Prediction of Electrode Contacts for Clinically Effective Deep Brain Stimulation in Essential Tremor.

BACKGROUND/AIM: Deep brain stimulation (DBS) is an established neurosurgical treatment that can be used to alleviate symptoms in essential tremor (ET) and other movement disorders. The aim was to develop a method and software tool for the prediction of effective DBS electrode contacts based on probabilistic stimulation maps (PSMs) in patients with ET treated with caudal zona incerta (cZi) DBS. METHODS: A total of 33 patients (37 leads) treated with DBS were evaluated with the Essential Tremor Rating Scale (ETRS) 12 months after surgery. In addition, hand tremor and hand function (ETRS items 5/6 and 11-14) were evaluated for every contact during stimulation with best possible outcome without inducing side effects. Prediction of effective DBS electrode contacts was carried out in a retrospective leave-one-out manner based on PSMs, simulated stimulation fields, and a scoring function. Electrode contacts were ranked according to their likelihood of being included in the clinical setting. Ranked electrode contacts were compared to actual clinical settings. RESULTS: Predictions made by the software tool showed that electrode contacts with rank 1 matched the clinically used contacts in 60% of the cases. Contacts with a rank of 1-2 and 1-3 matched the clinical contacts in 83 and 94% of the cases, respectively. Mean improvement of hand tremor and hand function was 79 ± 21% and 77 ± 22% for the clinically used and the predicted electrode contacts, respectively. CONCLUSIONS: Effective electrode contacts can be predicted based on PSMs in patients treated with cZi DBS for ET. Predictions may in the future be used to reduce the number of clinical assessments that are carried out before a satisfying stimulation setting is defined.

The reliability of quantitative analysis on digital images of the scoliotic spine.

Although analysis of scoliotic deformity is still studied extensively by means of conventional roentgenograms, computer-assisted digital analysis may allow a faster, more accurate and more complete evaluation of the scoliotic spine. In this study, a new computer-assisted measurement method was evaluated. This method uses digital reconstruction images for quantitative analysis of the scoliotic spine. The aim of the current study was to determine the reliability of the computer-assisted measuring method, which was done by establishing coefficients of repeatability for a variety of measurements. Measurements were carried out by five observers on 30 frontal and 10 lateral scoliotic digital reconstruction images. Each image was measured on three separate occasions by placing anatomical vertebral landmarks and drawing lines with a computer pointing device. The computer then calculated a number of geometrical shape parameters from scale calibration, landmarks and lines. The intra- and interobserver results were subjected to an analysis of variance to assess the level of agreement, and the means and standard deviations were calculated. The coefficient of repeatability (CR) was taken to be equal to two standard deviations. The mean intraobserver CR was found to be 3.1 degrees for the Cobb angle on the frontal digital image and 3.3 degrees for the kyphosis Cobb angle on the lateral overview. The mean difference in the intraobserver CR of the Cobb angle between measurements made by placing landmarks and those made by drawing lines was not statistically significant (P>0.05). The mean intraobserver CR for the other parameters can be summarized as follows: for lateral deviation it was 0.8 mm, for axial rotation 4.0 degrees and for length of the spine 3.3 mm. The interobserver bias was negligible. It can be concluded that the reliability of our new method for quantifying geometrical variables on digital reconstruction images is better than measurements on conventional roentgenograms in previously published reports. The presented method is therefore considered to be more accurate for research of spinal deformities and more adequate for clinical management of scoliosis.

Semi-automatic landmark detection in digital X-ray images of the spine.

Quantitative diagnosis of 3D scoliotic deformities depends on a number of dedicated measurements. Existing methods rely on the manual determination of a series of anatomical landmarks in X-ray images. We have developed an automatic method to alleviate the burden of this tedious task. Our method looks for a compromise between local image information and global prior constraints and finds the most probable points using dynamic programming optimization. Remaining errors can be quickly corrected by effective user interaction. The first results are promising.

3D reconstruction and analysis of the vertebral body line.

Quantitative analysis of 3D spinal deformities includes measurements related to individual vertebrae and measurements related to the overall shape of the spine. For the latter aspect, we propose to build a 3D model of the line that connects all vertebrae centres. We present two methods that allow reconstructing this vertebral body line in a quick and easy way. Various new descriptors of the spinal shape can be automatically computed. A study is under way to assess their clinical relevance and reliability.