Hemm-Ode, Simone
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How sample size impacts probabilistic stimulation maps in deep brain stimulation
Probabilistic stimulation maps of deep brain stimulation (DBS) effect based on voxel-wise statistics (p-maps) have increased in literature over the last decade. These p-maps require correction for Type-1 errors due to multiple testing based on the same data. Some analyses do not reach overall significance, and this study aims to evaluate the impact of sample size on p-map computation. A dataset of 61 essential tremor patients treated with DBS was used for the investigation. Each patient contributed with four stimulation settings, one for each contact. From the dataset, 5 to 61 patients were randomly sampled with replacement for computation of p-maps and extraction of high- and low-improvement volumes. For each sample size, the process was iterated 20 times with new samples generating in total 1140 maps. The overall p-value corrected for multiple comparisons, significance volumes, and dice coefficients (DC) of the volumes within each sample size were evaluated. With less than 30 patients (120 simulations) in the sample, the variation in overall significance was larger and the median significance volumes increased with sample size. Above 120 simulations, the trends stabilize but present some variations in cluster location, with a highest median DC of 0.73 for n = 57. The variation in location was mainly related to the region between the high- and low-improvement clusters. In conclusion, p-maps created with small sample sizes should be evaluated with caution, and above 120 simulations in single-center studies are probably required for stable results.
Experimental assessment of the performances of an anisotropic magnetoresistive sensor after exposure to strong magnetic fields
On-chip magnetometers are already integrated within long-term implants such as cardiac implantable electronic devices. They are also good candidates to be integrated within the next generations of brain stimulation electrodes to provide their position and orientation. In all cases, long-term implants are expected to be at least certified as MRI conditional. We investigated the resilience to the exposure to 3 T and 7 T of an anisotropic magnetoresistive sensor integrating a set/reset function. The sensitivity, non-linearity, and offset of a batch of 63 identical sensors were not affected by the exposure. These preliminary results provide new insights on the usability of magnetoresistive sensors for biomedical applications requiring MRI conditionality.
Probabilistic maps for deep brain stimulation – Impact of methodological differences
Background Group analysis of patients with deep brain stimulation (DBS) has the potential to help understand and optimize the treatment of patients with movement disorders. Probabilistic stimulation maps (PSM) are commonly used to analyze the correlation between tissue stimulation and symptomatic effect but are applied with different methodological variations. Objective To compute a group-specific MRI template and PSMs for investigating the impact of PSM model parameters. Methods Improvement and occurrence of dizziness in 68 essential tremor patients implanted in caudal zona incerta were analyzed. The input data includes the best parameters for each electrode contact (screening), and the clinically used settings. Patient-specific electric field simulations (n = 488) were computed for all DBS settings. The electric fields were transformed to a group-specific MRI template for analysis and visualization. The different comparisons were based on PSMs representing occurrence (N-map), mean improvement (M-map), weighted mean improvement (wM-map), and voxel-wise t-statistics (p-map). These maps were used to investigate the impact from input data (clinical/screening settings), clustering methods, sampling resolution, and weighting function. Results Screening or clinical settings showed the largest impacts on the PSMs. The average differences of wM-maps were 12.4 and 18.2% points for the left and right sides respectively. Extracting clusters based on wM-map or p-map showed notable variation in volumes, while positioning was similar. The impact on the PSMs was small from weighting functions, except for a clear shift in the positioning of the wM-map clusters. Conclusion The distribution of the input data and the clustering method are most important to consider when creating PSMs for studying the relationship between anatomy and DBS outcome.
Test-re-test reliability and dynamics of the Fukuda–Unterberger stepping test
The Fukuda-stepping-test (FST), i.e., repetitive walking on the spot while blindfolded, has been proposed as a means to assess the integrity of the vestibular pathways. While its sensitivity to detect abnormalities in patients is limited, it may be useful in studying the physiology of the subjective-straight-ahead (SSA). Considering reported systematic shifts in SSA in humans, we hypothesize that such asymmetries arise from individual differences in the orientation/configuration of the macular organs and in central processing of vestibular input. We hypothesize that such asymmetries are stable over time in individual subjects. Alternatively, such asymmetries may arise from random noise in the sensory/motor systems involved, demonstrating low reproducibility over time. Materials and methods: Twenty-four subjects walked on the spot over 60 s while blindfolded. Using an inertial measurement unit (IMU) placed at the chest, angular deviations were recorded and compared to manually-measured final positions. Both static (direction, magnitude) and dynamic (time-to-onset of deviation, pattern of deviations) parameters were retrieved from the yaw slopes. Significant deviations were found in 15/24 participants for the manual measurements (leftwards = 8; rightwards = 7), whereas when using the IMU-sensor 13/24 participants showed significant shifts (leftwards = 9; rightwards = 4). There was a high correlation (0.98) between manually measured rotation angles (average absolute deviations = 58.0 deg ± 48.6 deg; intra-individual variability = 39 deg ± 24 deg) and sensor-based yaw slopes (1.00 deg/s ± 0.88 deg/s; 0.67 deg/s ± 0.41 deg/s). Relevant yaw deviation was detected 22.1 s ± 12.3 s (range = 5.6 s-59.2 s) after the onset of marching (no relevant yaw-deviation in 15/139 measurements), showing a mostly linear behavior over time. Conclusion: We observed significant inter-individual variability in task performance in the FST, reproducing findings from previous studies. With test-re-test reliability being moderate only, but at the same time observing a preference in the side of shifts in most trials and subjects, we conclude that likely both individually varying estimates of straight-ahead and random noise contribute to the pattern of angular deviations observed. Using an IMU-sensory based approach, additional dynamic parameters could be retrieved, emphasizing the value of such a quantitative approach over manual measurements. Such an approach may provide useful additional information to distinguish patients from healthy controls.
Towards a new generation of electromagnetic navigation system for deep brain stimulation
Towards tracking of deep brain stimulation electrodes using an integrated magnetometer
This paper presents a tracking system using magnetometers, possibly integrable in a deep brain stimulation (DBS) electrode. DBS is a treatment for movement disorders where the position of the implant is of prime importance. Positioning challenges during the surgery could be addressed thanks to a magnetic tracking. The system proposed in this paper, complementary to existing procedures, has been designed to bridge preoperative clinical imaging with DBS surgery, allowing the surgeon to increase his/her control on the implantation trajectory. Here the magnetic source required for tracking consists of three coils, and is experimentally mapped. This mapping has been performed with an in-house three-dimensional magnetic camera. The system demonstrates how magnetometers integrated directly at the tip of a DBS electrode, might improve treatment by monitoring the position during and after the surgery. The three-dimensional operation without line of sight has been demonstrated using a reference obtained with magnetic resonance imaging (MRI) of a simplified brain model. We observed experimentally a mean absolute error of 1.35 mm and an Euclidean error of 3.07 mm. Several areas of improvement to target errors below 1 mm are also discussed.
An online movement and tremor identification algorithm for evaluation during deep brain stimulation
INTRODUCTION: Deep brain stimulation (DBS) is widely used to alleviate symptoms of movement disorders. During intraoperative stimulation the influence of active or passive movements on the neuronal activity is often evaluated but the evaluation remains mostly subjective. The objective of this paper is to investigate the potential of a previously developed Weighted-frequency Fourier Linear combiner and Kalman filter-based recursive algorithm to identify tremor phases and types. METHODS: Ten accelerometer recordings from eight patients were acquired during DBS from which 186 phases were manually annotated into: rest, postural and kinetic phase without tremor, and rest, postural and kinetic phase with tremor. The method first estimates the instantaneous tremor frequency and then decomposes the motion signal into voluntary and tremorous parts. The tremorous part is used to quantify tremor and the voluntary part to differentiate rest, postural and kinetic phases. RESULTS: Instantaneous tremor frequency and amplitude are successfully tracked online. The overall accuracy for tremorous phases only is 89.1% and 76.3% when also non-tremorous phases are considered. Two main misclassification cases are identified and further discussed. CONCLUSION: The results demonstrate the potential of the developed algorithm as an online tremorous movement classifier. It would benefit from a more advanced tremor detector but nevertheless the obtained digital biomarkers offer an evidence-based analysis and could optimize the efficacy of DBS treatment.
Tracking the orientation of deep brain stimulation electrodes using an embedded magnetic sensor
This paper proposes a three-dimensional (3D) orientation tracking method of a 3D magnetic sensor embedded in a 2.5 mm diameter electrode. Our system aims to be used during intraoperative surgery to detect the orientation of directional leads (D-leads) for deep brain stimulation (DBS).