Faculty Bibliography

X-linked myopathy with excessive autophagy is a rare disorder caused by a mutation in the vacuolar ATPase assembly factor gene which causes slowly progressive early onset proximal weakness and loss of ambulation by the age of 50-70 years. Electrodiagnostic (EDx) testing usually shows widespread complex repetitive and myotonic discharges, even in muscles unaffected clinically. We report a 65-year-old man who presented with progressive proximal weakness since his teenage years. Extensive workup over 30 years revealed inconclusive EDx and muscle histopathology findings. The diagnosis was finally made with genetic testing. Subsequent neuromuscular ultrasound was more informative of disease severity than repeat EDx and directed a muscle biopsy that showed an autophagic vacuolar myopathy and the novel identification of vacuoles in capillary endothelial cells. Although genetic testing is required for confirmation, in milder cases of X-linked myopathy with excessive autophagy, neuromuscular ultrasound may aid in diagnosis even when EDx findings are inconclusive.

BACKGROUND:Neuro-ophthalmology frequently requires a complex and multi-faceted clinical assessment supported by sophisticated imaging techniques in order to assess disease status. The current approach to diagnosis requires substantial expertise and time. The emergence of AI has brought forth innovative solutions to streamline and enhance this diagnostic process, which is especially valuable given the shortage of neuro-ophthalmologists. Machine learning algorithms, in particular, have demonstrated significant potential in interpreting imaging data, identifying subtle patterns, and aiding clinicians in making more accurate and timely diagnosis while also supplementing nonspecialist evaluations of neuro-ophthalmic disease. EVIDENCE ACQUISITION/METHODS:Electronic searches of published literature were conducted using PubMed and Google Scholar. A comprehensive search of the following terms was conducted within the Journal of Neuro-Ophthalmology: AI, artificial intelligence, machine learning, deep learning, natural language processing, computer vision, large language models, and generative AI. RESULTS:This review aims to provide a comprehensive overview of the evolving landscape of AI applications in neuro-ophthalmology. It will delve into the diverse applications of AI, optical coherence tomography (OCT), and fundus photography to the development of predictive models for disease progression. Additionally, the review will explore the integration of generative AI into neuro-ophthalmic education and clinical practice. CONCLUSIONS:We review the current state of AI in neuro-ophthalmology and its potentially transformative impact. The inclusion of AI in neuro-ophthalmic practice and research not only holds promise for improving diagnostic accuracy but also opens avenues for novel therapeutic interventions. We emphasize its potential to improve access to scarce subspecialty resources while examining the current challenges associated with the integration of AI into clinical practice and research.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Despite the well-established efficacy of deep brain stimulation (DBS) of the subthalamic nucleus (STN) for Parkinson's Disease (PD), there remains a subset of patients with only a moderate improvement in symptoms even with appropriate lead placement and optimal programming. In patients with persistent tremor or dyskinesias, one consideration is the addition of a second "rescue lead" to provide dual stimulation to primary and secondary targets to address the refractory component. This study aimed to assess all "rescue lead" cases from our institution and characterize the patients and their outcomes. METHODS:Records of all patients with PD treated at our institution between 2005 and 2023 were retrospectively reviewed. Clinical data of all patients treated with a second rescue lead to supplement a positive but inadequate initial DBS response were collected and reviewed. RESULTS:Of 670 patients with PD treated at our institution during the study period, 7 were managed with a rescue lead. All 7 were initially treated with STN DBS with a partial improvement in underlying symptoms, had confirmed appropriate lead placement, and underwent thorough programming. Four patients underwent rescue with a globus pallidus interna lead for persistent dyskinesias, all with subsequent improvement in their dyskinesias. Three patients had persistent tremors that were treated with a rescue ventrointermediate thalamus stimulation with subsequent improvement in tremor scores. There were no operative complications, and all patients tolerated dual stimulation. CONCLUSION/CONCLUSIONS:For a small subset of patients with PD with persistent dyskinesias or tremors after STN DBS despite optimized lead parameters and adequate lead placement, rescue lead placement offers an effective treatment option.

BACKGROUND AND OBJECTIVES/OBJECTIVE:Psychosocial adversity and stress, known to predispose adults to neurodegenerative and inflammatory immune disorders, are widespread among children who experience socioeconomic disadvantage, and the associated neurotoxicity and proinflammatory profile may predispose these children to multiple sclerosis (MS). We sought to determine associations of socioeconomic disadvantage and psychosocial adversity with odds of pediatric-onset MS (POMS), age at POMS onset, and POMS disease activity. METHODS:This case-control study used data collected across 17 sites in the United States by the Environmental and Genetic Risk Factors for Pediatric Multiple Sclerosis Study. Cases (n = 381) were youth aged 3-21 years diagnosed with POMS or a clinically isolated demyelinating syndrome indicating high risk of MS. Frequency-matched controls (n = 611) aged 3-21 years were recruited from the same institutions. Prenatal and postnatal adversity and postnatal socioeconomic factors were assessed using retrospective questionnaires and zip code data. The primary outcome was MS diagnosis. Secondary outcomes were age at onset, relapse rate, and Expanded Disability Status Scale (EDSS). Predictors were maternal education, maternal prenatal stress events, child separation from caregivers during infancy and childhood, parental death during childhood, and childhood neighborhood disadvantage. RESULTS:= 0.025). There were no associations of the socioeconomic variables with age at onset, relapse rate, or EDSS, or of prenatal or postnatal adverse events with risk of POMS, age at onset, relapse rate, or EDSS. DISCUSSION/CONCLUSIONS:Low socioeconomic status at the neighborhood level may increase the risk of POMS while high parental education may be protective against POMS. Although we did not find associations of other evaluated prenatal or postnatal adversities with POMS, future research should explore such associations further by assessing a broader range of stressful childhood experiences.

BACKGROUND AND OBJECTIVES/OBJECTIVE:scores of OCT-derived measures to prognosticate future disease activity and disability worsening in people with MS (PwMS). METHODS:scores (pRNFL-z and GCIP-z) based on the reference data. Finally, we investigated the association of pRNFL-z or GCIP-z as predictors with future confirmed disability worsening (Expanded Disability Status Scale score increase) or disease activity (failing of the no evidence of disease activity [NEDA-3] criteria) as outcomes. Cox proportional hazards models or logistic regression analyses were applied according to the original studies. Optimal cutoffs were identified using the Akaike information criterion as well as location with the log-rank and likelihood-ratio tests. RESULTS:score approach with optimal cutoffs showed better performance in discrimination and calibration (higher Harrell's concordance index and lower integrated Brier score). DISCUSSION/CONCLUSIONS:scores that account for age, a major driver for disease progression in MS, to be a promising approach for creating OCT-derived measures useable across devices and toward individualized prognostication.

Unintended on-target chromosomal alterations induced by CRISPR/Cas9 in mammalian cells are common, particularly large deletions and chromosomal translocations, and present a safety challenge for genome editing. Thus, there is still an unmet need to develop safer and more efficient editing tools. We screened diverse DNA polymerases of distinct origins and identified a T4 DNA polymerase derived from phage T4 that strongly prevents undesired on-target damage while increasing the proportion of precise 1- to 2-base-pair insertions generated during CRISPR/Cas9 editing (termed CasPlus). CasPlus induced substantially fewer on-target large deletions while increasing the efficiency of correcting common frameshift mutations in DMD and restored higher level of dystrophin expression than Cas9-alone in human cardiomyocytes. Moreover, CasPlus greatly reduced the frequency of on-target large deletions during mouse germline editing. In multiplexed guide RNAs mediating gene editing, CasPlus repressed chromosomal translocations while maintaining gene disruption efficiency that was higher or comparable to Cas9 in primary human T cells. Therefore, CasPlus offers a safer and more efficient gene editing strategy to treat pathogenic variants or to introduce genetic modifications in human applications.

PURPOSE OF REVIEW/OBJECTIVE:This review critically analyzes the recent literature on virtual reality's (VR) use in acute and chronic pain management, offering insights into its efficacy, applications, and limitations. RECENT FINDINGS/RESULTS:Recent studies, including meta-analyses and randomized controlled trials, have demonstrated VR's effectiveness in reducing pain intensity in various acute pain scenarios, such as procedural/acute pain and in chronic pain conditions. The role of factors such as immersion and presence in enhancing VR's efficacy has been emphasized. Further benefits have been identified in the use of VR for assessment as well as symptom gathering through conversational avatars. However, studies are limited, and strong conclusions will require further investigation. VR is emerging as a promising non-pharmacological intervention in pain management for acute and chronic pain. However, its long-term efficacy, particularly in chronic pain management, remains an area requiring further research. Key findings highlight that VR programs vary in efficacy depending on the specificity of the origin of pain.

INTRODUCTION/BACKGROUND:The Accreditation Council for Graduate Medical Education (ACGME) approved the first pain medicine fellowship programs over three decades ago, designed around a pharmacological philosophy. Following that, there has been a rise in the transition of pain medicine education toward a multidisciplinary interventional model based on a tremendous surge of contemporaneous literature in these areas. This trend has created variability in clinical experience and education amongst accredited pain medicine programs with minimal literature evaluating the differences and commonalities in education and experience of different pain medicine fellowships through Program Director (PD) experiences. This study aims to gather insight from pain medicine fellowship program directors across the country to assess clinical and interventional training, providing valuable perspectives on the future of pain medicine education. METHODS:This study involved 56 PDs of ACGME-accredited pain fellowship programs in the United States. The recruitment process included three phases: advanced notification, invitation, and follow-up to maximize response rate. Participants completed a standard online questionnaire, covering various topics such as subcategory fields, online platforms for supplemental education, clinical experience, postgraduate practice success, and training adequacy. RESULTS:Surveys were completed by 39/56 (69%) standing members of the Association of Pain Program Directors (APPD). All PDs allowed fellows to participate in industry-related and professional society-related procedural workshops, with 59% encouraging these workshops. PDs emphasized the importance of integrity, professionalism, and diligence for long-term success. Fifty-four percent of PDs expressed the need for extension of fellowship training to avoid supplemental education by industry or pain/spine societies. CONCLUSION/CONCLUSIONS:This study highlights the challenge of providing adequate training in all Pain Medicine subtopics within a 12-month pain medicine fellowship. PDs suggest the need for additional training for fellows and discuss the importance of curriculum standardization.

PURPOSE OF REVIEW/OBJECTIVE:This review provides an overview of the current and future role of artificial intelligence (AI) and virtual reality (VR) in addressing the complexities inherent to the diagnosis, classification, and management of headache disorders. RECENT FINDINGS/RESULTS:Through machine learning and natural language processing approaches, AI offers unprecedented opportunities to identify patterns within complex and voluminous datasets, including brain imaging data. This technology has demonstrated promise in optimizing diagnostic approaches to headache disorders and automating their classification, an attribute particularly beneficial for non-specialist providers. Furthermore, AI can enhance headache disorder management by enabling the forecasting of acute events of interest, such as migraine headaches or medication overuse, and by guiding treatment selection based on insights from predictive modeling. Additionally, AI may facilitate the streamlining of treatment efficacy monitoring and enable the automation of real-time treatment parameter adjustments. VR technology, on the other hand, offers controllable and immersive experiences, thus providing a unique avenue for the investigation of the sensory-perceptual symptomatology associated with certain headache disorders. Moreover, recent studies suggest that VR, combined with biofeedback, may serve as a viable adjunct to conventional treatment. Addressing challenges to the widespread adoption of AI and VR in headache medicine, including reimbursement policies and data privacy concerns, mandates collaborative efforts from stakeholders to enable the equitable, safe, and effective utilization of these technologies in advancing headache disorder care. This review highlights the potential of AI and VR to support precise diagnostics, automate classification, and enhance management strategies for headache disorders.