Delayed vagal nerve compressive neuropathy following placement of vagal nerve stimulator: case report.

Vagal neuropathy causing vocal fold palsy is an uncommon complication of vagal nerve stimulator (VNS) placement. It may be associated with intraoperative nerve injury or with device stimulation. Here we present the first case of delayed, compressive vagal neuropathy associated with VNS coil placement which presented with progressive hoarseness and vocal cord paralysis. Coil removal and vagal neurolysis was performed to relieve the compression. Larger 3 mm VNS coils were placed for continuation of therapy. Coils with a larger inner diameter should be employed where possible to prevent this complication. The frequency of VNS-associated vagal nerve compression may warrant further investigation.

Mapping the structure-function relationship along macroscale gradients in the human brain.

Functional coactivation between human brain regions is partly explained by white matter connections; however, how the structure-function relationship varies by function remains unclear. Here, we reference large data repositories to compute maps of structure-function correspondence across hundreds of specific functions and brain regions. We use natural language processing to accurately predict structure-function correspondence for specific functions and to identify macroscale gradients across the brain that correlate with structure-function correspondence as well as cortical thickness. Our findings suggest structure-function correspondence unfolds along a sensory-fugal organizational axis, with higher correspondence in primary sensory and motor cortex for perceptual and motor functions, and lower correspondence in association cortex for cognitive functions. Our study bridges neuroscience and natural language to describe how structure-function coupling varies by region and function in the brain, offering insight into the diversity and evolution of neural network properties.

Systematic 1 Hz direct electrical stimulation for seizure induction: A reliable method for localizing seizure onset zone and predicting seizure freedom.

OBJECTIVE: To prospectively investigate the utility of seizure induction using systematic 1 Hz stimulation by exploring its concordance with the spontaneous seizure onset zone (SOZ) and relation to surgical outcome; comparison with seizures induced by non-systematic 50 Hz stimulation was attempted as well. METHODS: Prospective cohort study from 2018 to 2021 with ≥ 1 y post-surgery follow up at Yale New Haven Hospital. With 1 Hz, all or most of the gray matter contacts were stimulated at 1, 5, and 10 mA for 30-60s. With 50 Hz, selected gray matter contacts outside of the medial temporal regions were stimulated at 1-5 mA for 0.5-3s. Stimulation was bipolar, biphasic with 0.3 ms pulse width. The Yale Brain Atlas was used for data visualization. Variables were analyzed using Fisher's exact, χ2, or Mann-Whitney test. RESULTS: Forty-one consecutive patients with refractory epilepsy undergoing intracranial EEG for localization of SOZ were included. Fifty-six percent (23/41) of patients undergoing 1 Hz stimulation had seizures induced, 83% (19/23) habitual (clinically and electrographically). Eighty two percent (23/28) of patients undergoing 50 Hz stimulation had seizures, 65% (15/23) habitual. Stimulation of medial temporal or insular regions with 1 Hz was more likely to induce seizures compared to other regions [15/32 (47%) vs. 2/41 (5%), p < 0.001]. Sixteen patients underwent resection; 11/16 were seizure free at one year and all 11 had habitual seizures induced by 1 Hz; 5/16 were not seizure free at one year and none of those 5 had seizures with 1 Hz (11/11 vs 0/5, p < 0.0001). No patients had convulsions with 1 Hz stimulation, but four did with 50 Hz (0/41 vs. 4/28, p = 0.02). SIGNIFICANCE: Induction of habitual seizures with 1 Hz stimulation can reliably identify the SOZ, correlates with excellent surgical outcome if that area is resected, and may be superior (and safer) than 50 Hz for this purpose. However, seizure induction with 1 Hz was infrequent outside of the medial temporal and insular regions in this study.

Artificial intelligence and medical education: A global mixed-methods study of medical students' perspectives.

Objective: Medical students, as clinicians and healthcare leaders of the future, are key stakeholders in the clinical roll-out of artificial intelligence-driven technologies. The authors aim to provide the first report on the state of artificial intelligence in medical education globally by exploring the perspectives of medical students. Methods: The authors carried out a mixed-methods study of focus groups and surveys with 128 medical students from 48 countries. The study explored knowledge around artificial intelligence as well as what students wished to learn about artificial intelligence and how they wished to learn this. A combined qualitative and quantitative analysis was used. Results: Support for incorporating teaching on artificial intelligence into core curricula was ubiquitous across the globe, but few students had received teaching on artificial intelligence. Students showed knowledge on the applications of artificial intelligence in clinical medicine as well as on artificial intelligence ethics. They were interested in learning about clinical applications, algorithm development, coding and algorithm appraisal. Hackathon-style projects and multidisciplinary education involving computer science students were suggested for incorporation into the curriculum. Conclusions: Medical students from all countries should be provided teaching on artificial intelligence as part of their curriculum to develop skills and knowledge around artificial intelligence to ensure a patient-centred digital future in medicine. This teaching should focus on the applications of artificial intelligence in clinical medicine. Students should also be given the opportunity to be involved in algorithm development. Students in low- and middle-income countries require the foundational technology as well as robust teaching on artificial intelligence to ensure that they can drive innovation in their healthcare settings.

Optimizing the surgical management of MRI-negative epilepsy in the neuromodulation era.

OBJECTIVE: To evaluate the role of intracranial electroencephalography monitoring in diagnosing and directing the appropriate therapy for MRI-negative epilepsy and to present the surgical outcomes of patients following treatment. METHODS: Retrospective chart review between 2015-2021 at a single institution identified 48 patients with no lesion on MRI, who received surgical intervention for their epilepsy. The outcomes assessed were the surgical treatment performed and the International League Against Epilepsy seizure outcomes at 1 year of follow-up. RESULTS: Eleven patients underwent surgery without invasive monitoring, including vagus nerve stimulation (10%), deep brain stimulation (8%), laser interstitial thermal therapy (2%), and callosotomy (2%). The remaining 37 patients received invasive monitoring followed by resection (35%), responsive neurostimulation (21%), and deep brain stimulation (15%) or no treatment (6%). At 1 year postoperatively, 39% were Class 1-2, 36% were Class 3-4 and 24% were Class 5. More patients with Class 1-2 or 3-4 outcomes underwent invasive monitoring (100% and 83% respectively) compared with those with poor outcomes (25%, P < .001). Patients with Class 1-2 outcomes more commonly underwent resection or responsive neurostimulation: 69% and 31%, respectively (P < .001). SIGNIFICANCE: The optimal management of MRI-negative focal epilepsy may involve invasive monitoring followed by resection or responsive neurostimulation in most cases, as these treatments were associated with the best seizure outcomes in our cohort. Unless multifocal onset is clear from the noninvasive evaluation, invasive monitoring is preferred before pursuing deep brain stimulation or vagal nerve stimulation directly.

High-resolution cortical parcellation based on conserved brain landmarks for localization of multimodal data to the nearest centimeter.

Precise cortical brain localization presents an important challenge in the literature. Brain atlases provide data-guided parcellation based on functional and structural brain metrics, and each atlas has its own unique benefits for localization. We offer a parcellation guided by intracranial electroencephalography, a technique which has historically provided pioneering advances in our understanding of brain structure-function relationships. We used a consensus boundary mapping approach combining anatomical designations in Duvernoy's Atlas of the Human Brain, a widely recognized textbook of human brain anatomy, with the anatomy of the MNI152 template and the magnetic resonance imaging scans of an epilepsy surgery cohort. The Yale Brain Atlas consists of 690 one-square centimeter parcels based around conserved anatomical features and each with a unique identifier to communicate anatomically unambiguous localization. We report on the methodology we used to create the Atlas along with the findings of a neuroimaging study assessing the accuracy and clinical usefulness of cortical localization using the Atlas. We also share our vision for the Atlas as a tool in the clinical and research neurosciences, where it may facilitate precise localization of data on the cortex, accurate description of anatomical locations, and modern data science approaches using standardized brain regions.

Management of patients with medically intractable epilepsy and anterior temporal lobe encephaloceles.

OBJECTIVE: Temporal lobe encephaloceles (TLENs) are a significant cause of medically refractory epilepsy, but there is little consensus regarding their workup and treatment. This study characterizes these lesions and their role in seizures and aims to standardize preoperative evaluation and surgical management. METHODS: Patients with TLEN who had undergone resective epilepsy surgery from December 2015 to August 2020 at a single institution were included in the study. Medical records were reviewed for each patient to collect relevant seizure workup information including demographics, radiological findings, surgical data, and neuropsychological evaluation. RESULTS: For patients who presented to the authors' program with suspected medically intractable temporal lobe epilepsy (219 patients), TLEN was considered to be the epileptogenic focus in 5.5%. Ten patients with TLEN had undergone resection and were included in this study. Concordance between ictal scalp electroencephalography (EEG) lateralization and TLEN was found in 9/10 patients (90%), and 4/10 patients (40%) had signs suggestive of idiopathic intracranial hypertension (IIH). Surgical outcome was reported in patients with at least 12 months of follow-up (9/10). Patients with scalp EEG findings concordant with the TLEN side had a good outcome (Engel class I: 7 patients, class II: 1 patient). One patient with discordant EEG findings had a bad outcome (Engel class III). No significant neuropsychological deficits were observed after the surgery. CONCLUSIONS: TLENs are epileptogenic lesions that should be screened for in patients with medically refractory epilepsy who have signs of IIH and no other lesions on MRI. Restricted resection is safe and effective in patients with scalp EEG findings concordant with TLEN.

Manual segmentation versus semi-automated segmentation for quantifying vestibular schwannoma volume on MRI.

PURPOSE: Management of vestibular schwannoma (VS) is based on tumour size as observed on T1 MRI scans with contrast agent injection. The current clinical practice is to measure the diameter of the tumour in its largest dimension. It has been shown that volumetric measurement is more accurate and more reliable as a measure of VS size. The reference approach to achieve such volumetry is to manually segment the tumour, which is a time intensive task. We suggest that semi-automated segmentation may be a clinically applicable solution to this problem and that it could replace linear measurements as the clinical standard. METHODS: Using high-quality software available for academic purposes, we ran a comparative study of manual versus semi-automated segmentation of VS on MRI with 5 clinicians and scientists. We gathered both quantitative and qualitative data to compare the two approaches; including segmentation time, segmentation effort and segmentation accuracy. RESULTS: We found that the selected semi-automated segmentation approach is significantly faster (167 s vs 479 s, [Formula: see text]), less temporally and physically demanding and has approximately equal performance when compared with manual segmentation, with some improvements in accuracy. There were some limitations, including algorithmic unpredictability and error, which produced more frustration and increased mental effort in comparison with manual segmentation. CONCLUSION: We suggest that semi-automated segmentation could be applied clinically for volumetric measurement of VS on MRI. In future, the generic software could be refined for use specifically for VS segmentation, thereby improving accuracy.