Citations

Background: Viral myocarditis presents a significant burden of disease, particularly among children and young adults. However, clinical guidelines and treatment strategies for pediatric patients are derived from those for adult patients due to a lack of pediatric data. Current animal models of viral myocarditis use adult mice, so conclusions from these models cannot necessarily be extrapolated to the pediatric population. We sought to develop a juvenile mouse model of myocarditis to examine differences between these two distinct clinical populations. Methods: Male and female BALB/c 3-4-week-old 'juvenile' and 8-week-old 'adult' mice were infected intraperitoneally with 103 PFU of heart-passaged coxsackievirus B3. Sera was used to evaluate testosterone and estradiol levels. Cardiac histological evaluations included overall inflammation, fibrosis, and specific cell-type infiltration. RNA was extracted from cardiac tissue and evaluated for changes in gene expression of cell-type markers, complement components, and NLRP3 inflammasome components. Results: Juvenile mice exhibited more severe inflammation than adult mice but no sex differences in overall inflammation. Juvenile mice demonstrated increased infiltration of CD11b+ cells, F4/80+ cells, and CD3+ T-cells vs. adults. Inflammasome genes NLRP3 and caspase-1 were significantly increased in juvenile compared with adult myocarditis. Conclusions: This paper is the first to describe a juvenile mouse model of coxsackievirus B3 myocarditis and provides a direct comparison to a translational adult mouse model. Juvenile mice had greater cardiac inflammation than adults. This model replicates clinical populations and provides a valuable tool to study age as a factor in the pathogenesis of myocarditis.

Abstract Asthma is a chronic inflammatory condition marked by episodic airway narrowing, with exercise-induced bronchoconstriction (EIB) a common trigger. Up to 70% of athletes experience EIB-related symptoms, yet current management relies on reactive treatment rather than early physiological monitoring. This study presents a proof-of-concept multimodal wearable platform integrating impedance pneumography (IPG), electrocardiography (ECG), and inertial measurement unit (IMU) sensing to detect early physiological signatures of EIB. Candidate biomarkers include elevated heart rate, increased respiratory rate, and reduced thoracic impedance amplitude. Real-time embedded algorithms perform on-device feature extraction and threshold-based decision logic without cloud dependence, while IMU data provide posture context for signal interpretation. The system was evaluated through subsystem validation and a resistive-breathing protocol simulating bronchoconstriction. Results demonstrate reliable detection of characteristic cardiorespiratory changes, establishing the feasibility of real-time wearable detection of early EIB markers and supporting future large-cohort validation and form-factor refinement.

Abstract Introduction Mediastinal masses encompass broad differentials of reactive, inflammatory, infectious or neoplastic etiology. In the background of extra thoracic malignancy, it raises a high suspicion for primary cancer or metastatic lymphadenopathy. However, a benign anatomical variant can mimic these findings and lead to unnecessary diagnostic procedures and patient anxiety. Recognizing mimickers becomes crucial in avoiding misdiagnosis and overtreatment. Case A 50-year-old woman with no significant past medical history presented with a two-day history of headache, associated with cough, orthopnea and lower extremity edema. Vital signs were significant for elevated blood pressure at 199/107 mm Hg. Laboratory findings noted a markedly elevated B-type natriuretic peptide (19,000 pg/mL), increased serum creatinine (1.4 mg/dL from baseline 0.7 mg/dL) and proteinuria. Chest X-ray revealed pulmonary vascular congestion. Autoimmune serologies were positive for antinuclear antibody (titer 1:2560), ribonucleoprotein antibody, and RNA polymerase III antibody. Renal biopsy confirmed scleroderma renal crisis. She was treated for hypertensive emergency secondary to scleroderma renal crisis. Further evaluation for elevated total protein revealed monoclonal gammopathy on electrophoresis and 30% plasma cells on bone marrow biopsy, consistent with smoldering multiple myeloma. A chest computed tomography scan incidentally identified a 4 × 3 cm lobular right paratracheal mass. Tissue biopsy was requested to exclude plasmacytoma. Bronchoscopy with endobronchial ultrasound revealed a large hypoechoic paratracheal lesion. Biopsy was aborted due to its cystic appearance and risk of airway flooding. Subsequent magnetic resonance imaging was obtained for tissue characterization which delineated the mass as a thin walled, fluid filled structure communicating with the superior aortic recess, consistent with a high riding superior pericardial recess which is a benign anatomical variant. She was discharged with plans for outpatient multidisciplinary follow up, including pulmonary evaluation for interstitial lung disease surveillance. Discussion High riding pericardial recess is a benign anatomical variant which can closely mimic pathologic masses or lymphadenopathy on cross sectional imaging. Key is identification of probable communication with the superior aortic recess associated with fluid attenuation. Knowledge of anatomy, comprehensive multimodal imaging review, and multidisciplinary discussion are key to prevent unnecessary investigation of mediastinal abnormalities. This abstract is funded by: None

Background Hypermobile Ehlers–Danlos syndrome (hEDS) and hypermobility spectrum disorders (HSDs) are heritable connective tissue disorders characterized by widespread fragile soft connective tissue affecting the skin, ligaments, joints, vasculature, and internal organs. Although hEDS and HSD are autosomal-dominant conditions and would be expected to display a 1:1 sex ratio, studies report higher prevalence in women. Objectives The purpose of this exploratory study was to determine whether self-reported sexual problems differed between females and males diagnosed with hEDS or HSD compared with controls with chronic pain but no hypermobility. Methods In this exploratory retrospective study, we examined 1,407 patients diagnosed with hEDS or HSD according to the 2017 diagnostic criteria for eight indicators of sexual problems based on a validated screening tool. Results Patients in each diagnosis primarily self-reported as White, non-Hispanic females (90%). Of the 1,407 patients who attended the EDS Clinic, 976 (69%) were diagnosed with HSD, 240 (17%) with hEDS, and 191 (14%) were chronic pain controls with neither diagnosis. For HSD, 937 (96%) were females vs. 39 (4%) males (24:1 females to males), while for hEDS, 210 (88%) were females vs. 30 (13%) males (7:1 females to males), and controls were 165 (86%) females vs. 26 (14%) males (6:1 females to males). Females with hEDS reported significantly higher rates of sexual issues than chronic pain controls, including sexual problems (69%, p = 0.018), problems with sexual interest (41%, p = 0.023), sexual pain (45%, p = 0.006), and orgasm difficulty (34%, p = 0.022) compared with males with hEDS or males or females with HSD. In contrast, males diagnosed with hEDS did not report any sexual problems over controls, and males and females diagnosed with HSD reported only one issue—more problems with sexual interest—compared with controls (females p = 0.019, males p = 0.018). However, the small number of males in this study limits conclusions that can be drawn for them. Conclusions This study is unique because we examine sex differences in sexual problems in patients with hEDS and HSD. Our findings indicate a higher percentage of sexual problems in females with hEDS than chronic pain controls without hypermobility, but this was not observed for females with HSD.

Pediatric central nervous system tumors are the leading cause of cancer-related deaths in children. The five-year survival rate for high-grade glioma in children is less than 20%. The development of new treatments is dependent upon multi-institutional collaborative clinical trials requiring reproducible and accurate centralized response assessment. We present the results of the BraTS-PEDs 2023 challenge, the first Brain Tumor Segmentation (BraTS) challenge focused on pediatric brain tumors. This challenge utilized data acquired from multiple international consortia dedicated to pediatric neuro-oncology and clinical trials. BraTS-PEDs 2023 aimed to evaluate volumetric segmentation algorithms for pediatric brain gliomas from magnetic resonance imaging using standardized quantitative performance evaluation metrics employed across the BraTS 2023 challenges. The top-performing AI approaches for pediatric tumor analysis included ensembles of nnU-Net and Swin UNETR, Auto3DSeg, or nnU-Net with a self-supervised framework. The BraTS-PEDs 2023 challenge fostered collaboration between clinicians (neuro-oncologists, neuroradiologists) and AI/imaging scientists, promoting faster data sharing and the development of automated volumetric analysis techniques. These advancements could significantly benefit clinical trials and improve the care of children with brain tumors.

The translation of AI-generated brain metastases (BM) segmentation into clinical practice relies heavily on diverse, high-quality annotated medical imaging datasets. The BraTS-METS 2023 challenge has gained momentum for testing and benchmarking algorithms using rigorously annotated internationally compiled real-world datasets. This study presents the results of the segmentation challenge and characterizes the challenging cases that impacted the performance of the winning algorithms. Untreated brain metastases on standard anatomic MRI sequences (T1, T2, FLAIR, T1PG) from eight contributed international datasets were annotated in stepwise method: published UNET algorithms, student, neuroradiologist, final approver neuroradiologist. Segmentations were ranked based on lesion-wise Dice and Hausdorff distance (HD95) scores. False positives (FP) and false negatives (FN) were rigorously penalized, receiving a score of 0 for Dice and a fixed penalty of 374 for HD95. The mean scores for the teams were calculated. Eight datasets comprising 1303 studies were annotated, with 402 studies (3076 lesions) released on Synapse as publicly available datasets to challenge competitors. Additionally, 31 studies (139 lesions) were held out for validation, and 59 studies (218 lesions) were used for testing. Segmentation accuracy was measured as rank across subjects, with the winning team achieving a LesionWise mean score of 7.9. The Dice score for the winning team was 0.65 ± 0.25. Common errors among the leading teams included false negatives for small lesions and misregistration of masks in space. The Dice scores and lesion detection rates of all algorithms diminished with decreasing tumor size, particularly for tumors smaller than 100 mm3. In conclusion, algorithms for BM segmentation require further refinement to balance high sensitivity in lesion detection with the minimization of false positives and negatives. The BraTS-METS 2023 challenge successfully curated well- annotated, diverse datasets and identified common errors, facilitating the translation of BM segmentation across varied environments and providing the tools for future development of personalized volumetric reports to patients undergoing BM treatment.

Abstract Femtech, a sector dedicated to the development of technologies addressing women's health issues, holds significant potential to revolutionize healthcare for women. This study provides an overview of current Femtech solutions tailored to meet the unique needs of women. It analyzes the present landscape, highlighting key areas where artificial intelligence (AI) and generative technologies have made substantial impacts. Furthermore, the study explores strategies to foster future growth and broader adoption of Femtech within the healthcare sector with a glance at Artificial Intelligence. The ultimate objective is to advance the development of more effective, personalized, accessible, and equitable healthcare solutions for women. The study will review and categorize 56 women’s health-related applications and devices currently available on the US market, identifying existing gaps and areas for potential improvement.

We describe the design and results from the BraTS 2023 Intracranial Meningioma Segmentation Challenge. The BraTS Meningioma Challenge differed from prior BraTS Glioma challenges in that it focused on meningiomas, which are typically benign extra-axial tumors with diverse radiologic and anatomical presentation and a propensity for multiplicity. Nine participating teams each developed deep-learning automated segmentation models using image data from the largest multi-institutional systematically expert annotated multilabel multi-sequence meningioma MRI dataset to date, which included 1000 training set cases, 141 validation set cases, and 283 hidden test set cases. Each case included T2, FLAIR, T1, and T1Gd brain MRI sequences with associated tumor compartment labels delineating enhancing tumor, non-enhancing tumor, and surrounding non-enhancing FLAIR hyperintensity. Participant automated segmentation models were evaluated and ranked based on a scoring system evaluating lesion-wise metrics including dice similarity coefficient (DSC) and 95% Hausdorff Distance. The top ranked team had a lesion-wise median dice similarity coefficient (DSC) of 0.976, 0.976, and 0.964 for enhancing tumor, tumor core, and whole tumor, respectively and a corresponding average DSC of 0.899, 0.904, and 0.871, respectively. These results serve as state-of-the-art benchmarks for future pre-operative meningioma automated segmentation algorithms. Additionally, we found that 1286 of 1424 cases (90.3%) had at least 1 compartment voxel abutting the edge of the skull-stripped image edge, which requires further investigation into optimal pre-processing face anonymization steps.