Wheeler, Lydia

Abstract Objective An accurate evaluation of behavioral responsiveness during and after seizures in people with epilepsy is critical for diagnosis and management. Current methods for assessing behavioral responsiveness are characterized by substantial variation, subjectivity, and limited reliability and reproducibility in ambulatory and epilepsy monitoring unit settings. In this study, we aimed to develop and implement a novel mobile platform for deployment of automated responsiveness testing in epilepsy—the ARTiE Watch—to facilitate standardized, objective assessments of behavioral responsiveness during and after seizures. Methods We prospectively recruited patients admitted to the epilepsy monitoring units for diagnostic evaluation and long‐term video‐electroencephalographic monitoring at Mayo Clinic and Yale New Haven Hospital. Participants wore the ARTiE Watch, a smartwatch paired with custom smartphone software integrated with cloud infrastructure allowing for remote activation of standardized assessment on the participants' smartwatches. The assessment consisted of 18 command prompts that test behavioral responsiveness across motor, language, and memory domains. Upon visually identifying an electrographic seizure during EMU monitoring, the BrainRISE platform was used to deploy the ARTiE Watch behavioral testing sequence. Responsiveness scoring was conducted on smartwatch files. Results Eighteen of 56 participants had a total of 39 electrographic seizures assessed with the ARTiE Watch. The 18 subjects with ARTiE Watch‐tested seizures had a total of 67 baseline (interictal) ARTiE Watch tests collected for analysis. The analysis showed distinct ARTiE Watch behavioral responsiveness phenotypes: (1) decreased responsiveness across all ARTiE Watch commands during seizure (ictal–postictal) periods compared (to baseline ( p < .0001), (2) decreased responsiveness in bilateral tonic–clonic seizures compared to baseline ( p < .0001) and compared to focal seizures ( p < .0001), and (3) decreased responsiveness during focal impaired awareness seizures compared to baseline ( p < .0001) and compared to focal aware seizures ( p < .001). Significance ARTiE Watch behavioral testing deployed utilizing a mobile cloud‐based platform is feasible and can provide standardized, objective behavioral responsiveness assessments during seizures.

Abstract Early implantable epilepsy therapy devices provided open-loop electrical stimulation without brain sensing, computing, or an interface for synchronized behavioural inputs from patients. Recent epilepsy stimulation devices provide brain sensing but have not yet developed analytics for accurately tracking and quantifying behaviour and seizures. Here we describe a distributed brain co-processor providing an intuitive bi-directional interface between patient, implanted neural stimulation and sensing device, and local and distributed computing resources. Automated analysis of continuous streaming electrophysiology is synchronized with patient reports using a handheld device and integrated with distributed cloud computing resources for quantifying seizures, interictal epileptiform spikes and patient symptoms during therapeutic electrical brain stimulation. The classification algorithms for interictal epileptiform spikes and seizures were developed and parameterized using long-term ambulatory data from nine humans and eight canines with epilepsy, and then implemented prospectively in out-of-sample testing in two pet canines and four humans with drug-resistant epilepsy living in their natural environments. Accurate seizure diaries are needed as the primary clinical outcome measure of epilepsy therapy and to guide brain-stimulation optimization. The brain co-processor system described here enables tracking interictal epileptiform spikes, seizures and correlation with patient behavioural reports. In the future, correlation of spikes and seizures with behaviour will allow more detailed investigation of the clinical impact of spikes and seizures on patients.

OBJECTIVE Multiple endocrine neoplasia type 1 (MEN1) is a rare, autosomal-dominant tumor disorder characterized by the development of pituitary tumors and other endocrine neoplasms. Diagnosis is made clinically based on the development of 2 or more canonical lesions (parathyroid gland, anterior pituitary, and enteropancreatic tumors) or in family members of a patient with a clinical diagnosis of MEN1 and the occurrence of one of the MEN1-associated tumors. The goal of this study was to characterize pituitary tumors arising in the setting of MEN1 at a single institution. The probability of tumor progression and the likelihood of surgical intervention in patients with asymptomatic nonfunctional pituitary adenomas were also analyzed. METHODS A retrospective review of a prospectively maintained institutional database was performed for patients with MEN1 diagnosed from 1970 to 2017. Data included patient demographics, tumor characteristics, treatment strategies, and outcomes. RESULTS A review of the database identified 268 patients diagnosed with MEN1, of whom 158 (59%) were female. Among the 268 patients, 139 (51.8%) had pituitary adenomas. There was a higher prevalence in women than in men (65% vs 35%, p < 0.005). Functional adenomas (57%) were more common. Prolactin-secreting adenomas were the most common functional tumors. Macroadenomas were seen in 27% of patients and were more likely to be symptomatic and locally aggressive (p < 0.001). Forty-nine patients (35%) underwent transsphenoidal resection at some point during their disease course. In 52 patients who were initially observed with MEN1 asymptomatic nonfunctional adenomas, only 5 (10%) progressed to need surgery. In MEN1 patients, an initial parathyroid lesion is most likely followed in order by pituitary, pancreatic, adrenal, and, finally, rare carcinoid tumors. CONCLUSIONS Asymptomatic nonfunctional pituitary adenomas in patients with MEN1 may be followed safely with MRI. In this series, parathyroid tumors developed at the lowest median age of all cardinal tumors, and development of additional cardinal MEN1 lesions followed a predictable pattern. This pattern of disease progression could have significant implications for disease surveillance in clinical practice and may help to target clinical resources to the lesions most likely to develop next. This may aid with early detection and treatment and warrants further study.