A randomized controlled educational pilot trial of interictal epileptiform discharge identification for neurology residents.

OBJECTIVE: To assess the effectiveness of an educational program leveraging technology-enhanced learning and retrieval practice to teach trainees how to correctly identify interictal epileptiform discharges (IEDs). METHODS: This was a bi-institutional prospective randomized controlled educational trial involving junior neurology residents. The intervention consisted of three video tutorials focused on the six IFCN criteria for IED identification and rating 500 candidate IEDs with instant feedback either on a web browser (intervention 1) or an iOS app (intervention 2). The control group underwent no educational intervention ("inactive control"). All residents completed a survey and a test at the onset and offset of the study. Performance metrics were calculated for each participant. RESULTS: Twenty-one residents completed the study: control (n = 8); intervention 1 (n = 6); intervention 2 (n = 7). All but two had no prior EEG experience. Intervention 1 residents improved from baseline (mean) in multiple metrics including AUC (.74; .85; p < .05), sensitivity (.53; .75; p < .05), and level of confidence (LOC) in identifying IEDs/committing patients to therapy (1.33; 2.33; p < .05). Intervention 2 residents improved in multiple metrics including AUC (.81; .86; p < .05) and LOC in identifying IEDs (2.00; 3.14; p < .05) and spike-wave discharges (2.00; 3.14; p < .05). Controls had no significant improvements in any measure. SIGNIFICANCE: This program led to significant subjective and objective improvements in IED identification. Rating candidate IEDs with instant feedback on a web browser (intervention 1) generated greater objective improvement in comparison to rating candidate IEDs on an iOS app (intervention 2). This program can complement trainee education concerning IED identification.

Insights From Chronic ECoG by RNS.

SUMMARY: The NeuroPace responsive neurostimulation system (RNS) has revolutionized the care of patients suffering from focal epilepsy since its approval in 2014. One major advantage of this device is its innate ability to gather long-term electrocorticographic (ECoG) data that the device uses in its novel closed-loop treatment paradigm. Beyond the standard stimulation treatments, which have been demonstrated to be safe and well-tolerated, the data collected by the RNS provide valuable information, such as the long-term circadian and ultradian variations that affect seizure risk, obtained under naturalistic conditions. Additionally, these data inform future surgical procedures, supplementing clinically reported seizures by patients, assessing the response to newly added anti-seizure medications, helping to forecast the risk of future seizures, and understanding the mechanisms of certain long-term outcomes in patients with postsurgical epilepsy. By leveraging these data, the delivery of high-quality clinical care for patients with epilepsy can only be enhanced. Finally, these data open significant avenues of research, including machine learning and artificial intelligence algorithms, which may also translate to improved outcomes in patients who struggle with recurrent seizures.

Expert and deep learning model identification of iEEG seizures and seizure onset times.

Hundreds of 90-s iEEG records are typically captured from each NeuroPace RNS System patient between clinic visits. While these records provide invaluable information about the patient's electrographic seizure and interictal activity patterns, manually classifying them into electrographic seizure/non-seizure activity, and manually identifying the seizure onset channels and times is an extremely time-consuming process. A convolutional neural network based Electrographic Seizure Classifier (ESC) model was developed in an earlier study. In this study, the classification model is tested against iEEG annotations provided by three expert reviewers board certified in epilepsy. The three experts individually annotated 3,874 iEEG channels from 36, 29, and 35 patients with leads in the mesiotemporal (MTL), neocortical (NEO), and MTL + NEO regions, respectively. The ESC model's seizure/non-seizure classification scores agreed with the three reviewers at 88.7%, 89.6%, and 84.3% which was similar to how reviewers agreed with each other (92.9%-86.4%). On iEEG channels with all 3 experts in agreement (83.2%), the ESC model had an agreement score of 93.2%. Additionally, the ESC model's certainty scores reflected combined reviewer certainty scores. When 0, 1, 2 and 3 (out of 3) reviewers annotated iEEG channels as electrographic seizures, the ESC model's seizure certainty scores were in the range: [0.12-0.19], [0.32-0.42], [0.61-0.70], and [0.92-0.95] respectively. The ESC model was used as a starting-point model for training a second Seizure Onset Detection (SOD) model. For this task, seizure onset times were manually annotated on a relatively small number of iEEG channels (4,859 from 50 patients). Experiments showed that fine-tuning the ESC models with augmented data (30,768 iEEG channels) resulted in a better validation performance (on 20% of the manually annotated data) compared to training with only the original data (3.1s vs 4.4s median absolute error). Similarly, using the ESC model weights as the starting point for fine-tuning instead of other model weight initialization methods provided significant advantage in SOD model validation performance (3.1s vs 4.7s and 3.5s median absolute error). Finally, on iEEG channels where three expert annotations of seizure onset times were within 1.5 s, the SOD model's seizure onset time prediction was within 1.7 s of expert annotation.

Powassan Meningoencephalitis: A Case Report Highlighting Diagnosis and Management.

Powassan virus (POWV), a rare flavivirus that may be transmitted by a tick bite, causes rare but severe cases of encephalitis, meningitis, and meningoencephalitis in humans. We present the case of a 62-year-old man with prior Lyme disease and reactive arthritis who presented to the hospital with symptoms of fever, headache, and fatigue. The patient developed rapid deterioration of mental status including profound expressive aphasia and required intubation and high-dose steroids. Cerebrospinal fluid (CSF) serologies were found to be positive for the POWV.

Progressive Tetraparesis in a 57-Year-Old Man With Congenital Absence of an Anterior Spinal Artery: A Case of Anterior Spinal Cord Infarction.

A 57-year-old man presented with sudden neck pain radiating down his arms. This pain progressed to bilateral upper and subsequently lower extremity weakness and numbness. His vitals were notable for systolic blood pressures lower than his baseline (down to 90 mm Hg). The patient's neurological examination as well as magnetic resonance imaging of the cervical and thoracic spine localized to a lesion in the anterior spinal cord. The differential diagnosis for such an acute presentation included stroke, demyelination, intramedullary neoplasm, infection, metabolic myelopathy, and a dural arteriovenous fistula. Further imaging with angiography demonstrated that our patient lacked an anterior spinal artery. In its place, collateral flow from cervical artery branches provided sustenance to the anterior spinal cord. In the setting of hemodynamic instability, this variant anatomy likely predisposed the patient to ischemia, leading to the classic presentation of anterior cord syndrome.

Somatic PRKAR1A mutation in sporadic atrial myxoma with cerebral parenchymal metastases: a case report.

BACKGROUND: Atrial myxomas are generally considered benign neoplasms. The majority of tumors are sporadic and less than 10% are associated with an autosomal dominant condition known as the Carney complex, which is most often caused by germline mutation in the gene PRKAR1A. Whether this gene plays a role in the development of sporadic myxomas has been an area of debate, although recent studies have suggested that some fraction of sporadic tumors also carry mutations in PRKARIA. Extra-cardiac complications of atrial myxoma include dissemination of tumor to the brain; however, the dissemination of viable invasive tumor cells is exceedingly rare. CASE PRESENTATION: We present here a 48-year-old white woman who developed multiple intracranial hemorrhagic lesions secondary to tumor embolism that progressed to 'false' aneurysm formation and invasion through the vascular wall into brain parenchyma 7 months after resection of an atrial myxoma. Whole exome sequencing of her tumor revealed multiple mutations in PRKAR1A not found in her germline deoxyribonucleic acid (DNA), suggesting that the myxoma in this patient was sporadic. CONCLUSIONS: Our patient illustrates that mutations in PRKAR1A may be found in sporadic lesions. Whether the presence of this mutation affects the clinical behavior of sporadic tumors and increases risk for metastasis is not clear. Regardless, the protein kinase A pathway which is regulated by PRKAR1A represents a possible target for treatment in patients with metastatic cardiac myxomas harboring mutations in the PRKARIA gene.

Medical Ethics Education for Neurology Residents: Where Do We Go from Here?

Neurologists regularly confront complex clinical scenarios that require the application of ethical principles to achieve a respectful and fair resolution. In this article, we describe the types of ethically precarious scenarios neurologists encounter, the current status of standards for ethics and communication training for neurology residents, and the present practice of ethics training in neurology residency programs. We make recommendations for optimizing bioethics training for neurology residents and suggest methods for assessing the efficacy of these training initiatives. We emphasize the current need for strengthening the practical bioethics skills of neurologists.