Faculty Bibliography

Neurologists have long-recognized the importance of the visual system in the diagnosis and monitoring of neurological disorders. This is particularly true since approximately 50% of the brain's pathways subserve afferent and efferent aspects of vision. During the past 30 years, researchers and clinicians have further refined this concept to include investigation of the visual system for patients with specific neurologic diagnoses, including multiple sclerosis (MS), concussion, Parkinson's disease (PD) and conditions along the spectrum of Alzheimer's disease (AD, mild cognitive impairment [MCI] and subjective cognitive decline [SCD]). This review, highlights the visual "toolbox" that has been developed over the past three decades and beyond to capture both structural and functional aspects of vision in neurologic disease. While the efforts to accelerate the emphasis on structure-function relationships in neurological disorders began with MS during the early 2000's, such investigations have broadened to recognize the need for outcomes of visual pathway structure, function and quality of life for clinical trials of therapies across the spectrum of neurological disorders. This review begins with a patient case study highlighting the importance utilizing the most modern technologies for visual pathway assessment, including optical coherence tomography (OCT). We emphasize that both structural and functional tools for vision testing can be used in parallel to detect what might otherwise be sub-clinical events or markers of visual and, perhaps, more global neurological, decline. Such measures will be critical as clinical trials and therapies become more available across the neurological disease spectrum.

Myelin oligodendrocyte glycoprotein antibody-associated disease (MOGAD) is a recently described CNS inflammatory disorder that may manifest with optic neuritis, myelitis, seizures, and/or acute disseminated encephalomyelitis. While MOG-specific antibodies in patients with MOGAD are IgG1, a T-cell-dependent antibody isotype, immunologic mechanisms of this disease are not fully understood. Thymic hyperplasia can be associated with certain autoimmune diseases. In this report we describe a case of MOGAD associated with thymic hyperplasia in a young adult.

We describe a woman with a history of relapsing acute optic neuritis and perineuritis. Testing failed to confirm a specific diagnosis; hence, she was diagnosed with seronegative neuromyelitis optica spectrum disorder and treated with the immunotherapy rituximab, later in conjunction with mycophenolate mofetil. She achieved a durable remission for 9 years until she presented with paresthesia affecting her left fifth digit, right proximal thigh, and left foot, while also reporting a 25-pound weight loss over the prior 3 months. New imaging demonstrated a longitudinally extensive and enhancing optic nerve, in conjunction with multifocal enhancing lesions within the spinal cord, in a skip-like distribution. The differential diagnosis is discussed.

A woman presented at age 18 years with partial myelitis and diplopia and experienced multiple subsequent relapses. Her MRI demonstrated T2 abnormalities characteristic of multiple sclerosis (MS) (white matter ovoid lesions and Dawson fingers), and CSF demonstrated an elevated IgG index and oligoclonal bands restricted to the CSF. Diagnosed with clinically definite relapsing-remitting MS, she was treated with various MS disease-modifying therapies and eventually began experiencing secondary progression. At age 57 years, she developed an acute longitudinally extensive transverse myelitis and was found to have AQP4 antibodies by cell-based assay. Our analysis of the clinical course, radiographic findings, molecular diagnostic methods, and treatment response characteristics support the hypothesis that our patient most likely had 2 CNS inflammatory disorders: MS, which manifested as a teenager, and neuromyelitis optica spectrum disorder, which evolved in her sixth decade of life. This case emphasizes a key principle in neurology practice, which is to reconsider whether the original working diagnosis remains tenable, especially when confronted with evidence (clinical and/or paraclinical) that raises the possibility of a distinctively different disorder.

Optic neuritis is an inflammatory optic neuropathy that is commonly indicative of autoimmune neurological disorders including multiple sclerosis, myelin-oligodendrocyte glycoprotein antibody-associated disease, and neuromyelitis optica spectrum disorder. Early clinical recognition of optic neuritis is important in determining the potential aetiology, which has bearing on prognosis and treatment. Regaining high-contrast visual acuity is common in people with idiopathic optic neuritis and multiple sclerosis-associated optic neuritis; however, residual deficits in contrast sensitivity, binocular vision, and motion perception might impair vision-specific quality-of-life metrics. In contrast, recovery of visual acuity can be poorer and optic nerve atrophy more severe in individuals who are seropositive for antibodies to myelin oligodendrocyte glycoprotein, AQP4, and CRMP5 than in individuals with typical optic neuritis from idiopathic or multiple-sclerosis associated optic neuritis. Key clinical, imaging, and laboratory findings differentiate these disorders, allowing clinicians to focus their diagnostic studies and optimise acute and preventive treatments. Guided by early and accurate diagnosis of optic neuritis subtypes, the timely use of high-dose corticosteroids and, in some instances, plasmapheresis could prevent loss of high-contrast vision, improve contrast sensitivity, and preserve colour vision and visual fields. Advancements in our knowledge, diagnosis, and treatment of optic neuritis will ultimately improve our understanding of autoimmune neurological disorders, improve clinical trial design, and spearhead therapeutic innovation.

BACKGROUND:The diagnosis of multiple sclerosis (MS) requires demyelinating events that are disseminated in time and space. Peripapillary retinal nerve fiber layer (pRNFL) thickness as measured by optical coherence tomography (OCT) distinguishes eyes with a prior history of acute optic neuritis (ON) and may provide evidence to support a demyelinating attack. OBJECTIVE:To investigate whether a deep learning (DL)-based network can distinguish between eyes with prior ON and healthy control (HC) eyes using peripapillary ring scans. METHODS:We included 1033 OCT scans from 415 healthy eyes (213 HC subjects) and 510 peripapillary ring scans from 164 eyes with prior acute ON (140 patients with MS). Data were split into 70% training, 15% validation, and 15% test data. We included 102 OCT scans from 80 healthy eyes (40 HC) and 61 scans from 40 ON eyes (31 MS patients) from an independent second center. Receiver operating characteristic curve analyses with area under the curve (AUC) were used to investigate performance. RESULTS:We used a dilated residual convolutional neural network for the classification. The final network had an accuracy of 0.85 and an AUC of 0.86, whereas pRNFL only had an AUC of 0.77 in recognizing ON eyes. Using data from a second center, the network achieved an accuracy of 0.77 and an AUC of 0.90 compared to pRNFL, which had an AUC of 0.84. INTERPRETATION:DL-based disease classification of prior ON is feasible and has the potential to outperform thickness-based classification of eyes with and without history of prior ON.

BACKGROUND:Limited data exists evaluating predictors of long-term outcomes after hospitalization for COVID-19. METHODS:We conducted a prospective, longitudinal cohort study of patients hospitalized for COVID-19. The following outcomes were collected at 6 and 12-months post-diagnosis: disability using the modified Rankin Scale (mRS), activities of daily living assessed with the Barthel Index, cognition assessed with the telephone Montreal Cognitive Assessment (t-MoCA), Neuro-QoL batteries for anxiety, depression, fatigue and sleep, and post-acute symptoms of COVID-19. Predictors of these outcomes, including demographics, pre-COVID-19 comorbidities, index COVID-19 hospitalization metrics, and life stressors, were evaluated using multivariable logistic regression. RESULTS:Of 790 COVID-19 patients who survived hospitalization, 451(57%) completed 6-month (N = 383) and/or 12-month (N = 242) follow-up, and 77/451 (17%) died between discharge and 12-month follow-up. Significant life stressors were reported in 121/239 (51%) at 12-months. In multivariable analyses, life stressors including financial insecurity, food insecurity, death of a close contact and new disability were the strongest independent predictors of worse mRS, Barthel Index, depression, fatigue, and sleep scores, and prolonged symptoms, with adjusted odds ratios ranging from 2.5 to 20.8. Other predictors of poor outcome included older age (associated with worse mRS, Barthel, t-MoCA, depression scores), baseline disability (associated with worse mRS, fatigue, Barthel scores), female sex (associated with worse Barthel, anxiety scores) and index COVID-19 severity (associated with worse Barthel index, prolonged symptoms). CONCLUSIONS:Life stressors contribute substantially to worse functional, cognitive and neuropsychiatric outcomes 12-months after COVID-19 hospitalization. Other predictors of poor outcome include older age, female sex, baseline disability and severity of index COVID-19.

Saccadic slowing as a component of supranuclear saccadic gaze palsy is an important diagnostic sign in multiple neurologic conditions, including degenerative, inflammatory, genetic, or ischemic lesions affecting brainstem structures responsible for saccadic generation. Little attention has been given to the accuracy with which clinicians correctly identify saccadic slowing. We compared clinician (n = 19) judgements of horizontal and vertical saccade speed on video recordings of saccades (from 9 patients with slow saccades, 3 healthy controls) to objective saccade peak velocity measurements from infrared oculographic recordings. Clinician groups included neurology residents, general neurologists, and fellowship-trained neuro-ophthalmologists. Saccades with normal peak velocities on infrared recordings were correctly identified as normal in 57% (91/171; 171 = 9 videos × 19 clinicians) of clinician decisions; saccades determined to be slow on infrared recordings were correctly identified as slow in 84% (224/266; 266 = 14 videos × 19 clinicians) of clinician decisions. Vertical saccades were correctly identified as slow more often than horizontal saccades (94% versus 74% of decisions). No significant differences were identified between clinician training levels. Reliable differentiation between normal and slow saccades is clinically challenging; clinical performance is most accurate for detection of vertical saccade slowing. Quantitative analysis of saccade peak velocities enhances accurate detection and is likely to be especially useful for detection of mild saccadic slowing.

Although visual symptoms are common following concussion, quantitative measures of visual function are missing from concussion evaluation protocols on the athletic sideline. For the past half century, rapid automatized naming (RAN) tasks have demonstrated promise as quantitative neuro-visual assessment tools in the setting of head trauma and other disorders but have been previously limited in accessibility and scalability. The Mobile Interactive Cognitive Kit (MICK) App is a digital RAN test that can be downloaded on most mobile devices and can therefore provide a quantitative measure of visual function anywhere, including the athletic sideline. This investigation examined the feasibility of MICK App administration in a cohort of Division 1 college football players. Participants (n = 82) from a National Collegiate Athletic Association (NCAA) Division 1 football team underwent baseline testing on the MICK app. Total completion times of RAN tests on the MICK app were recorded; magnitudes of best time scores and between-trial learning effects were determined by paired t-test. Consistent with most timed performance measures, there were significant learning effects between the two baseline trials for both RAN tasks on the MICK app: Mobile Universal Lexicon Evaluation System (MULES) (p < 0.001, paired t-test, mean improvement 13.3 s) and the Staggered Uneven Number (SUN) (p < 0.001, mean improvement 3.3 s). This study demonstrated that the MICK App can be feasibly administered in the setting of pre-season baseline testing in a Division I environment. These data provide a foundation for post-injury sideline testing that will include comparison to baseline in the setting of concussion.