Osteoporosis is a major and growing health concern in the Asia-Pacific region, y et it remains widely underdiagnosed and undertreated due to limited access to dual-energy X-ray absorptiometry (DXA) in many areas. Artificial intelligence (AI) offers new opportunities to improve osteoporosis screening and management, but unvalidated tools pose risks of inconsistent care. This consensus was developed to provide regionally harmonized guidance on the safe, effective, and equitable use of AI in osteoporosis care. Purpose The aim of this work was to establish expert consensus recommendations on the role of AI in osteoporosis screening and management in the Asia-Pacific region. Key objectives were to define appropriate applications of AI (e.g., imaging-based bone assessment and fracture risk prediction) and specify minimum standards for validation and reporting, addressing region-specific implementation challenges and ensuring that AI use aligns with clinical guidelines and ethical principles. Methods This consensus was developed through multidisciplinary collaboration among experts across the Asia-Pacific region. Each participant reviewed draft statements, contributed feedback during virtual meetings, and provided insights based on clinical experience and current evidence. Consensus was reached iteratively until full agreement was achieved for all statements. The process integrated global best practices and regional adaptations, drawing from peer-reviewed studies, international AI guidelines, and local fracture registry data. The final recommendations emphasize the validation, transparency, and ethical implementation of AI within regional healthcare systems, ensuring compatibility with local regulations. Ultimately, twelve consensus statements were established to guide the responsible use of AI for osteoporosis screening and management in the Asia-Pacific region. Results The panel produced 12 consensus statements covering the role of AI as an adjunct for opportunistic osteoporosis screening rather than a diagnostic tool, requirements for imaging quality and AI model transparency, standards for validation and performance reporting, integration of AI with clinical risk stratification, demonstration of clinical utility in real-world settings, adherence to data protection laws and ethical AI principles, training of clinicians in AI use, strategies for implementation and monitoring (including post-market surveillance and feedback loops), and recognition of technical, clinical, and equity limitations of AI. All 12 statements give extensive recommendations for using AI to improve osteoporosis management while ensuring patient safety, accuracy, and equity. Conclusion This first Asia-Pacific consensus on AI in osteoporosis concludes that AI, when appropriately validated and implemented, can help bridge the osteoporosis care gap by identifying high-risk patients who would otherwise remain undiagnosed, thus facilitating earlier intervention. It emphasizes that AI should complement-not replace-standard diagnostic methods and clinical judgment. The guidance emphasizes validation, transparency, and ethical oversight to facilitate early intervention while minimizing risks associated with unvalidated or premature AI adoption.
Follicular dendritic cell sarcoma (FDCS) is a rare neoplasm with morphologic and phenotypic features resembling those of normal follicular dendritic cells (FDCs). FDCS has been classified into two distinct entities based on their association with Epstein-Barr Virus (EBV): classic FDCS (cFDCS) and EBV-positive inflammatory FDCS (EBV + IFDCS). Diagnosis relies on characteristic histopathology and immunohistochemistry using FDC markers and EBV in situ hybridization (EBER). This study aimed to compare the clinical presentations, histologic features, and immunoprofiles between these two entities in a Taiwanese cohort. We retrospectively reviewed histological features of in-house and consultation cases of FDCS. Immunohistochemistry with novel markers including serglycin (SRGN), FDC-secreted protein (FDCSP) was applied, together with conventional FDC markers (CD21, CD23, CD35) and EBER. Programmed death ligand-1 (PD-L1), a potential therapeutic marker, was additionally evaluated and scored. Clinical and histological parameters, inflammatory cell infiltration, mitotic rate, and PD-L1 tumor proportion score (TPS) were compared statistically. We identified 30 patients including 16 cFDCS and 14 EBV + IFDCS. The median age was 56 years old (range, 22–80), with a female preponderance in EBV + IFDCS. EBV + IFDCS occurred exclusively in extra-nodal sites, while cFDCS more commonly involved lymph nodes. EBV + IFDCS showed significantly higher PD-L1 TPS (p = 0.012), more prominent inflammatory cell infiltration (90.0
Mammary mucinous cystadenocarcinoma (MCA) is an exceedingly rare subtype of breast carcinoma with fewer than 50 cases reported worldwide and limited molecular characterization. We investigated three mammary MCA cases using integrated histopathological assessment, tumor mutation burden (TMB) analysis and targeted next‑generation sequencing of 275 cancer‑associated genes. All tumors demonstrated characteristic multiloculated cystic architecture with papillary proliferations and abundant extracellular mucin. TMB values were uniformly low, ranging from 1.461 to 4.129 mutations/Mb. Representative pivotal alterations included TP53 (truncating and missense) and RB1 (truncating) mutations in all three cases, activating PIK3CA mutations (p.Q546K, p.H419Y) and oncogenic AKT1 mutations (p.E49K, p.E17K) in two cases, whereas KRAS and TERT alterations were each identified in one case. The expanded targeted sequencing results further revealed additional pathogenic and likely pathogenic variants within TP53, PIK3CA and KRAS, particularly in case #1. Of note, the case #1 PIK3CA p.Q546K alteration was concordantly identified in our prior study. Overall, recurrent TP53 and RB1 involvement, together with frequent PI3K-AKT pathway abnormalities and low TMB, supports a distinctive molecular profile for mammary MCA by comparison to conventional mucinous breast carcinoma. These findings may assist in differential diagnosis when interpreted in conjunction with histomorphology and immunophenotype.
To evaluate long-term visual outcomes and prognostic factors after small-gauge pars plana vitrectomy (PPV) for exogenous endophthalmitis. Single-center, retrospective cohort of 45 eyes (45 patients) undergoing PPV for exogenous endophthalmitis (June 2014–September 2024). Demographics, etiology, microbiology, surgical parameters, and outcomes were reviewed. Best-corrected visual acuity (BCVA) was recorded preoperatively and at final follow-up. Associations with final BCVA were explored using univariate tests. Median BCVA improved from hand motion ( 20/4000; logMAR 2.30) to approximately 20/1200 (logMAR 1.78; p = 0.004). Overall, 51.1
Bronchiectasis has traditionally been characterized as a neutrophil-driven disease, yet emerging evidence suggested inflammatory heterogeneities. The prognostic significance of elevated serum immunoglobulin E (IgE) in patients without peripheral eosinophilia remains unclear. We conducted a multicenter prospective cohort study between 2017 and 2020 across 16 institutions in Taiwan. Individuals with bronchiectasis but without allergic bronchopulmonary aspergillosis were included. Patients were stratified by baseline absolute eosinophil count (cutoff 300 /uL) and serum IgE level (≤ 100, 100–500, > 500 IU/mL). The primary endpoint was severe exacerbations resulting in hospitalization at one year. Secondary endpoints included all-cause mortality, distribution of sputum pathogen, imaging pattern, and lung function. A total of 579 individuals were enrolled. Nontuberculous mycobacteria (10.7
