Search

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.

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.

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.