Faculty Bibliography

The aim of this review is to describe the acquisition and reformatting of state of the art high resolution cone beam CT (HR-CBCT) and demonstrate its role in multiple neurovascular conditions as a tool to improve the understanding of disease and guide therapeutic decisions. First, we will review the basic principle of CBCT acquisition, followed by the injection protocols and the reformatting paradigms. Next, multiple applications in different pathological conditions such as aneurysms, arteriovenous malformations, dural arteriovenous fistulas, and stroke will be described. HR-CBCT angiography, widely available, is uniquely useful in certain clinical scenarios to improve the understanding of disease and guide therapeutic decisions. It rapidly is becoming an essential tool for the contemporary neurointerventionalist.AChoAho.

The Neuropsychiatric Inventory Questionnaire (NPI-Q) is a collateral-rated measure of behavioral and psychological symptoms commonly found in dementia (BPSD). Several factor structures have been published, but they have not been systematically compared. Furthermore, the possibility of hierarchical models or presence of measurement invariance around cognitive stage or dementia syndrome has not been previously evaluated. This study addressed these gaps with confirmatory factor analyses using a multicenter sample (n = 41,801; M

Visual impairment represents a significant health and economic burden affecting 596 million globally. The incidence of visual impairment is expected to double by 2050 as our population ages. Independent navigation is challenging for persons with visual impairment, as they often rely on non-visual sensory signals to find the optimal route. In this context, electronic travel aids are promising solutions that can be used for obstacle detection and/or route guidance. However, electronic travel aids have limitations such as low uptake and limited training that restrict their widespread use. Here, we present a virtual reality platform for testing, refining, and training with electronic travel aids. We demonstrate the viability on an electronic travel aid developed in-house, consist of a wearable haptic feedback device. We designed an experiment in which participants donned the electronic travel aid and performed a virtual task while experiencing a simulation of three different visual impairments: age-related macular degeneration, diabetic retinopathy, and glaucoma. Our experiments indicate that our electronic travel aid significantly improves the completion time for all the three visual impairments and reduces the number of collisions for diabetic retinopathy and glaucoma. Overall, the combination of virtual reality and electronic travel aid may have a beneficial role on mobility rehabilitation of persons with visual impairment, by allowing early-phase testing of electronic travel aid prototypes in safe, realistic, and controllable settings.

Large vessel occlusion stroke due to underlying intracranial atherosclerotic disease (ICAD-LVO) is prevalent in 10 to 30% of LVOs depending on patient factors such as vascular risk factors, race and ethnicity, and age. Patients with ICAD-LVO derive similar functional outcome benefit from endovascular thrombectomy as other mechanisms of LVO, but up to half of ICAD-LVO patients reocclude after revascularization. Therefore, early identification and treatment planning for ICAD-LVO are important given the unique considerations before, during, and after endovascular thrombectomy. In this review of ICAD-LVO, we propose a multistep approach to ICAD-LVO identification, pretreatment and endovascular thrombectomy considerations, adjunctive medications, and medical management. There have been no large-scale randomized controlled trials dedicated to studying ICAD-LVO, therefore this review focuses on observational studies.

OBJECTIVE:Stereotactic laser amygdalohippocampotomy (SLAH) is an appealing option for patients with temporal lobe epilepsy, who often require intracranial monitoring to confirm mesial temporal seizure onset. However, given limited spatial sampling, it is possible that stereotactic electroencephalography (stereo-EEG) may miss seizure onset elsewhere. We hypothesized that stereo-EEG seizure onset patterns (SOPs) may differentiate between primary onset and secondary spread and predict postoperative seizure control. In this study, we characterized the 2-year outcomes of patients who underwent single-fiber SLAH after stereo-EEG and evaluated whether stereo-EEG SOPs predict postoperative seizure freedom. METHODS:This retrospective five-center study included patients with or without mesial temporal sclerosis (MTS) who underwent stereo-EEG followed by single-fiber SLAH between August 2014 and January 2022. Patients with causative hippocampal lesions apart from MTS or for whom the SLAH was considered palliative were excluded. An SOP catalogue was developed based on literature review. The dominant pattern for each patient was used for survival analysis. The primary outcome was 2-year Engel I classification or recurrent seizures before then, stratified by SOP category. RESULTS:Fifty-eight patients were included, with a mean follow-up duration of 39 ± 12 months after SLAH. Overall 1-, 2-, and 3-year Engel I seizure freedom probability was 54%, 36%, and 33%, respectively. Patients with SOPs, including low-voltage fast activity or low-frequency repetitive spiking, had a 46% 2-year seizure freedom probability, compared to 0% for patients with alpha or theta frequency repetitive spiking or theta or delta frequency rhythmic slowing (log-rank test, p = .00015). SIGNIFICANCE:Patients who underwent SLAH after stereo-EEG had a low probability of seizure freedom at 2 years, but SOPs successfully predicted seizure recurrence in a subset of patients. This study provides proof of concept that SOPs distinguish between hippocampal seizure onset and spread and supports using SOPs to improve selection of SLAH candidates.

OBJECTIVE:In vitro data prompted U.S Food and Drug Administration warnings that lamotrigine, a common sodium channel modulating anti-seizure medication (NaM-ASM), could increase the risk of sudden death in patients with structural or ischaemic cardiac disease, however, its implications for Sudden Unexpected Death in Epilepsy (SUDEP) are unclear. METHODS:This retrospective, nested case-control study identified 101 sudden unexpected death in epilepsy (SUDEP) cases and 199 living epilepsy controls from Epilepsy Monitoring Units (EMUs) in Australia and the USA. Differences in proportions of lamotrigine and NaM-ASM use were compared between cases and controls at the time of admission, and survival analyses from the time of admission up to 16 years were conducted. Multivariable logistic regression and survival analyses compared each ASM subgroup adjusting for SUDEP risk factors. RESULTS:Proportions of cases and controls prescribed lamotrigine (P = 0.166), one NaM-ASM (P = 0.80), or ≥2NaM-ASMs (P = 0.447) at EMU admission were not significantly different. Patients taking lamotrigine (adjusted hazard ratio [aHR] = 0.56; P = 0.054), one NaM-ASM (aHR = 0.8; P = 0.588) or ≥2 NaM-ASMs (aHR = 0.49; P = 0.139) at EMU admission were not at increased SUDEP risk up to 16 years following admission. Active tonic-clonic seizures at EMU admission associated with >2-fold SUDEP risk, irrespective of lamotrigine (aHR = 2.24; P = 0.031) or NaM-ASM use (aHR = 2.25; P = 0.029). Sensitivity analyses accounting for incomplete ASM data at follow-up suggest undetected changes to ASM use are unlikely to alter our results. SIGNIFICANCE/CONCLUSIONS:This study provides additional evidence that lamotrigine and other NaM-ASMs are unlikely to be associated with an increased long-term risk of SUDEP, up to 16 years post-EMU admission.

Artificial intelligence methods including deep neural networks (DNN) can provide rapid molecular classification of tumors from routine histology with accuracy that matches or exceeds human pathologists. Discerning how neural networks make their predictions remains a significant challenge, but explainability tools help provide insights into what models have learned when corresponding histologic features are poorly defined. Here, we present a method for improving explainability of DNN models using synthetic histology generated by a conditional generative adversarial network (cGAN). We show that cGANs generate high-quality synthetic histology images that can be leveraged for explaining DNN models trained to classify molecularly-subtyped tumors, exposing histologic features associated with molecular state. Fine-tuning synthetic histology through class and layer blending illustrates nuanced morphologic differences between tumor subtypes. Finally, we demonstrate the use of synthetic histology for augmenting pathologist-in-training education, showing that these intuitive visualizations can reinforce and improve understanding of histologic manifestations of tumor biology.

During the past 15 years, new treatment paradigms for neovascular age-related macular degeneration (nvAMD) have evolved due to the advent of intravitreal anti-vascular endothelial growth factor (VEGF) therapy and rapid advances in retinal imaging. Recent publications describe eyes with type 1 macular neovascularization (MNV) as showing more resistance to macular atrophy than eyes with other lesion types. We sought to explore whether the perfusion status of the native choriocapillaris (CC) surrounding type 1 MNV influences its pattern of growth. To evaluate this effect, we analyzed a case series of 22 eyes from 19 nvAMD patients with type 1 MNV exhibiting growth on swept-source optical coherence tomography angiography (SS-OCTA) over a minimum follow-up of 12 months. We observed an overall weak correlation between type 1 MNV growth and CC flow deficits (FDs) average size (τ = 0.17, 95% CI [- 0.20, 0.62]) and a moderate correlation with CC FD % (τ = 0.21, 95% CI [- 0.16, 0.68]). Type 1 MNV was located beneath the fovea in most of the eyes (86%) and median visual acuity was 20/35 Snellen equivalent. Our results support that type 1 MNV recapitulates areas of CC blood flow impairment while serving to preserve foveal function.

Stroke commonly affects the ability of the upper extremities (UEs) to move normally. In clinical settings, identifying and measuring movement abnormality is challenging due to the imprecision and impracticality of available assessments. These challenges interfere with therapeutic tracking, communication, and treatment. We thus sought to develop an approach that blends precision and pragmatism, combining high-dimensional motion capture with out-of-distribution (OOD) detection. We used an array of wearable inertial measurement units to capture upper body motion in healthy and chronic stroke subjects performing a semi-structured, unconstrained 3D tabletop task. After data were labeled by human coders, we trained two deep learning models exclusively on healthy subject data to classify elemental movements (functional primitives). We tested these healthy subject-trained models on previously unseen healthy and stroke motion data. We found that model confidence, indexed by prediction probabilities, was generally high for healthy test data but significantly dropped when encountering OOD stroke data. Prediction probabilities worsened with more severe motor impairment categories and were directly correlated with individual impairment scores. Data inputs from the paretic UE, rather than trunk, most strongly influenced model confidence. We demonstrate for the first time that using OOD detection with high-dimensional motion data can reveal clinically meaningful movement abnormality in subjects with chronic stroke.