Deep Learning and fMRI-Based Pipeline for Optimization of Deep Brain Stimulation During Parkinson's Disease Treatment: Toward Rapid Semi-Automated Stimulation Optimization.

OBJECTIVE: Optimized deep brain stimulation (DBS) is fast becoming a therapy of choice for the treatment of Parkinson's disease (PD). However, the post-operative optimization (aimed at maximizing patient clinical benefits and minimizing adverse effects) of all possible DBS parameter settings using the standard-of-care clinical protocol requires numerous clinical visits, which substantially increases the time to optimization per patient (TPP), patient cost burden and limit the number of patients who can undergo DBS treatment. The TPP is further elongated in electrodes with stimulation directionality or in diseases with latency in clinical feedback. In this work, we proposed a deep learning and fMRI-based pipeline for DBS optimization that can potentially reduce the TPP from ~1 year to a few hours during a single clinical visit. METHODS AND PROCEDURES: We developed an unsupervised autoencoder (AE)-based model to extract meaningful features from 122 previously acquired blood oxygenated level dependent (BOLD) fMRI datasets from 39 a priori clinically optimized PD patients undergoing DBS therapy. The extracted features are then fed into multilayer perceptron (MLP)-based parameter classification and prediction models for rapid DBS parameter optimization. RESULTS: The AE-extracted features of optimal and non-optimal DBS were disentangled. The AE-MLP classification model yielded accuracy, precision, recall, F1 score, and combined AUC of 0.96 ± 0.04, 0.95 ± 0.07, 0.92 ± 0.07, 0.93 ± 0.06, and 0.98 respectively. Accuracies of 0.79 ± 0.04, 0.85 ± 0.04, 0.82 ± 0.05, 0.83 ± 0.05, and 0.70 ± 0.07 were obtained in the prediction of voltage, frequency, and x-y-z contact locations, respectively. CONCLUSION: The proposed AE-MLP models yielded promising results for fMRI-based DBS parameter classification and prediction, potentially facilitating rapid semi-automated DBS parameter optimization. Clinical and Translational Impact Statement-A deep learning-based pipeline for semi-automated DBS parameter optimization is presented, with the potential to significantly decrease the optimization duration per patient and patients' financial burden while increasing patient throughput.

Lateralized Subthalamic Stimulation for Axial Dysfunction in Parkinson's Disease: Exploratory Outcomes and Open-Label Extension.

BACKGROUND: A randomized trial suggested that reducing left-sided subthalamic stimulation amplitude could improve axial dysfunction. OBJECTIVES: To explore open-label tolerability and associations between trial outcomes and asymmetry data. METHODS: We collected adverse events in trial participants treated with open-label lateralized settings for ≥3 months. We explored associations between trial outcomes, location of stimulation and motor asymmetry. RESULTS: 14/17 participants tolerated unilateral amplitude reduction (left-sided = 10, right-sided = 4). Two hundred eighty-four left-sided and 1113 right-sided stimulated voxels were associated with faster gait velocity, 81 left-sided and 22 right-sided stimulated voxels were associated with slower gait velocity. Amplitude reduction contralateral to shorter step length was associated with 2.4-point reduction in axial MDS-UPDRS. Reduction contralateral to longer step length was associated with 10-point increase in MDS-UPDRS. CONCLUSIONS: Left-sided amplitude reduction is potentially more tolerable than right-sided amplitude reduction. Right-sided more than left-sided stimulation could be associated with faster gait velocity. Shortened step length might reflect contralateral overstimulation.

Probabilistic Refinement of Focused Ultrasound Thalamotomy Targeting for Parkinson's Disease Tremor.

BACKGROUND: There remains high variability in clinical outcomes when the same magnetic resonance image-guided focused ultrasound (MRgFUS) thalamotomy target is used for both essential tremor (ET) and tremor-dominant Parkinson's disease (TDPD). OBJECTIVE: Our goal is to refine the MRgFUS thalamotomy target for TDPD versus ET. METHODS: We retrospectively performed voxel-wise efficacy and structural connectivity mapping using 3-12-month post-procedure hand tremor scores for a multicenter cohort of 32 TDPD patients and a previously published cohort of 79 ET patients, and 24-hour T1-weighted post-MRgFUS brain images. We validated our findings using Unified Parkinson's Disease Rating Scale part III scores for an independent cohort of nine TDPD patients. RESULTS: The post-MRgFUS clinical improvements were 45.9% ± 35.9%, 55.5% ± 36%, and 46.1% ± 18.6% for ET, multicenter TDPD and validation TDPD cohorts, respectively. The TDPD and ET efficacy maps differed significantly (ppermute < 0.05), with peak TDPD improvement (87%) at x = -13.5; y = -15.0; z = 1.5, ~3.5 mm anterior and 3 mm dorsal to the ET target. Discriminative connectivity projections were to the motor and premotor regions in TDPD, and to the motor and somatosensory regions in ET. The disorder-specific voxel-wise efficacy map could be used to estimate outcome in TDPD patients with high accuracy (R = 0.8; R2 = 0.64; P < 0.0001). The model was validated using the independent cohort of nine TDPD patients (R = 0.73; R2 = 0.53; P = 0.025-voxel analysis). CONCLUSION: We demonstrated that the most effective MRgFUS thalamotomy target in TDPD is in the ventral intermediate nucleus/ventralis oralis posterior border region. This finding offers new insights into the thalamic regions instrumental in tremor control, with pivotal implications for improving treatment outcomes. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Enlarging and shrinking focal perivascular spaces.

BACKGROUND AND PURPOSE: Perivascular spaces (PVS) are interstitial fluid-filled spaces surrounding blood vessels traversing the deep gray nuclei and white matter of the brain. These are commonly encountered on CT and MR imaging and are generally asymptomatic and of no clinical significance. However, occasional changes in the size of focal PVS, for example, when enlarging, may mimic pathologies including neoplasms and infections, hence potentially confounding radiological interpretation. Given these potential diagnostic issues, we sought to better characterize common clinical and imaging features of focal PVS demonstrating size fluctuations. MATERIALS AND METHODS: Upon institutional approval, we retrospectively identified 4 cases demonstrating PVS with size changes at our institution. To supplement our cases, we also performed a literature review, which identified an additional 14 cases. Their clinical and imaging data were analyzed to identify characteristic features. RESULTS: Of the 18 total cases (including the 4 institutional cases), 10 cases increased and 8 decreased in size. These focal PVS ranged from 0.4-4.5 cm in size. Whereas a decrease in size did not represent a diagnostic issue, focal increase in size of PVS led to concerning differential diagnoses in at least 30% of the radiology reports. These enlarging PVS were most found in the basal ganglia and temporal lobe, and in patients with previous brain radiation treatment. CONCLUSION: Focal size change of PVS can occur, especially years after brain radiation treatment. Being cognizant of this benign finding is important to consider in the differential diagnosis to avoid undue patient anxiety or unnecessary medical intervention.

Deep brain stimulation for Alzheimer's disease - current status and next steps.

INTRODUCTION: Alzheimer's disease (AD) requires novel therapeutic approaches due to limited efficacy of current treatments. AREAS COVERED: This article explores AD as a manifestation of neurocircuit dysfunction and evaluates deep brain stimulation (DBS) as a potential intervention. Focusing on fornix-targeted stimulation (DBS-f), the article summarizes safety, feasibility, and outcomes observed in phase 1/2 trials, highlighting findings such as cognitive improvement, increased metabolism, and hippocampal growth. Topics for further study include optimization of electrode placement, and the role of stimulation-induced autobiographical-recall. Nucleus basalis of Meynert (DBS-NBM) DBS is also discussed and compared with DBS-f. Challenges with both DBS-f and DBS-NBM are identified, emphasizing the need for further research on optimal stimulation parameters. The article also reviews alternative DBS targets, including medial temporal lobe structures and the ventral capsule/ventral striatum. EXPERT OPINION: Looking ahead, a phase-3 DBS-f trial, and the prospect of closed-loop stimulation using EEG-derived biomarkers or hippocampal theta activity are highlighted. Recent FDA-approved therapies and other neuromodulation techniques like temporal interference and low-intensity ultrasound are considered. The article concludes by underscoring the importance of imaging-based diagnosis and staging to allow for circuit-targeted therapies, given the heterogeneity of AD and varied stages of neurocircuit dysfunction.

A large normative connectome for exploring the tractographic correlates of focal brain interventions.

Diffusion-weighted MRI (dMRI) is a widely used neuroimaging modality that permits the in vivo exploration of white matter connections in the human brain. Normative structural connectomics - the application of large-scale, group-derived dMRI datasets to out-of-sample cohorts - have increasingly been leveraged to study the network correlates of focal brain interventions, insults, and other regions-of-interest (ROIs). Here, we provide a normative, whole-brain connectome in MNI space that enables researchers to interrogate fiber streamlines that are likely perturbed by given ROIs, even in the absence of subject-specific dMRI data. Assembled from multi-shell dMRI data of 985 healthy Human Connectome Project subjects using generalized Q-sampling imaging and multispectral normalization techniques, this connectome comprises ~12 million unique streamlines, the largest to date. It has already been utilized in at least 18 peer-reviewed publications, most frequently in the context of neuromodulatory interventions like deep brain stimulation and focused ultrasound. Now publicly available, this connectome will constitute a useful tool for understanding the wider impact of focal brain perturbations on white matter architecture going forward.

Neural signatures of indirect pathway activity during subthalamic stimulation in Parkinson's disease.

Deep brain stimulation (DBS) of the subthalamic nucleus (STN) produces an electrophysiological signature called evoked resonant neural activity (ERNA); a high-frequency oscillation that has been linked to treatment efficacy. However, the single-neuron and synaptic bases of ERNA are unsubstantiated. This study proposes that ERNA is a subcortical neuronal circuit signature of DBS-mediated engagement of the basal ganglia indirect pathway network. In people with Parkinson's disease, we: (i) showed that each peak of the ERNA waveform is associated with temporally-locked neuronal inhibition in the STN; (ii) characterized the temporal dynamics of ERNA; (iii) identified a putative mesocircuit architecture, embedded with empirically-derived synaptic dynamics, that is necessary for the emergence of ERNA in silico; (iv) localized ERNA to the dorsal STN in electrophysiological and normative anatomical space; (v) used patient-wise hotspot locations to assess spatial relevance of ERNA with respect to DBS outcome; and (vi) characterized the local fiber activation profile associated with the derived group-level ERNA hotspot.

Assessing the Emergence and Evolution of Artificial Intelligence and Machine Learning Research in Neuroradiology.

BACKGROUND AND PURPOSE: Interest in artificial intelligence (AI) and machine learning (ML) has been growing in neuroradiology, but there is limited knowledge on how this interest has manifested into research and specifically, its qualities and characteristics. This study aims to characterize the emergence and evolution of AI/ML articles within neuroradiology and provide a comprehensive overview of the trends, challenges, and future directions of the field. MATERIALS AND METHODS: We performed a bibliometric analysis of the American Journal of Neuroradiology; the journal was queried for original research articles published since inception (January 1, 1980) to December 3, 2022 that contained any of the following key terms: "machine learning," "artificial intelligence," "radiomics," "deep learning," "neural network," "generative adversarial network," "object detection," or "natural language processing." Articles were screened by 2 independent reviewers, and categorized into statistical modeling (type 1), AI/ML development (type 2), both representing developmental research work but without a direct clinical integration, or end-user application (type 3), which is the closest surrogate of potential AI/ML integration into day-to-day practice. To better understand the limiting factors to type 3 articles being published, we analyzed type 2 articles as they should represent the precursor work leading to type 3. RESULTS: A total of 182 articles were identified with 79% being nonintegration focused (type 1 n = 53, type 2 n = 90) and 21% (n = 39) being type 3. The total number of articles published grew roughly 5-fold in the last 5 years, with the nonintegration focused articles mainly driving this growth. Additionally, a minority of type 2 articles addressed bias (22%) and explainability (16%). These articles were primarily led by radiologists (63%), with most (60%) having additional postgraduate degrees. CONCLUSIONS: AI/ML publications have been rapidly increasing in neuroradiology with only a minority of this growth being attributable to end-user application. Areas identified for improvement include enhancing the quality of type 2 articles, namely external validation, and addressing both bias and explainability. These results ultimately provide authors, editors, clinicians, and policymakers important insights to promote a shift toward integrating practical AI/ML solutions in neuroradiology.

Uncovering neuroanatomical correlates of impaired coordinated movement after pallidal deep brain stimulation.

BACKGROUND: The loss of the ability to swim following deep brain stimulation (DBS), although rare, poses a worrisome risk of drowning. It is unclear what anatomic substrate and neural circuitry underlie this phenomenon. We report a case of cervical dystonia with lost ability to swim and dance during active stimulation of globus pallidus internus. We investigated the anatomical underpinning of this phenomenon using unique functional and structural imaging analysis. METHODS: Tesla (3T) functional MRI (fMRI) of the patient was used during active DBS and compared with a cohort of four matched patients without this side effect. Structural connectivity mapping was used to identify brain network engagement by stimulation. RESULTS: fMRI during stimulation revealed significant (Pbonferroni<0.0001) stimulation-evoked responses (DBS ON

Successful magnetic resonance-guided focused ultrasound treatment of tremor in patients with a skull density ratio of 0.4 or less.

OBJECTIVE: The use of magnetic resonance-guided focused ultrasound (MRgFUS) for the treatment of tremor-related disorders and other novel indications has been limited by guidelines advocating treatment of patients with a skull density ratio (SDR) above 0.45 ± 0.05 despite reports of successful outcomes in patients with a low SDR (LSDR). The authors' goal was to retrospectively analyze the sonication strategies, adverse effects, and clinical and imaging outcomes in patients with SDR ≤ 0.4 treated for tremor using MRgFUS. METHODS: Clinical outcomes and adverse effects were assessed at 3 and 12 months after MRgFUS. Outcomes and lesion location, volume, and shape characteristics (elongation and eccentricity) were compared between the SDR groups. RESULTS: A total of 102 consecutive patients were included in the analysis, of whom 39 had SDRs ≤ 0.4. No patient was excluded from treatment because of an LSDR, with the lowest being 0.22. Lesioning temperatures (> 52°C) and therapeutic ablations were achieved in all patients. There were no significant differences in clinical outcome, adverse effects, lesion location, and volume between the high SDR group and the LSDR group. SDR was significantly associated with total energy (rho = -0.459, p < 0.001), heating efficiency (rho = 0.605, p < 0.001), and peak temperature (rho = 0.222, p = 0.025). CONCLUSIONS: The authors' results show that treatment of tremor in patients with an LSDR using MRgFUS is technically possible, leading to a safe and lasting therapeutic effect. Limiting the number of sonications and adjusting the energy and duration to achieve the required temperature early during the treatment are suitable strategies in LSDR patients.

Comparative neural correlates of DBS and MRgFUS lesioning for tremor control in essential tremor.

BACKGROUND: Given high rates of early complications and non-reversibility, refined targeting is necessitated for magnetic resonance-guided focused ultrasound (MRgFUS) thalamotomy for essential tremor (ET). Selection of lesion location can be informed by considering optimal stimulation area from deep brain stimulation (DBS). METHODS: 118 patients with ET who received DBS (39) or MRgFUS (79) of the ventral intermediate nucleus (VIM) underwent stimulation/lesion mapping, probabilistic mapping of clinical efficacy and normative structural connectivity analysis. The efficacy maps were compared, which depict the relationship between stimulation/lesion location and clinical outcome. RESULTS: Efficacy maps overlap around the VIM ventral border and encompass the dentato-rubro-thalamic tract. While the MRgFUS map extends inferiorly into the posterior subthalamic area, the DBS map spreads inside the VIM antero-superiorly. CONCLUSION: Comparing the efficacy maps of DBS and MRgFUS suggests a potential alternative location for lesioning, more antero-superiorly. This may reduce complications, without sacrificing efficacy, and individualise targeting. TRIAL REGISTRATION NUMBER: NCT02252380.

WarpDrive: Improving spatial normalization using manual refinements.

Spatial normalization-the process of mapping subject brain images to an average template brain-has evolved over the last 20+ years into a reliable method that facilitates the comparison of brain imaging results across patients, centers & modalities. While overall successful, sometimes, this automatic process yields suboptimal results, especially when dealing with brains with extensive neurodegeneration and atrophy patterns, or when high accuracy in specific regions is needed. Here we introduce WarpDrive, a novel tool for manual refinements of image alignment after automated registration. We show that the tool applied in a cohort of patients with Alzheimer's disease who underwent deep brain stimulation surgery helps create more accurate representations of the data as well as meaningful models to explain patient outcomes. The tool is built to handle any type of 3D imaging data, also allowing refinements in high-resolution imaging, including histology and multiple modalities to precisely aggregate multiple data sources together.

Postoperative cerebellar mutism syndrome is an acquired Autism-like network disturbance.

BACKGROUND: Cerebellar mutism syndrome (CMS) is a common and debilitating complication of posterior fossa tumour surgery in children. Affected children exhibit communication and social impairments that overlap phenomenologically with subsets of deficits exhibited by children with Autism spectrum disorder (ASD). Although both CMS and ASD are thought to involve disrupted cerebro-cerebellar circuitry, they are considered independent conditions due to an incomplete understanding of their shared neural substrates. METHODS: In this study, we analyzed post-operative cerebellar lesions from 90 children undergoing posterior fossa resection of medulloblastoma, 30 of whom developed CMS. Lesion locations were mapped to a standard atlas, and the networks functionally connected to each lesion were computed in normative adult and paediatric datasets. Generalizability to ASD was assessed using an independent cohort of children with ASD and matched controls (n=427). RESULTS: Lesions in children who developed CMS involved the vermis and inferomedial cerebellar lobules. They engaged large-scale cerebellothalamocortical circuits with a preponderance for the prefrontal and parietal cortices in the paediatric and adult connectomes, respectively. Moreover, with increasing connectomic age, CMS-associated lesions demonstrated stronger connectivity to the midbrain/red nuclei, thalami and inferior parietal lobules and weaker connectivity to prefrontal cortex. Importantly, the CMS-associated lesion network was independently reproduced in ASD and correlated with communication and social deficits, but not repetitive behaviours. CONCLUSIONS: Our findings indicate that CMS-associated lesions result in an ASD-like network disturbance that occurs during sensitive windows of brain development. A common network disturbance between CMS and ASD may inform improved treatment strategies for affected children.

Trends and disparities in deep brain stimulation utilization in the United States: a Nationwide Inpatient Sample analysis from 1993 to 2017.

Background: Deep brain stimulation (DBS) is an approved treatment option for Parkinson's Disease (PD), essential tremor (ET), dystonia, obsessive-compulsive disorder and epilepsy in the United States. There are disparities in access to DBS, and clear understanding of the contextual factors driving them is important. Previous studies aimed at understanding these factors have been limited by single indications or small cohort sizes. The aim of this study is to provide an updated and comprehensive analysis of DBS utilization for multiple indications to better understand the factors driving disparities in access. Methods: The United States based National Inpatient Sample (NIS) database was utilized to analyze the surgical volume and trends of procedures based on indication, using relevant ICD codes. Predictors of DBS use were analyzed using a logistic regression model. DBS-implanted patients in each indication were compared based on the patient-, hospital-, and outcome-related variables. Findings: Our analysis of 104,356 DBS discharges from 1993 to 2017 revealed that the most frequent indications for DBS were PD (67%), ET (24%), and dystonia (4%). Although the number of DBS procedures has consistently increased over the years, radiofrequency ablation utilization has significantly decreased to only a few patients per year since 2003. Negative predictors for DBS utilization in PD and ET cohorts included age increase and female sex, while African American status was a negative predictor across all cohorts. Significant differences in patient-, hospital-, and outcome-related variables between DBS indications were also determined. Interpretation: Demographic and socioeconomic-based disparities in DBS use are evident. Although racial disparities are present across all indications, other disparities such as age, sex, wealth, and insurance status are only relevant in certain indications. Funding: This work was supported by Alan & Susan Hudson Cornerstone Chair in Neurosurgery at University Health Network.

Dissociable default-mode subnetworks subserve childhood attention and cognitive flexibility: Evidence from deep learning and stereotactic electroencephalography.

Cognitive flexibility encompasses the ability to efficiently shift focus and forms a critical component of goal-directed attention. The neural substrates of this process are incompletely understood in part due to difficulties in sampling the involved circuitry. We leverage stereotactic intracranial recordings to directly resolve local-field potentials from otherwise inaccessible structures to study moment-to-moment attentional activity in children with epilepsy performing a flexible attentional task. On an individual subject level, we employed deep learning to decode neural features predictive of task performance indexed by single-trial reaction time. These models were subsequently aggregated across participants to identify predictive brain regions based on AAL atlas and FIND functional network parcellations. Through this approach, we show that fluctuations in beta (12-30 Hz) and gamma (30-80 Hz) power reflective of increased top-down attentional control and local neuronal processing within relevant large-scale networks can accurately predict single-trial task performance. We next performed connectomic profiling of these highly predictive nodes to examine task-related engagement of distributed functional networks, revealing exclusive recruitment of the dorsal default mode network during shifts in attention. The identification of distinct substreams within the default mode system supports a key role for this network in cognitive flexibility and attention in children. Furthermore, convergence of our results onto consistent functional networks despite significant inter-subject variability in electrode implantations supports a broader role for deep learning applied to intracranial electrodes in the study of human attention.

Deep Brain Stimulation for Refractory Status Dystonicus in Children: Multicenter Case Series and Systematic Review.

OBJECTIVE: We sought to better understand the workflow, outcomes, and complications of deep brain stimulation (DBS) for pediatric status dystonicus (SD). We present a systematic review, alongside a multicenter case series of pediatric patients with SD treated with DBS. METHODS: We collected individual data regarding treatment, stimulation parameters, and dystonia severity for a multicenter case series (n = 8) and all previously published cases (n = 77). Data for case series were used to create probabilistic voxelwise maps of stimulated tissue associated with dystonia improvement. RESULTS: In our institutional series, DBS was implanted a mean of 25 days after SD onset. Programming began a mean of 1.6 days after surgery. All 8 patients in our case series and 73 of 74 reported patients in the systematic review had resolution of their SD with DBS, most within 2 to 4 weeks of surgery. Mean follow-up for patients in the case series was 16 months. DBS target for all patients in the case series and 68 of 77 in our systematic review was the globus pallidus pars interna (GPi). In our case series, stimulation of the posterior-ventrolateral GPi was associated with improved dystonia. Mean dystonia improvement was 32% and 51% in our institutional series and systematic review, respectively. Mortality was 4% in the review, which is lower than reported for treatment with pharmacotherapy alone (10-12.5%). INTERPRETATION: DBS is a feasible intervention with potential to reverse refractory pediatric SD and improve survival. More work is needed to increase awareness of DBS in this setting, so that it can be implemented in a timely manner. ANN NEUROL 2023.

Deep Brain Stimulation of the Globus Pallidus Internus and Externus in Multiple System Atrophy.

BACKGROUND: Multiple system atrophy with parkinsonism (MSA-P) is a progressive condition with no effective treatment. OBJECTIVE: The aim of this study was to describe the safety and efficacy of deep brain stimulation (DBS) of globus pallidus pars interna and externa in a cohort of patients with MSA-P. METHODS: Six patients were included. Changes in Movement Disorders Society Unified Parkinson's Disease Rating Scale Part III (MDS-UPDRS III), Parkinson's Disease Questionnaire (PDQ-39) scores, and levodopa equivalent daily dose were compared before and after DBS. Electrode localization and volume tissue activation were calculated. RESULTS: DBS surgery did not result in any major adverse events or intraoperative complications. Overall, no differences in MDS-UPDRS III scores were demonstrated (55.2 ± 17.6 preoperatively compared with 67.3 ± 19.2 at 1 year after surgery), although transient improvement in mobility and dyskinesia was reported in some subjects. CONCLUSIONS: Globus pallidus pars interna and externa DBS for patients with MSA-P did not result in major complications, although it did not provide significant clinical benefit as measured by MDS-UPDRS III. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Local neuroanatomical and tract-based proxies of optimal subcallosal cingulate deep brain stimulation.

BACKGROUND: Deep brain stimulation of the subcallosal cingulate area (SCC-DBS) is a promising neuromodulatory therapy for treatment-resistant depression (TRD). Biomarkers of optimal target engagement are needed to guide surgical targeting and stimulation parameter selection and to reduce variance in clinical outcome. OBJECTIVE/HYPOTHESIS: We aimed to characterize the relationship between stimulation location, white matter tract engagement, and clinical outcome in a large (n = 60) TRD cohort treated with SCC-DBS. A smaller cohort (n = 22) of SCC-DBS patients with differing primary indications (bipolar disorder/anorexia nervosa) was utilized as an out-of-sample validation cohort. METHODS: Volumes of tissue activated (VTAs) were constructed in standard space using high-resolution structural MRI and individual stimulation parameters. VTA-based probabilistic stimulation maps (PSMs) were generated to elucidate voxelwise spatial patterns of efficacious stimulation. A whole-brain tractogram derived from Human Connectome Project diffusion-weighted MRI data was seeded with VTA pairs, and white matter streamlines whose overlap with VTAs related to outcome ('discriminative' streamlines; Puncorrected < 0.05) were identified using t-tests. Linear modelling was used to interrogate the potential clinical relevance of VTA overlap with specific structures. RESULTS: PSMs varied by hemisphere: high-value left-sided voxels were located more anterosuperiorly and squarely in the lateral white matter, while the equivalent right-sided voxels fell more posteroinferiorly and involved a greater proportion of grey matter. Positive discriminative streamlines localized to the bilateral (but primarily left) cingulum bundle, forceps minor/rostrum of corpus callosum, and bilateral uncinate fasciculus. Conversely, negative discriminative streamlines mostly belonged to the right cingulum bundle and bilateral uncinate fasciculus. The best performing linear model, which utilized information about VTA volume overlap with each of the positive discriminative streamline bundles as well as the negative discriminative elements of the right cingulum bundle, explained significant variance in clinical improvement in the primary TRD cohort (R = 0.46, P < 0.001) and survived repeated 10-fold cross-validation (R = 0.50, P = 0.040). This model was also able to predict outcome in the out-of-sample validation cohort (R = 0.43, P = 0.047). CONCLUSION(S): These findings reinforce prior indications of the importance of white matter engagement to SCC-DBS treatment success while providing new insights that could inform surgical targeting and stimulation parameter selection decisions.

Spinal Cord Stimulation for Parkinson's Disease: A Systematic Review and Meta-Analysis of Pain and Motor Outcomes.

BACKGROUND: Spinal cord stimulation (SCS) has been investigated as a potential therapeutic option for managing refractory symptoms in patients with Parkinson's disease (PD). OBJECTIVE: This systematic review and meta-analysis aimed to evaluate the safety and efficacy of SCS in PD. METHOD: A comprehensive literature search was conducted on PubMed and Web of Science to identify SCS studies reporting Unified Parkinson Disease Rating Scale-III (UPDRS-III) or Visual Analogue Scale (VAS) score changes in PD cohorts with at least 3 patients and a follow-up period of at least 1 month. Treatment effect was measured as the mean change in outcome scores and analyzed using an inverse variance random-effects model. The risk of bias was assessed using the Newcastle-Ottawa Scale and funnel plots. RESULTS: A total of 11 studies comprising 76 patients were included. Nine studies involving 72 patients reported an estimated decrease of 4.43 points (95% confidence interval [CI]: 2.11; 6.75, p < 0.01) in UPDRS-III score, equivalent to a 14% reduction. The axial subscores in 48 patients decreased by 2.35 points (95% CI: 1.26; 3.45, p < 0.01, 20% reduction). The pooled effect size of five studies on back and leg pain VAS scores was calculated as 4.38 (95% CI: 2.67; 6.09, p < 0.001), equivalent to a 59% reduction. CONCLUSIONS: Our analysis suggests that SCS may provide significant motor and pain benefits for patients with PD, although the results should be interpreted with caution due to several potential limitations including study heterogeneity, open-label designs, small sample sizes, and the possibility of publication bias. Further research using larger sample sizes and placebo-/sham-controlled designs is needed to confirm effectiveness.

Use of cortical volume to predict response to temporary CSF drainage in patients with idiopathic normal pressure hydrocephalus.

OBJECTIVE: Temporary drainage of CSF with lumbar puncture or lumbar drainage has a high predictive value for identifying patients with suspected idiopathic normal pressure hydrocephalus (iNPH) who may benefit from ventriculoperitoneal shunt insertion. However, it is unclear what differentiates responders from nonresponders. The authors hypothesized that nonresponders to temporary CSF drainage would have patterns of reduced regional gray matter volume (GMV) as compared with those of responders. The objective of the current investigation was to compare regional GMV between temporary CSF drainage responders and nonresponders. Machine learning using extracted GMV was then used to predict outcomes. METHODS: This retrospective cohort study included 132 patients with iNPH who underwent temporary CSF drainage and structural MRI. Demographic and clinical variables were examined between groups. Voxel-based morphometry was used to calculate GMV across the brain. Group differences in regional GMV were assessed and correlated with change in results on the Montreal Cognitive Assessment (MoCA) and gait velocity. A support vector machine (SVM) model that used extracted GMV values and was validated with leave-one-out cross-validation was used to predict clinical outcome. RESULTS: There were 87 responders and 45 nonresponders. There were no group differences in terms of age, sex, baseline MoCA score, Evans index, presence of disproportionately enlarged subarachnoid space hydrocephalus, baseline total CSF volume, or baseline white matter T2-weighted hyperintensity volume (p > 0.05). Nonresponders demonstrated decreased GMV in the right supplementary motor area (SMA) and right posterior parietal cortex as compared with responders (p < 0.001, p < 0.05 with false discovery rate cluster correction). GMV in the posterior parietal cortex was associated with change in MoCA (r2 = 0.075, p < 0.05) and gait velocity (r2 = 0.076, p < 0.05). Response status was classified by the SVM with 75.8% accuracy. CONCLUSIONS: Decreased GMV in the SMA and posterior parietal cortex may help identify patients with iNPH who are unlikely to benefit from temporary CSF drainage. These patients may have limited capacity for recovery due to atrophy in these regions that are known to be important for motor and cognitive integration. This study represents an important step toward improving patient selection and predicting clinical outcomes in the treatment of iNPH.