Jamaica Hospital Medical Center is a private, non-profit teaching hospital and emergency facility in the Jamaica neighborhood of Queens, New York City, on the service road of the Van Wyck Expressway at Jamaica Avenue. The hospital is a clinical campus of the New York Institute of Technology College of Osteopathic Medicine and provides clinical clerkship education for the college's osteopathic medical students.
Gliomas are generally readily detected and broadly characterized using conventional MRI; however, substantial challenges remain in accurately delineating tumor extent, grading heterogeneous disease, and translating imaging findings into consistent, reproducible clinical decisions. Despite reported Dice coefficients of 0.85–0.91 for whole-tumor segmentation and classification AUC values exceeding 0.90 for glioma grading in curated datasets, most AI systems remain limited by validation design, dataset bias, and inadequate external generalizability. This narrative review synthesizes current AI applications for MRI-based glioma detection and segmentation, highlighting the evolution from radiomics-based classical machine learning approaches relying on handcrafted features to deep learning models capable of end-to-end representation learning. Commonly used MRI sequences, algorithmic paradigms, and reported performance trends are reviewed, with particular emphasis on tumor segmentation as a foundational enabling task. Key limitations that hinder clinical translation are examined, including limited dataset diversity, validation practices that inflate reported performance, domain shift across institutions, acquisition-related bias, and inadequate model interpretability. Emerging strategies to address these challenges, such as multi-institutional training, harmonization techniques, explainable AI frameworks, and workflow-integrated validation, are also discussed. While AI-based models demonstrate strong technical performance in research settings, their clinical impact will depend on rigorous external validation, transparency, and alignment with real-world neuro-oncology workflows.
This study is the first to examine the prevalence and correlates of severe depressive symptoms among internally displaced populations in Haiti due to gang violence. A cross-sectional survey was conducted among 1,545 participants (mean age = 36.5 years old, SD = 15.4; 60.5%). Findings reveal that the prevalence of clinically significant depression symptoms was 68.3% (95% CI; 66.0%, 70.6%), while the prevalence of severe depression symptoms was 38.1% (95% CI; 35.7%, 40.5%). Both outcomes were higher in women (72.9%; 40.6%) compared to men (61.1%; 33.2%), χ2 (1) = 23.29, p < 0.0001; χ2 (1) = 8.40, p = 0.004. Significant associations were also found for geographical areas, age, education, marital status, paid job, religion. Hierarchical logistic regression analyses, using adjusted odds ratio (aOR) identified community violence as the strongest predictor of severe depressive symptoms (aOR = 1.29, 95%CI: 1.22-1.31, p < 0.0001), whereas witnessing violence did not reach statistical significance. Conversely, resilience and social support (aOR= 0.97, 95% CI: 0.97-0.98, p < 0.0001; aOR = 0.77, 95%CI: 0.67-0.88, p = 0.0001) were inversely associated with depressive symptoms, highlighting their protective roles. These results underscore the magnitude of the mental health crisis among internally displaced populations in Haiti. While resilience and social support play a key protective role, they remain insufficient in the face of pervasive, cumulative, and traumatic armed gang violence. Findings highlight the urgent need for structural interventions, integrated mental health services, and community-based approaches targeting the most vulnerable populations, particularly women and rural residents.
Abstract Ludwig’s angina (LA) is a severe cellulitis affecting the submandibular, sublingual, and submental spaces. We report a rare case of LA initially presenting as pericarditis, later progressing to descending necrotizing mediastinitis (DNM) in a previously healthy adult. This case highlights the importance of early imaging, airway management, and prompt surgical drainage for a favorable outcome. A 30-year-old female presented to the emergency department (ED) with acute pericardial symptoms and neck swelling. Eight days prior, she had sustained bilateral mandibular fractures but had declined both intravenous antibiotics and surgical intervention. Upon examination and initial CT imaging in the ED, phlegmonous inflammation and fluid collections were observed in the submental and submandibular spaces, extending into the sternocleidomastoid muscles and mediastinum. Despite receiving IV antibiotics, the patient developed a complicated parapneumonic effusion, resulting in complete left lung collapse, which was confirmed by bronchoscopy.In response, emergent incision and drainage (I&D) was performed, followed by placement of a left chest tube. The patient was transferred to the surgical intensive care unit (SICU) and later referred to a tertiary care center for possible lung decortication. At the center, she underwent drainage of a right neck abscess, insertion of a right chest tube, and mediastinal drainage via a posterolateral thoracotomy. On day 4 of admission, she returned to the operating room for drainage of a right supraclavicular abscess. Following these procedures, her clinical status improved significantly. Antibiotics were switched to Augmentin, chest tubes were removed, and the patient was ultimately discharged home in stable condition.Ludwig’s angina (LA) is a rapidly progressing cellulitis that can lead to life-threatening complications such as empyema or, more critically, descending necrotizing mediastinitis (DNM). This case presents a rare and striking progression of LA, initially manifesting as pericarditis in a previously healthy adult, which swiftly escalated to DNM, as confirmed by CT imaging showing extensive mediastinal involvement. The exceptional nature of this case lies in the rapid progression from local infection to severe mediastinal sepsis, highlighting the critical importance of early diagnosis and multidisciplinary management. Timely airway management, aggressive antibiotic therapy, and surgical drainage were pivotal in averting further complications. This case serves as a powerful reminder that heightened clinician awareness and prompt intervention are essential in preventing catastrophic outcomes, underscoring the need for vigilance in similar cases to optimize patient prognosis. This abstract is funded by: None
RATIONALE:Although low-dose computed tomography (LDCT) performed for lung cancer screening (LCS) frequently identifies previously unrecognized significant incidental findings (SIFs), the most effective way to report these findings remains unclear. Clinical follow-up of SIFs is suboptimal, likely resulting in missed opportunities to improve patient outcomes, but research on contributing factors remains limited. METHODS:We retrospectively reviewed medical records of 296 patients undergoing LDCT between 12/01/2023-09/30/2024. SIF frequency, report structure, and clinical follow-up over 6-months were evaluated. Using mixed-effects logistic regression, follow-up likelihood was examined as a function of radiology report structure, including presence of impression section reporting (IS), management recommendations (MR), and a Lung Imaging and Reporting Data System (Lung-RADS) S Modifier. RESULTS:Most (n = 212) patients had at least one SIF. Of 337 SIFs, 63.8% were reported in the IS; 50.5% were given MRs, while 36.2% were addressed at follow-up. IS reporting (OR: 2.43; CI: 1.06-5.59), MRs (OR: 2.83; CI: 1.31-6.13), and increasing comorbidity burden (OR: 1.13; CI: 1.00-1.27) were associated with greater odds of follow-up. Among SIFs not highlighted in the IS or given MRs, only 17.2% were addressed at follow-up. If either was done, the follow-up rate was 46.2%; if both, 50.6%. S-Modifier use did not improve follow-up. CONCLUSIONS:SIFs found on LDCT conducted for LCS are common, but clinical follow-up rates are suboptimal and impacted by reporting practices and provider-related factors. IS reporting and MRs significantly increase likelihood of follow-up. Efforts to improve SIF follow-up, including standardizing reporting practices, are indicated.
