Structural Connectivity Patterns of Side Effects Induced by Subthalamic Deep Brain Stimulation for Parkinson's Disease.

Background: Tractography based on diffusion-weighted magnetic resonance imaging (DWI) models the structural connectivity of the human brain. Deep brain stimulation (DBS) targeting the subthalamic nucleus is an effective treatment for advanced Parkinson's disease, but may induce adverse effects. This study investigated the relationship between structural connectivity patterns of DBS electrodes and stimulation-induced side effects. Materials and Methods: Twenty-one patients with Parkinson's disease treated with bilateral subthalamic DBS were examined. Overall, 168 electrode contacts were categorized as inducing or noninducing depending on their capability for inducing side effects such as motor effects, paresthesia, dysarthria, oculomotor effects, hyperkinesia, and other complications as assessed during the initial programming session. Furthermore, the connectivity of each contact with target regions was evaluated by probabilistic tractography based on DWI. Finally, stimulation sites and structural connectivity patterns of inducing and noninducing contacts were compared. Results: Inducing contacts differed across the various side effects and from those mitigating Parkinson's symptoms. Although contacts showed a largely overlapping spatial distribution within the subthalamic region, they could be distinguished by their connectivity patterns. In particular, inducing contacts were more likely connected with supplementary motor areas (hyperkinesia, dysarthria), frontal cortex (oculomotor), fibers of the internal capsule (paresthesia), and the basal ganglia-thalamo-cortical circuitry (dysarthria). Discussion: Side effects induced by DBS seem to be associated with distinct connectivity patterns. Cerebellar connections are hardly associated with side effects, although they seem relevant for mitigating motor symptoms in Parkinson's disease. A symptom-specific, connectivity-based approach for target planning in DBS may enhance treatment outcomes and reduce adverse effects. Impact statement Tractography based on diffusion-weighted magnetic resonance imaging has become a prominent technique for investigating the connectivity of human brain networks in vivo. However, the relationship between structural connections and brain function is still hardly known. The present study examined the relationship between adverse behavioral effects induced by deep brain stimulation (DBS) and tractography patterns in individual brains. The results suggest that DBS-based side effects depend on the structural connections of electrode contacts rather than their location. Network-based target planning in DBS may improve treatment by avoiding side effects. Moreover, the adopted approach may serve as a paragon for investigating structure/function relationships.

Deep brain stimulation: Connectivity profile for bradykinesia alleviation.

OBJECTIVE: Subthalamic deep brain stimulation may alleviate bradykinesia in Parkinson patients. Research suggests that this stimulation effect may be mediated by brain networks like the corticocerebellar loop. This study investigated the connectivity between stimulation sites and cortical and subcortical structures to identify connections for effective stimulation. METHODS: We retrospectively investigated 21 patients with Parkinson disease with bilateral subthalamic deep brain stimulation. Stimulation effectiveness in reducing bradykinesia, tremor, and rigidity was evaluated for each electrode contact in brain hemispheres contralateral to the affected hemibody. Dysarthric side effects were also examined. Probabilistic tractography based on diffusion-weighted imaging was performed in individual patient-specific brains using electrode contacts as seeds. Connectivity profiles of contacts with effective and noneffective stimulation were compared. RESULTS: Connectivity profiles of effective and noneffective contacts differed. Moreover, the connectivity profile for bradykinesia differed from that for rigidity, tremor, or dysarthria. Regarding bradykinesia, effective contacts were significantly more often connected with the ipsilateral superior cerebellar peduncle and the ipsilateral dentate nucleus, which correspond to the ipsilateral portion of the cerebellothalamocortical pathway. Rigidity was mitigated by stimulation of ascending brainstem and intralaminar thalamic connections. Tremor alleviation was related to connections with the internal capsule (anterior limb) and the pallidum. Dysarthric side effects were associated with connections to the supplementary motor area and the decussating cerebellothalamocortical pathway. INTERPRETATION: Whereas bradykinesia seems to be mitigated by stimulation of the ascending, ipsilateral cerebellothalamocortical pathway, stimulation of the descending corticopontocerebellar pathway may be ineffective. Rigidity, tremor, and dysarthric side effects seem to be influenced by different neural networks. ANN NEUROL 2019;85:852-864.

A Patient-Independent Significance Test by Means of False-Positive Rates in Selected Correlation Analysis of Brain Multimodal Monitoring Data.

Recently, we introduced a mathematical toolkit called selected correlation analysis (sca) that reliably detects negative and positive correlations between arterial blood pressure (ABP) and intracranial pressure (ICP) data, recorded during multimodal monitoring, in a time-resolved way. As has been shown with the aid of a mathematical model of cerebral perfusion, such correlations reflect impaired autoregulation and reduced intracranial compliance in patients with critical neurological diseases. Sca calculates a Fourier transform-based index called selected correlation (sc) that reflects the strength of correlation between the input data and simultaneously an index called mean Hilbert phase difference (mhpd) that reflects the phasing between the data. To reliably detect pathophysiological conditions during multimodal monitoring, some thresholds for the abovementioned indexes sc and mhpd have to be established that assign predefined significance levels to that thresholds. In this paper, we will present a method that determines the rate of false positives for fixed pairs of thresholds (lsc, lmhpd). We calculate these error rates as a function of the predefined thresholds for each individual out of a patient cohort of 52 patients in a retrospective way. Based on the deviation of the individual error rates, we subsequently determine a globally valid upper limit of the error rate by calculating the predictive interval. From this predictive interval, we deduce a globally valid significance level for appropriate pairs of thresholds that allows the application of sca to every future patient in a prospective, bedside fashion.

Probabilistic vs. deterministic fiber tracking and the influence of different seed regions to delineate cerebellar-thalamic fibers in deep brain stimulation.

This study compared tractography approaches for identifying cerebellar-thalamic fiber bundles relevant to planning target sites for deep brain stimulation (DBS). In particular, probabilistic and deterministic tracking of the dentate-rubro-thalamic tract (DRTT) and differences between the spatial courses of the DRTT and the cerebello-thalamo-cortical (CTC) tract were compared. Six patients with movement disorders were examined by magnetic resonance imaging (MRI), including two sets of diffusion-weighted images (12 and 64 directions). Probabilistic and deterministic tractography was applied on each diffusion-weighted dataset to delineate the DRTT. Results were compared with regard to their sensitivity in revealing the DRTT and additional fiber tracts and processing time. Two sets of regions-of-interests (ROIs) guided deterministic tractography of the DRTT or the CTC, respectively. Tract distances to an atlas-based reference target were compared. Probabilistic fiber tracking with 64 orientations detected the DRTT in all twelve hemispheres. Deterministic tracking detected the DRTT in nine (12 directions) and in only two (64 directions) hemispheres. Probabilistic tracking was more sensitive in detecting additional fibers (e.g. ansa lenticularis and medial forebrain bundle) than deterministic tracking. Probabilistic tracking lasted substantially longer than deterministic. Deterministic tracking was more sensitive in detecting the CTC than the DRTT. CTC tracts were located adjacent but consistently more posterior to DRTT tracts. These results suggest that probabilistic tracking is more sensitive and robust in detecting the DRTT but harder to implement than deterministic approaches. Although sensitivity of deterministic tracking is higher for the CTC than the DRTT, targets for DBS based on these tracts likely differ.

Detection of Impaired Cerebral Autoregulation Using Selected Correlation Analysis: A Validation Study.

Multimodal brain monitoring has been utilized to optimize treatment of patients with critical neurological diseases. However, the amount of data requires an integrative tool set to unmask pathological events in a timely fashion. Recently we have introduced a mathematical model allowing the simulation of pathophysiological conditions such as reduced intracranial compliance and impaired autoregulation. Utilizing a mathematical tool set called selected correlation analysis (sca), correlation patterns, which indicate impaired autoregulation, can be detected in patient data sets (scp). In this study we compared the results of the sca with the pressure reactivity index (PRx), an established marker for impaired autoregulation. Mean PRx values were significantly higher in time segments identified as scp compared to segments showing no selected correlations (nsc). The sca based approach predicted cerebral autoregulation failure with a sensitivity of 78.8% and a specificity of 62.6%. Autoregulation failure, as detected by the results of both analysis methods, was significantly correlated with poor outcome. Sca of brain monitoring data detects impaired autoregulation with high sensitivity and sufficient specificity. Since the sca approach allows the simultaneous detection of both major pathological conditions, disturbed autoregulation and reduced compliance, it may become a useful analysis tool for brain multimodal monitoring data.

Parameter Optimization for Selected Correlation Analysis of Intracranial Pathophysiology.

Recently we proposed a mathematical tool set, called selected correlation analysis, that reliably detects positive and negative correlations between arterial blood pressure (ABP) and intracranial pressure (ICP). Such correlations are associated with severe impairment of the cerebral autoregulation and intracranial compliance, as predicted by a mathematical model. The time resolved selected correlation analysis is based on a windowing technique combined with Fourier-based coherence calculations and therefore depends on several parameters. For real time application of this method at an ICU it is inevitable to adjust this mathematical tool for high sensitivity and distinct reliability. In this study, we will introduce a method to optimize the parameters of the selected correlation analysis by correlating an index, called selected correlation positive (SCP), with the outcome of the patients represented by the Glasgow Outcome Scale (GOS). For that purpose, the data of twenty-five patients were used to calculate the SCP value for each patient and multitude of feasible parameter sets of the selected correlation analysis. It could be shown that an optimized set of parameters is able to improve the sensitivity of the method by a factor greater than four in comparison to our first analyses.

Windowed multitaper correlation analysis of multimodal brain monitoring parameters.

Although multimodal monitoring sets the standard in daily practice of neurocritical care, problem-oriented analysis tools to interpret the huge amount of data are lacking. Recently a mathematical model was presented that simulates the cerebral perfusion and oxygen supply in case of a severe head trauma, predicting the appearance of distinct correlations between arterial blood pressure and intracranial pressure. In this study we present a set of mathematical tools that reliably detect the predicted correlations in data recorded at a neurocritical care unit. The time resolved correlations will be identified by a windowing technique combined with Fourier-based coherence calculations. The phasing of the data is detected by means of Hilbert phase difference within the above mentioned windows. A statistical testing method is introduced that allows tuning the parameters of the windowing method in such a way that a predefined accuracy is reached. With this method the data of fifteen patients were examined in which we found the predicted correlation in each patient. Additionally it could be shown that the occurrence of a distinct correlation parameter, called scp, represents a predictive value of high quality for the patients outcome.

Cerebral blood flow reactivity in patients undergoing selective amygdalohippocampectomy for epilepsy of mesial temporal origin. A prospective randomized comparison of the trans-Sylvian and the transcortical approach.

OBJECTIVE: The aim of this study was to assess (1) whether vasoreactivity is altered in patients with epilepsy and (2) whether the two most commonly used approaches, the trans-Sylvian (TS) and the trans-cortical (TC) route, differ in their impact on cortical blood flow. METHODS: Patients were randomized to undergo selective amygdalohippocampectomy (selAH) through a TC or TS route. Before and after selAH, we recorded microcirculation parameters on the superficial cortex surrounding the surgical corridor. Blood flow and velocity were measured using laser Doppler flowmetry and micro-Doppler, respectively. Cortical oxygen saturation (SO2) was measured using remission spectrophotometry under hypocapnic and normocapnic conditions. RESULTS: Ten patients were operated using the TS approach, and eight were operated via the TC approach. Vasomotor reactivity patterns measured with micro-Doppler were physiologically prior to selAH in both groups. After completion of surgery, a significant increase in SO2-values occurred in the TS group (before: 56.7 ± 2.2, after: 65.5 ± 3.0%SO2), but not in the TC group (before: 52.9 ± 5.2, after: 53.0 ± 3.7%SO2). The rate of critical SO2 values below 25% was significantly higher after the TC approach (12.3%) compared to the TS approach (5.2%; p < 0.05). DISCUSSION: Our findings provide the first invasively measured evidence that patients with mesial temporal lobe epilepsy have preserved cerebral blood flow responses to alterations in CO2. In addition, local cortical SO2 was higher in the TS group than in the TC group after selAH. This may be a sign of reactive cortical vessel dilation after proximal vessel manipulation associated with the TS approach. In contrast, the lower values of SO2 after the TC approach indicate tissue ischaemia surrounding the surgical corridor surrounding the corticotomy.

Mathematical modeling of human brain physiological data.

Recently, a mathematical model of the basic physiological processes regulating the cerebral perfusion and oxygen supply was introduced [Jung et al., J. Math. Biol. 51, 491 (2005)]. Although this model correctly describes the interdependence of arterial blood pressure (ABP) and intracranial pressure (ICP), it fails badly when it comes to explaining certain abnormal correlations seen in about 80% of the recordings of ABP together with ICP and the partial oxygen pressure (TiPO(2)) of the neuronal tissue, taken at an intensive care unit during neuromonitoring of patients with a severe brain trauma. Such recordings occasionally show segments, where the mean arterial blood pressure is correlated with the partial oxygen pressure in tissue but anticorrelated with the intracranial pressure. The origin of such abnormal correlations has not been fully understood yet. Here, two extensions to the previous approach are proposed which can reproduce such abnormal correlations in simulations quantitatively. Furthermore, as the simulations are based on a mathematical model, additional insight into the physiological mechanisms from which such abnormal correlations originate can be gained.

Computerized data analysis of neuromonitoring parameters identifies patients with reduced cerebral compliance as seen on CT.

OBJECTIVE: Computer-assisted analysis of neuromonitoring parameters may provide important decision-making support to the neurointensivist. A recently developed mathematical model for the simulation of cerebral autoregulation and brain swelling showed that in the case of an intact autoregulation but diminished cerebral compliance, a negative correlation between arterial blood pressure (ABP) and intracranial pressure (ICP) occurs. The goal of our study was to verify these simulation results in an appropriate patient cohort. METHODS: Simultaneously measured data (ABP, ICP) of 6 patients (1 female; 5 male) with severe head trauma (n = 5) and stroke (n = 1) were used to calculate time resolved multitaper cross coherence. Further, we calculated the Hilbert phases of both signals, defining a negative correlation in case of a mean Hilbert phase difference greater than 130°. To validate the results, CT scans performed during the critical phases identified were analyzed. RESULTS: In five out of six datasets we found long lasting events of negative correlation between ABP and ICP. In all patients, corresponding CT scans demonstrated changes in the intracranial compartment characterized by diminished cerebral compliance. CONCLUSIONS: Our data indicate that complex multidimensional data analysis of neuromonitoring parameters can identify complication-specific data patterns with a high degree of accuracy.

Influence of fibre and filler reinforcement of plastic brackets: an in vitro study.

In spite of their popularity in fulfilling aesthetic requirements, plastic brackets still present some disadvantages because of their low elastic modulus, decreased fracture toughness, and reduced wear resistance. Fibre-reinforced composites are well established in dentistry and consist of a polymer matrix in which reinforcing fibres are embedded. Stress is transferred from the polymer matrix to the fibres which present a high tensile strength. Hence, the mechanical properties of polymers could be improved. The purpose of this study was to compare fracture strength, fracture toughness and flexural strength of an experimental fibre-reinforced bracket material, an SiO(2) filler-reinforced bracket and an unfilled plastic bracket material (control group). Experimental brackets and specialized bars were manufactured. Tests were performed after thermal cycling (5 degrees C/55 degrees C) the samples in an artificial oral environment of a device to simulate mastication. Statistical evaluation was undertaken. The median, 25th and 75th percentiles were calculated and a Mann-Whitney U-test was performed. In this study two findings were obvious. (1) Filler reinforcement of plastic brackets improved fracture strength and fracture toughness in comparison with the unfilled bracket material. (2) Glass fibre reinforcement of orthodontic bracket materials resulted in the greatest enhancement of the mechanical properties in comparison with the other test groups. Therefore, the application of glass fibres in plastic brackets is a successful method to enhance fracture strength.

Influence of filler level on the bond strength of orthodontic adhesives.

OBJECTIVE: To evaluate the effect of different filler contents of orthodontic adhesives on shear bond strength and Adhesive Remnant Index (ARI). MATERIALS AND METHODS: Four experimental adhesive groups were created: group 1 was an unfilled urethane-dimethacrylate (UDMA) adhesive, group 2 consisted of UDMA and a filler content of 30 vol%, group 3 consisted of UDMA and a filler content of 50 vol%, and group 4 was manufactured with a filler level of 70 vol% in a UDMA matrix. The embedded filler was silicon dioxide. After etching and priming, stainless steel brackets were bonded to extracted human third molars (n = 60) with the experimental adhesives (15 teeth per group). After storage in distilled water for 72 hours, shear bond strength and ARI scores were evaluated. Kruskal-Wallis and post hoc test were performed for statistical analysis. RESULTS: Shear bond strength of UDMA-based adhesives depends on filler content. Higher adhesive filler levels reveal greater bond strength between enamel and stainless steel brackets. ARI scores showed no significant difference among the groups. However, higher filled adhesives (filler content 70 vol%) seem to present higher ARI scores. CONCLUSION: Highly filled UDMA adhesives offer greater bond strength than do lower filled or unfilled resins.

A mathematical model of cerebral circulation and oxygen supply.

A compartment model of cerebral circulation and oxygen supply including an autoregulation mechanism is presented. The model is focused on the analysis of slow dynamical variations of long term neurophysiological parameters like the partial oxygen pressure of brain tissue or the cerebral blood flow. The circulatory part of the model is built up of seven compartments including arteries, capillaries, veins, brain tissue, cerebrospinal fluid, the sagittal sinus and an artificial compartment for the simulation of brain swelling. The description of oxygen supply is based on a Krogh model. Numerical calculations reproduce the experimentally well established connection between arterial blood pressure and the production of cerebrospinal fluid. Furthermore we found an approximately linear correlation of the partial oxygen pressure of brain tissue to the mean arterial blood pressure in the case of an impaired autoregulation mechanism. In a first test such a linear dependence could also be detected in clinical data from the neurosurgical intensive care monitoring.

Lack of correlation between Xenon133 and near infrared spectroscopy/indocyanine green rCBF measurements.

In recent literature there are some reports describing cerebral blood flow measurements by a near infrared spectroscopy-based technique with indocyanine-green as an absorbant. To our knowledge there is no systematical study which evaluates this technique in comparison to absolute cerebral blood flow measurements. Ten patients suffering from head injury (n = 9) or subarachnoid hemorrhage (n = 1) were included. Twenty measurements of cerebral blood flow were performed, employing a Xenon133 clearance technique. Near-infrared spectroscopy measurements were performed with the Somanetics 4100 System. Indocyanine-green was given at a total dose of 0.2 mg kg-1 bodyweight intravenously. The indocyanine-green curve was compared to cerebral blood flow measurements according to rising time and area under the curve as suggested in the literature. No correlation between the indocyanine-green clearance curve and the Xenon133 cerebral blood flow measurements could be found. Neither the area under the curve (p = 0.93) nor the rising time (p = 0.75) showed a statistically significant correlation. The near-infrared spectroscopy based indocyanine-green clearance curve measurement method of cerebral blood flow seems not to give reliable results using simple mathematical models (area under the curve and rising time). In view of our findings, we have serious reservations in the potential of this technique.

Comparison of near-infrared spectroscopy and tissue p(O2) time series in patients after severe head injury and aneurysmal subarachnoid hemorrhage.

Monitoring of local oxygen pressure in brain white matter (tip(O2)) and of local hemoglobin oxygen saturation (rS(O2)) with near-infrared spectroscopy (NIRS) are increasingly employed techniques in neurosurgical intensive care units. Using frequency-based mathematical methods, the authors sought to ascertain whether both techniques contained similar information. Twelve patients treated in the intensive care unit were included (subarachnoid hemorrhage, n = 3; traumatic brain injury, n = 9). A tip(O2) probe and an NIRS sensor were positioned over the frontal lobe with the most pathologic changes on initial computed tomography scan. The authors calculated coherence of tip(O2) and rS(O2) ts overall density distribution, its distribution per data set, and its time evolution. The authors identified a band of significantly correlated frequencies (from 0 to 1.3 x 10(3) Hz) in more than 90% of the data sets for coherence and overall density distribution. Time evolution showed slow but marked changes of significant coherence. By means of spectral analysis the authors show that tip(O2) and rS(O2)signals contain similar information, albeit using completely different registration methodologies.