Educational stereoscopic representation of a step-by-step brain white fiber dissection according to Klingler's method.

BACKGROUND: Understanding and teaching the three-dimensional architecture of the brain remains difficult because of the intricate arrangement of grey nuclei within white matter tracts. Although cortical area functions have been well studied, educational and three-dimensional descriptions of the organization of deep nuclei and white matter tracts are still missing. OBJECTIVE: We propose herein a detailed step-by-step dissection of the lateral aspect of a left hemisphere using the Klingler method and provide high-quality stereoscopic views with the aim to help teach medical students or surgeons the three-dimensional anatomy of the brain. METHODS: Three left hemispheres were extracted and prepared. Then, according to the Klingler method, dissections were carried out from the lateral aspect. Photographs were taken at each step and were modified to provide stereoscopic three-dimensional views. RESULTS: Gray and white structures were described: cortex, claustrum, putamen, pallidum, caudate nucleus, amygdala; U-fibers, external and internal capsules, superior longitudinal fasciculus, frontal aslant fasciculus, uncinate fasciculus, inferior fronto-occipital fasciculus, inferior longitudinal fasciculus, corticospinal fasciculus, corona radiata, anterior commissure, and optic radiations. CONCLUSION: This educational stereoscopic presentation of an expert dissection of brain white fibers and basal ganglia would be of value for theoretical or hands-on teaching of brain anatomy; labeling and stereoscopy could, moreover, improve the teaching, understanding, and memorizing of brain anatomy. In addition, this could be also used for the creation of a mental map by neurosurgeons for the preoperative planning of brain tumor surgery.

Defining benchmark outcomes for mesial temporal lobe epilepsy surgery: A global multicenter analysis of 1119 cases.

OBJECTIVE: Benchmarking has been proposed to reflect surgical quality and represents the highest standard reference values for desirable results. We sought to determine benchmark outcomes in patients after surgery for drug-resistant mesial temporal lobe epilepsy (MTLE). METHODS: This retrospective multicenter study included patients who underwent MTLE surgery at 19 expert centers on five continents. Benchmarks were defined for 15 endpoints covering surgery and epilepsy outcome at discharge, 1 year after surgery, and the last available follow-up. Patients were risk-stratified by applying outcome-relevant comorbidities, and benchmarks were calculated for low-risk ("benchmark") cases. Respective measures were derived from the median value at each center, and the 75th percentile was considered the benchmark cutoff. RESULTS: A total of 1119 patients with a mean age (range) of 36.7 (1-74) years and a male-to-female ratio of 1:1.1 were included. Most patients (59.2%) underwent anterior temporal lobe resection with amygdalohippocampectomy. The overall rate of complications or neurological deficits was 14.4%, with no in-hospital death. After risk stratification, 377 (33.7%) benchmark cases of 1119 patients were identified, representing 13.6%-72.9% of cases per center and leaving 742 patients in the high-risk cohort. Benchmark cutoffs for any complication, clinically apparent stroke, and reoperation rate at discharge were ≤24.6%, ≤.5%, and ≤3.9%, respectively. A favorable seizure outcome (defined as International League Against Epilepsy class I and II) was reached in 83.6% at 1 year and 79.0% at the last follow-up in benchmark cases, leading to benchmark cutoffs of ≥75.2% (1-year follow-up) and ≥69.5% (mean follow-up of 39.0 months). SIGNIFICANCE: This study presents internationally applicable benchmark outcomes for the efficacy and safety of MTLE surgery. It may allow for comparison between centers, patient registries, and novel surgical and interventional techniques.

Motor Symptom Asymmetry Predicts Cognitive and Neuropsychiatric Profile Following Deep Brain Stimulation of the Subthalamic Nucleus in Parkinson's Disease: a 5-Year Longitudinal Study.

INTRODUCTION: Risk factors (e.g., motor symptom asymmetry) for short- and long-term cognitive and neuropsychiatric symptoms following deep brain stimulation (DBS) of the subthalamic nucleus (STN) in patients with Parkinson's disease have yet to be fully identified. The objectives of the present study were to determine whether motor symptom asymmetry in Parkinson's disease is one such risk factor and to identify predictors of subnormal cognitive decline. METHODS: A total of 26 patients receiving STN-DBS (13 with left-sided motor symptoms and 13 with right-sided ones) underwent follow-up neuropsychological, depression and apathy assessments over a 5-year period. Nonparametric intergroup comparisons were performed on raw scores, as well as Cox regression analyses on standardized Mattis Dementia Rating Scale scores. RESULTS: Compared with patients who had predominantly left-sided symptoms, right-sided patients scored higher on both apathy (at 3 months and 36 months) and depressive symptoms (at 6 months and 12 months) and scored lower on global cognitive efficiency (at 36 months and 60 months). Survival analyses revealed that only right-sided patients had subnormal standardized dementia scores, which were negatively associated with the number of perseverations in the Wisconsin Card Scoring Test. CONCLUSION: Right-sided motor symptoms are a risk factor for more severe short- and long-term cognitive and neuropsychiatric symptoms following STN-DBS, confirming literature findings on left hemispheric vulnerability.

Voxel-based diktiometry: Combining convolutional neural networks with voxel-based analysis and its application in diffusion tensor imaging for Parkinson's disease.

Extracting population-wise information from medical images, specifically in the neurological domain, is crucial to better understanding disease processes and progression. This is frequently done in a whole-brain voxel-wise manner, in which a population of patients and healthy controls are registered to a common co-ordinate space and a statistical test is performed on the distribution of image intensities for each location. Although this method has yielded a number of scientific insights, it is further from clinical applicability as the differences are often small and altogether do not permit for a high-performing classifier. In this article, we take the opposite approach of using a high-performing classifier, specifically a traditional convolutional neural network, and then extracting insights from it which can be applied in a population-wise manner, a method we call voxel-based diktiometry. We have applied this method to diffusion tensor imaging (DTI) analysis for Parkinson's disease (PD), using the Parkinson's Progression Markers Initiative database. By using the network sensitivity information, we can decompose what elements of the DTI contribute the most to the network's performance, drawing conclusions about diffusion biomarkers for PD that are based on metrics which are not readily expressed in the voxel-wise approach.

Motor symptom asymmetry predicts non-motor outcome and quality of life following STN DBS in Parkinson's disease.

Risk factors for long-term non-motor symptoms and quality of life following subthalamic nucleus deep brain stimulation (STN DBS) have not yet been fully identified. In the present study, we investigated the impact of motor symptom asymmetry in Parkinson's disease. Data were extracted for 52 patients with Parkinson's disease (half with predominantly left-sided motor symptoms and half with predominantly right-sided ones) who underwent bilateral STN and a matched healthy control group. Performances for cognitive tests, apathy and depression symptoms, as well as quality-of-life questionnaires at 12 months post-DBS were compared with a pre-DBS baseline. Results indicated a deterioration in cognitive performance post-DBS in patients with predominantly left-sided motor symptoms. Performances of patients with predominantly right-sided motor symptoms were maintained, except for a verbal executive task. These differential effects had an impact on patients' quality of life. The results highlight the existence of two distinct cognitive profiles of Parkinson's disease, depending on motor symptom asymmetry. This asymmetry is a potential risk factor for non-motor adverse effects following STN DBS.

Enhancing Safety in Epilepsy Surgery (EASINESS): Study Protocol for a Retrospective, Multicenter, Open Registry.

Introduction: Optimizing patient safety and quality improvement is increasingly important in surgery. Benchmarks and clinical quality registries are being developed to assess the best achievable results for several surgical procedures and reduce unwarranted variation between different centers. However, there is no clinical database from international centers for establishing standardized reference values of patients undergoing surgery for mesial temporal lobe epilepsy. Design: The Enhancing Safety in Epilepsy Surgery (EASINESS) study is a retrospectively conducted, multicenter, open registry. All patients undergoing mesial temporal lobe epilepsy surgery in participating centers between January 2015 and December 2019 are included in this study. The patient characteristics, preoperative diagnostic tools, surgical data, postoperative complications, and long-term seizure outcomes are recorded. Outcomes: The collected data will be used for establishing standardized reference values ("benchmarks") for this type of surgical procedure. The primary endpoints include seizure outcomes according to the International League Against Epilepsy (ILAE) classification and defined postoperative complications. Discussion: The EASINESS will define robust and standardized outcome references after amygdalohippocampectomy for temporal lobe epilepsy. After the successful definition of benchmarks from an international cohort of renowned centers, these data will serve as reference values for the evaluation of novel surgical techniques and comparisons among centers for future clinical trials. Clinical trial registration: This study is indexed at clinicaltrials.gov (NT 04952298).

PassFlow: a multimodal workflow for predicting deep brain stimulation outcomes.

PURPOSE: Deep Brain Stimulation (DBS) is a proven therapy for Parkinson's Disease (PD), frequently resulting in an enhancement of motor function. Nonetheless, several undesirable side effects can occur after DBS, which can worsen the quality of life of the patient. Thus, the clinical team has to carefully select patients on whom to perform DBS. Over the past decade, there have been some attempts to relate pre-operative data and DBS clinical outcomes, with most focused on the motor symptomatology. In this paper, we propose a machine learning-based method able to predict a large number of DBS clinical outcomes for PD. METHODS: We propose a multimodal pipeline, referred to as PassFlow, which predicts 84 clinical post-operative clinical scores. PassFlow is composed of an artificial neural network to compress clinical information, an image processing method from the state-of-the-art to extract morphological biomarkers our of T1 imaging, and an SVM to perform the regressions. We validated PassFlow on 196 PD patients who undergone a DBS. RESULTS: PassFlow showed correlation coefficients as high as 0.71 and were able to significantly predict 63 out of the 84 scores, outperforming a comparative linear method. The number of metrics that are predicted with this pre-operative information was also found to be correlated with the number of patients with this information available, indicating that the PassFlow method is still actively learning. CONCLUSION: We presented a novel, machine learning-based pipeline to predict a variety of post-operative clinical outcomes of DBS for PD patients. PassFlow took into account various bio-markers, arising from different data modalities, showing high correlation coefficients for some scores from pre-operative data only. It indicates that many clinical outcomes of DBS can be predicted agnostic to the specific simulation parameters, as PassFlow has been validated without such stimulation-related information.

Adapting the listening time for micro-electrode recordings in deep brain stimulation interventions.

PURPOSE: Deep brain stimulation (DBS) is a common treatment for a variety of neurological disorders which involves the precise placement of electrodes at particular subcortical locations such as the subthalamic nucleus. This placement is often guided by auditory analysis of micro-electrode recordings (MERs) which informs the clinical team as to the anatomic region in which the electrode is currently positioned. Recent automation attempts have lacked flexibility in terms of the amount of signal recorded, not allowing them to collect more signal when higher certainty is needed or less when the anatomy is unambiguous. METHODS: We have addressed this problem by evaluating a simple algorithm that allows for MER signal collection to terminate once the underlying model has sufficient confidence. We have parameterized this approach and explored its performance using three underlying models composed of one neural network and two Bayesian extensions of said network. RESULTS: We have shown that one particular configuration, a Bayesian model of the underlying network's certainty, outperforms the others and is relatively insensitive to parameterization. Further investigation shows that this model also allows for signals to be classified earlier without increasing the error rate. CONCLUSION: We have presented a simple algorithm that records the confidence of an underlying neural network, thus allowing for MER data collection to be terminated early when sufficient confidence is reached. This has the potential to improve the efficiency of DBS electrode implantation by reducing the time required to identify anatomical structures using MERs.

Data imputation and compression for Parkinson's disease clinical questionnaires.

Medical questionnaires are a valuable source of information but are often difficult to analyse due to both their size and the high possibility of them having missing values. This is a problematic issue in biomedical data science as it may complicate how individual questionnaire data is represented for statistical or machine learning analysis. In this paper, we propose a deeply-learnt residual autoencoder to simultaneously perform non-linear data imputation and dimensionality reduction. We present an extensive analysis of the dynamics of the performance of this autoencoder regarding the compression rate and the proportion of missing values. This method is evaluated on motor and non-motor clinical questionnaires of the Parkinson's Progression Markers Initiative (PPMI) database and consistently outperforms linear coupled imputation and reduction approaches.

Deep brain stimulation of the internal globus pallidus does not affect the limbic circuit in patients with Parkinson's disease: a PET study.

INTRODUCTION: Internal globus pallidus (GPi) deep brain stimulation (DBS) is a safe and effective alternative treatment in Parkinson's disease (PD) for patients with cognitive impairment. However, no study has yet investigated metabolic changes within a large series of patients undergoing GPi stimulation. OBJECTIVE: We assessed motor, cognitive and psychiatric changes, as well as modifications in brain glucose metabolism measured with FDG-PET, before and after bilateral GPi-DBS. METHODS: In the same week, 32 patients with PD underwent a motor, cognitive and psychiatric assessment and a resting-state FDG-PET scan, 4 months before and 4 months after GPi-DBS surgery. For the voxelwise metabolic change assessment, the p value was controlled for multiple comparisons using the family wise error rate. RESULTS: After GPi-DBS surgery, patients showed a significant overall improvement in motor status. No cognitive or psychiatric changes were observed after surgery. Nor were any clusters with significantly relative metabolic changes found in the limbic circuit after surgery. Clusters with significantly relative metabolic changes were observed in the left and right Brodmann area (BA) 6, the right BA 9, the right and left BA 39 and the left BA 17. CONCLUSION: The present study confirmed that GPi-DBS is an effective treatment in patients with advanced PD, owing to metabolic changes in the areas involved in motor execution. The absence of relative metabolic decrease in the limbic circuit and the few changes affecting the associative circuit could explain why GPi-DBS is cognitively safe.

SepaConvNet for Localizing the Subthalamic Nucleus Using One Second Micro-electrode Recordings.

Micro-electrode recording (MER) is a powerful way of localizing target structures during neurosurgical procedures such as the implantation of deep brain stimulation electrodes, which is a common treatment for Parkinson's disease and other neurological disorders. While Micro-electrode Recording (MER) provides adjunctive information to guidance assisted by pre-operative imaging, it is not unanimously used in the operating room. The lack of standard use of MER may be in part due to its long duration, which can lead to complications during the operation, or due to high degree of expertise required for their interpretation. Over the past decade, various approaches addressing automating MER analysis for target localization have been proposed, which have mainly focused on feature engineering. While the accuracies obtained are acceptable in certain configurations, one issue with handcrafted MER features is that they do not necessarily capture more subtle differences in MER that could be detected auditorily by an expert neurophysiologist. In this paper, we propose and validate a deep learning-based pipeline for subthalamic nucleus (STN) localization with micro-electrode recordings motivated by the human auditory system. Our proposed Convolutional Neural Network (CNN), referred as SepaConvNet, shows improved accuracy over two comparative networks for locating the STN from one second MER samples.

Subthalamic nucleus oscillations during vocal emotion processing are dependent of the motor asymmetry of Parkinson's disease.

The subthalamic nucleus (STN) is involved in different aspects of emotional processes and more specifically in emotional prosody recognition. Recent studies on the behavioral effects of deep brain stimulation (DBS) in patients with Parkinson's disease (PD) have uncovered an asymmetry in vocal emotion decoding in PD, with left-onset PD patients showing deficits for the processing of happy voices. Whether and how PD asymmetry affects STN electrophysiological responses to emotional prosody, however, remains unknown. In the current study, local field potential activity was recorded from eight left- and six right-lateralized motor-onset PD patients (LOPD/ROPD) undergoing DBS electrodes implantation, while they listened to angry, happy and neutral voices. Time-frequency decomposition revealed that theta (2-6 Hz), alpha (6-12 Hz) and gamma (60-150 Hz) band responses to emotion were mostly bilateral with a differential pattern of response according to patient's sides-of onset. Conversely, beta-band (12-20 Hz and 20-30 Hz) emotional responses were mostly lateralized in the left STN for both patient groups. Furthermore, STN theta, alpha and gamma band responses to happiness were either absent (theta band) or reduced (alpha and gamma band) in the most affected STN hemisphere (contralateral to the side-of onset), while a late low-beta band left STN happiness-specific response was present in ROPD patients and did not occur in LOPD patients. Altogether, in this study, we demonstrate a complex pattern of oscillatory activity in the human STN in response to emotional voices and reveal a crucial influence of disease laterality on STN low-frequency oscillatory activity.

Striatal shape alteration as a staging biomarker for Parkinson's Disease.

Parkinson's Disease provokes alterations of subcortical deep gray matter, leading to subtle changes in the shape of several subcortical structures even before the manifestation of motor and non-motor clinical symptoms. We used an automated registration and segmentation pipeline to measure this structural alteration in one early and one advanced Parkinson's Disease (PD) cohorts, one prodromal stage cohort and one healthy control cohort. These structural alterations are then passed to a machine learning pipeline to classify these populations. Our workflow is able to distinguish different stages of PD based solely on shape analysis of the bilateral caudate nucleus and putamen, with balanced accuracies in the range of 59% to 85%. Furthermore, we compared the significance of each of these subcortical structure, compared the performances of different classifiers on this task, thus quantifying the informativeness of striatal shape alteration as a staging bio-marker for PD.

Motor symptom asymmetry in Parkinson's disease predicts emotional outcome following subthalamic nucleus deep brain stimulation.

The objective of this study was to explore the brain modifications associated with vocal emotion (i.e., emotional prosody) processing deficits in patients with Parkinson's disease after deep brain stimulation of the subthalamic nucleus, and the impact of motor asymmetry on these deficits. We therefore conducted 18-fluorodeoxyglucose positron emission tomography scans of 29 patients with left- or right-sided motor symptoms of Parkinson's disease before and after surgery, and correlated changes in their glucose metabolism with modified performances on the recognition of emotional prosody. Results were also compared with those of a matched healthy control group. Patients with more left-sided motor symptoms exhibited a deficit in vocal emotion recognition for neutral, anger, happiness and sadness in the preoperative condition that was normalized postoperatively. Patients with more right-sided motor symptoms performed comparably to controls in the preoperative condition, but differed significantly on fear postoperatively. At the metabolic level, the improvement observed among patients with left-sided motor symptoms was correlated with metabolic modifications in a right-lateralized network known to be involved in emotional prosody, while the behavioral worsening observed among patients with right-sided motor symptoms was correlated with metabolic modifications in the left parahippocampal gyrus and right cerebellum. We suggest that surgery has a differential impact on emotional processing according to motor symptom lateralization, and interpret these results as reflecting the (de)synchronization of the limbic loop in the postoperative condition.

Selective neurotomy of the sciatic nerve branches to the hamstring muscles: An anatomical study.

BACKGROUND: Hamstring spasticity can bring about a flexion deformity of the knee, liable to cause disability. Surgical treatment by selective neurotomies of the sciatic nerve branches leading to the hamstring muscles may then be indicated. Few studies have investigated the precise origin of these branches on the sciatic nerve, describing the innervation pattern of the hamstring muscles. Further anatomical data are needed to enhance surgical techniques in neurotomies of the sciatic nerve branches, to define the best incision and surgical approach and what section and length of the SN need to be exposed. Therefore, we performed an anatomical study to: (1) define a surgical approach to perform selective neurotomies of the sciatic nerve branches for hamstring spasticity?(2) whether the anatomical variants of the hamstring innervation have been identified? HYPOTHESIS: Our anatomical data could lead to the definition of an approach to the sciatic nerve for the purpose of selective neurotomy. MATERIAL AND METHODS: Twenty posterior compartments of the thigh were dissected. We counted each branch of the sciatic nerve leading to the hamstring and described their arising point using the centre of the lateral surface of the great trochanter and the lower edge of the gluteus maximus muscle as main anatomical landmarks. We also described the presence of branch divisions and their muscular penetrating points. RESULTS: The mean distances between the center of the lateral surface of the great trochanter and the emergence of branches from the SN were: 2.2±3.6cm (-5 to 9cm) for the long head of the biceps femoris muscle, 2.3±3cm (-4 to 10cm) for the semitendinosus muscle, and 2.2±3cm (-5 to 8cm) for the semimembranosus muscle. No branches originated from the sciatic nerve below the lower edge of the gluteus maximus muscle. In summary the branches innervating the hamstrings originated from the SN within an interval of 15cm (5cm above and 10cm below the centre of the lateral surface of great trochanter). The average number of sciatic nerve branches for the hamstring muscles was 4.7 (minimum: 3; maximum: 6) with 1.8 branches for the long head of the biceps [1 in 7/20 (35%), 2 in 10/20 (50%), and 3 in 3/20 (15%)], 1.5 branches for the semitendinosus [1 in 11/20 (55%) and 2 in 9/20 (45%)], 1.4 branches for the semimembranosus [1 in 12/20 (60%) and 2 in 8/20 (40%)]. No branches had a common origin with cutaneous nerves. DISCUSSION: This anatomical study enabled us to propose an approach to exposing the sciatic nerve in order to perform a selective neurotomy: horizontal cutaneous incision on the gluteal fold, incision of the lower edge of the gluteus maximus, exposure of the sciatic nerve to a distance of 10cm below the great trochanter, and visualization of the nerve branches to the hamstring muscles. Exposure of the nerve above the great trochanter is not necessary because the branches which emerge from the SN above the great trochanter are still contiguous with the SN. LEVEL OF EVIDENCE: IV: prospective study without control.

Subthalamic nucleus local field potentials recordings reveal subtle effects of promised reward during conflict resolution in Parkinson's disease.

Cognitive action control depends on cortical-subcortical circuits, involving notably the subthalamic nucleus (STN), as evidenced by local field potentials recordings (LFPs) studies. The STN consistently shows an increase in theta oscillations power during conflict resolution. Some studies have shown that cognitive action control in Parkinson's disease (PD) could be influenced by the occurrence of monetary reward. In this study, we investigated whether incentive motivation could modulate STN activity, and notably STN theta activity, during response conflict resolution. To achieve this objective, we recorded STN LFPs during a motivated Simon task in PD patients who had undergone deep brain stimulation surgery. Behavioral results revealed that promised rewards increased the difficulty in resolving conflict situations, thus replicating previous findings. Signal analyses locked on the imperative stimulus onset revealed the typical pattern of increased theta power in a conflict situation. However, this conflict-related modulation of theta power was not influenced by the size of the reward cued. We nonetheless identified a significant effect of the reward size on local functional organization (indexed by inter-trial phase clustering) of theta oscillations, with higher organization associated with high rewards while resolving conflict. When focusing on the period following the onset of the reward cue, we unveiled a stronger beta power decrease in higher reward conditions. However, these LFPs results were not correlated to behavioral results. Our study suggests that the STN is involved in how reward information can influence computations during conflict resolution. However, considering recent studies as well as the present results, we suspect that these effects are subtle.

Functional atlases for analysis of motor and neuropsychological outcomes after medial globus pallidus and subthalamic stimulation.

Anatomical atlases have been developed to improve the targeting of basal ganglia in deep brain stimulation. However, the sole anatomy cannot predict the functional outcome of this surgery. Deep brain stimulation is often a compromise between several functional outcomes: motor, fluency and neuropsychological outcomes in particular. In this study, we have developed anatomo-clinical atlases for the targeting of subthalamic and medial globus pallidus deep brain stimulation. The activated electrode coordinates of 42 patients implanted in the subthalamic nucleus and 29 patients in the medial globus pallidus were studied. The atlas was built using the representation of the volume of tissue theoretically activated by the stimulation. The UPDRS score was used to represent the motor outcome. The Stroop test was represented as well as semantic and phonemic fluencies. For the subthalamic nucleus, best motor outcomes were obtained when the supero-lateral part of the nucleus was stimulated whereas the semantic fluency was impaired in this same region. For the medial globus pallidus, best outcomes were obtained when the postero ventral part of the nucleus was stimulated whereas the phonemic fluency was impaired in this same region. There was no significant neuropsychological impairment. We have proposed new anatomo-clinical atlases to visualize the motor and neuropsychological consequences at 6 months of subthalamic nucleus and pallidal stimulation in patients with Parkinson's disease.

Data-Driven Prediction of the Therapeutic Window during Subthalamic Deep Brain Stimulation Surgery.

BACKGROUND: Moving from awake surgery under local anesthesia to asleep surgery under general anesthesia will require to precisely predict the outcome of deep brain stimulation. OBJECTIVE: To propose a data-driven prediction of both the therapeutic effect and side effects of the surgery. METHODS: The retrospective intraoperative data from 30 patients operated on in the subthalamic nucleus were used to train an artificial neural network to predict the deep brain stimulation outcome. A leave-one-out validation was undertaken to give a predictive performance that would reflect the performance of the predictive model in clinical practice. Three-dimensional coordinates and the amount of current of the electrodes were used to train the model. RESULTS: 130 electrode positions were reviewed. The areas under the curve were 0.902 and 0.89 for therapeutic and side effects, respectively. The mean sensitivity and specificity were 93.07% (SD 0.95) and 69.24% (SD 5.27) for the therapeutic effect, 73.47% (SD 10.55) and 91.82% (SD 0.12) for the side effect. CONCLUSION: Data-driven prediction could be an additional modality to predict deep brain stimulation outcome. Further validation is needed to precisely use this method for performing surgery under general anesthesia.

Self-guided training for deep brain stimulation planning using objective assessment.

OBJECTIVE: Deep brain stimulation (DBS) is an increasingly common treatment for neurodegenerative diseases. Neurosurgeons must have thorough procedural, anatomical, and functional knowledge to plan electrode trajectories and thus ensure treatment efficacy and patient safety. Developing this knowledge requires extensive training. We propose a training approach with objective assessment of neurosurgeon proficiency in DBS planning. METHODS: To assess proficiency, we propose analyzing both the viability of the planned trajectory and the manner in which the operator arrived at the trajectory. To improve understanding, we suggest a self-guided training course for DBS planning using real-time feedback. To validate the proposed measures of proficiency and training course, two experts and six novices followed the training course, and we monitored their proficiency measures throughout. RESULTS: At baseline, experts planned higher quality trajectories and did so more efficiently. As novices progressed through the training course, their proficiency measures increased significantly, trending toward expert measures. CONCLUSION: We developed and validated measures which reliably discriminate proficiency levels. These measures are integrated into a training course, which quantitatively improves trainee performance. The proposed training course can be used to improve trainees' proficiency, and the quantitative measures allow trainees' progress to be monitored.