Susceptibility-Weighted MRI for Deep Brain Stimulation: Potentials in Trajectory Planning.

BACKGROUND: Deep brain stimulation (DBS) trajectory planning is mostly based on standard 3-D T1-weighted gadolinium-enhanced MRI sequences (T1-Gd). Susceptibility-weighted MRI sequences (SWI) show neurovascular structures without the use of contrast agents. The aim of this study was to investigate whether SWI might be useful in DBS trajectory planning. METHODS: We performed bilateral DBS planning using conventional T1-Gd images of 10 patients with different kinds of movement disorders. Afterwards, we matched SWI sequences and compared the visibility of vascular structures in both imaging modalities. RESULTS: By analyzing 100 possible trajectories, we found a potential vascular conflict in 13 trajectories based on T1-Gd in contrast to 53 in SWI. Remarkably, all vessels visible in T1-Gd were also depicted in SWI, whereas SWI showed many additional vascular structures which could not be identified in T1-Gd. CONCLUSION/DISCUSSION: The sensitivity for detecting neurovascular structures for DBS planning seems to be significantly higher in SWI. As SWI does not require a contrast agent, we suggest that SWI may be a valuable alternative to T1-Gd MRI for DBS trajectory planning. Furthermore, the data analysis suggests that vascular interactions of DBS trajectories might be more frequent than expected from the very low incidence of symptomatic bleedings. The explanation for this is currently the subject of debate and merits further studies.

Post-operative deep brain stimulation assessment: Automatic data integration and report generation.

BACKGROUND: The gold standard for post-operative deep brain stimulation (DBS) parameter tuning is a monopolar review of all stimulation contacts, a strategy being challenged by recent developments of more complex electrode leads. OBJECTIVE: Providing a method to guide clinicians on DBS assessment and parameter tuning by automatically integrating patient individual data. METHODS: We present a fully automatic method for visualization of individual deep brain structures in relation to a DBS lead by combining precise electrode recovery from post-operative imaging with individual estimates of deep brain morphology utilizing a 7T-MRI deep brain atlas. RESULTS: The method was evaluated on 20 STN DBS cases. It demonstrated robust automatic creation of 3D-enabled PDF reports visualizing electrode to brain structure relations and proved valuable in detecting miss placed electrodes. DISCUSSION: Automatic DBS assessment is feasible and can conveniently provide clinicians with relevant information on DBS contact positions in relation to important anatomical structures.

PaCER - A fully automated method for electrode trajectory and contact reconstruction in deep brain stimulation.

Deep brain stimulation (DBS) is a neurosurgical intervention where electrodes are permanently implanted into the brain in order to modulate pathologic neural activity. The post-operative reconstruction of the DBS electrodes is important for an efficient stimulation parameter tuning. A major limitation of existing approaches for electrode reconstruction from post-operative imaging that prevents the clinical routine use is that they are manual or semi-automatic, and thus both time-consuming and subjective. Moreover, the existing methods rely on a simplified model of a straight line electrode trajectory, rather than the more realistic curved trajectory. The main contribution of this paper is that for the first time we present a highly accurate and fully automated method for electrode reconstruction that considers curved trajectories. The robustness of our proposed method is demonstrated using a multi-center clinical dataset consisting of N = 44 electrodes. In all cases the electrode trajectories were successfully identified and reconstructed. In addition, the accuracy is demonstrated quantitatively using a high-accuracy phantom with known ground truth. In the phantom experiment, the method could detect individual electrode contacts with high accuracy and the trajectory reconstruction reached an error level below 100 µm (0.046 ± 0.025 mm). An implementation of the method is made publicly available such that it can directly be used by researchers or clinicians. This constitutes an important step towards future integration of lead reconstruction into standard clinical care.

Shape-aware surface reconstruction from sparse 3D point-clouds.

The reconstruction of an object's shape or surface from a set of 3D points plays an important role in medical image analysis, e.g. in anatomy reconstruction from tomographic measurements or in the process of aligning intra-operative navigation and preoperative planning data. In such scenarios, one usually has to deal with sparse data, which significantly aggravates the problem of reconstruction. However, medical applications often provide contextual information about the 3D point data that allow to incorporate prior knowledge about the shape that is to be reconstructed. To this end, we propose the use of a statistical shape model (SSM) as a prior for surface reconstruction. The SSM is represented by a point distribution model (PDM), which is associated with a surface mesh. Using the shape distribution that is modelled by the PDM, we formulate the problem of surface reconstruction from a probabilistic perspective based on a Gaussian Mixture Model (GMM). In order to do so, the given points are interpreted as samples of the GMM. By using mixture components with anisotropic covariances that are "oriented" according to the surface normals at the PDM points, a surface-based fitting is accomplished. Estimating the parameters of the GMM in a maximum a posteriori manner yields the reconstruction of the surface from the given data points. We compare our method to the extensively used Iterative Closest Points method on several different anatomical datasets/SSMs (brain, femur, tibia, hip, liver) and demonstrate superior accuracy and robustness on sparse data.

Eyelid contour detection and tracking for startle research related eye-blink measurements from high-speed video records.

Using the positions of the eyelids is an effective and contact-free way for the measurement of startle induced eye-blinks, which plays an important role in human psychophysiological research. To the best of our knowledge, no methods for an efficient detection and tracking of the exact eyelid contours in image sequences captured at high-speed exist that are conveniently usable by psychophysiological researchers. In this publication a semi-automatic model-based eyelid contour detection and tracking algorithm for the analysis of high-speed video recordings from an eye tracker is presented. As a large number of images have been acquired prior to method development it was important that our technique is able to deal with images that are recorded without any special parametrisation of the eye tracker. The method entails pupil detection, specular reflection removal and makes use of dynamic model adaption. In a proof-of-concept study we could achieve a correct detection rate of 90.6%. With this approach, we provide a feasible method to accurately assess eye-blinks from high-speed video recordings.

Implantation of electrodes for deep brain stimulation of the subthalamic nucleus in advanced Parkinson's disease with the aid of intraoperative microrecording under general anesthesia.

OBJECTIVE: Deep brain stimulation (DBS) is widely accepted in the treatment of advanced Parkinson's disease (PD) and other movement disorders. The standard implantation procedure is performed under local anesthesia (LA). Certain groups of patients may not be eligible for surgery under LA because of clinical reasons, such as massive fear, reduced cooperativity, or coughing attacks. Microrecording (MER) has been shown to be helpful in DBS surgery. The purpose of this study was to evaluate the feasibility of MER for DBS surgery under general anesthesia (GA) and to compare the data of intraoperative MER as well as the clinical data with that of the current literature of patients undergoing operation under LA. CLINICAL PRESENTATION: The data of nine patients with advanced PD (mean Hoehn and Yahr status, 4.2) who were operated with subthalamic nucleus (STN) DBS under GA, owing to certain clinical circumstances ruling out DBS under LA, were retrospectively analyzed. All operations were performed under analgosedation with propofol or remifentanil and intraoperative MER. For MER, remifentanil was ceased completely and propofol was lowered as far as possible. INTERVENTION: The STN could be identified intraoperatively in all patients with MER. The typical bursting pattern was identified, whereas a widening of the baseline noise could not be as adequately detected as in patients under LA. The daily off phases of the patients were reduced from 50 to 17%, whereas the Unified Parkinson's Disease Rating Scale III score was reduced from 43 (preoperative, medication off) to 19 (stimulation on, medication off) and 12 (stimulation on, medication on). Two patients showed a transient neuropsychological deterioration after surgery, but both also had preexisting episodes of disorientation. One implantable pulse generator infection was noticed. No further significant clinical complications were observed. CONCLUSION: STN surgery for advanced PD with MER guidance is possible with good clinical results under GA. Intraoperative MER of the STN region can be performed under GA with a special anesthesiological protocol. In this setting, the typical STN bursting pattern can be identified, whereas the typical widening of the background noise baseline while entering the STN region is obviously absent. This technique may enlarge the group of patients eligible for STN surgery. Although the clinical improvements and parameter settings in this study were within the range of the current literature, further randomized controlled studies are necessary to compare the results of STN DBS under GA and LA, respectively.