouds as rigid bodies consisting of particles. Forces can be applied between both particle systems so that they attract or repel each other. These forces are used to cause rigid-body motion of one particle system toward the other, until both are aligned. The framework supports physics-based registration processes with arbitrary driving forces, depending on the desired behaviour. Additionally, the approach handles feature-enhanced point clouds, e.g., by colours or intensity values. Our framework is freely accessible for download. In contrast to already existing algorithms, our contribution is to precisely register high-resolution point clouds with nearly constant computational effort and without the need for pre-processing, sub-sampling or pre-alignment. At the same time, the quality is up to 28 percent higher than for state-of-the-art algorithms and up to 49 percent higher when considering feature-enhanced point clouds. Even in the presence of noise, our registration approach is one of the most robust, on par with state-of-the-art implementations.

A visual probe positioning tool for 4D ultrasound-guided radiotherapy

Ultrasound (US) guidance is a rapidly growing area in image-guided radiotherapy. For motion compensation, the therapy target needs to be visualized with the US probe to continuously determine its position and adapt for shifts. While US has obvious benefits such as real-time capability and proven safety, one of the main drawbacks to date is its user dependency - high quality results require long years of clinical experience. To provide positioning assistance for the setup of US equipment by non-experts, we developed a visual guidance tool combining real-time US volume and CT visualization in a geometrically calibrated setup. By using a 4D US station with real-time data access and an optical tracking system, we achieved a calibration accuracy of 1.2 mm and a mean 2D contour distance of 1.7 mm between organ boundaries identified in US and CT. With this low calibration error as well as the good visual alignment of the structures, the developed probe positioning tool could be a valuable aid for ultrasound-guided radiotherapy and other interventions by guiding the user to a suitable acoustic window while potentially improving setup reproducibility.

Treatment planning for spinal radiosurgery : A competitive multiplatform benchmark challenge

PURPOSE

To investigate the quality of treatment plans of spinal radiosurgery derived from different planning and delivery systems. The comparisons include robotic delivery and intensity modulated arc therapy (IMAT) approaches. Multiple centers with equal systems were used to reduce a bias based on individual's planning abilities. The study used a series of three complex spine lesions to maximize the difference in plan quality among the various approaches.

METHODS

Internationally recognized experts in the field of treatment planning and spinal radiosurgery from 12 centers with various treatment planning systems participated. For a complex spinal lesion, the results were compared against a previously published benchmark plan derived for CyberKnife radiosurgery (CKRS) using circular cones only. For two additional cases, one with multiple small lesions infiltrating three vertebrae and a single vertebra lesion treated with integrated boost, the results were compared against a benchmark plan generated using a best practice guideline for CKRS. All plans were rated based on a previously established ranking system.

RESULTS

All 12 centers could reach equality (n = 4) or outperform (n = 8) the benchmark plan. For the multiple lesions and the single vertebra lesion plan only 5 and 3 of the 12 centers, respectively, reached equality or outperformed the best practice benchmark plan. However, the absolute differences in target and critical structure dosimetry were small and strongly planner-dependent rather than system-dependent. Overall, gantry-based IMAT with simple planning techniques (two coplanar arcs) produced faster treatments and significantly outperformed static gantry intensity modulated radiation therapy (IMRT) and multileaf collimator (MLC) or non-MLC CKRS treatment plan quality regardless of the system (mean rank out of 4 was 1.2 vs. 3.1, p = 0.002).

CONCLUSIONS

High plan quality for complex spinal radiosurgery was achieved among all systems and all participating centers in this planning challenge. This study concludes that simple IMAT techniques can generate significantly better plan quality compared to previous established CKRS benchmarks.

Towards X-ray free endovascular interventions - using HoloLens for on-line holographic visualisation

A major challenge during endovascular interventions is visualising the position and orientation of the catheter being inserted. This is typically achieved by intermittent X-ray imaging. Since the radiation exposure to the surgeon is considerable, it is desirable to reduce X-ray exposure to the bare minimum needed. Additionally, transferring two-dimensional (2D) X-ray images to 3D locations is challenging. The authors present the development of a real-time navigation framework, which allows a 3D holographic view of the vascular system without any need of radiation. They extract the patient's surface and vascular tree from pre-operative computed tomography data and register it to the patient using a magnetic tracking system. The system was evaluated on an anthropomorphic full-body phantom by experienced clinicians using a four-point questionnaire. The average score of the system (maximum of 20) was found to be 17.5. The authors’ approach shows great potential to improve the workflow for endovascular procedures, by simultaneously reducing X-ray exposure. It will also improve the learning curve and help novices to more quickly master the required skills.

Treatment Planning for Self-Shielded Radiosurgery

A five degree of freedom, robotic, radiosurgical system dedicated to the brain is currently under development. In the proposed design, the machine is entirely self-shielded. The main advantage of a self-shielded system is the simplification of the system's installation, which can reduce the cost of radiosurgery. In this way, more patients can benefit from this minimally invasive and highly effective type of procedure. For technical reasons, space inside the shielded region is limited, which leads to constraints on the design. Here, two axes of rotation move a 3-megavolt linear accelerator around the patient’s head at a source axis distance of 400 millimeters (mm), while the integrated patient table is characterized by two additional rotational, and one translational, degrees of freedom. Eight cone collimators of different diameters are available. The system can change the collimator automatically during treatment, using a collimator wheel. Since the linear accelerator can only move with two rotational axes, it is not possible to reposition the beam translationally (as it is in six degrees of freedom robotic radiosurgery). To achieve translational repositioning, it is necessary to move the patient couch. Thus, translational repositioning must be kept to a minimum during treatment. Our goal in this contribution is a preliminary investigation of dose distributions attainable with this type of design. Thus, we do not intend to design and evaluate the treatment planning system itself, but rather to establish that appropriate dose distributions can be achieved with this design under realistic clinical circumstances. Our simulation suggests that dose gradients and conformity for complex target shapes, corresponding to state-of-the-art systems, can be achieved with this construction, although a detailed evaluation of the system itself would be needed in the future.

Simultaneous acquisition of 4D ultrasound and wireless electromagnetic tracking for in-vivo accuracy validation

Ultrasound is being increasingly investigated for real-time target localization in image-guided interventions. Yet, in-vivo validation remains challenging due to the difficulty to obtain a reliable ground truth. For this purpose, real-time volumetric (4D) ultrasound imaging was performed simultaneously with electromagnetic localization of three wireless transponders implanted in the liver of a radiotherapy patient. 4D ultrasound and electromagnetic tracking were acquired at framerates of 12Hz and 8Hz, respectively, during free breathing over 8 min following treatment. The electromagnetic antenna was placed directly above and the ultrasound probe on the right side of the patient to visualize the liver transponders. It was possible to record 25.7 s of overlapping ultrasound and electromagnetic position data of one transponder. Good spatial alignment with 0.6 mm 3D root-mean-square error between both traces was achieved using a rigid landmark transform. However, data acquisition was impaired since the electromagnetic tracking highly influenced the ultrasound equipment and vice versa. High intensity noise streaks appeared in the ultrasound scan lines irrespective of the chosen frequency (1.7-3.3 MHz, 2/4 MHz harmonic). To allow for target visualization and tracking in the ultrasound volumes despite the artefacts, an online filter was designed where corrupted pixels in the newest ultrasound frame were replaced with non-corrupted pixels from preceding frames. Aside from these artefacts, the recorded electromagnetic tracking data was fragmented and only the transponder closest to the antenna could be detected over a limited period of six consecutive breathing cycles. This problem was most likely caused by interference from the metal holder of the ultrasound probe and was solved in a subsequent experiment using a 3D-printed non-metal probe fixation. Real-time wireless electromagnetic tracking was compared with 4D ultrasound imaging in-vivo for the first time. For stable tracking, large metal components need to be avoided during data acquisition and ultrasound filtering is required.

Online 4D ultrasound guidance for real-time motion compensation by MLC tracking

PURPOSE

With the trend in radiotherapy moving toward dose escalation and hypofractionation, the need for highly accurate targeting increases. While MLC tracking is already being successfully used for motion compensation of moving targets in the prostate, current real-time target localization methods rely on repeated x-ray imaging and implanted fiducial markers or electromagnetic transponders rather than direct target visualization. In contrast, ultrasound imaging can yield volumetric data in real-time (3D + time = 4D) without ionizing radiation. The authors report the first results of combining these promising techniques-online 4D ultrasound guidance and MLC tracking-in a phantom.

METHODS

A software framework for real-time target localization was installed directly on a 4D ultrasound station and used to detect a 2 mm spherical lead marker inside a water tank. The lead marker was rigidly attached to a motion stage programmed to reproduce nine characteristic tumor trajectories chosen from large databases (five prostate, four lung). The 3D marker position detected by ultrasound was transferred to a computer program for MLC tracking at a rate of 21.3 Hz and used for real-time MLC aperture adaption on a conventional linear accelerator. The tracking system latency was measured using sinusoidal trajectories and compensated for by applying a kernel density prediction algorithm for the lung traces. To measure geometric accuracy, static anterior and lateral conformal fields as well as a 358° arc with a 10 cm circular aperture were delivered for each trajectory. The two-dimensional (2D) geometric tracking error was measured as the difference between marker position and MLC aperture center in continuously acquired portal images. For dosimetric evaluation, VMAT treatment plans with high and low modulation were delivered to a biplanar diode array dosimeter using the same trajectories. Dose measurements with and without MLC tracking were compared to a static reference dose using 3%/3 mm and 2%/2 mm γ-tests.

RESULTS

The overall tracking system latency was 172 ms. The mean 2D root-mean-square tracking error was 1.03 mm (0.80 mm prostate, 1.31 mm lung). MLC tracking improved the dose delivery in all cases with an overall reduction in the γ-failure rate of 91.2% (3%/3 mm) and 89.9% (2%/2 mm) compared to no motion compensation. Low modulation VMAT plans had no (3%/3 mm) or minimal (2%/2 mm) residual γ-failures while tracking reduced the γ-failure rate from 17.4% to 2.8% (3%/3 mm) and from 33.9% to 6.5% (2%/2 mm) for plans with high modulation.

CONCLUSIONS

Real-time 4D ultrasound tracking was successfully integrated with online MLC tracking for the first time. The developed framework showed an accuracy and latency comparable with other MLC tracking methods while holding the potential to measure and adapt to target motion, including rotation and deformation, noninvasively.

Robotic intrafractional US guidance for liver SABR: System design, beam avoidance, and clinical imaging

PURPOSE

To present a system for robotic 4D ultrasound (US) imaging concurrent with radiotherapy beam delivery and estimate the proportion of liver stereotactic ablative body radiotherapy (SABR) cases in which robotic US image guidance can be deployed without interfering with clinically used VMAT beam configurations.

METHODS

The image guidance hardware comprises a 4D US machine, an optical tracking system for measuring US probe pose, and a custom-designed robot for acquiring hands-free US volumes. In software, a simulation environment incorporating the LINAC, couch, planning CT, and robotic US guidance hardware was developed. Placement of the robotic US hardware was guided by a target visibility map rendered on the CT surface by using the planning CT to simulate US propagation. The visibility map was validated in a prostate phantom and evaluated in patients by capturing live US from imaging positions suggested by the visibility map. In 20 liver SABR patients treated with VMAT, the simulation environment was used to virtually place the robotic hardware and US probe. Imaging targets were either planning target volumes (PTVs, range 5.9-679.5 ml) or gross tumor volumes (GTVs, range 0.9-343.4 ml). Presence or absence of mechanical interference with LINAC, couch, and patient body as well as interferences with treated beams was recorded.

RESULTS

For PTV targets, robotic US guidance without mechanical interference was possible in 80% of the cases and guidance without beam interference was possible in 60% of the cases. For the smaller GTV targets, these proportions were 95% and 85%, respectively. GTV size (1/20), elongated shape (1/20), and depth (1/20) were the main factors limiting the availability of noninterfering imaging positions. The robotic US imaging system was deployed in two liver SABR patients during CT simulation with successful acquisition of 4D US sequences in different imaging positions.

CONCLUSIONS

This study indicates that for VMAT liver SABR, robotic US imaging of a relevant internal target may be possible in 85% of the cases while using treatment plans currently deployed in the clinic. With beam replanning to account for the presence of robotic US guidance, intrafractional US may be an option for 95% of the liver SABR cases.

Dosimetric Implications of Residual Tracking Errors During Robotic SBRT of Liver Metastases

PURPOSE

Although the metric precision of robotic stereotactic body radiation therapy in the presence of breathing motion is widely known, we investigated the dosimetric implications of breathing phase-related residual tracking errors.

METHODS AND MATERIALS

In 24 patients (28 liver metastases) treated with the CyberKnife, we recorded the residual correlation, prediction, and rotational tracking errors from 90 fractions and binned them into 10 breathing phases. The average breathing phase errors were used to shift and rotate the clinical tumor volume (CTV) and planning target volume (PTV) for each phase to calculate a pseudo 4-dimensional error dose distribution for comparison with the original planned dose distribution.

RESULTS

The median systematic directional correlation, prediction, and absolute aggregate rotation errors were 0.3 mm (range, 0.1-1.3 mm), 0.01 mm (range, 0.00-0.05 mm), and 1.5° (range, 0.4°-2.7°), respectively. Dosimetrically, 44%, 81%, and 92% of all voxels differed by less than 1%, 3%, and 5% of the planned local dose, respectively. The median coverage reduction for the PTV was 1.1% (range in coverage difference, -7.8% to +0.8%), significantly depending on correlation (P=.026) and rotational (P=.005) error. With a 3-mm PTV margin, the median coverage change for the CTV was 0.0% (range, -1.0% to +5.4%), not significantly depending on any investigated parameter. In 42% of patients, the 3-mm margin did not fully compensate for the residual tracking errors, resulting in a CTV coverage reduction of 0.1% to 1.0%.

CONCLUSIONS

For liver tumors treated with robotic stereotactic body radiation therapy, a safety margin of 3 mm is not always sufficient to cover all residual tracking errors. Dosimetrically, this translates into only small CTV coverage reductions.

Multifactorial Modeling of Impairment of Evoked Gamma Range Oscillations in Schizophrenia

Despite a significant increase in efforts to identify biomarkers and endophenotypic measures of psychiatric illnesses, only a very limited amount of computational models of these markers and measures has been implemented so far. Moreover, existing computational models dealing with biomarkers typically only examine one possible mechanism in isolation, disregarding the possibility that other combinations of model parameters might produce the same network behavior (what has been termed "multifactoriality"). In this study we describe a step toward a computational instantiation of an endophenotypic finding for schizophrenia, namely the impairment of evoked auditory gamma and beta oscillations in schizophrenia. We explore the multifactorial nature of this impairment using an established model of primary auditory cortex, by performing an extensive search of the parameter space. We find that single network parameters contain only little information about whether the network will show impaired gamma entrainment and that different regions in the parameter space yield similar network level oscillation abnormalities. These regions in the parameter space, however, show strong differences in the underlying network dynamics. To sum up, we present a first step toward an in silico instantiation of an important biomarker of schizophrenia, which has great potential for the identification and study of disease mechanisms and for understanding of existing treatments and development of novel ones.

25th Annual Computational Neuroscience Meeting: CNS-2016

A1 Functional advantages of cell-type heterogeneity in neural circuits

Tatyana O. Sharpee

A2 Mesoscopic modeling of propagating waves in visual cortex

Alain Destexhe

A3 Dynamics and biomarkers of mental disorders

Mitsuo Kawato

F1 Precise recruitment of spiking output at theta frequencies requires dendritic h-channels in multi-compartment models of oriens-lacunosum/moleculare hippocampal interneurons

Vladislav Sekulić, Frances K. Skinner

F2 Kernel methods in reconstruction of current sources from extracellular potentials for single cells and the whole brains

Daniel K. Wójcik, Chaitanya Chintaluri, Dorottya Cserpán, Zoltán Somogyvári

F3 The synchronized periods depend on intracellular transcriptional repression mechanisms in circadian clocks.

Jae Kyoung Kim, Zachary P. Kilpatrick, Matthew R. Bennett, Kresimir Josić

O1 Assessing irregularity and coordination of spiking-bursting rhythms in central pattern generators

Irene Elices, David Arroyo, Rafael Levi, Francisco B. Rodriguez, Pablo Varona

O2 Regulation of top-down processing by cortically-projecting parvalbumin positive neurons in basal forebrain

Eunjin Hwang, Bowon Kim, Hio-Been Han, Tae Kim, James T. McKenna, Ritchie E. Brown, Robert W. McCarley, Jee Hyun Choi

O3 Modeling auditory stream segregation, build-up and bistability

James Rankin, Pamela Osborn Popp, John Rinzel

O4 Strong competition between tonotopic neural ensembles explains pitch-related dynamics of auditory cortex evoked fields

Alejandro Tabas, André Rupp, Emili Balaguer-Ballester

O5 A simple model of retinal response to multi-electrode stimulation

Matias I. Maturana, David B. Grayden, Shaun L. Cloherty, Tatiana Kameneva, Michael R. Ibbotson, Hamish Meffin

O6 Noise correlations in V4 area correlate with behavioral performance in visual discrimination task

Veronika Koren, Timm Lochmann, Valentin Dragoi, Klaus Obermayer

O7 Input-location dependent gain modulation in cerebellar nucleus neurons

Maria Psarrou, Maria Schilstra, Neil Davey, Benjamin Torben-Nielsen, Volker Steuber

O8 Analytic solution of cable energy function for cortical axons and dendrites

Huiwen Ju, Jiao Yu, Michael L. Hines, Liang Chen, Yuguo Yu

O9 C. elegans interactome: interactive visualization of Caenorhabditis elegans worm neuronal network

Jimin Kim, Will Leahy, Eli Shlizerman

O10 Is the model any good? Objective criteria for computational neuroscience model selection

Justas Birgiolas, Richard C. Gerkin, Sharon M. Crook

O11 Cooperation and competition of gamma oscillation mechanisms

Atthaphon Viriyopase, Raoul-Martin Memmesheimer, Stan Gielen

O12 A discrete structure of the brain waves

Yuri Dabaghian, Justin DeVito, Luca Perotti

O13 Direction-specific silencing of the Drosophila gaze stabilization system

Anmo J. Kim, Lisa M. Fenk, Cheng Lyu, Gaby Maimon

O14 What does the fruit fly think about values? A model of olfactory associative learning

Chang Zhao, Yves Widmer, Simon Sprecher,Walter Senn

O15 Effects of ionic diffusion on power spectra of local field potentials (LFP)

Geir Halnes, Tuomo Mäki-Marttunen, Daniel Keller, Klas H. Pettersen,Ole A. Andreassen, Gaute T. Einevoll

O16 Large-scale cortical models towards understanding relationship between brain structure abnormalities and cognitive deficits

Yasunori Yamada

O17 Spatial coarse-graining the brain: origin of minicolumns

Moira L. Steyn-Ross, D. Alistair Steyn-Ross

O18 Modeling large-scale cortical networks with laminar structure

Jorge F. Mejias, John D. Murray, Henry Kennedy, Xiao-Jing Wang

O19 Information filtering by partial synchronous spikes in a neural population

Alexandra Kruscha, Jan Grewe, Jan Benda, Benjamin Lindner

O20 Decoding context-dependent olfactory valence in Drosophila

Laurent Badel, Kazumi Ohta, Yoshiko Tsuchimoto, Hokto Kazama

P1 Neural network as a scale-free network: the role of a hub

B. Kahng

P2 Hemodynamic responses to emotions and decisions using near-infrared spectroscopy optical imaging

Nicoladie D. Tam

P3 Phase space analysis of hemodynamic responses to intentional movement directions using functional near-infrared spectroscopy (fNIRS) optical imaging technique

Nicoladie D.Tam, Luca Pollonini, George Zouridakis

P4 Modeling jamming avoidance of weakly electric fish

Jaehyun Soh, DaeEun Kim

P5 Synergy and redundancy of retinal ganglion cells in prediction

Minsu Yoo, S. E. Palmer

P6 A neural field model with a third dimension representing cortical depth

Viviana Culmone, Ingo Bojak

P7 Network analysis of a probabilistic connectivity model of the Xenopus tadpole spinal cord

Andrea Ferrario, Robert Merrison-Hort, Roman Borisyuk

P8 The recognition dynamics in the brain

Chang Sub Kim

P9 Multivariate spike train analysis using a positive definite kernel

Taro Tezuka

P10 Synchronization of burst periods may govern slow brain dynamics during general anesthesia

Pangyu Joo

P11 The ionic basis of heterogeneity affects stochastic synchrony

Young-Ah Rho, Shawn D. Burton, G. Bard Ermentrout, Jaeseung Jeong, Nathaniel N. Urban

P12 Circular statistics of noise in spike trains with a periodic component

Petr Marsalek

P14 Representations of directions in EEG-BCI using Gaussian readouts

Hoon-Hee Kim, Seok-hyun Moon, Do-won Lee, Sung-beom Lee, Ji-yong Lee, Jaeseung Jeong

P15 Action selection and reinforcement learning in basal ganglia during reaching movements

Yaroslav I. Molkov, Khaldoun Hamade, Wondimu Teka, William H. Barnett, Taegyo Kim, Sergey Markin, Ilya A. Rybak

P17 Axon guidance: modeling axonal growth in T-Junction assay

Csaba Forro, Harald Dermutz, László Demkó, János Vörös

P19 Transient cell assembly networks encode persistent spatial memories

Yuri Dabaghian, Andrey Babichev

P20 Theory of population coupling and applications to describe high order correlations in large populations of interacting neurons

Haiping Huang

P21 Design of biologically-realistic simulations for motor control

Sergio Verduzco-Flores

P22 Towards understanding the functional impact of the behavioural variability of neurons

Filipa Dos Santos, Peter Andras

P23 Different oscillatory dynamics underlying gamma entrainment deficits in schizophrenia

Christoph Metzner, Achim Schweikard, Bartosz Zurowski

P24 Memory recall and spike frequency adaptation

James P. Roach, Leonard M. Sander, Michal R. Zochowski

P25 Stability of neural networks and memory consolidation preferentially occur near criticality

Quinton M. Skilling, Nicolette Ognjanovski, Sara J. Aton, Michal Zochowski

P26 Stochastic Oscillation in Self-Organized Critical States of Small Systems: Sensitive Resting State in Neural Systems

Sheng-Jun Wang, Guang Ouyang, Jing Guang, Mingsha Zhang, K. Y. Michael Wong, Changsong Zhou

P27 Neurofield: a C++ library for fast simulation of 2D neural field models

Peter A. Robinson, Paula Sanz-Leon, Peter M. Drysdale, Felix Fung, Romesh G. Abeysuriya, Chris J. Rennie, Xuelong Zhao

P28 Action-based grounding: Beyond encoding/decoding in neural code

Yoonsuck Choe, Huei-Fang Yang

P29 Neural computation in a dynamical system with multiple time scales

Yuanyuan Mi, Xiaohan Lin, Si Wu

P30 Maximum entropy models for 3D layouts of orientation selectivity

Joscha Liedtke, Manuel Schottdorf, Fred Wolf

P31 A behavioral assay for probing computations underlying curiosity in rodents

Yoriko Yamamura, Jeffery R. Wickens

P32 Using statistical sampling to balance error function contributions to optimization of conductance-based models

Timothy Rumbell, Julia Ramsey, Amy Reyes, Danel Draguljić, Patrick R. Hof, Jennifer Luebke, Christina M. Weaver

P33 Exploration and implementation of a self-growing and self-organizing neuron network building algorithm

Hu He, Xu Yang, Hailin Ma, Zhiheng Xu, Yuzhe Wang

P34 Disrupted resting state brain network in obese subjects: a data-driven graph theory analysis

Kwangyeol Baek, Laurel S. Morris, Prantik Kundu, Valerie Voon

P35 Dynamics of cooperative excitatory and inhibitory plasticity

Everton J. Agnes, Tim P. Vogels

P36 Frequency-dependent oscillatory signal gating in feed-forward networks of integrate-and-fire neurons

William F. Podlaski, Tim P. Vogels

P37 Phenomenological neural model for adaptation of neurons in area IT

Martin Giese, Pradeep Kuravi, Rufin Vogels

P38 ICGenealogy: towards a common topology of neuronal ion channel function and genealogy in model and experiment

Alexander Seeholzer, William Podlaski, Rajnish Ranjan, Tim Vogels

P39 Temporal input discrimination from the interaction between dynamic synapses and neural subthreshold oscillations

Joaquin J. Torres, Fabiano Baroni, Roberto Latorre, Pablo Varona

P40 Different roles for transient and sustained activity during active visual processing

Bart Gips, Eric Lowet, Mark J. Roberts, Peter de Weerd, Ole Jensen, Jan van der Eerden

P41 Scale-free functional networks of 2D Ising model are highly robust against structural defects: neuroscience implications

Abdorreza Goodarzinick, Mohammad D. Niry, Alireza Valizadeh

P42 High frequency neuron can facilitate propagation of signal in neural networks

Aref Pariz, Shervin S. Parsi, Alireza Valizadeh

P43 Investigating the effect of Alzheimer’s disease related amyloidopathy on gamma oscillations in the CA1 region of the hippocampus

Julia M. Warburton, Lucia Marucci, Francesco Tamagnini, Jon Brown, Krasimira Tsaneva-Atanasova

P44 Long-tailed distributions of inhibitory and excitatory weights in a balanced network with eSTDP and iSTDP

Florence I. Kleberg, Jochen Triesch

P45 Simulation of EMG recording from hand muscle due to TMS of motor cortex

Bahar Moezzi, Nicolangelo Iannella, Natalie Schaworonkow, Lukas Plogmacher, Mitchell R. Goldsworthy, Brenton Hordacre, Mark D. McDonnell, Michael C. Ridding, Jochen Triesch

P46 Structure and dynamics of axon network formed in primary cell culture

Martin Zapotocky, Daniel Smit, Coralie Fouquet, Alain Trembleau

P47 Efficient signal processing and sampling in random networks that generate variability

Sakyasingha Dasgupta, Isao Nishikawa, Kazuyuki Aihara, Taro Toyoizumi

P48 Modeling the effect of riluzole on bursting in respiratory neural networks

Daniel T. Robb, Nick Mellen, Natalia Toporikova

P49 Mapping relaxation training using effective connectivity analysis

Rongxiang Tang, Yi-Yuan Tang

P50 Modeling neuron oscillation of implicit sequence learning

Guangsheng Liang, Seth A. Kiser, James H. Howard, Jr., Yi-Yuan Tang

P51 The role of cerebellar short-term synaptic plasticity in the pathology and medication of downbeat nystagmus

Julia Goncharenko, Neil Davey, Maria Schilstra, Volker Steuber

P52 Nonlinear response of noisy neurons

Sergej O. Voronenko, Benjamin Lindner

P53 Behavioral embedding suggests multiple chaotic dimensions underlie C. elegans locomotion

Tosif Ahamed, Greg Stephens

P54 Fast and scalable spike sorting for large and dense multi-electrodes recordings

Pierre Yger, Baptiste Lefebvre, Giulia Lia Beatrice Spampinato, Elric Esposito, Marcel Stimberg et Olivier Marre

P55 Sufficient sampling rates for fast hand motion tracking

Hansol Choi, Min-Ho Song

P56 Linear readout of object manifolds

SueYeon Chung, Dan D. Lee, Haim Sompolinsky

P57 Differentiating models of intrinsic bursting and rhythm generation of the respiratory pre-Bötzinger complex using phase response curves

Ryan S. Phillips, Jeffrey Smith

P58 The effect of inhibitory cell network interactions during theta rhythms on extracellular field potentials in CA1 hippocampus

Alexandra Pierri Chatzikalymniou, Katie Ferguson, Frances K. Skinner

P59 Expansion recoding through sparse sampling in the cerebellar input layer speeds learning

N. Alex Cayco Gajic, Claudia Clopath, R. Angus Silver

P60 A set of curated cortical models at multiple scales on Open Source Brain

Padraig Gleeson, Boris Marin, Sadra Sadeh, Adrian Quintana, Matteo Cantarelli, Salvador Dura-Bernal, William W. Lytton, Andrew Davison, R. Angus Silver

P61 A synaptic story of dynamical information encoding in neural adaptation

Luozheng Li, Wenhao Zhang, Yuanyuan Mi, Dahui Wang, Si Wu

P62 Physical modeling of rule-observant rodent behavior

Youngjo Song, Sol Park, Ilhwan Choi, Jaeseung Jeong, Hee-sup Shin

P64 Predictive coding in area V4 and prefrontal cortex explains dynamic discrimination of partially occluded shapes

Hannah Choi, Anitha Pasupathy, Eric Shea-Brown

P65 Stability of FORCE learning on spiking and rate-based networks

Dongsung Huh, Terrence J. Sejnowski

P66 Stabilising STDP in striatal neurons for reliable fast state recognition in noisy environments

Simon M. Vogt, Arvind Kumar, Robert Schmidt

P67 Electrodiffusion in one- and two-compartment neuron models for characterizing cellular effects of electrical stimulation

Stephen Van Wert, Steven J. Schiff

P68 STDP improves speech recognition capabilities in spiking recurrent circuits parameterized via differential evolution Markov Chain Monte Carlo

Richard Veale, Matthias Scheutz

P69 Bidirectional transformation between dominant cortical neural activities and phase difference distributions

Sang Wan Lee

P70 Maturation of sensory networks through homeostatic structural plasticity

Júlia Gallinaro, Stefan Rotter

P71 Corticothalamic dynamics: structure, number of solutions and stability of steady-state solutions in the space of synaptic couplings

Paula Sanz-Leon, Peter A. Robinson

P72 Optogenetic versus electrical stimulation of the parkinsonian basal ganglia. Computational study

Leonid L. Rubchinsky, Chung Ching Cheung, Shivakeshavan Ratnadurai-Giridharan

P73 Exact spike-timing distribution reveals higher-order interactions of neurons

Safura Rashid Shomali, Majid Nili Ahmadabadi, Hideaki Shimazaki, S. Nader Rasuli

P74 Neural mechanism of visual perceptual learning using a multi-layered neural network

Xiaochen Zhao, Malte J. Rasch

P75 Inferring collective spiking dynamics from mostly unobserved systems

Jens Wilting, Viola Priesemann

P76 How to infer distributions in the brain from subsampled observations

Anna Levina, Viola Priesemann

P77 Influences of embedding and estimation strategies on the inferred memory of single spiking neurons

Lucas Rudelt, Joseph T. Lizier, Viola Priesemann

P78 A nearest-neighbours based estimator for transfer entropy between spike trains

Joseph T. Lizier, Richard E. Spinney, Mikail Rubinov, Michael Wibral, Viola Priesemann

P79 Active learning of psychometric functions with multinomial logistic models

Ji Hyun Bak, Jonathan Pillow

P81 Inferring low-dimensional network dynamics with variational latent Gaussian process

Yuan Zaho, Il Memming Park

P82 Computational investigation of energy landscapes in the resting state subcortical brain network

Jiyoung Kang, Hae-Jeong Park

P83 Local repulsive interaction between retinal ganglion cells can generate a consistent spatial periodicity of orientation map

Jaeson Jang, Se-Bum Paik

P84 Phase duration of bistable perception reveals intrinsic time scale of perceptual decision under noisy condition

Woochul Choi, Se-Bum Paik

P85 Feedforward convergence between retina and primary visual cortex can determine the structure of orientation map

Changju Lee, Jaeson Jang, Se-Bum Paik

P86 Computational method classifying neural network activity patterns for imaging data

Min Song, Hyeonsu Lee, Se-Bum Paik

P87 Symmetry of spike-timing-dependent-plasticity kernels regulates volatility of memory

Youngjin Park, Woochul Choi^, Se-Bum Paik

P88 Effects of time-periodic coupling strength on the first-spike latency dynamics of a scale-free network of stochastic Hodgkin-Huxley neurons

Ergin Yilmaz, Veli Baysal, Mahmut Ozer

P89 Spectral properties of spiking responses in V1 and V4 change within the trial and are highly relevant for behavioral performance

Veronika Koren, Klaus Obermayer

P90 Methods for building accurate models of individual neurons

Daniel Saska, Thomas Nowotny

P91 A full size mathematical model of the early olfactory system of honeybees

Ho Ka Chan, Alan Diamond, Thomas Nowotny

P92 Stimulation-induced tuning of ongoing oscillations in spiking neural networks

Christoph S. Herrmann, Micah M. Murray, Silvio Ionta, Axel Hutt, Jérémie Lefebvre

P93 Decision-specific sequences of neural activity in balanced random networks driven by structured sensory input

Philipp Weidel, Renato Duarte, Abigail Morrison

P94 Modulation of tuning induced by abrupt reduction of SST cell activity

Jung H. Lee, Ramakrishnan Iyer, Stefan Mihalas

P95 The functional role of VIP cell activation during locomotion

Jung H. Lee, Ramakrishnan Iyer, Christof Koch, Stefan Mihalas

P96 Stochastic inference with spiking neural networks

Mihai A. Petrovici, Luziwei Leng, Oliver Breitwieser, David Stöckel, Ilja Bytschok, Roman Martel, Johannes Bill, Johannes Schemmel, Karlheinz Meier

P97 Modeling orientation-selective electrical stimulation with retinal prostheses

Timothy B. Esler, Anthony N. Burkitt, David B. Grayden, Robert R. Kerr, Bahman Tahayori, Hamish Meffin

P98 Ion channel noise can explain firing correlation in auditory nerves

Bahar Moezzi, Nicolangelo Iannella, Mark D. McDonnell

P99 Limits of temporal encoding of thalamocortical inputs in a neocortical microcircuit

Max Nolte, Michael W. Reimann, Eilif Muller, Henry Markram

P100 On the representation of arm reaching movements: a computational model

Antonio Parziale, Rosa Senatore, Angelo Marcelli

P101 A computational model for investigating the role of cerebellum in acquisition and retention of motor behavior

Rosa Senatore, Antonio Parziale, Angelo Marcelli

P102 The emergence of semantic categories from a large-scale brain network of semantic knowledge

K. Skiker, M. Maouene

P103 Multiscale modeling of M1 multitarget pharmacotherapy for dystonia

Samuel A. Neymotin, Salvador Dura-Bernal, Alexandra Seidenstein, Peter Lakatos, Terence D. Sanger, William W. Lytton

P104 Effect of network size on computational capacity

Salvador Dura-Bernal, Rosemary J. Menzies, Campbell McLauchlan, Sacha J. van Albada, David J. Kedziora, Samuel Neymotin, William W. Lytton, Cliff C. Kerr

P105 NetPyNE: a Python package for NEURON to facilitate development and parallel simulation of biological neuronal networks

Salvador Dura-Bernal, Benjamin A. Suter, Samuel A. Neymotin, Cliff C. Kerr, Adrian Quintana, Padraig Gleeson, Gordon M. G. Shepherd, William W. Lytton

P107 Inter-areal and inter-regional inhomogeneity in co-axial anisotropy of Cortical Point Spread in human visual areas

Juhyoung Ryu, Sang-Hun Lee

P108 Two bayesian quanta of uncertainty explain the temporal dynamics of cortical activity in the non-sensory areas during bistable perception

Joonwon Lee, Sang-Hun Lee

P109 Optimal and suboptimal integration of sensory and value information in perceptual decision making

Hyang Jung Lee, Sang-Hun Lee

P110 A Bayesian algorithm for phoneme Perception and its neural implementation

Daeseob Lim, Sang-Hun Lee

P111 Complexity of EEG signals is reduced during unconsciousness induced by ketamine and propofol

Jisung Wang, Heonsoo Lee

P112 Self-organized criticality of neural avalanche in a neural model on complex networks

Nam Jung, Le Anh Quang, Seung Eun Maeng, Tae Ho Lee, Jae Woo Lee

P113 Dynamic alterations in connection topology of the hippocampal network during ictal-like epileptiform activity in an in vitro rat model

Chang-hyun Park, Sora Ahn, Jangsup Moon, Yun Seo Choi, Juhee Kim, Sang Beom Jun, Seungjun Lee, Hyang Woon Lee

P114 Computational model to replicate seizure suppression effect by electrical stimulation

Sora Ahn, Sumin Jo, Eunji Jun, Suin Yu, Hyang Woon Lee, Sang Beom Jun, Seungjun Lee

P115 Identifying excitatory and inhibitory synapses in neuronal networks from spike trains using sorted local transfer entropy

Felix Goetze, Pik-Yin Lai

P116 Neural network model for obstacle avoidance based on neuromorphic computational model of boundary vector cell and head direction cell

Seonghyun Kim, Jeehyun Kwag

P117 Dynamic gating of spike pattern propagation by Hebbian and anti-Hebbian spike timing-dependent plasticity in excitatory feedforward network model

Hyun Jae Jang, Jeehyun Kwag

P118 Inferring characteristics of input correlations of cells exhibiting up-down state transitions in the rat striatum

Marko Filipović, Ramon Reig, Ad Aertsen, Gilad Silberberg, Arvind Kumar

P119 Graph properties of the functional connected brain under the influence of Alzheimer’s disease

Claudia Bachmann, Simone Buttler, Heidi Jacobs, Kim Dillen, Gereon R. Fink, Juraj Kukolja, Abigail Morrison

P120 Learning sparse representations in the olfactory bulb

Daniel Kepple, Hamza Giaffar, Dima Rinberg, Steven Shea, Alex Koulakov

P121 Functional classification of homologous basal-ganglia networks

Jyotika Bahuguna,Tom Tetzlaff, Abigail Morrison, Arvind Kumar, Jeanette Hellgren Kotaleski

P122 Short term memory based on multistability

Tim Kunze, Andre Peterson, Thomas Knösche

P123 A physiologically plausible, computationally efficient model and simulation software for mammalian motor units

Minjung Kim, Hojeong Kim

P125 Decoding laser-induced somatosensory information from EEG

Ji Sung Park, Ji Won Yeon, Sung-Phil Kim

P126 Phase synchronization of alpha activity for EEG-based personal authentication

Jae-Hwan Kang, Chungho Lee, Sung-Phil Kim

P129 Investigating phase-lags in sEEG data using spatially distributed time delays in a large-scale brain network model

Andreas Spiegler, Spase Petkoski, Matias J. Palva, Viktor K. Jirsa

P130 Epileptic seizures in the unfolding of a codimension-3 singularity

Maria L. Saggio, Silvan F. Siep, Andreas Spiegler, William C. Stacey, Christophe Bernard, Viktor K. Jirsa

P131 Incremental dimensional exploratory reasoning under multi-dimensional environment

Oh-hyeon Choung, Yong Jeong

P132 A low-cost model of eye movements and memory in personal visual cognition

Yong-il Lee, Jaeseung Jeong

P133 Complex network analysis of structural connectome of autism spectrum disorder patients

Su Hyun Kim, Mir Jeong, Jaeseung Jeong

P134 Cognitive motives and the neural correlates underlying human social information transmission, gossip

Jeungmin Lee, Jaehyung Kwon, Jerald D. Kralik, Jaeseung Jeong

P135 EEG hyperscanning detects neural oscillation for the social interaction during the economic decision-making

Jaehwan Jahng, Dong-Uk Hwang, Jaeseung Jeong

P136 Detecting purchase decision based on hyperfrontality of the EEG

Jae-Hyung Kwon, Sang-Min Park, Jaeseung Jeong

P137 Vulnerability-based critical neurons, synapses, and pathways in the Caenorhabditis elegans connectome

Seongkyun Kim, Hyoungkyu Kim, Jerald D. Kralik, Jaeseung Jeong

P138 Motif analysis reveals functionally asymmetrical neurons in C. elegans

Pyeong Soo Kim, Seongkyun Kim, Hyoungkyu Kim, Jaeseung Jeong

P139 Computational approach to preference-based serial decision dynamics: do temporal discounting and working memory affect it?

Sangsup Yoon, Jaehyung Kwon, Sewoong Lim, Jaeseung Jeong

P141 Social stress induced neural network reconfiguration affects decision making and learning in zebrafish

Choongseok Park, Thomas Miller, Katie Clements, Sungwoo Ahn, Eoon Hye Ji, Fadi A. Issa

P142 Descriptive, generative, and hybrid approaches for neural connectivity inference from neural activity data

JeongHun Baek, Shigeyuki Oba, Junichiro Yoshimoto, Kenji Doya, Shin Ishii

P145 Divergent-convergent synaptic connectivities accelerate coding in multilayered sensory systems

Thiago S. Mosqueiro, Martin F. Strube-Bloss, Brian Smith, Ramon Huerta

P146 Swinging networks

Michal Hadrava, Jaroslav Hlinka

P147 Inferring dynamically relevant motifs from oscillatory stimuli: challenges, pitfalls, and solutions

Hannah Bos, Moritz Helias

P148 Spatiotemporal mapping of brain network dynamics during cognitive tasks using magnetoencephalography and deep learning

Charles M. Welzig, Zachary J. Harper

P149 Multiscale complexity analysis for the segmentation of MRI images

Won Sup Kim, In-Seob Shin, Hyeon-Man Baek, Seung Kee Han

P150 A neuro-computational model of emotional attention

René Richter, Julien Vitay, Frederick Beuth, Fred H. Hamker

P151 Multi-site delayed feedback stimulation in parkinsonian networks

Kelly Toppin, Yixin Guo

P152 Bistability in Hodgkin–Huxley-type equations

Tatiana Kameneva, Hamish Meffin, Anthony N. Burkitt, David B. Grayden

P153 Phase changes in postsynaptic spiking due to synaptic connectivity and short term plasticity: mathematical analysis of frequency dependency

Mark D. McDonnell, Bruce P. Graham

P154 Quantifying resilience patterns in brain networks: the importance of directionality

Penelope J. Kale, Leonardo L. Gollo

P155 Dynamics of rate-model networks with separate excitatory and inhibitory populations

Merav Stern, L. F. Abbott

P156 A model for multi-stable dynamics in action recognition modulated by integration of silhouette and shading cues

Leonid A. Fedorov, Martin A. Giese

P157 Spiking model for the interaction between action recognition and action execution

Mohammad Hovaidi Ardestani, Martin Giese

P158 Surprise-modulated belief update: how to learn within changing environments?

Mohammad Javad Faraji, Kerstin Preuschoff, Wulfram Gerstner

P159 A fast, stochastic and adaptive model of auditory nerve responses to cochlear implant stimulation

Margriet J. van Gendt, Jeroen J. Briaire, Randy K. Kalkman, Johan H. M. Frijns

P160 Quantitative comparison of graph theoretical measures of simulated and empirical functional brain networks

Won Hee Lee, Sophia Frangou

P161 Determining discriminative properties of fMRI signals in schizophrenia using highly comparative time-series analysis

Ben D. Fulcher, Patricia H. P. Tran, Alex Fornito

P162 Emergence of narrowband LFP oscillations from completely asynchronous activity during seizures and high-frequency oscillations

Stephen V. Gliske, William C. Stacey, Eugene Lim, Katherine A. Holman, Christian G. Fink

P163 Neuronal diversity in structure and function: cross-validation of anatomical and physiological classification of retinal ganglion cells in the mouse

Jinseop S. Kim, Shang Mu, Kevin L. Briggman, H. Sebastian Seung, the EyeWirers

P164 Analysis and modelling of transient firing rate changes in area MT in response to rapid stimulus feature changes

Detlef Wegener, Lisa Bohnenkamp, Udo A. Ernst

P165 Step-wise model fitting accounting for high-resolution spatial measurements: construction of a layer V pyramidal cell model with reduced morphology

Tuomo Mäki-Marttunen, Geir Halnes, Anna Devor, Christoph Metzner, Anders M. Dale, Ole A. Andreassen, Gaute T. Einevoll

P166 Contributions of schizophrenia-associated genes to neuron firing and cardiac pacemaking: a polygenic modeling approach

Tuomo Mäki-Marttunen, Glenn T. Lines, Andy Edwards, Aslak Tveito, Anders M. Dale, Gaute T. Einevoll, Ole A. Andreassen

P167 Local field potentials in a 4 × 4 mm² multi-layered network model

Espen Hagen, Johanna Senk, Sacha J. van Albada, Markus Diesmann

P168 A spiking network model explains multi-scale properties of cortical dynamics

Maximilian Schmidt, Rembrandt Bakker, Kelly Shen, Gleb Bezgin, Claus-Christian Hilgetag, Markus Diesmann, Sacha Jennifer van Albada

P169 Using joint weight-delay spike-timing dependent plasticity to find polychronous neuronal groups

Haoqi Sun, Olga Sourina, Guang-Bin Huang, Felix Klanner, Cornelia Denk

P170 Tensor decomposition reveals RSNs in simulated resting state fMRI

Katharina Glomb, Adrián Ponce-Alvarez, Matthieu Gilson, Petra Ritter, Gustavo Deco

P171 Getting in the groove: testing a new model-based method for comparing task-evoked vs resting-state activity in fMRI data on music listening

Matthieu Gilson, Maria AG Witek, Eric F. Clarke, Mads Hansen, Mikkel Wallentin, Gustavo Deco, Morten L. Kringelbach^, Peter Vuust

P172 STochastic engine for pathway simulation (STEPS) on massively parallel processors

Guido Klingbeil, Erik De Schutter

P173 Toolkit support for complex parallel spatial stochastic reaction–diffusion simulation in STEPS

Weiliang Chen, Erik De Schutter

P174 Modeling the generation and propagation of Purkinje cell dendritic spikes caused by parallel fiber synaptic input

Yunliang Zang, Erik De Schutter

P175 Dendritic morphology determines how dendrites are organized into functional subunits

Sungho Hong, Akira Takashima, Erik De Schutter

P176 A model of Ca²⁺/calmodulin-dependent protein kinase II activity in long term depression at Purkinje cells

Criseida Zamora, Andrew R. Gallimore, Erik De Schutter

P177 Reward-modulated learning of population-encoded vectors for insect-like navigation in embodied agents

Dennis Goldschmidt, Poramate Manoonpong, Sakyasingha Dasgupta

P178 Data-driven neural models part II: connectivity patterns of human seizures

Philippa J. Karoly, Dean R. Freestone, Daniel Soundry, Levin Kuhlmann, Liam Paninski, Mark Cook

P179 Data-driven neural models part I: state and parameter estimation

Dean R. Freestone, Philippa J. Karoly, Daniel Soundry, Levin Kuhlmann, Mark Cook

P180 Spectral and spatial information processing in human auditory streaming

Jaejin Lee, Yonatan I. Fishman, Yale E. Cohen

P181 A tuning curve for the global effects of local perturbations in neural activity: Mapping the systems-level susceptibility of the brain

Leonardo L. Gollo, James A. Roberts, Luca Cocchi

P182 Diverse homeostatic responses to visual deprivation mediated by neural ensembles

Yann Sweeney, Claudia Clopath

P183 Opto-EEG: a novel method for investigating functional connectome in mouse brain based on optogenetics and high density electroencephalography

Soohyun Lee, Woo-Sung Jung, Jee Hyun Choi

P184 Biphasic responses of frontal gamma network to repetitive sleep deprivation during REM sleep

Bowon Kim, Youngsoo Kim, Eunjin Hwang, Jee Hyun Choi

P185 Brain-state correlate and cortical connectivity for frontal gamma oscillations in top-down fashion assessed by auditory steady-state response

Younginha Jung, Eunjin Hwang, Yoon-Kyu Song, Jee Hyun Choi

P186 Neural field model of localized orientation selective activation in V1

James Rankin, Frédéric Chavane

P187 An oscillatory network model of Head direction and Grid cells using locomotor inputs

Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P188 A computational model of hippocampus inspired by the functional architecture of basal ganglia

Karthik Soman, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P189 A computational architecture to model the microanatomy of the striatum and its functional properties

Sabyasachi Shivkumar, Vignesh Muralidharan, V. Srinivasa Chakravarthy

P190 A scalable cortico-basal ganglia model to understand the neural dynamics of targeted reaching

Vignesh Muralidharan, Alekhya Mandali, B. Pragathi Priyadharsini, Hima Mehta, V. Srinivasa Chakravarthy

P191 Emergence of radial orientation selectivity from synaptic plasticity

Catherine E. Davey, David B. Grayden, Anthony N. Burkitt

P192 How do hidden units shape effective connections between neurons?

Braden A. W. Brinkman, Tyler Kekona, Fred Rieke, Eric Shea-Brown, Michael Buice

P193 Characterization of neural firing in the presence of astrocyte-synapse signaling

Maurizio De Pittà, Hugues Berry, Nicolas Brunel

P194 Metastability of spatiotemporal patterns in a large-scale network model of brain dynamics

James A. Roberts, Leonardo L. Gollo, Michael Breakspear

P195 Comparison of three methods to quantify detection and discrimination capacity estimated from neural population recordings

Gary Marsat, Jordan Drew, Phillip D. Chapman, Kevin C. Daly, Samual P. Bradley

P196 Quantifying the constraints for independent evoked and spontaneous NMDA receptor mediated synaptic transmission at individual synapses

Sat Byul Seo, Jianzhong Su, Ege T. Kavalali, Justin Blackwell

P199 Gamma oscillation via adaptive exponential integrate-and-fire neurons

LieJune Shiau, Laure Buhry, Kanishka Basnayake

P200 Visual face representations during memory retrieval compared to perception

Sue-Hyun Lee, Brandon A. Levy, Chris I. Baker

P201 Top-down modulation of sequential activity within packets modeled using avalanche dynamics

Timothée Leleu, Kazuyuki Aihara

Q28 An auto-encoder network realizes sparse features under the influence of desynchronized vascular dynamics

Ryan T. Philips, Karishma Chhabria, V. Srinivasa Chakravarthy

Treatment Planning Considerations for Robotic Guided Cardiac Radiosurgery for Atrial Fibrillation

Purpose

Robotic guided stereotactic radiosurgery has recently been investigated for the treatment of atrial fibrillation (AF). Before moving into human treatments, multiple implications for treatment planning given a potential target tracking approach have to be considered.   

Materials & Methods

Theoretical AF radiosurgery treatment plans for twenty-four patients were generated for baseline comparison. Eighteen patients were investigated under ideal tracking conditions, twelve patients under regional dose rate (RDR = applied dose over a certain time window) optimized conditions (beam delivery sequence sorting according to regional beam targeting), four patients under ultrasound tracking conditions (beam block of the ultrasound probe) and four patients with temporary single fiducial tracking conditions (differential surrogate-to-target respiratory and cardiac motion).  

Results

With currently known guidelines on dose limitations of critical structures, treatment planning for AF radiosurgery with 25 Gy under ideal tracking conditions with a 3 mm safety margin may only be feasible in less than 40% of the patients due to the unfavorable esophagus and bronchial tree location relative to the left atrial antrum (target area). Beam delivery sequence sorting showed a large increase in RDR coverage (% of voxels having a larger dose rate for a given time window) of 10.8-92.4% (median, 38.0%) for a 40-50 min time window, which may be significant for non-malignant targets. For ultrasound tracking, blocking beams through the ultrasound probe was found to have no visible impact on plan quality given previous optimal ultrasound window estimation for the planning CT. For fiducial tracking in the right atrial septum, the differential motion may reduce target coverage by up to -24.9% which could be reduced to a median of -0.8% (maximum, -12.0%) by using 4D dose optimization. The cardiac motion was also found to have an impact on the dose distribution, at the anterior left atrial wall; however, the results need to be verified.

Conclusion

Robotic AF radiosurgery with 25 Gy may be feasible in a subgroup of patients under ideal tracking conditions. Ultrasound tracking was found to have the lowest impact on treatment planning and given its real-time imaging capability should be considered for AF robotic radiosurgery. Nevertheless, advanced treatment planning using RDR or 4D respiratory and cardiac dose optimization may be still advised despite using ideal tracking methods.

Efficient Linear Unboundedness Testing: Algorithm and Applications to Translational Assembly Planning

We address the problem of efficiently testing for linear unboundedness and its applications to translational assembly planning. We describe a new algorithm that performs the test by solving a single homogeneous system of equations followed by a single linear feasibility test. We show that testing for unboundedness is computationally at least as hard as these two subproblems. The new algorithm is the fastest known algorithm and is practical. We then present a framework for general translational assembly planning based on linear constraints. We show the relation of m-handed assembly planning to unboundedness testing and present a polynomial-time algorithm for m-handed assembly of polygonal part assemblies with no initially separated pairs of parts. For the general translational assembly–planning problem, we present a new algorithm that uses unboundedness testing and a cell reduction technique to significantly increase the search efficiency. Experimental results of our implementation on a variety of planar and spatial assemblies demonstrate the practicality of the algorithms.

Technical Description, Phantom Accuracy, and Clinical Feasibility for Single-Session Lung Radiosurgery Using Robotic Image-Guided Real-time Respiratory Tumor Tracking

To describe the technological background, the accuracy, and clinical feasibility for single session lung radiosurgery using a real-time robotic system with respiratory tracking. The latest version of image-guided real-time respiratory tracking software (Synchrony®, Accuray Incorporated, Sunnyvale, CA) was applied and is described. Accuracy measurements were performed using a newly designed moving phantom model. We treated 15 patients with 19 lung tumors with robotic radiosurgery (CyberKnife®, Accuray) using the same treatment parameters for all patients. Ten patients had primary tumors and five had metastatic tumors. All patients underwent computed tomography-guided percutaneous placement of one fiducial directly into the tumor, and were all treated with single session radiosurgery to a dose of 24 Gy. Follow up CT scanning was performed every two months.

All patients could be treated with the automated robotic technique. The respiratory tracking error was less than 1 mm and the overall shape of the dose profile was not affected by target motion and/or phase shift between fiducial and optical marker motion. Two patients required a chest tube insertion after fiducial implantation because of pneumothorax. One patient experienced nausea after treatment. No other short-term adverse reactions were found. One patient showed imaging signs of pneumonitis without a clinical correlation.

Single-session radiosurgery for lung tumor tracking using the described technology is a stable, safe, and feasible concept for respiratory tracking of tumors during robotic lung radiosurgery in selected patients. Longer follow-up is needed for definitive clinical results.

Enhanced Optical Head Tracking for Cranial Radiation Therapy: Supporting Surface Registration by Cutaneous Structures

PURPOSE

To support surface registration in cranial radiation therapy by structural information. The risk for spatial ambiguities is minimized by using tissue thickness variations predicted from backscattered near-infrared (NIR) light from the forehead.

METHODS AND MATERIALS

In a pilot study we recorded NIR surface scans by laser triangulation from 30 volunteers of different skin type. A ground truth for the soft-tissue thickness was segmented from MR scans. After initially matching the NIR scans to the MR reference, Gaussian processes were trained to predict tissue thicknesses from NIR backscatter. Moreover, motion starting from this initial registration was simulated by 5000 random transformations of the NIR scan away from the MR reference. Re-registration to the MR scan was compared with and without tissue thickness support.

RESULTS

By adding prior knowledge to the backscatter features, such as incident angle and neighborhood information in the scanning grid, we showed that tissue thickness can be predicted with mean errors of <0.2 mm, irrespective of the skin type. With this additional information, the average registration error improved from 3.4 mm to 0.48 mm by a factor of 7. Misalignments of more than 1 mm were almost thoroughly (98.9%) pushed below 1 mm.

CONCLUSIONS

For almost all cases tissue-enhanced matching achieved better results than purely spatial registration. Ambiguities can be minimized if the cutaneous structures do not agree. This valuable support for surface registration increases tracking robustness and avoids misalignment of tumor targets far from the registration site.

Inverse treatment planning for spinal robotic radiosurgery: an international multi-institutional benchmark trial

Stereotactic radiosurgery (SRS) is the accurate, conformal delivery of high‐dose radiation to well‐defined targets while minimizing normal structure doses via steep dose gradients. While inverse treatment planning (ITP) with computerized optimization algorithms are routine, many aspects of the planning process remain user‐dependent. We performed an international, multi‐institutional benchmark trial to study planning variability and to analyze preferable ITP practice for spinal robotic radiosurgery. 10 SRS treatment plans were generated for a complex‐shaped spinal metastasis with 21 Gy in 3 fractions and tight constraints for spinal cord (V14Gy<2 cc, V18Gy<0.1 cc) and target (coverage >95%). The resulting plans were rated on a scale from 1 to 4 (excellent‐poor) in five categories (constraint compliance, optimization goals, low‐dose regions, ITP complexity, and clinical acceptability) by a blinded review panel. Additionally, the plans were mathematically rated based on plan indices (critical structure and target doses, conformity, monitor units, normal tissue complication probability, and treatment time) and compared to the human rankings. The treatment plans and the reviewers' rankings varied substantially among the participating centers. The average mean overall rank was 2.4 (1.2‐4.0) and 8/10 plans were rated excellent in at least one category by at least one reviewer. The mathematical rankings agreed with the mean overall human rankings in 9/10 cases pointing toward the possibility for sole mathematical plan quality comparison. The final rankings revealed that a plan with a well‐balanced trade‐off among all planning objectives was preferred for treatment by most participants, reviewers, and the mathematical ranking system. Furthermore, this plan was generated with simple planning techniques. Our multi‐institutional planning study found wide variability in ITP approaches for spinal robotic radiosurgery. The participants', reviewers', and mathematical match on preferable treatment plans and ITP techniques indicate that agreement on treatment planning and plan quality can be reached for spinal robotic radiosurgery.

PACS number(s): 87.55.de

Efficient estimation of tissue thicknesses using sparse approximation for Gaussian processes

Highly accurate localization of the human skull is vital in cranial radiotherapy. Marker-less optical head tracking provides a fast and accurate way to monitor this motion. Recent research has given evidence that marker-less tracking of the forehead benefits from tissue thickness information in addition to the 3D surface geometry. Using Gaussian Processes (GPs) tissue thickness is determined from optical backscatter of a sweeping laser. However, the computational complexity of the GPs scales cubically with the number of training samples. A full head scan contains 1024 points, whereas scans from several perspectives may be required for a comprehensive model for each subject. In five subjects, we thus evaluate sparse approximation methods to reduce the computational effort. We found a better - computation time versus root mean square error (RMSE) - tradeoff for a simple subset of data (SoD) technique. The increase of RMSE when dropping data was not found steep enough to justify the computational overhead of a better approximation by inducing point methods (namely FITC). Promising results were, however, obtained when clustering the training data before selecting the subset.

Radiotherapy beyond cancer: target localization in real-time MRI and treatment planning for cardiac radiosurgery

PURPOSE

Atrial fibrillation (AFib) is the most common cardiac arrhythmia that affects millions of patients world-wide. AFib is usually treated with minimally invasive, time consuming catheter ablation techniques. While recently noninvasive radiosurgery to the pulmonary vein antrum (PVA) in the left atrium has been proposed for AFib treatment, precise target location during treatment is challenging due to complex respiratory and cardiac motion. A MRI linear accelerator (MRI-Linac) could solve the problems of motion tracking and compensation using real-time image guidance. In this study, the authors quantified target motion ranges on cardiac magnetic resonance imaging (MRI) and analyzed the dosimetric benefits of margin reduction assuming real-time motion compensation was applied.

METHODS

For the imaging study, six human subjects underwent real-time cardiac MRI under free breathing. The target motion was analyzed retrospectively using a template matching algorithm. The planning study was conducted on a CT of an AFib patient with a centrally located esophagus undergoing catheter ablation, representing an ideal case for cardiac radiosurgery. The target definition was similar to the ablation lesions at the PVA created during catheter treatment. Safety margins of 0 mm (perfect tracking) to 8 mm (untracked respiratory motion) were added to the target, defining the planning target volume (PTV). For each margin, a 30 Gy single fraction IMRT plan was generated. Additionally, the influence of 1 and 3 T magnetic fields on the treatment beam delivery was simulated using Monte Carlo calculations to determine the dosimetric impact of MRI guidance for two different Linac positions.

RESULTS

Real-time cardiac MRI showed mean respiratory target motion of 10.2 mm (superior-inferior), 2.4 mm (anterior-posterior), and 2 mm (left-right). The planning study showed that increasing safety margins to encompass untracked respiratory motion leads to overlapping structures even in the ideal scenario, compromising either normal tissue dose constraints or PTV coverage. The magnetic field caused a slight increase in the PTV dose with the in-line MRI-Linac configuration.

CONCLUSIONS

The authors' results indicate that real-time tracking and motion compensation are mandatory for cardiac radiosurgery and MRI-guidance is feasible, opening the possibility of treating cardiac arrhythmia patients completely noninvasively.

Multitask Gaussian processes for multivariate physiological time-series analysis

Gaussian process (GP) models are a flexible means of performing nonparametric Bayesian regression. However, GP models in healthcare are often only used to model a single univariate output time series, denoted as single-task GPs (STGP). Due to an increasing prevalence of sensors in healthcare settings, there is an urgent need for robust multivariate time-series tools. Here, we propose a method using multitask GPs (MTGPs) which can model multiple correlated multivariate physiological time series simultaneously. The flexible MTGP framework can learn the correlation between multiple signals even though they might be sampled at different frequencies and have training sets available for different intervals. Furthermore, prior knowledge of any relationship between the time series such as delays and temporal behavior can be easily integrated. A novel normalization is proposed to allow interpretation of the various hyperparameters used in the MTGP. We investigate MTGPs for physiological monitoring with synthetic data sets and two real-world problems from the field of patient monitoring and radiotherapy. The results are compared with standard Gaussian processes and other existing methods in the respective biomedical application areas. In both cases, we show that our framework learned the correlation between physiological time series efficiently, outperforming the existing state of the art.

Micro-anatomical and functional assessment of ciliated epithelium in mouse trachea using optical coherence phase microscopy

Motile cilia perform a range of important mechanosensory and chemosensory functions, along with expulsion of mucus and inhaled pathogens from the lungs. Here we demonstrate that spectral domain optical coherence phase microscopy (SD-OCPM), which combines the principles of optical coherence tomography (OCT) and confocal microscopy, is particularly well-suited for characterization of both morphology and the ciliary dynamics of mouse trachea. We present micro-anatomical images of mouse trachea, where different cell types can be clearly visualized. The phase contrast, which measures the sub-nanometer changes in axial optical pathlength is used to determine the frequency and direction of cilia beatings.

Tissue segmentation from head MRI: a ground truth validation for feature-enhanced tracking

Accuracy is essential for optical head-tracking in cranial radiotherapy. Recently, the exploitation of local patterns of tissue information was proposed to achieve a more robust registration. Here, we validate a ground truth for this information obtained from high resolution MRI scans. In five subjects we compared the segmentation accuracy of a semi-automatic algorithm with five human experts. While the algorithm segments the skin and bone surface with an average accuracy of less than 0.1 mm and 0.2 mm, respectively, the mean error on the tissue thickness was 0.17 mm. We conclude that this accuracy is a reasonable basis for extracting reliable cutaneous structures to support surface registration.

Closed-loop transcranial alternating current stimulation of slow oscillations

Transcranial alternating current stimulation (tACS) is an emerging non-invasive tool for modulating brain oscillations. There is evidence that weak oscillatory electrical stimulation during sleep can entrain cortical slow oscillations to improve the memory consolidation in rodents and humans. Using a novel method and a custom built stimulation device, automatic stimulation of slow oscillations in-phase with the endogenous activity in a real-time closed-loop setup is possible. Preliminary data from neuroplasticity experiments show a high detection performance of the proposed method, electrical measurements demonstrate the outstanding quality of the presented stimulation device.

Enriching 3D optical surface scans with prior knowledge: tissue thickness computation by exploiting local neighborhoods

PURPOSE

Patient immobilization and X-ray-based imaging provide neither a convenient nor a very accurate way to ensure low repositioning errors or to compensate for motion in cranial radiotherapy. We therefore propose an optical tracking device that exploits subcutaneous structures as landmarks in addition to merely spatial registration. To develop such head tracking algorithms, precise and robust computation of these structures is necessary. Here, we show that the tissue thickness can be predicted with high accuracy and moreover exploit local neighborhood information within the laser spot grid on the forehead to further increase this estimation accuracy.

METHODS

We use statistical learning with Support Vector Regression and Gaussian Processes to learn a relationship between optical backscatter features and an MR tissue thickness ground truth. We compare different kernel functions for the data of five different subjects. The incident angle of the laser on the forehead as well as local neighborhoods is incorporated into the feature space. The latter represent the backscatter features from four neighboring laser spots.

RESULTS

We confirm that the incident angle has a positive effect on the estimation error of the tissue thickness. The root-mean-square error falls even below 0.15 mm when adding the complete neighborhood information. This prior knowledge also leads to a smoothing effect on the reconstructed skin patch. Learning between different head poses yields similar results. The partial overlap of the point clouds makes the trade-off between novel information and increased feature space dimension obvious and hence feature selection by e.g., sequential forward selection necessary.

Transcranial magnetic stimulation reveals complex cognitive control representations in the rostral frontal cortex

Convergent evidence suggests that the lateral frontal cortex is at the heart of a brain network subserving cognitive control. Recent theories assume a functional segregation along the rostro-caudal axis of the lateral frontal cortex based on differences in the degree of complexity of cognitive control. However, the functional contribution of specific rostral and caudal sub-regions remains elusive. Here we investigate the impact of disrupting rostral and caudal target regions on cognitive control processes, using Transcranial Magnetic Stimulation (TMS). Participants performed three different task-switching conditions that assessed differences in the degree of complexity of cognitive control processes, after temporally disrupting rostral, or caudal target regions, or a control region. Disrupting the rostral lateral frontal region specifically impaired behavioral performance of the most complex task-switching condition, in comparison to the caudal target region and the control region. These novel findings shed light on the neuroanatomical architecture supporting control over goal-directed behavior.

Tissue thickness estimation for high precision head-tracking using a galvanometric laser scanner - a case study

Marker-less optical head-tracking constitutes a comfortable alternative with no exposure to radiation for realtime monitoring in radiation therapy. Supporting information such as tissue thickness has the potential to improve spatial tracking accuracy. Here we study how accurate tissue thickness can be estimated from the near-infrared (NIR) backscatter obtained from laser scans. In a case study, optical data was recorded with a galvanometric laser scanner from three subjects. A tissue ground truth from MRI was robustly matched via customized bite blocks. We show that Gaussian Processes accurately model the relationship between NIR features and tissue thickness. They were able to predict the tissue thickness with less than 0.5 mm root mean square error. Individual scaling factors for all features and an additional incident angle feature had positive effects on this performance.

An Approach to Improve Accuracy of Optical Tracking Systems in Cranial Radiation Therapy

This work presents a new method for the accurate estimation of soft tissue thickness based on near infrared (NIR) laser measurements. By using this estimation, our goal is to develop an improved non-invasive marker-less optical tracking system for cranial radiation therapy. Results are presented for three subjects and reveal an RMS error of less than 0.34 mm.

Accuracy analysis for triangulation and tracking based on time-multiplexed structured light

PURPOSE

The authors' research group is currently developing a new optical head tracking system for intracranial radiosurgery. This tracking system utilizes infrared laser light to measure features of the soft tissue on the patient's forehead. These features are intended to offer highly accurate registration with respect to the rigid skull structure by means of compensating for the soft tissue. In this context, the system also has to be able to quickly generate accurate reconstructions of the skin surface. For this purpose, the authors have developed a laser scanning device which uses time-multiplexed structured light to triangulate surface points.

METHODS

The accuracy of the authors' laser scanning device is analyzed and compared for different triangulation methods. These methods are given by the Linear-Eigen method and a nonlinear least squares method. Since Microsoft's Kinect camera represents an alternative for fast surface reconstruction, the authors' results are also compared to the triangulation accuracy of the Kinect device. Moreover, the authors' laser scanning device was used for tracking of a rigid object to determine how this process is influenced by the remaining triangulation errors. For this experiment, the scanning device was mounted to the end-effector of a robot to be able to calculate a ground truth for the tracking.

RESULTS

The analysis of the triangulation accuracy of the authors' laser scanning device revealed a root mean square (RMS) error of 0.16 mm. In comparison, the analysis of the triangulation accuracy of the Kinect device revealed a RMS error of 0.89 mm. It turned out that the remaining triangulation errors only cause small inaccuracies for the tracking of a rigid object. Here, the tracking accuracy was given by a RMS translational error of 0.33 mm and a RMS rotational error of 0.12°.

CONCLUSIONS

This paper shows that time-multiplexed structured light can be used to generate highly accurate reconstructions of surfaces. Furthermore, the reconstructed point sets can be used for high-accuracy tracking of objects, meeting the strict requirements of intracranial radiosurgery.