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Abstract INTRODUCTION M0 images were missing in Siemens ASL data in Alzheimer's Disease Neuroimaging Initiative (ADNI) dataset, prohibiting cerebral blood flow (CBF) quantification. METHODS A conditional latent diffusion model was trained and evaluated on in‐house datasets, then applied to the Siemens data in ADNI‐3. Regional CBF differences by Alzheimer's disease (AD) stages, their accuracy for AD classification, and CBF trajectory slopes were compared between generated data (Siemens) and acquired data (General Electric). RESULTS The diffusion model generated M0 images with high fidelity (SSIM = 0.918 ± 0.023, PSNR = 31.361 ± 2.537) and minimal CBF bias (mean difference is 0.21 ± 1.58 mL/100 g/min). Both generated and acquired CBF showed similar spatial patterns and decreasing trends with AD progression in specific AD‐related regions. Generated CBF also improved accuracy in classifying AD stages compared to qualitative perfusion images. CONCLUSION This study shows the potential of diffusion models for imputing missing modalities in large‐scale studies exploring the use of ASL as a biomarker of AD. Highlights Using latent diffusion model, we can generate M0 image from control image in arterial spin labeling (ASL) with high fidelity. The generated M0 can be used for cerebral blood flow (CBF) quantification in Alzheimer's Disease Neuroimaging Initiative dataset. The performance of classification between Alzheimer's disease (AD) patients and cognitive normal people is better when using generated CBF maps than using non‐quantitative perfusion images. ASL CBF decreases with AD progression in key AD‐related brain regions.

The Quantitative Imaging Biomarkers Alliance Profile for dynamic susceptibility contrast (DSC) MRI and its longitudinal claims for the precision of a DSC MRI–derived quantitative imaging biomarker to assess the relative cerebral blood volume changes in gliomas are summarized.

Background Despite its approval for acute ischemic stroke >25 years ago, intravenous thrombolysis (IVT) remains underused, with inequities by age, sex, race, ethnicity, and geography. Little is known about IVT rates by insurance status. Methods and Results We assessed temporal trends from 2002 to 2015 in IVT for acute ischemic stroke in the Nationwide Inpatient Sample using adjusted, survey ‐ weighted logistic regression. We calculated odds ratios for IVT for each category in 2002 to 2008 (period 1) and 2009 to 2015 (period 2). IVT use for acute ischemic stroke increased from 1.0% in 2002 to 6.8% in 2015 (adjusted annual relative ratio, 1.15). Individuals aged ≥85 years had the most pronounced increase during 2002 to 2015 (adjusted annual relative ratio, 1.18) but were less likely to receive IVT compared with 18‐ to 44‐year‐olds in period 1 (adjusted odds ratio [aOR], 0.23) and period 2 (aOR, 0.36). Women were less likely than men to receive IVT, but the disparity narrowed over time (period 1: aOR, 0.81; period 2: aOR, 0.94). Inequities in IVT resolved for Hispanic individuals in period 2 (aOR, 0.96) but not for Black individuals (period 2: aOR, 0.81). The disparity in IVT for Medicare patients, compared with privately insured patients, lessened over time (period 1: aOR, 0.59; period 2: aOR, 0.75). Patients treated in rural hospitals remained less likely to receive IVT than in urban hospitals; a more dramatic increase in urbanity widened the inequity (period 2, urban nonteaching versus rural: aOR, 2.58, period 2, urban teaching versus rural: aOR, 3.90). Conclusions IVT for acute ischemic stroke increased among adults. Despite some encouraging trends, the remaining disparities highlight the need for intensified efforts at addressing inequities.

Background: Intravenous thrombolysis (IVT) was approved for acute ischemic stroke (AIS) 25 yrs ago, yet few AIS patients receive it, with inequities by race/ethnicity, sex, and geography. With expanding evidence-based programs, we hypothesized increases in IVT utilization and reduction in inequities. Methods: Using the Nationwide Inpatient Sample (NIS), we assessed temporal trends from 2002 to 2015 in IVT for AIS (weighted N=6,694,081) by sex, race/ethnicity, age, insurance, and hospital location/teaching status strata using survey - weighted logistic regression. Covariates included socio-demographics, comorbidities, and hospital characteristics. We calculated odds ratios for IVT by each category in 2002-2008 and 2009-2015. Results: IVT for AIS increased from 1.0% in 2002 to 6.8% in 2015, with an overall adjusted annual relative ratio (AARR) of 1.15 (CI 1.14-1.16). Individuals 18-44 yrs had the highest rate of IVT in 2015. The very elderly (≥85 yrs) had the most pronounced increase in IVT (AARR 1.18, CI 1.17-1.19). The sex disparity in IVT improved, but in 2009-2015, women were still 6% less likely to receive IVT than men (Fig 1). Individuals 18-44 yrs were ~3-fold more likely to receive IVT than the very elderly. IVT inequities for black and Hispanic stroke survivors lessened, but blacks remained ~20% less likely than whites to receive IVT. Government-insured patients were ~25% less likely to receive IVT compared to privately insured. Urban AIS patients were up to 4-fold more likely to receive IVT than rural dwellers. Conclusion: From 2002 through 2015, IVT for AIS in the U.S. increased regardless of race/ethnicity, sex, and age among ≥18 yrs, with the most pronounced increase among the very elderly. Despite encouraging trends, only 1 in 15 AIS patients received IVT and persistent inequities remain for blacks, women, government-insured, and rural stroke survivors, highlighting the need for intensifying stroke literacy and preparedness and enhancing systems of care.

Background: In the initial PARTNER trial (Placement of Aortic Transcatheter Valves) of transcatheter aortic valve replacement for high-risk (HR) and inoperable patients, mortality at 1 year was 24% in HR and 31% in inoperable patients. A recent report of the 30-day outcomes with the low-profile SAPIEN 3 transcatheter aortic valve replacement system demonstrated very low rates of adverse events, but little is known about the longer-term outcomes with this device. Methods: Between October 2013 and September 2014, 583 HR (65%) or inoperable (35%) patients were treated via the transfemoral (84%) or transapical/transaortic (16%) access route at 29 US sites. Major clinical events at 1 year were adjudicated by an independent clinical events committee, and echocardiographic results were analyzed by a core laboratory. Results: Baseline characteristics included age of 83 years, 42% female, and median Society of Thoracic Surgeons score of 8.4%. At the 1-year follow-up, survival (all-cause) was 85.6% for all patients, 87.3% in the HR subgroup, and 82.3% in the inoperable subgroup. Survival free of all-cause and cardiovascular mortality in the transfemoral patients from the HR cohort was 87.7% and 93.3%, respectively. There was no severe paravalvular leak. Moderate paravalvular leak (2.7%) was associated with an increase in mortality at 1 year, whereas mild paravalvular leak had no significant association with mortality. Symptomatic improvement as assessed by the percentage of patients in New York Heart Association class III and IV (90.1% to 7.7% at 1 year; P <0.0001) and by Kansas City Cardiomyopathy Questionnaire overall summary score (improved from 46.9 to 72.4; P <0.0001) was marked. Multivariable predictors of 1-year mortality included alternative access, Society of Thoracic Surgeons score, and disabling stroke. Conclusions: In this large, adjudicated registry of SAPIEN 3 HR and inoperable patients, the very low rates of important complications resulted in a strikingly low mortality rate at 1 year. Between 30 and 365 days, the incidence of moderate paravalvular aortic regurgitation did not increase, and no association between mild paravalvular leak and 1-year mortality was observed, although a small increase in disabling stroke occurred. These results, which likely reflect device iteration and procedural evolution, support the use of transcatheter aortic valve replacement as the preferred therapy in HR and inoperable patients with aortic stenosis. Clinical Trial Registration : URL: http://www.clinicaltrials.gov . Unique identifier: NCT01314313.