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Background and purpose: Motion management strategies such as gating under breath-hold can reduce breathing-induced motion during stereotactic arrhythmia radioablation (STAR) for refractory ventricular tachycardia. However, heartbeat-induced motion is essential to define an appropriate cardiac internal target volume (ITV) margin. In this study, we introduce a patient- and segment-specific cardiac motion estimation method and cardiac motion data of the clinical target volume (CTV), ICD lead tips and left ventricle (LV) segments. Materials and methods: Data from 10 STAR-treated patients were retrospectively analyzed. The LV was semi-automatically segmented according to the 17-segment model. Electrocardiogram-gated contrast-enhanced breath-hold cardiac CTs were automatically non-rigidly registered for motion estimation. The correlation and significant differences between ICD tip motion and CTV motion were assessed using the Pearson correlation coefficient (PCC) and Wilcoxon signed-rank test, while spatial discrepancies with both CTV and segment motion were quantified using the Euclidean distance. Results: The CTVs (center of mass) moved 3.4 ± 1.4 mm and the ICD lead tips moved 4.9 ± 2.2 mm. The maximum motion per patient was observed in basal and mid-cavity LV segments in 3D. The PCC showed a strong positive motion correlation between the ICD tip and CTV in 3D (0.84), while the p-values indicated statistically significant differences in the right-left, anterior-posterior and 3D directions. Conclusion: The proposed methods enable patient- and segment-specific cardiac ITV margin estimation. The motion in most LV segments was limited, however, cardiac ITV margins may need adjustment in individual cases. The impact of cardiac motion on the dosimetry needs further investigation.

Complex medical therapies can require a multitude of imaging modalities and are often supervised by a team with different medical backgrounds. This necessitates the conversion of medical data between technical systems and visualizations. In the case of stereotactic arrhythmia radioablation therapy (STAR-therapy) of the left ventricle, electroanatomical mapping, ultrasound (US) and computed tomography (CT) are the central imaging modalities that are needed for defining the target volume as well as for the examination and validation pre and post treatment. In the interest of developing a motion management system for STAR-therapy, a way to transfer information and visualizations between these modalities and to compare data from different patients is needed. For this purpose, we present a landmark-based approach for the generation of commonly used ultrasound views and the 17-segment model from cardiac computed tomography (CCT) data. The developed tool can already be used to aid the examination process by extracting function-based views from CT datasets, comparing them to live US imaging, localize CT structures within the 17-segment model or to transfer information like motion or strain data from one modality to the other. In the future, it will be used in the development of a live or predictive management system for cardiac and respiratory motion.

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.

In radiation therapy of abdominal targets, optimal tumor irradiation can be challenging due to intrafractional motion. Current target localization methods are mainly indirect, surrogate-based and the patient is exposed to additional radiation due to X-ray imaging. In contrast, 4D ultrasound (4DUS) imaging provides volumetric images of soft tissue tumors in real-time without ionizing radiation, facilitating a non-invasive, direct tracking method. In this study, the target was defined by features located in its local neighborhood. Features were extracted using the FAST detector and the BRISK descriptor, which were extended to 3D. To account for anatomical variability, a feature library was generated that contains manually annotated target information and relative locations of the features. During tracking, features were extracted from the current 4DUS volume and compared to the feature library. Recognized features are used to estimate feature position and shape. The developed method was evaluated in 4DUS sequences of the liver of three healthy subjects. For each dataset, a target was defined and manually contoured in a training and a test sequence. Training was used for library creation, the test sequence for target tracking. The target estimations are compared to the annotations to quantify a tracking error. The results show that binary feature libraries can be used for robust target localization in 4DUS data of the liver and could potentially serve as a tracking method less sensitive to target deformation.

4D ultrasound (4D US) is gaining relevance as a tracking method in radiation therapy (RT) with modern matrix array probes offering new possibilities for real-time target detection. However, for clinical implementation of USguided RT, image quality, volumetric framerate and artifacts caused by the probe’s presence during planning and / or setup computed tomography (CT) must be quantified. We compared three diagnostic 4D US systems with matrix array probes using a commercial wire phantom to measure spatial resolution as well as a calibration and a torso phantom to assess different image quality metrics. CT artifacts were quantified in the torso phantom by calculating the total variation and percentage of affected voxels between a reference CT scan and CT scans with probes in place. We found that state-of-the-art 4D US systems with small probes can fit inside the CT bore and cause fewer metal artifacts than larger probes. US image quality varies between systems and is task-dependent. Volume sizes and framerates are much higher than the commercial guidance solution for US-guided RT, warranting further investigation regarding clinical performance for image guidance.

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.

In this paper, we presented a deep convolutional neural network (CNN) approach for forehead tissue thickness estimation. We use down sampled NIR laser backscattering images acquired from a novel marker-less near-infrared laser-based head tracking system, combined with the beam’s incident angle parameter. These two-channel augmented images were constructed for the CNN input, while a single node output layer represents the estimated value of the forehead tissue thickness. The models were – separately for each subject – trained and tested on datasets acquired from 30 subjects (high resolution MRI data is used as ground truth). To speed up training, we used a pre-trained network from the first subject to bootstrap training for each of the other subjects. We could show a clear improvement for the tissue thickness estimation (mean RMSE of 0.096 mm). This proposed CNN model outperformed previous support vector regression (mean RMSE of 0.155 mm) or Gaussian processes learning approaches (mean RMSE of 0.114 mm) and eliminated their restrictions for future research.

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.

Real-time target localization with ultrasound holds high potential for image guidance and motion compensation in radiosurgery due to its non-invasive image acquisition free from ionizing radiation. However, a two-step localization has to be performed when integrating ultrasound into the existing radiosurgery workflow. In addition to target localization inside the ultrasound volume, the probe itself has to be localized in order to transform the target position into treatment room coordinates. By adapting existing camera calibration tools, we have developed a method to extend the stereoscopic X-ray tracking system of a radiosurgery platform in order to locate objects such as marker geometries with six degrees of freedom. The calibration was performed with 0.1 mm reprojection error. By using the full area of the flat-panel detectors without pre-processing the extended software increased the tracking volume and resolution by up to 80%, substantially improving patient localization and marker detectability. Furthermore, marker-tracking showed sub-millimeter accuracy and rotational errors below 0.1°. This demonstrates that the developed extension framework can accurately localize marker geometries using an integrated X-ray system, establishing the link for the integration of real-time ultrasound image guidance into the existing system.

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.

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.

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.

Despite a significant increase in efforts to identify biomarkers and endophenotypic measuresof psychiatric illnesses, only a very limited amount of computational models of these markersand measures has been implemented so far. Moreover, existing computational models dealingwith biomarkers typically only examine one possible mechanism in isolation, disregarding thepossibility that other combinations of model parameters might produce the same networkbehaviour (what has been termed ’multifactoriality’). In this study we describe a step towardsa computational instantiation of an endophenotypic finding for schizophrenia, namely theimpairment of evoked auditory gamma and beta oscillations in schizophrenia. We explorethe multifactorial nature of this impairment using an established model of primary auditorycortex, by performing an extensive search of the parameter space. We find that singlenetwork parameters contain only little information about whether the network will show impairedgamma entrainment and that different regions in the parameter space yield similar networklevel oscillation abnormalities. These regions in the parameter space, however, show strongdifferences in the underlying network dynamics. To sum up, we present a first step towards anin silico instantiation of an important biomarker of schizophrenia, which has great potential forthe identification and study of disease mechanisms and for understanding of existing treatmentsand development of novel ones.

Social Ontology encompasses a wide variety of inquiries into the nature, structure and perhaps essence of social phenomena, and their role and place in our world. Topics of research in Social Ontology range from small-scale interactions to large-scale institutions, from spontaneous teamwork to the functioning of formal organizations, and from unintended consequences to institutional design. Social Ontology brings together theoretical work from a large number of disciplines. This rapidly evolving field of research has attracted increasing attention over the last couple of decades, and the conceptual tools recent research in Social Ontology has provided have proved to be useful in a large number of domains, such as the study of the evolution of communication, the structure of social norms, social structure, and social change, the nature of collective responsibility, and the status of corporate agents. The Journal of Social Ontology aims to further this research. It provides a forum of exchange between scholars of diverse disciplinary, scholarly, and methodological backgrounds, and invites submissions from all branches of Social Ontology. The Journal of Social Ontology adopts strict standards of selection and relies heavily on its carefully selected referees. In a world in which publication strategies and outlets are changing at a tremendous pace, it is difficult to say what the future of scholarly publication will look like. With a generous grant from the University of Vienna for the start-up phase, the Journal of Social Ontology now appears as an Open Access Journal with De Gruyter, thus combining professional support by an established publisher with unlimited accessibility. In addition, the Journal of Social Ontology has been founded together with the International Social Ontology Society (ISOS) that supports the work of this journal. We wish to express our thanks to our supporters, contributors, and referees; we hope that our joint effort will grant the work published in this journal the impact it deserves.

We study the impact of coil orientation on the motor threshold (MT) and present an optimal coil orientation for stimulation of the foot. The result can be compared to results of models that predict this orientation from electrodynamic properties of the media in the skull and from orientations of cells, respectively. We used a robotized TMS system for precise coil placement and recorded motor-evoked potentials with surface electrodes on the abductor hallucis muscle of the right foot in 8 healthy control subjects. First, we performed a hot-spot search in standard (lateral) orientation and then rotated the coil in steps of 10° or 20°. At each step we estimated the MT. For navigated stimulation and for correlation with the underlying anatomy a structural MRI scan was obtained. Optimal coil orientation was 33.1 ± 18.3° anteriorly in relation to the standard lateral orientation. In this orientation the threshold was 54 ± 18% in units of maximum stimulator output. There was a significant difference of 8.0 ± 5.9% between the MTs at optimal and at standard orientation. The optimal coil orientations were significantly correlated with the direction perpendicular to the postcentral gyrus ([Formula: see text]). Robotized TMS facilitates sufficiently precise coil positioning and orientation to study even small variations of the MT with coil orientation. The deviations from standard orientation are more closely matched by models based on field propagation in media than by models based on orientations of pyramidal cells.