Faculty Bibliography

The inherently slow acquisition speed of MRI makes abdominal imaging highly sensitive to respiratory motion artifacts. Since the early days of MRI, the development of respiratory motion compensation techniques has been an active research topic, and this field has seen substantial progress. Despite these advances, the majority of these techniques are not used in daily clinical practice, and motion management methods used in clinical abdominal MRI today have changed little over the past decades. This observation points to a significant gap between technical innovation and clinical translation in this area. This review is motivated by this question: why have so many motion management techniques not been adopted into routine clinical workflows? Unlike conventional survey-style reviews that focus on summarizing emerging methods, this article takes a different, and perhaps opposite, perspective to investigate why those technologically sophisticated innovations are misaligned with practical clinical needs. Specifically, we discuss the barriers behind the gap between research advances and clinical practice, clarify the clinical requirements for effective respiratory motion management in abdominal MRI, and highlight research directions with stronger relevance to routine workflows. The review begins with an overview of the clinical impact of respiratory motion in abdominal MRI, followed by a discussion of standard abdominal MRI sequences and their motion sensitivity. We then summarize current clinical strategies and advanced approaches, along with the barriers that hinder their clinical adoption. The article concludes with future directions and broader lessons learned from this translational gap, with the goal of guiding future developments toward improved clinical integration.

Air pollution remains a leading cause of mortality. Few studies have leveraged residential relocation to examine impacts of intra-individual changes in PM2.5 exposure. As the largest integrated health system in the U.S., the Veterans Health Administration (VHA) is an ideal setting to examine relocation-induced changes in air pollution. We constructed a cohort of Veterans who relocated from one ZIP code to another between 2011 and 2017 (n = 762 905). We linked spatially averaged annual PM2.5 estimates to each person based on residential address. We examined relocation-induced PM2.5 changes and post-move mortality in discrete time models, accounting for individual- and area-level confounding variables. We estimated pooled odds ratios over 5 years of follow up and examined effect measure modification by age (<65, 65+), sex, and neighborhood-level poverty. The pooled OR associated with a 2 μg/m3 increase in PM2.5 levels between the origin and destination areas was 1.03 (95% CI = 1.01-1.03). Associations appeared more pronounced among older individuals when assessing potential additive effect measure modification. Examining intra-individual changes in PM2.5 exposure and subsequent health outcomes can elucidate potential impacts of air pollution and pollution reduction policies. Results suggest survival benefits associated with policies that continue to reduce PM2.5 levels.

INTRODUCTION/BACKGROUND:In recent years, there has been growing concern over the wellbeing and mental health of medical students in the United States, driven by the academic, personal, and professional challenges inherent in medical school. Recent data indicates that medical students experience higher rates of psychological stress, anxiety, and depression compared to the general population, with the COVID-19 pandemic exacerbating these challenges. Medical student suicide, linked to burnout and depression, highlights the urgent need for effective wellbeing support. Despite the documented barriers to mental wellbeing, such as self-imposed pressures, imposter syndrome, stigma around help-seeking, and financial difficulties, medical student wellbeing programs remain understudied at the structural and design level. METHODS:This is a multi‑phase qualitative study (sequential-exploratory) that combines a web-based environmental scan and content analysis with key informant interviews and focus groups, using methodological triangulation to develop a framework for evaluating wellbeing programs. First, we will conduct a web-based content analysis of publicly available resources across medical school websites. We will identify key characteristics of wellbeing programs, such as mental health resources, structural well-being components, and culturally integrated approaches. Then, we will conduct key informant interviews with medical school administrative staff to discuss wellbeing programs in detail and hold focus group interviews with medical students to gather their perspectives on how to improve their health and wellbeing. Based on the findings from these three components, we will develop a comprehensive and standardized framework for evaluating medical school wellbeing programs that can be used across institutions. ETHICS AND DISSEMINATION/BACKGROUND:Human Research Ethics Approval was obtained from the NYU Langone Health Institutional Review Board (IRB ID: i25-00965). The content analysis results and qualitative themes extracted from key informant and focus group interviews will be made available to all study participants. They will also be disseminated in a peer-reviewed journal.

The potential of Large Language Models (LLMs) in medicine is often linked to massive, resource-intensive models. However, their practical application in specialized fields like pediatric critical care requires exploring the capability of more efficient, locally-deployable open-source alternatives. In this study, we evaluated the accuracy and clinical reasoning of open-source LLMs of varying sizes, specifically assessing if smaller, efficient models can perform comparably to larger ones on pediatric critical care multiple-choice questions. A set of 100 pediatric critical care MCQs across six clinical domains, i.e. calculation, diagnosis, ethics, management, pharmacology, and physiology, was curated by two pediatric specialists to evaluate eight open-source LLMs, ranging from 2 to 70 billion parameters. The LLMs were assessed using the overall and category-specific accuracy and clinical reasoning quality score based on a 5-points Likert scale. Additionally, six pediatric critical care fellows completed the MCQs for comparison. Cochran's Q test, McNemar's test, the Friedman test, Cohen's kappa, and Fleiss's kappa were used for the statistical analysis. While the largest model (Llama-3.3-70B) achieved the highest accuracy (78%; 95% CI, 69%-86%), a key finding was the performance of the much smaller, 14.7-billion parameter Phi-4. This efficient model was strikingly comparable, with 75% accuracy (95% CI, 65%-83%) and a similar reasoning score (4.40 vs. 4.49/5). Both models' performance was comparable to that of the pediatric critical care fellows included in this study. The LLMs showed a strong performance in ethics but struggled with calculations. Inter-rater reliability was excellent for the clinical reasoning assessment (κ = 0.92). Our findings demonstrate that smaller, efficient LLMs can approach the performance of much larger models and pediatric critical care fellows for complex pediatric critical care reasoning. These results support further investigation for developing secure, locally-deployable decision support tools without relying on massive, proprietary systems. At the same time, these models hold potential as complementary resources for trainee education in pediatric critical care. However, their identified weaknesses, especially in calculations, pose a prohibitive barrier that underscores the need for rigorous, domain-specific validation followed by evaluation in more realistic clinical scenarios to ensure safe use in both clinical and educational contexts.

INTRODUCTION/BACKGROUND:Sexual and gender minority (SGM) populations experience health disparities linked to minority stress (socially-based stressors), including proximal (e.g., SGM internalized stigma) and distal stressors (e.g., negative bias from non-SGM people toward SGM individuals). We synthesized and evaluated the effectiveness of interventions reducing proximal and distal SGM stress. METHODS:We followed PRISMA and Joanna Briggs Institute guidelines (CRD42024604568). Five databases were searched and eligible studies evaluated interventions reducing minority stress with sufficient data for effect size estimation. We estimated three-level multivariate meta-regression models for distal and proximal minority stress using restricted maximum likelihood estimation and robust standard error estimates. RESULTS:Fifty-one studies (31 distal, 20 proximal) with 11253 participants (SGM n = 3168) were included. Distal stress interventions yielded a null-to-small pooled effect (g = 0.185, 95% CI = 0.078, 0.292). Psychological interventions had a small effect (g = 0.361, 95% CI = 0.178, 0.544) and outperformed psychoeducation and social contact-based interventions (-0.257 < β < -0.221, p < 0.05). For proximal minority stress, although the overall pooled effect was nonsignificant (g = 0.071, 95% CI = -0.154, 0.297) the intervention × outcome interaction was (Wald Q = 4.661, p = 0.005). Narrative therapy targeting identity affirmation showed a large pooled effect (g = 1.846, 95% CI = 1.032, 2.659). Pairwise contrasts using this intervention-outcome combination as reference indicated that psychoeducation and psychological interventions had greater effects on internalized stigma and perceived social support (2.172 < β < 2.719, p < 0.05). CONCLUSION/CONCLUSIONS:Psychological interventions may reduce both proximal and distal stress. However, aligning interventions to specific minority stressors may yield greater benefit on SGM populations' health.

The neighborhood environment influences the amount of children's screen time, which in turn affects later development. Few studies have examined the potential for parent-child interventions to moderate such associations. This study examined the link between neighborhood disorder (observed and parent-reported) and infant screen time at 9 months, and whether the PlayReadVIP intervention attenuates this relation among Black/African-American and White families in Flint, MI. Three -hundred and ninety-nine families were included in analyses. Multigroup SEM path analyses indicated that observed neighborhood disorder predicted screen time for all participants (β=.19), but perceived neighborhood disorder was a significant -predictor of infant screen time only for the Control group (β=.11). Findings support the potential of early parent-child -programs to attenuate a range of risk factors for children's development.

BACKGROUND/UNASSIGNED:. those who proceeded directly to mTESE. METHODS/UNASSIGNED:A retrospective cohort study of 73 male patients with NOA or cryptozoospermia severe enough to qualify for mTESE at NYU Langone Fertility Center between 2018 and 2024. Patients were categorized based on their initial intervention: ESSM-first group (n=45), in which ESSM was attempted prior to surgical retrieval, and an mTESE-first group (n=28), in which patients proceeded directly to surgery. The primary outcome was overall sperm identification rate per patient. Secondary outcomes included sperm retrieval success from mTESE after failed ESSM, and among patient proceeding to in vitro fertilization (IVF) with ICSI, fertilization rate, blastocyst formation rate, euploid rate, and live birth rate. RESULTS/UNASSIGNED:. 46%, P=0.66). CONCLUSIONS/UNASSIGNED:In men with NOA or cryptozoospermia eligible for surgical sperm retrieval, an ESSM-first strategy was associated with higher overall sperm identification rates while preserving comparable reproductive outcomes among those proceeding to IVF with ICSI. These findings support consideration of ESSM as an initial, non-invasive strategy prior to mTESE in appropriately selected patients.

Virtual urgent care (VUC) has become an increasingly utilized resource for acute care delivery. Frequent utilization of VUC may reflect unmet longitudinal care needs and contribute to fragmented care. While high-utilizer patterns are well described in emergency departments, they have not been systematically characterized in telemedicine. We evaluated a clinical decision support (CDS) nudge designed to identify and address high utilizers of VUC at a large academic health system. An electronic health record alert triggered when patients met predefined high-utilizer criteria (>3 visits in 30 days, >12 in six months, or >20 in 12 months) and prompted providers to document a structured follow-up plan using a SmartPhrase. Among 473 eligible patients, 162 (34%) received the SmartPhrase. After adjustment for baseline utilization using negative binomial regression, SmartPhrase use was associated with a 22% relative reduction in VUC visits over the subsequent 30 days (incidence rate ratio 0.78, p = .03). Bootstrapped analyses confirmed a significant reduction in the SmartPhrase group (-1.47 visits; 95% CI [-2.19 to -0.62]), while no significant change occurred in the comparison group. These findings suggest that a low-cost, workflow-integrated CDS nudge may reduce short-term telehealth overutilization by prompting structured follow-up discussions and encouraging longitudinal care planning.

[This corrects the article DOI: 10.1016/j.waojou.2021.100613.].