Citations

ABSTRACT Objective Hypertension is a key risk factor for aortic dissection (AD). AD, if left untreated, carries significant mortality rates. Our aim is to analyse trends in mortality due to AD in adults with primary hypertension in the United States (US). Methods We used the CDC WONDER database to extract mortality data for patients with primary hypertension who died due to AD. Age‐adjusted mortality rates (AAMRs) and crude mortality rates (CMRs) were extracted per 100 000 persons. Annual percentage changes (APCs) and average APCs (AAPCs) in AAMRs and CMRs were calculated using Joinpoint regression. Results From 1999 to 2020, a total of 13 128 deaths due to AD were reported in patients with primary hypertension in the US. Males displayed a higher overall AAMR (0.3) than females (0.2) throughout the study period. Slight regional variations were observed, with the West showing the highest overall AAMR (0.4), followed by the Midwest (0.3), and the Northeast and South (0.2). In urban areas, AAMRs were higher than in rural areas until 2008. From 2009 to 2020, AAMRs remained stable in urban areas (0.3) but increased in rural areas from 2010 to 2020 (4.7). The highest state‐level AAMRs were observed in Hawaii, Oregon, and Oklahoma. Conclusion Significant differences were observed in AAPCs compared to AD‐related mortality trends in the general population. Mortality trends revealed an initial decline followed by a gradual rise. Clinicians should focus on high‐risk groups and raise awareness about the disease in these populations.

ABSTRACT Objective To evaluate demographic and clinical factors influencing survival in patients with major salivary gland tumors (MSGTs) using the surveillance, epidemiology, and end results (SEER) database. Study Design A retrospective cohort study using SEER data from 2000 to 2021. Setting Data were collected from the SEER registry, a comprehensive database capturing cancer statistics across the United States. Methods Patients diagnosed with major salivary gland malignancies were analyzed for demographic factors, including age, sex, race, marital status, and income, as well as clinical variables, including tumor grade and site. Stratification by sex was done to assess sex‐specific outcomes. Results The cohort included 13,869 patients. Key findings include that older age and male sex were associated with worse survival outcomes. Single patients had better survival than married individuals, likely due to younger age at diagnosis. Additionally, higher income and Asian/Pacific Islander race conferred a survival advantage. There were disparate impacts between males and females in income, marital status, and race, with higher income and marriage providing a survival advantage for male patients but none for females. Additionally, Black females but not Black males, and widowed females but not widowed males, had slightly increased hazard ratios compared to White individuals. Conclusion Men and women experience disparate effects that impact survival and outcomes in major salivary gland tumors. These findings highlight the need for targeted interventions to address disparities in care and improve survival outcomes while emphasizing the importance of further research to understand the underlying mechanisms driving these disparities.

Chest CTs done for unrelated reasons have the potential to reveal unsuspected abnormalities and provide complementary information to help direct appropriate management. By thoroughly understanding the diagnostic role and limitations of CT in assessing ventricular size and morphology as well as myocardial attenuation, enhancement, and thickness, radiologists will be better equipped to differentiate between normal and abnormal findings and provide precise, clinically appropriate recommendations.

Abstract Aim This study aimed to identify what young adults with type 1 diabetes (T1D) do to make diabetes care fit in their lives and the impact of diabetes and diabetes care on living. Methods Dutch young adults with T1D (18–30 years old) submitted photographed real‐life situations of efforts to make care fit and of the impact of care on their lives. Participants organised their photos in themes, which guided the focus group discussions. We added a reflective questionnaire, semi‐structured interview and iterative validation to identify participant‐defined themes and summarise the data. Results Participants ( N = 18) submitted 240 photographs in total, showing a broad range of situations and emotions. Participants identified 16 themes, grouped into four overarching categories describing their experiences with diabetes: (1) My diabetes: glucose levels, workload, 24/7 present; (2) My life: flow of (daily) life, special and irregular circumstances, life changes, body and health; (3) Support: devices and technology, social network, clinical (diabetes) care; (4) Mental aspects: emotional processes, perspective, being a patient. In the overlap of My diabetes and My life, they identified eating and counting carbohydrates, activity and exercise, recreational substances. Conclusion Young adults with T1D face the complex challenge of fitting their care into their ever‐changing lives. While support systems, such as devices, healthcare professionals and social networks can help, they can also create burdens. Participants emphasised the importance of mental health in their lives with T1D. This study highlights the need for diabetes care that acknowledges the emotional, social and practical realities of young adults' lives.

Abstract Background Quantitative myocardial blood flow (MBF) and myocardial flow reserve (MFR) provide incremental diagnostic and prognostic value in cardiac PET, but their widespread use is limited by the technical demands of dynamic imaging protocols. We evaluated the feasibility of using artificial intelligence (AI) to predict MBF and MFR from static and gated PET images, without the need for dynamic acquisition. Methods A machine learning (XGBoost) model was trained on 82Rb PET multi-center dataset using static perfusion imaging, injected dose, hemodynamic measures, clinical data and CT-derived features (including body composition) from the hybrid CT attenuation scan. Model performance was evaluated externally in an independent cohort. Results In total, 10,566 (derivation-cohort) and 7,842 (external-cohort) patients were included in this multi-center study. On the external-cohort, AI approach achieved an Area under the curve (AUC) of 0.92 (0.92–0.93) for abnormal stress MBF and 0.91 (0.90–0.92) for abnormal MFR; Intra-class correlation (ICC) 0.80 (0.78–0.82) and 0.78 (0.76–0.79), respectively. AI MFR closely mirrored the prognostic performance of measured MFR, showing nearly identical Kaplan–Meier risk stratification (both p<0.0001) and maintaining strong, and independently significant associations with all-cause mortality (HR 3.4 [2.8–4.2] vs. 4.6 [3.6–5.8]; both p<0.001), and demonstrated similar added value to perfusion for mortality prediction. Conclusion AI-predicted virtual stress MBF and MFR assessment using static and gated PET data is feasible and generalizable across cohorts. By removing the dependency on dynamic acquisitions, this approach has the potential to broaden the clinical adoption of flow quantification. STRUCTURED GRAPHICAL ABSTRACT PET: Positron Emission Tomography, CT: Computed Tomography, MFR: Myocardial Flow Reserve Key Question: Can machine learning models trained on dynamic PET datasets accurately predict regional stress myocardial blood flow (MBF) and myocardial flow reserve (MFR) from static image features, physiological parameters, and CT-based anatomical measures? Key Finding: Artificial intelligence can accurately estimate MBF and MFR from non-dynamic PET data, with strong agreement to reference standards. Take-home Message: By eliminating reliance on dynamic PET acquisitions, machine-learning has the potential to broaden clinical adoption of quantitative flow assessment.

Abstract Distinguishing atypical parkinsonian disorders (APS) from Parkinson’s disease (PD) remains challenging due to overlapping clinical features, yet accurate differentiation is critical for prognosis and treatment. Here, we employed multi-model diffusion MRI (dMRI) analysis to characterize microstructural alterations across corticobasal syndrome (CBS), progressive supranuclear palsy-Richardson syndrome (PSP-RS) and PD, with the aim of identifying which dMRI model provides optimum differentiation. We analyzed 25 CBS, 42 PSP-RS, and 21 PD participants compared to 35 age and sex-matched controls. Using a clinically feasible 3-shell high angular resolution diffusion imaging (HARDI) protocol, we applied 11 metrics from five complementary dMRI models—diffusion tensor imaging (DTI), free-water-eliminated model of DTI (FWE), neurite orientation dispersion and density imaging (NODDI), tissue-weighted NODDI, and Fixel Density (FD) in fixel-based analysis (FBA) —to comprehensively assess regional white and gray matter integrity. Group differentiation was assessed using Cohen’s d effect sizes and spearman correlations were assessed between dMRI metrics and clinical scales. Distinct microstructural signatures were observed across disorders and the sensitivity of the dMRI models differed. In group contrasts, DTI and NODDI-derived metrics consistently captured the strongest effects in midbrain and peduncular pathways for PSP-RS, whereas precentral and corticospinal alterations in CBS were most prominent using NODDI and FBA measures. Free-water-corrected metrics showed attenuated group differences. Across clinical-diffusion analyses, NODDI metrics exhibited the most robust associations with disease severity, while DTI and FWE measures detected more limited, regionally constrained effects. Together, these findings highlight complementary yet distinct sensitivities of tensor, free-water, multi-compartment, and fixel-based models to APS-related neurodegeneration.

Abstract Isolated/idiopathic rapid-eye-movement (REM)-Sleep Behavior Disorder (iRBD) is characterized by dream enactment behaviors associated with loss of REM atonia. iRBD is in most cases a prodromal synucleinopathy, and emerging evidence suggests associations between RBD and other neurological and psychiatric conditions. In this study, we performed pathway-based polygenic risk score (PRS) and rare variant burden analyses to examine these potential associations. Pathway-specific PRS were constructed from genome-wide association study summary statistics of five neurodegenerative and seven psychiatric traits across 10 biologically relevant pathway categories, including a total of 279 pathways, in 1,573 iRBD cases and 16,022 controls from the International RBD Study Group and UK Biobank. Rare variant burden tests were performed in 1,264 iRBD cases and 2,581 controls. We identified multiple potential pathways indicating shared polygenic risk between RBD and both neurodegenerative and psychiatric disorders. Lewy body diseases and post-traumatic stress disorder had the most shared polygenic risk pathways in neurological and psychiatric disorders, respectively. Two pathways, the serotonin transport pathway and the chaperone-mediated autophagy pathway, showed the strongest association with iRBD, and gene-based rare variants analyses revealed five genes associated with iRBD: GBA1 , PLEKHM1 , LRP2 , P2RX1 , and HAP1. Subsequent analysis of these genes in Parkinson’s disease and dementia with Lewy bodies replicated several associations. Together, these findings provide novel insights into the shared genetic architecture underlying iRBD, neurodegenerative disorders, and psychiatric traits, with implications for early identification and mechanistic understanding.

We provide the first longitudinal and most comprehensive analysis of the intrarenal microvasculature in a slowly progressive model of autosomal dominant polycystic kidney disease (ADPKD) and integrate the findings with studies in a young cohort of individuals with ADPKD. We identified vasculature-related pathways that could be targeted for therapeutic interventions and contribute promising, noninvasive biomarkers in patients with ADPKD. Alterations of the intrarenal microcirculation may affect drug delivery; a better understanding of its longitudinal changes may aid in treatment management.

Abstract In a real-world analysis of brexucabtagene autoleucel recipients with relapsed/refractory B-cell acute lymphoblastic leukemia (N = 278), lack of response to prior blinatumomab correlates with significantly worse following chimeric antigen receptor T-cell therapy outcomes.