BACKGROUND:Deep brain stimulation (DBS) is an established treatment for movement disorders such as Parkinson's disease (PD) and essential tremor (ET). However, the decision between unilateral, staged bilateral, or simultaneous bilateral DBS remains controversial, influenced by clinical presentation, patient preferences, and economic factors. OBJECTIVE:The aim was to compare motor score improvements, adverse events (AE), incremental benefits, and progression with unilateral to bilateral procedures and the rationale for second-side surgery. METHODS:This systematic review examined studies on patients treated with unilateral or bilateral (simultaneous or staged) DBS from 1999 to 2025, focusing on outcomes, safety, and efficacy. RESULTS:In PD, unilateral DBS targeting the subthalamic nucleus (STN) or globus pallidus internus (GPi) improves motor scores by up to 37%, whereas bilateral DBS yields improvements of up to 66%. Unilateral DBS provides up to 75% improvement in contralateral symptoms but only up to 28% in ipsilateral symptoms. More than half of PD patients eventually opt for second-side surgery due to worsening symptoms. In ET, unilateral ventral intermediate nucleus (VIM) DBS improves hand tremor by up to 89%, with staged bilateral procedures offering an additional 77% to 89% improvement contralaterally. Axial tremor improves by up to 60% with unilateral VIM DBS and a further 60% after bilateral surgery. Bilateral VIM DBS is linked to more AEs, such as gait disorders and dysarthria, whereas STN and GPi DBS have comparable risks. Staged surgeries are associated with longer surgical times and increased revisions and programming. CONCLUSIONS:Individualized treatment decisions are essential, with bilateral DBS providing superior long-term outcomes for both PD and ET.

Optimizing the resection volume to maximize clinical benefits and minimize postoperative deficits is crucial to neurosurgeons and their patients. While conventional magnetic resonance imaging (MRI) provides surgical planning guidance by visualizing the relationship between the pathology and nearby structures, it does not show brain function. Functional MRI (fMRI) can supplement invasive tests to determine hemispheric dominance and localize eloquent brain functions and serves as a useful adjunct in surgical planning. To provide an accurate answer to the clinical query, expertise is required to define the most appropriate task and image post-processing decisions. Evidence-based guidelines for these aspects are required to enable the implementation of fMRI as a routine clinical test beyond specialized centers. Recently, fMRI has been shown to provide localizing information for more complex cognitive operations in neurosurgical settings, helping to minimize disruption of whole brain networks following neurosurgery. Furthermore, fMRI has been utilized in other branches of neurosurgery, paving the way for personalized stereotactic functional neurosurgeries for movement and psychiatric disorders.

Background: Deep brain stimulation (DBS) in Parkinson’s disease (PD) requires extensive trial-and-error programming, often taking over a year to optimize. An objective, rapid biomarker of stimulation success is needed. Our team developed a functional magnetic resonance imaging (fMRI)-based algorithm to identify optimal DBS settings. This study prospectively compared fMRI-guided programming with standard-of-care (SoC) clinical programming in a double-blind, crossover, non-inferiority trial. Methods: Twenty-two PD-DBS patients were prospectively enrolled for fMRI using a 30-sec DBS-ON/OFF cycling paradigm. Optimal settings were identified using our published classification algorithm. Subjects then underwent >1 year of SoC programming. Clinical improvement was assessed under SoC and fMRI-determined stimulation conditions. Results: fMRI optimization significantly reduced the time required to determine optimal settings (1.6 vs. 5.6 months, p<0.001). Unified Parkinson’s Disease Rating Scale (UPDRSIII) improved comparably with both approaches (23.8 vs. 23.6, p=0.9). Non-inferiority was demonstrated within a predefined margin of 5 points ( p =0.0018). SoC led to greater tremor improvement (p=0.019), while fMRI showed greater bradykinesia improvement (p=0.040). Conclusions: This is the first prospective evaluation of an algorithm able to suggest stimulation parameters solely from the fMRI response to stimulation. It suggests that fMRI-based programming may achieve equivalent outcomes in less time than SoC, reducing patient burden while potentially enhancing bradykinesia response.

OBJECTIVE:Studies have suggested that there may be sex differences in the preoperative characteristics and postoperative outcomes of patients with Parkinson's disease (PD) treated with subthalamic nucleus (STN) deep brain stimulation (DBS). Authors of this study aimed to reveal differences in preoperative and 1-year postoperative motor symptoms, dopaminergic medication use, and quality of life (QOL) domains between men and women who had undergone STN DBS. METHODS:In this retrospective cohort study, the authors evaluated patients who underwent bilateral STN DBS at a single center from 2008 to 2023. Motor symptoms were measured using the Unified Parkinson's Disease Rating Scale Part III (UPDRS-III), levodopa equivalent daily dose (LEDD) was used to measure the dosage of dopaminergic medications, and the 39-Item Parkinson's Disease Questionnaire (PDQ-39) was used to determine QOL outcomes. Exploratory linear mixed-effect models were used to investigate sex and time interactions for the UPDRS-III, LEDD, and PDQ-39 scores. RESULTS:Ninety-four patients, 26 females and 68 males, were included in the study. Preoperatively, women presented with a significantly longer disease duration (p = 0.014), greater UPDRS-III off-medication scores (p < 0.001), lower LEDDs (p = 0.001), and worse PDQ-39 mean total score (p < 0.001). One year postoperatively, after adjusting for disease duration, age, UPDRS-III off scores, and LEDD, there was a significant sex and time interaction for the cognition domain of the PDQ-39, which showed worsening over time in women (p = 0.009). There was no significant sex and time interaction in the UPDRS-III off-medication/on-stimulation scores. CONCLUSIONS:Although STN DBS is equally clinically efficacious for both sexes, women are treated later in the disease course. Preoperatively, women present during more advanced stages of PD with worse motor symptoms and a lower QOL. Postoperatively, women score worse on the cognition index, a proxy for mood rather than cognition.

Understanding the spatial distribution of gliomas in the brain and their molecular subtypes can aid in the diagnosis and development of targeted therapies. This study aims to create probabilistic radiologic maps of glioma locations using large MRI datasets and the most recent consensus brain tumour classification. Neuroimaging data from multiple databases were analysed. Patients included had MRI T1 images and validated tumour segmentations. Probabilistic tumour maps were generated whereby binary tumour masks were aligned to a standard brain template and aggregated to compute voxel-wise frequency maps of glioma occurrence detailing glioma volume, molecular subtype, age, sex and overall survival with tumour location. The study included 2164 patients with gliomas. Key findings include distinct spatial patterns associated with glioma size and molecular subtype: smaller tumours favoured the left temporal region, medium-sized tumours the medial frontoparietal and bilateral temporal regions and larger tumours the frontotemporoparietal regions, predominantly on the right. Isocitrate dehydrogenase (IDH)-wild-type tumours were more common in medial parietotemporal regions, while IDH-mutant tumours were preferentially found in frontotemporal regions. Younger patients had more frontal tumours, while older patients had higher parieto-occipital tumour burdens. Tumours in medial structures and parietal lobes were linked to lower survival, whereas right temporal tumours were associated with higher rates of survival. These findings likely correlate with IDH mutation status. Leveraging eight glioma databases, probabilistic tumour maps revealed significant relationships between brain regions, molecular subtypes and clinical outcomes. These findings could be used in clinical decision-making and offer insights into glioma pathogenesis and treatment of patients impacted by this disease.

Purpose The “July effect” refers to the phenomenon of a higher complication incidence and lower survival rate for patients treated at academic institutions during the beginning of the academic medical calendar. To date, no multi-center study has examined the presence of a “July effect” in a large cohort of trauma patients. We sought to determine if there is a by-month effect on survival and length of stay (LOS) for trauma patients in large academic centers. Methods We performed a multicenter, retrospective cohort study between 2010 and 2020 from five high-volume academic trauma centers in the United States. We included all adult motor vehicle collision (MVC) traumas evaluated at all centers in the study population (age >16 years, mechanism of injury classified as “motor vehicle collision”). Data included date and time of injury, injury severity score (ISS), LOS, and mortality. Each injury was classified as minor (ISS 1–8), moderate (9–15), severe (16–24), and very severe (>25). The mortality and LOS for each range over the entire epoch was calculated by month for each ISS classification. Results We analyzed 39,668 MVC traumas (mean age 41.83, range 39.9–43.3 among sites, 58.9% male and range 56.1–60.4%, 67.4% white range 42.3–84.7%). Survival for the “very severe” traumas ranged from 86.7–90.3%. Across the five sites, there was no significant change in survival (either increased or decreased mortality) or LOS for MVC patients in July or August for any injury classification level. Both age and ISS had a significant effect on survival (OR 0.02 for ISS >25, 0.22 for patients >65 years-old, both p < 0.05). Conclusions In five high-volume centers, there was no significant effect of the July transition on survival or LOS of MVC trauma patients.

BackgroundDeep brain stimulation (DBS) surgery is offered to a subset of Parkinson's disease (PD) patients. It is unclear if there are features at diagnosis that predict future DBS surgery. ObjectiveTo assess predictors of eventual DBS surgery in de novo PD patients. MethodsSubjects from the Parkinson's Progression Marker Initiative (PPMI) database with newly diagnosed, sporadic PD (n = 416) were identified and stratified by their eventual DBS status (DBS+, n = 43; DBS-, n = 373). A total of 50 baseline clinical, imaging, and biospecimen features were extracted for each subject and cross-validated lasso regression was used for feature reduction. Multivariate logistic regression assessed their relationship with DBS status and a receiver operating characteristic curve evaluated model performance. Linear mixed effect models assessed disease progression over 4 years in DBS+ and DBS- patients. ResultsAge at symptom onset, Hoehn and Yahr (H&Y) stage, tremor score, and ratio of CSF Tau to amyloid-beta 1-42 (Tau: Ab) were identified as important baseline features for predicting DBS surgery. Each independently predicted DBS surgery (area under the curve = 0.83). DBS- patients had faster memory decline (P < 0.05), while DBS+ patients had faster decline in H&Y stage (P < 0.001) and motor scores (P < 0.05) prior to surgery. ConclusionThe identified features may be used for early identification of patients who may be surgical candidates during the course of their disease. Disease progression in these groups reflects surgical eligibility criteria, with DBS- patients having more rapid decline in memory while DBS+ patients experienced a faster decline in motor scores prior to DBS surgery.

A major goal of modern neurosurgery is the personalization of treatment to optimize or predict individual outcomes. One strategy in this regard has been to create whole-brain models of individual patients. Whole-brain modeling is a subfield of computational neuroscience that focuses on simulations of large-scale neural activity patterns across distributed brain networks. Recent advances allow for the personalization of these models by incorporating distinct connectivity architecture obtained from noninvasive neuroimaging of individual patients. Local dynamics of each brain region are simulated with neural mass models and subsequently coupled together, considering the subject’s empirical structural connectome. The parameters of the model can be optimized by comparing model-generated and empirical data. The resulting personalized whole-brain models have translational potential in neurosurgery, allowing investigators to simulate the effects of virtual therapies (such as resections or brain stimulations), assess the effect of brain pathology on network dynamics, or discern epileptic networks and predict seizure propagation in silico. The information gained from these simulations can be used as clinical decision support, guiding patient-specific treatment plans. Here the authors provide an overview of the rapidly advancing field of whole-brain modeling and review the literature on neurosurgical applications of this technology.

INTRODUCTION: Temporary drainage of cerebrospinal fluid (CSF) by lumbar puncture or lumbar drain has a high predictive value for identifying patients with idiopathic normal pressure hydrocephalus (iNPH) who will benefit from shunt insertion. However, it is unclear what differentiates responders from non-responders. One hypothesis is that there are patterns of reduced grey-matter volume (GMV) that predispose patients to a poor response. METHODS: Subjects included 132 patients with iNPH who underwent testing with temporary CSF drainage and who had undergone structural MRI between 2013 and 2021. Subjects were classified as responders or non-responders to temporary CSF drainage based on clinical examination and standardized measures of cognition (MoCA) and gait velocity. Demographic and clinical variables were examined between groups. Group differences in GMV were assessed using VBM while adjusting for age, sex, and total intracranial volume. RESULTS: There were 87 responders and 45 non-responders. There were no differences in age, sex, baseline gait velocity, CSF volume, or white-matter T2 hyperintensity volume. Non-responders had higher baseline MoCA scores and were more likely to have received lumbar puncture vs extended lumbar drainage. Responders had greater increases in MoCA and gait velocity scores. Non-responders demonstrated decreased GMV in the right supplementary motor area and in the right posterior parietal cortex as compared to responders. CONCLUSIONS: Decreased GMV in the supplementary motor area and posterior parietal cortex may identify patients with suspected iNPH likely to experience a negative response following temporary CSF drainage. These patients may have limited capacity for recovery due to atrophy in these regions known to be important for motor and cognitive integration.

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.

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.

Mild behavioral impairment (MBI) is a neurobehavioral syndrome characterized by later life emergence of sustained neuropsychiatric symptoms, as an at-risk state for incident cognitive decline and dementia. Prior studies have reported that neuropsychiatric symptoms are associated with cognitive abilities in Parkinson's disease (PD) patients, and we have recently found a strong correlation between MBI and cognitive performance. However, the underlying neural activity patterns of cognitive performance linked to MBI in PD are unknown. Fifty-nine non-demented PD patients and 26 healthy controls were scanned using fMRI during performance of a modified version of the Wisconsin card sorting task. MBI was evaluated using the MBI-checklist, and PD patients were divided into two groups, PD-MBI and PD-noMBI. Compared to the PD-noMBI group and healthy controls, the PD-MBI group revealed less activation in the prefrontal and posterior parietal cortices, and reduced deactivation in the medial temporal region. These results suggest that in PD, MBI reflects deficits in the frontoparietal control network and the hippocampal memory system.

Background: Trigeminal neuralgia (TN) is a severe facial pain condition often requiring surgical treatment. Unfortunately, even technically successful surgery fails to achieve durable pain relief in many patients. The purpose of this study was to use resting-state functional magnetic resonance imaging (fMRI) to: (1) compare functional connectivity between limbic and accessory sensory networks in TN patients vs. healthy controls; and (2) determine if pre-operative variability in these networks can distinguish responders and non-responders to surgery for TN. Methods: We prospectively recruited 22 medically refractory classic or idiopathic TN patients undergoing surgical treatment over a 3-year period, and 19 age- and sex-matched healthy control subjects. fMRI was acquired within the month prior to surgery for all TN patients and at any time during the study period for controls. Functional connectivity analysis was restricted to six pain-relevant brain regions selected a priori: anterior cingulate cortex (ACC), posterior cingulate cortex, hippocampus, amygdala, thalamus, and insula. Two comparisons were performed: (1) TN vs. controls; and (2) responders vs. non-responders to surgical treatment for TN. Functional connectivity was assessed with a two-sample t-test, using a statistical significance threshold of p < 0.050 with false discovery rate (FDR) correction for multiple comparisons. Results: Pre-operative functional connectivity was increased in TN patients compared to controls between the right insular cortex and both the left thalamus [t(39) = 3.67, p = 0.0007] and right thalamus [t(39) = 3.22, p = 0.0026]. TN patients who were non-responders to surgery displayed increased functional connectivity between limbic structures, including between the left and right hippocampus [t(18) = 2.85, p = 0.0106], and decreased functional connectivity between the ACC and both the left amygdala [t(18) = 2.94, p = 0.0087] and right hippocampus [t(18) = 3.20, p = 0.0049]. Across all TN patients, duration of illness was negatively correlated with connectivity between the ACC and left amygdala (r2 = 0.34, p = 0.00437) as well as the ACC and right hippocampus (r2 = 0.21, p = 0.0318). Conclusions: TN patients show significant functional connectivity abnormalities in sensory-salience regions. However, variations in the strength of functional connectivity in limbic networks may explain why some TN patients fail to respond adequately to surgery.

Background:Patients presenting with visual impairment secondary to pituitary macroadenomas often experience variable recovery after surgery. Several factors may impact visual outcomes including the extent of neuroaxonal damage in the afferent visual pathway and cortical plasticity. Optical coherence tomography (OCT) measures of retinal structure and resting-state functional MRI (rsfMRI) can be used to evaluate the impact of neuroaxonal injury and cortical adaptive processes, respectively. The purpose of this study was to determine whether rsfMRI patterns of functional connectivity (FC) distinguish patients with good vs poor visual outcomes after surgical decompression of pituitary adenomas.Methods:In this retrospective cohort study, we compared FC patterns between patients who manifested good (GO) vs poor (PO) visual outcomes after pituitary tumor surgery. Patients (n = 21) underwent postoperative rsfMRI a minimum of 1 year after tumor surgery. Seed-based connectivity of the visual cortex (primary [V1], prestriate [V2], and extrastriate [V5]) was compared between GO and PO patients and between patients and healthy controls (HCs) (n = 19). Demographics, visual function, and OCT data were compared preoperatively and postoperatively between patient groups. The threshold for GO was visual field mean deviation equal or less than -5.00 dB and/or visual acuity equal to or better than 20/40.Results:Increased postoperative FC of the visual system was noted for GO relative to PO patients. Specifically, good visual outcomes were associated with increased connectivity of right V5 to the bilateral frontal cortices. Compared with HCs, GO patients showed increased connectivity of V1 and left V2 to sensorimotor cortex, increased connectivity of right and left V2 to medial prefrontal cortex, and increased connectivity of right V5 the right temporal and frontal cortices.Conclusions:Increased visual cortex connectivity is associated with good visual outcomes in patients with pituitary tumor, at late phase of recovery. Our findings suggest that rsfMRI does distinguish GO and PO patients after pituitary tumor surgery. This imaging modality may have a future role in characterizing the impact of cortical adaptation on visual recovery.

Background: Despite the expanding use of machine learning (ML) in fields such as finance and marketing, its application in the daily practice of clinical medicine is almost non-existent. In this systematic review, we describe the various areas within clinical medicine that have applied the use of ML to improve patient care. Methods: A systematic review was performed in accordance with the PRISMA guidelines using Medline(R), EBM Reviews, Embase, Psych Info, and Cochrane Databases, focusing on human studies that used ML to directly address a clinical problem. Included studies were published from January 1, 2000 to May 1, 2018 and provided metrics on the performance of the utilized ML tool. Results: A total of 1909 unique publications were reviewed, with 378 retrospective articles and 8 prospective articles meeting inclusion criteria. Retrospective publications were found to be increasing in frequency, with 61 % of articles published within the last 4 years. Prospective articles comprised only 2 % of the articles meeting our inclusion criteria. These studies utilized a prospective cohort design with an average sample size of 531. Conclusion: The majority of literature describing the use of ML in clinical medicine is retrospective in nature and often outlines proof-of-concept approaches to impact patient care. We postulate that identifying and overcoming key translational barriers, including real-time access to clinical data, data security, physician approval of "black box" generated results, and performance evaluation will allow for a fundamental shift in medical practice, where specialized tools will aid the healthcare team in providing better patient care.

Background: Tumor treatment fields (TTFields) are an approved adjuvant therapy for glioblastoma. The magnitude of applied electrical field is related to the anti-tumoral response. However, peritumoral edema (ptE) may result in shunting of electrical current around the tumor, thereby reducing the intra-tumoral electric field. In this study, we address this issue with computational simulations. Methods: Finite element models were created with varying amounts of ptE surrounding a virtual tumor. The electric field distribution was simulated using the standard TTFields electrode montage. Electric field magnitude was extracted from the tumor and related to edema thickness. Two patient specific models were created to confirm these results. Results: The inclusion of ptE decreased the magnitude of the electric field within the tumor. In the model considering a frontal tumor and an anterior-posterior electrode configuration, ≥ 6 mm of ptE decreased the electric field by 52%. In the patient specific models, ptE decreased the electric field within the tumor by an average of 26%. The effect of ptE on the electric field distribution was spatially heterogenous. Conclusions: Given the importance of electric field magnitude for the anti-tumoral effects of TTFields, the presence of edema should be considered both in future modelling studies and as a predictor of non-response.

Parkinson's disease (PD) is characterized by overlapping motor, neuropsychiatric, and cognitive symptoms. Worse performance in one domain is associated with worse performance in the other domains. Commonality analysis (CA) is a method of variance partitioning in multiple regression, used to separate the specific and common influence of collinear predictors. We apply, for the first time, CA to the functional connectome to investigate the unique and common neural connectivity underlying the interface of the symptom domains in 74 non-demented PD subjects. Edges were modeled as a function of global motor, cognitive, and neuropsychiatric scores. CA was performed, yielding measures of the unique and common contribution of the symptom domains. Bootstrap confidence intervals were used to determine the precision of the estimates and to directly compare each commonality coefficient. The overall model identified a network with the caudate nucleus as a hub. Neuropsychiatric impairment accounted for connectivity in the caudate-dorsal anterior cingulate and caudate-right dorsolateral prefrontal-right inferior parietal circuits, while caudate-medial prefrontal connectivity reflected a unique effect of both neuropsychiatric and cognitive impairment. Caudate-precuneus connectivity was explained by both unique and shared influence of neuropsychiatric and cognitive symptoms. Lastly, posterior cortical connectivity reflected an interplay of the unique and common effects of each symptom domain. We show that CA can determine the amount of variance in the connectome that is unique and shared amongst motor, neuropsychiatric, and cognitive symptoms in PD, thereby improving our ability to interpret the data while gaining novel insight into networks at the interface of these symptom domains.