GPi-DBS-induced brain metabolic activation in cervical dystonia.

BACKGROUND: Deep brain stimulation (DBS) of the globus pallidus interna (GPi) is a highly efficacious treatment for cervical dystonia, but its mechanism of action is not fully understood. Here, we investigate the brain metabolic effects of GPi-DBS in cervical dystonia. METHODS: Eleven patients with GPi-DBS underwent brain 18F-fluorodeoxyglucose positron emission tomography imaging during stimulation on and off. Changes in regional brain glucose metabolism were investigated at the active contact location and across the whole brain. Changes in motor symptom severity were quantified using the Toronto Western Spasmodic Torticollis Rating Scale (TWSTRS), executive function using trail making test (TMT) and parkinsonism using Unified Parkinson's Disease Rating Scale (UPDRS). RESULTS: The mean (SD) best therapeutic response to DBS during the treatment was 81 (22)%. The TWSTRS score was 3.2 (3.9) points lower DBS on compared with off (p=0.02). At the stimulation site, stimulation was associated with increased metabolism, which correlated with DBS stimulation amplitude (r=0.70, p=0.03) but not with changes in motor symptom severity (p>0.9). In the whole brain analysis, stimulation increased metabolism in the GPi, subthalamic nucleus, putamen, primary sensorimotor cortex (PFDR<0.05). Acute improvement in TWSTRS correlated with metabolic activation in the sensorimotor cortex and overall treatment response in the supplementary motor area. Worsening of TMT-B score was associated with activation of the anterior cingulate cortex and parkinsonism with activation in the putamen. CONCLUSIONS: GPi-DBS increases metabolic activity at the stimulation site and sensorimotor network. The clinical benefit and adverse effects are mediated by modulation of specific networks.

Clinical and Brain Morphometry Predictors of Deep Brain Stimulation Outcome in Parkinson's Disease.

Subthalamic deep brain stimulation (STN-DBS) is known to improve motor function in advanced Parkinson's disease (PD) and to enable a reduction of anti-parkinsonian medication. While the levodopa challenge test and disease duration are considered good predictors of STN-DBS outcome, other clinical and neuroanatomical predictors are less established. This study aimed to evaluate, in addition to clinical predictors, the effect of patients' individual brain topography on DBS outcome. The medical records of 35 PD patients were used to analyze DBS outcomes measured with the following scales: Part III of the Unified Parkinson's Disease Rating Scale (UPDRS-III) off medication at baseline, and at 6-months during medication off and stimulation on, use of anti-parkinsonian medication (LED), Abnormal Involuntary Movement Scale (AIMS) and Non-Motor Symptoms Questionnaire (NMS-Quest). Furthermore, preoperative brain MRI images were utilized to analyze the brain morphology in relation to STN-DBS outcome. With STN-DBS, a 44% reduction in the UPDRS-III score and a 43% decrease in the LED were observed (p<0.001). Dyskinesia and non-motor symptoms decreased significantly [median reductions of 78,6% (IQR 45,5%) and 18,4% (IQR 32,2%) respectively, p=0.001 - 0.047]. Along with the levodopa challenge test, patients' age correlated with the observed DBS outcome measured as UPDRS-III improvement (ρ= -0.466 - -0.521, p<0.005). Patients with greater LED decline had lower grey matter volumes in left superior medial frontal gyrus, in supplementary motor area and cingulum bilaterally. Additionally, patients with greater UPDRS-III score improvement had lower grey matter volume in similar grey matter areas. These findings remained significant when adjusted for sex, age, baseline LED and UPDRS scores respectively and for total intracranial volume (p=0.0041- 0.001). However, only the LED decrease finding remained significant when the analyses were further controlled for stimulation amplitude. It appears that along with the clinical predictors of STN-DBS outcome, individual patient topographic differences may influence DBS outcome. Clinical Trial Registration Number: NCT06095245, registration date October 23, 2023, retrospectively registered.

Overlapping stimulation of subthalamic nucleus and dentato-rubro-thalamic tract in Parkinson's disease after deep brain stimulation.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) reduces tremor, rigidity, and akinesia. According to the literature, the dentato-rubro-thalamic tract (DRTt) is verified target for DBS in essential tremor; however, its role in the treatment of Parkinson's disease is only vaguely described. The aim of our study was to identify the relationship between symptom alleviation in PD patients and the distance of the DBS electrode electric field (EF) to the DRTt. METHODS: A single-center retrospective analysis of patients (N = 30) with idiopathic Parkinson's disease (PD) who underwent DBS between November 2018 and January 2020 was performed. DRTt and STN were visualized using diffusion-weighted imaging (DWI) and tractography protocol of magnetic resonance (MR). The EF was calculated and compared with STN and course of DRTt. Evaluation of patients before and after surgery was performed with use of UPDRS-III scale. The association between distance from EF to DRTt and clinical outcomes was examined. To confirm the anatomical variation between DRTt and STN observed in tractography, white matter dissection was performed with the Klingler technique on ten human brains. RESULTS: Patients with EF overlapping STN and DRTt benefited from significant motor symptoms improvement. Anatomical findings confirmed the presence of population differences in variability of the DRTt course and were consistent with the DRTt visualized by MR. CONCLUSIONS: DRTt proximity to STN, the main target in PD DBS surgery, confirmed by DWI with tractography protocol of MR combined with proper predefined stimulation parameters may improve efficacy of DBS-STN.

The effect of subthalamic nucleus deep brain stimulation on speech performance: a prospective clinical and tractography study.

BACKGROUND: Speech changes significantly impact the quality of life for Parkinson's disease (PD) patients. Deep Brain Stimulation (DBS) of the Subthalamic Nucleus (STN) is a standard treatment for advanced PD, but its effects on speech remain unclear. This study aimed to investigate the relationship between STN-DBS and speech changes in PD patients using comprehensive clinical assessments and tractography. METHODS: Forty-seven PD patients underwent STN-DBS, with preoperative and 3-month postoperative assessments. Speech analyses included acoustic measurements, auditory-perceptual evaluations, and fluency-intelligibility tests. On the other hand, structures within the volume tissue activated (VTA) were identified using MRI and DTI. The clinical and demographic data and structures associated with VTA (Corticospinal tract, Internal capsule, Dentato-rubro-thalamic tract, Medial forebrain bundle, Medial lemniscus, Substantia nigra, Red nucleus) were compared with speech analyses. RESULTS: The majority of patients (36.2-55.4% good, 29.7-53.1% same) exhibited either improved or unchanged speech quality following STN-DBS. Only a small percentage (8.5-14.9%) experienced deterioration. Older patients and those with worsened motor symptoms postoperatively were more likely to experience negative speech changes (p < 0.05). Interestingly, stimulation of the right Substantia Nigra correlated with improved speech quality (p < 0.05). No significant relationship was found between other structures affected by VTA and speech changes. CONCLUSIONS: This study suggests that STN-DBS does not predominantly negatively impact speech in PD patients, with potential benefits observed, especially in younger patients. These findings underscore the importance of individualized treatment approaches and highlight the need for further long-term studies to optimize therapeutic outcomes and better understand the effects of STN-DBS on speech.

Dysconnectivity of the parafascicular nucleus in Parkinson's disease: A dynamic causal modeling analysis.

BACKGROUND: Recent animal model studies have suggested that the parafascicular nucleus has the potential to be an effective deep brain stimulation target for Parkinson's disease. However, our knowledge on the role of the parafascicular nucleus in Parkinson's disease patients remains limited. OBJECTIVE: We aimed to investigate the functional alterations of the parafascicular nucleus projections in Parkinson's disease patients. METHODS: We enrolled 72 Parkinson's disease patients and 60 healthy controls, then utilized resting-state functional MRI and spectral dynamic causal modeling to explore the effective connectivity of the bilateral parafascicular nucleus to the dorsal putamen, nucleus accumbens, and subthalamic nucleus. The associations between the effective connectivity of the parafascicular nucleus projections and clinical features were measured with Pearson partial correlations. RESULTS: Compared with controls, the effective connectivity from the parafascicular nucleus to dorsal putamen was significantly increased, while the connectivity to the nucleus accumbens and subthalamic nucleus was significantly reduced in Parkinson's disease patients. There was a significantly positive correlation between the connectivity of parafascicular nucleus-dorsal putamen projection and motor deficits. The connectivity from the parafascicular nucleus to the subthalamic nucleus was negatively correlated with motor deficits and apathy, while the connectivity from the parafascicular nucleus to the nucleus accumbens was negatively associated with depression. CONCLUSION: The present study demonstrates that the parafascicular nucleus-related projections are damaged and associated with clinical symptoms of Parkinson's disease. Our findings provide new insights into the impaired basal ganglia-thalamocortical circuits and give support for the parafascicular nucleus as a potential effective neuromodulating target of the disease.

Programming of subthalamic nucleus deep brain stimulation with hyperdirect pathway and corticospinal tract-guided parameter suggestions.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is an effective treatment for advanced Parkinson's disease. Stimulation of the hyperdirect pathway (HDP) may mediate the beneficial effects, whereas stimulation of the corticospinal tract (CST) mediates capsular side effects. The study's objective was to suggest stimulation parameters based on the activation of the HDP and CST. This retrospective study included 20 Parkinson's disease patients with bilateral STN DBS. Patient-specific whole-brain probabilistic tractography was performed to extract the HDP and CST. Stimulation parameters from monopolar reviews were used to estimate volumes of tissue activated and to determine the streamlines of the pathways inside these volumes. The activated streamlines were related to the clinical observations. Two models were computed, one for the HDP to estimate effect thresholds and one for the CST to estimate capsular side effect thresholds. In a leave-one-subject-out cross-validation, the models were used to suggest stimulation parameters. The models indicated an activation of 50% of the HDP at effect threshold, and 4% of the CST at capsular side effect threshold. The suggestions for best and worst levels were significantly better than random suggestions. Finally, we compared the suggested stimulation thresholds with those from the monopolar reviews. The median suggestion errors for the effect threshold and side effect threshold were 1 and 1.5 mA, respectively. Our stimulation models of the HDP and CST suggested STN DBS settings. Prospective clinical studies are warranted to optimize tract-guided DBS programming. Together with other modalities, these may allow for assisted STN DBS programming.

Simultaneous PET/fMRI revealed increased motor area input to subthalamic nucleus in Parkinson's disease.

Invasive electrophysiological recordings in patients with Parkinson's disease (PD) are extremely difficult for cross-sectional comparisons with healthy controls. Noninvasive approaches for identifying information flow between the motor area and the subthalamic nucleus (STN) are critical for evaluation of treatment strategy. We aimed to investigate the direction of the cortical-STN hyperdirect pathway using simultaneous 18F-FDG-PET/functional magnetic resonance imaging (fMRI). Data were acquired during resting state on 34 PD patients and 25 controls. The ratio of standard uptake value for PET images and the STN functional connectivity (FC) maps for fMRI data were generated. The metabolic connectivity mapping (MCM) approach that combines PET and fMRI data was used to evaluate the direction of the connectivity. Results showed that PD patients exhibited both increased FDG uptake and STN-FC in the sensorimotor area (PFDR < 0.05). MCM analysis showed higher cortical-STN MCM value in the PD group (F = 6.63, P = 0.013) in the left precentral gyrus. There was a high spatial overlap between the increased glucose metabolism and increased STN-FC in the sensorimotor area in PD. The MCM approach further revealed an exaggerated cortical input to the STN in PD, supporting the precentral gyrus as a target for treatment such as the repetitive transcranial magnetic stimulation.

Automatic Segmentation of Parkinson Disease Therapeutic Targets Using Nonlinear Registration and Clinical MR Imaging: Comparison of Methodology, Presence of Disease, and Quality Control.

INTRODUCTION: Accurate and precise delineation of the globus pallidus pars interna (GPi) and subthalamic nucleus (STN) is critical for the clinical treatment and research of Parkinson's disease (PD). Automated segmentation is a developing technology which addresses limitations of visualizing deep nuclei on MR imaging and standardizing their definition in research applications. We sought to compare manual segmentation with three workflows for template-to-patient nonlinear registration providing atlas-based automatic segmentation of deep nuclei. METHODS: Bilateral GPi, STN, and red nucleus (RN) were segmented for 20 PD and 20 healthy control (HC) subjects using 3T MRIs acquired for clinical purposes. The automated workflows used were an option available in clinical practice and two common research protocols. Quality control (QC) was performed on registered templates via visual inspection of readily discernible brain structures. Manual segmentation using T1, proton density, and T2 sequences was used as "ground truth" data for comparison. Dice similarity coefficient (DSC) was used to assess agreement between segmented nuclei. Further analysis was done to compare the influences of disease state and QC classifications on DSC. RESULTS: Automated segmentation workflows (CIT-S, CRV-AB, and DIST-S) had the highest DSC for the RN and lowest for the STN. Manual segmentations outperformed automated segmentation for all workflows and nuclei; however, for 3/9 workflows (CIT-S STN, CRV-AB STN, and CRV-AB GPi) the differences were not statically significant. HC and PD only showed significant differences in 1/9 comparisons (DIST-S GPi). QC classification only demonstrated significantly higher DSC in 2/9 comparisons (CRV-AB RN and GPi). CONCLUSION: Manual segmentations generally performed better than automated segmentations. Disease state does not appear to have a significant effect on the quality of automated segmentations via nonlinear template-to-patient registration. Notably, visual inspection of template registration is a poor indicator of the accuracy of deep nuclei segmentation. As automatic segmentation methods continue to evolve, efficient and reliable QC methods will be necessary to support safe and effective integration into clinical workflows.

Quantifying the Variability Associated with Postoperative Localization of Deep Brain Stimulation Electrodes.

INTRODUCTION: Computational models of deep brain stimulation (DBS) have become common tools in clinical research studies that attempt to establish correlations between stimulation locations in the brain and behavioral outcome measures. However, the accuracy of any patient-specific DBS model depends heavily upon accurate localization of the DBS electrodes within the anatomy, which is typically defined via co-registration of clinical CT and MRI datasets. Several different approaches exist for this challenging registration problem, and each approach will result in a slightly different electrode localization. The goal of this study was to better understand how different processing steps (e.g., cost-function masking, brain extraction, intensity remapping) affect the estimate of the DBS electrode location in the brain. METHODS: No "gold standard" exists for this kind of analysis, as the exact location of the electrode in the living human brain cannot be determined with existing clinical imaging approaches. However, we can estimate the uncertainty associated with the electrode position, which can be used to guide statistical analyses in DBS mapping studies. Therefore, we used high-quality clinical datasets from 10 subthalamic DBS subjects and co-registered their long-term postoperative CT with their preoperative surgical targeting MRI using 9 different approaches. The distances separating all of the electrode location estimates were calculated for each subject. RESULTS: On average, electrodes were located within a median distance of 0.57 mm (0.49-0.74) of one another across the different registration approaches. However, when considering electrode location estimates from short-term postoperative CTs, the median distance increased to 2.01 mm (1.55-2.78). CONCLUSIONS: The results of this study suggest that electrode location uncertainty needs to be factored into statistical analyses that attempt to define correlations between stimulation locations and clinical outcomes.

Improved visualization of the subthalamic nucleus on synthetic MRI with optimized parameters: initial study.

BACKGROUND: Synthetic magnetic resonance imaging (SyMRI) enables to reformat various images by adjusting the MR parameters. PURPOSE: To investigate whether customization of the repetition time (TR), echo time (TE), and inversion time (TI) in SyMRI could improve the visualization of subthalamic nucleus (STN). MATERIAL AND METHODS: We examined five healthy volunteers using both coronal SyMRI and quantitative susceptibility mapping (QSM), seven patients with Parkinson's disease (PD) using coronal SyMRI, and 15 patients with PD using coronal QSM. Two neuroradiologists reformatted SyMRI (optimized SyMRI) by adjusting TR, TE, and TI to achieve maximum tissue contrast between the STN and the adjacent brain parenchyma. The optimized MR parameters in the PD patients varied according to the individual. For regular SyMRI (T2-weighted imaging [T2WI] and STIR), optimized SyMRI, and QSM, qualitative visualization scores of the STN (STN score) were recorded. The contrast-to-noise ratio (CNR) of the STN was also measured. RESULTS: For the STN scores in both groups, the optimized SyMRI were significantly higher than the regular SyMRI (P < 0.05), and there were no significant differences between optimized SyMRI and QSM. For the CNR of differentiation of the STN from the substantia nigra, the optimized SyMRI was higher than the regular SyMRI (volunteer: T2WI P = 0.10 and STIR P = 0.26; PD patient: T2WI P = 0.43 and STIR P = 0.25), but the optimized SyMRI was lower than the QSM (volunteer: P = 0.26; PD patient: P = 0.03). CONCLUSIONS: On SyMRI, optimization of MR parameters (TR, TE, and TI) on an individual basis may be useful to increase the conspicuity of the STN.

Inhibition of impulsive action by projection-defined prefrontal pyramidal neurons.

The prefrontal cortex (PFC) plays a critical role in curbing impulsive behavior, but the underlying circuit mechanism remains incompletely understood. Here we show that a subset of dorsomedial PFC (dmPFC) layer 5 pyramidal neurons, which project to the subthalamic nucleus (STN) of the basal ganglia, play a key role in inhibiting impulsive responses in a go/no-go task. Projection-specific labeling and calcium imaging showed that the great majority of STN-projecting neurons were preferentially active in no-go trials when the mouse successfully withheld licking responses, but lateral hypothalamus (LH)-projecting neurons were more active in go trials with licking; visual cortex (V1)-projecting neurons showed only weak task-related activity. Optogenetic activation and inactivation of STN-projecting neurons reduced and increased inappropriate licking, respectively, partly through their direct innervation of the STN, but manipulating LH-projecting neurons had the opposite effects. These results identify a projection-defined subtype of PFC pyramidal neurons as key mediators of impulse control.

Comparison of two segmentation software tools for deep brain stimulation of the subthalamic and ventro-intermedius nuclei.

PURPOSE: Deep brain stimulation (DBS) relies on precise targeting of key structures such as the subthalamic nucleus (STN) for Parkinson's disease (PD) and the ventro-intermedius nucleus of the thalamus (Vim) for essential tremor (ET). Segmentation software, such as GuideXT© and Suretune©, are commercially available for atlas-based identification of deep brain structures. However, no study has compared the concordance of the segmentation results between the two software. METHODS: We retrospectively compared the concordance of segmentation of GuideXT© and Suretune© software by comparing the position of the segmented key structures with clinically predicted targets obtained using the newly developed RebrAIn© software as a reference. RESULTS: We targeted the STN in 44 MRI from PD patients (88 hemispheres) and the Vim in 31 MRI from ET patients (62 hemispheres) who were elected for DBS. In 22 STN targeting (25%), the target positioning was not correlating between GuideXT© and Suretune©. Regarding the Vim, targets were located in the segmented Vim in 37%, the posterior subthalamic area (PSA) in 60%, and the STN in 3% of the cases using GuideXT©; the proportions were 34%, 60%, and 6%, respectively, using Suretune©. The mean distance from the centre of the RebrAIn© targeting to the segmented Vim by Suretune© was closer (0.64 mm) than with GuideXT© (0.96 mm; p = 0.0004). CONCLUSION: While there is some level of concordance in the segmentation results of key structures for DBS treatment among software models, differences persist. Therefore, such software should still be considered as tools and should not replace clinician experience in DBS planning.

Comparison of direct MRI guided versus atlas-based targeting for subthalamic nucleus and globus pallidus deep brain stimulation.

PURPOSE: The subthalamic nucleus (STN) and globus pallidus internus (GPi) targets for deep brain stimulation (DBS) can be defined by atlas coordinates or direct visualisation of the target on MRI. The aim of this study was to evaluate geometric differences between atlas-based targeting and MRI-guided direct targeting. METHODS: One-hundred-nine Parkinson's disease or dystonia patients records who underwent DBS surgery between 2005 and 2016 were prospectively reviewed. MRI-guided direct targeting coordinates was used to implant 205 STN and 64 GPi electrodes and compared with atlas-based coordinates. RESULTS: The directly targeted coordinates (mean, SD, range) for STN were x: [9.9 ± 1.1 (7.1 - 13.2)], y: [-0.8 ± 1.1 (-4.2 - 2)] and z: [-4.7 ± 0.53 (-5.9 - -3.2)]. The mean value for the STN was 2.1 mm more medial (p < 0.0001), 1.2 mm more anterior (p < 0.0001) and 0.7 mm more ventral (p < 0.0001) than the atlas target. The targeted coordinates for GPi were x: [22.3 ± 2.0 (17.8 - 26.1)], y: [-0.2 ± 2.2 (-4.5 - 3.4)], z: [-4.3 ± 0.8 (-6.2 - -2.3)]. The mean value for the GPi was 2.2 mm (p < 0.001) more posterior and 0.3 mm (p < 0.01) more ventral than the atlas-based coordinates. CONCLUSION: MRI-guided targeting may be more accurate than atlas-based targeting due to individual variations in anatomy.

Utilizing 7-Tesla Subthalamic Nucleus Connectivity in Deep Brain Stimulation for Parkinson Disease.

BACKGROUND: Deep brain stimulation (DBS) of the subthalamic nucleus (STN) is a highly effective surgical treatment for patients with advanced Parkinson disease (PD). Combining 7.0-Tesla (7T) T2- and diffusion-weighted imaging (DWI) sequences allows for selective segmenting of the motor part of the STN and, thus, for possible optimization of DBS. MATERIALS AND METHODS: 7T T2 and DWI sequences were obtained, and probabilistic segmentation of motor, associative, and limbic STN segments was performed. Left- and right-sided motor outcome (Movement Disorders Society Unified Parkinson's Disease Rating Scale) scores were used for evaluating the correspondence between the active electrode contacts in selectively segmented STN and the clinical DBS effect. The Bejjani line was reviewed for crossing of segments. RESULTS: A total of 50 STNs were segmented in 25 patients and proved highly feasible. Although the highest density of motor connections was situated in the dorsolateral STN for all patients, the exact partitioning of segments differed considerably. For all the active electrode contacts situated within the predominantly motor-connected segment of the STN, the average hemi-body Unified Parkinson's Disease Rating Scale motor improvement was 80%; outside this segment, it was 52% (p < 0.01). The Bejjani line was situated in the motor segment for 32 STNs. CONCLUSION: The implementation of 7T T2 and DWI segmentation of the STN in DBS for PD is feasible and offers insight into the location of the motor segment. Segmentation-guided electrode placement is likely to further improve motor response in DBS for PD. However, commercially available DBS software for postprocessing imaging would greatly facilitate widespread implementation.

Intraoperative Local Field Potential Beta Power and Three-Dimensional Neuroimaging Mapping Predict Long-Term Clinical Response to Deep Brain Stimulation in Parkinson Disease: A Retrospective Study.

BACKGROUND: Directional deep brain stimulation (DBS) leads allow a fine-tuning control of the stimulation field, however, this new technology could increase the DBS programming time because of the higher number of the possible combinations used in directional DBS than in standard nondirectional electrodes. Neuroimaging leads localization techniques and local field potentials (LFPs) recorded from DBS electrodes implanted in basal ganglia are among the most studied biomarkers for DBS programing. OBJECTIVE: This study aimed to evaluate whether intraoperative LFPs beta power and neuroimaging reconstructions correlate with contact selection in clinical programming of DBS in patients with Parkinson disease (PD). MATERIALS AND METHODS: In this retrospective study, routine intraoperative LFPs recorded from all contacts in the subthalamic nucleus (STN) of 14 patients with PD were analyzed to calculate the beta band power for each contact. Neuroimaging reconstruction obtained through Brainlab Elements Planning software detected contacts localized within the STN. Clinical DBS programming contact scheme data were collected after one year from the implant. Statistical analysis evaluated the diagnostic performance of LFPs beta band power and neuroimaging data for identification of the contacts selected with clinical programming. We evaluated whether the most effective contacts identified based on the clinical response after one year from implant were also those with the highest level of beta activity and localized within the STN in neuroimaging reconstruction. RESULTS: LFPs beta power showed a sensitivity of 67%, a negative predictive value (NPV) of 84%, a diagnostic odds ratio (DOR) of 2.7 in predicting the most effective contacts as evaluated through the clinical response. Neuroimaging reconstructions showed a sensitivity of 62%, a NPV of 77%, a DOR of 1.20 for contact effectivity prediction. The combined use of the two methods showed a sensitivity of 87%, a NPV of 87%, a DOR of 2.7 for predicting the clinically more effective contacts. CONCLUSIONS: The combined use of LFPs beta power and neuroimaging localization and segmentations predict which are the most effective contacts as selected on the basis of clinical programming after one year from implant of DBS. The use of predictors in contact selection could guide clinical programming and reduce time needed for it.

Brain Morphometry Associated With Response to Levodopa and Deep Brain Stimulation in Parkinson Disease.

OBJECTIVES: Whether treatment response in patients with Parkinson disease depends on brain atrophy is insufficiently understood. The goal of this study is to identify specific atrophy patterns associated with response to dopaminergic therapy and deep brain stimulation. MATERIALS AND METHODS: In this study, we analyzed the association of gray matter brain atrophy patterns, as identified by voxel-based morphometry, with acute response to levodopa (N = 118) and subthalamic nucleus deep brain stimulation (N = 39). Motor status was measured as a change in points on the Unified Parkinson's Disease Rating Scale III score. Baseline values were obtained before surgery, after cessation of dopaminergic medication for at least 12 hours; response to medication was assessed after administration of a standardized dose of levodopa. Response to deep brain stimulation was measured three months after surgery in the clinical condition after withdrawal of dopaminergic medication. RESULTS: Although frontoparietal brain gray matter loss was associated with subpar response to deep brain stimulation, there was no significant link between brain atrophy and response to levodopa. CONCLUSION: We conclude that response to deep brain stimulation relies on gray matter integrity; hence, gray matter loss may present a risk factor for poor response to deep brain stimulation and may be considered when making decision regarding clinical practice.

Combining Multimodal Biomarkers to Guide Deep Brain Stimulation Programming in Parkinson Disease.

BACKGROUND: Deep brain stimulation (DBS) programming of multicontact DBS leads relies on a very time-consuming manual screening procedure, and strategies to speed up this process are needed. Beta activity in subthalamic nucleus (STN) local field potentials (LFP) has been suggested as a promising marker to index optimal stimulation contacts in patients with Parkinson disease. OBJECTIVE: In this study, we investigate the advantage of algorithmic selection and combination of multiple resting and movement state features from STN LFPs and imaging markers to predict three relevant clinical DBS parameters (clinical efficacy, therapeutic window, side-effect threshold). MATERIALS AND METHODS: STN LFPs were recorded at rest and during voluntary movements from multicontact DBS leads in 27 hemispheres. Resting- and movement-state features from multiple frequency bands (alpha, low beta, high beta, gamma, fast gamma, high frequency oscillations [HFO]) were used to predict the clinical outcome parameters. Subanalyses included an anatomical stimulation sweet spot as an additional feature. RESULTS: Both resting- and movement-state features contributed to the prediction, with resting (fast) gamma activity, resting/movement-modulated beta activity, and movement-modulated HFO being most predictive. With the proposed algorithm, the best stimulation contact for the three clinical outcome parameters can be identified with a probability of almost 90% after considering half of the DBS lead contacts, and it outperforms the use of beta activity as single marker. The combination of electrophysiological and imaging markers can further improve the prediction. CONCLUSION: LFP-guided DBS programming based on algorithmic selection and combination of multiple electrophysiological and imaging markers can be an efficient approach to improve the clinical routine and outcome of DBS patients.

The Effect of Surgical Positioning on Pneumocephalus in Subthalamic Nucleus Deep Brain Stimulation Surgery for Parkinson Disease.

OBJECTIVES: This research analyzed the effect of surgical positioning on postoperative pneumocephalus and assessed additional potential risk factors of pneumocephalus in subthalamic nucleus (STN) deep brain stimulation (DBS) for Parkinson disease (PD). MATERIALS AND METHODS: In this study, 255 consecutive patients with PD who received bilateral STN DBS under general anesthesia were retrospectively included. Of these, 180 patients underwent surgery with their heads in an elevated position, and 75 patients underwent surgery in a supine position. The postoperative pneumocephalus volume was compared between the two groups. Other potential risk factors for pneumocephalus also were analyzed. RESULTS: The mean pneumocephalus volume for the group with elevated-head positioning (16.76 ± 15.23 cm3) was greater than for the supine group (3.25 ± 8.78 cm3) (p < 0.001). Multivariable analysis indicated that the pneumocephalus volume was related to surgical positioning, lateral trajectory angle, intraoperative mean arterial pressure (MAP), microelectrode recording (MER) passage number, brain atrophy degree, and the anterior trajectory angle. No correlation was found between pneumocephalus and age, sex, duration of PD, surgery length, or intracranial volume. In the subgroup analysis, the pneumocephalus volume exhibited a negative correlation with intraoperative MAP (r = -0.210, p = 0.005) and positive correlations with degree of brain atrophy (r = 0.242, p = 0.001) and MER passage number (r = 0.184, p = 0.014) in the elevated-head group. Specifically, an MER passage number > 3 was a significant risk factor for pneumocephalus in the elevated-head group. A positive correlation was observed between the pneumocephalus volume and the lateral trajectory angle in both groups (elevated-head positioning, r = 0.153, p = 0.041; supine positioning, r = 0.546, p < 0.001). CONCLUSIONS: In patients with PD who were anesthetized and receiving STN DBS, supine positioning reduced pneumocephalus volume compared with patients with PD receiving STN DBS with their heads elevated. The pneumocephalus volume was negatively correlated with intraoperative MAP and positively correlated with the degree of brain atrophy, the lateral trajectory angle, and the MER passage number.

Effects of diffusion signal modeling and segmentation approaches on subthalamic nucleus parcellation.

The subthalamic nucleus (STN) is commonly used as a surgical target for deep brain stimulation in movement disorders such as Parkinson's Disease. Tractography-derived connectivity-based parcellation (CBP) has been recently proposed as a suitable tool for non-invasive in vivo identification and pre-operative targeting of specific functional territories within the human STN. However, a well-established, accurate and reproducible protocol for STN parcellation is still lacking. The present work aims at testing the effects of different tractography-based approaches for the reconstruction of STN functional territories. We reconstructed functional territories of the STN on the high-quality dataset of 100 unrelated healthy subjects and on the test-retest dataset of the Human Connectome Project (HCP) repository. Connectivity-based parcellation was performed with a hypothesis-driven approach according to cortico-subthalamic connectivity, after dividing cortical areas into three groups: associative, limbic and sensorimotor. Four parcellation pipelines were compared, combining different signal modeling techniques (single-fiber vs multi-fiber) and different parcellation approaches (winner takes all parcellation vs fiber density thresholding). We tested these procedures on STN regions of interest obtained from three different, commonly employed, subcortical atlases. We evaluated the pipelines both in terms of between-subject similarity, assessed on the cohort of 100 unrelated healthy subjects, and of within-subject similarity, using a second cohort of 44 subjects with available test-retest data. We found that each parcellation provides converging results in terms of location of the identified parcels, but with significative variations in size and shape. All pipelines obtained very high within-subject similarity, with tensor-based approaches outperforming multi-fiber pipelines. On the other hand, higher between-subject similarity was found with multi-fiber signal modeling techniques combined with fiber density thresholding. We suggest that a fine-tuning of tractography-based parcellation may lead to higher reproducibility and aid the development of an optimized surgical targeting protocol.

Probabilistic Mapping of Deep Brain Stimulation: Insights from 15 Years of Therapy.

Deep brain stimulation (DBS) depends on precise delivery of electrical current to target tissues. However, the specific brain structures responsible for best outcome are still debated. We applied probabilistic stimulation mapping to a retrospective, multidisorder DBS dataset assembled over 15 years at our institution (ntotal = 482 patients; nParkinson disease = 303; ndystonia = 64; ntremor = 39; ntreatment-resistant depression/anorexia nervosa = 76) to identify the neuroanatomical substrates of optimal clinical response. Using high-resolution structural magnetic resonance imaging and activation volume modeling, probabilistic stimulation maps (PSMs) that delineated areas of above-mean and below-mean response for each patient cohort were generated and defined in terms of their relationships with surrounding anatomical structures. Our results show that overlap between PSMs and individual patients' activation volumes can serve as a guide to predict clinical outcomes, but that this is not the sole determinant of response. In the future, individualized models that incorporate advancements in mapping techniques with patient-specific clinical variables will likely contribute to the optimization of DBS target selection and improved outcomes for patients. ANN NEUROL 2021;89:426-443.