Citations

Background: Among patients (pts) with coronary artery disease (CAD) who are candidates for coronary artery bypass graft surgery (CABG), a reduced ejection fraction (EF) identifies a high-risk group. The profile of pre-operative, intra-operative and post-operative factors contributing to 30 day (d) mortality in pts with low EF undergoing CABG has not been well characterized. Methods: The STICH trial enrolled 2136 pts with CAD amenable to CABG with an LVEF < 35% who were treated with medical therapy (MED) alone, MED with CABG, or with MED plus CABG and surgical ventricular resconstruction (SVR). Multivariable logistic regression models utilizing extensive baseline, intra-operative and post-operative care variables were developed to determine factors associated with mortality at 30d in a landmark analysis among pts surviving the first 36 hours (h). Results: Among those enrolled, 1460 pts received CABG; 673 (46.1%) on pump, 160 (11.0%) off pump, 132 (9.0%) with a mitral valve procedure (MVR), 393 (26.9%) with SVR, and 102 (7.0%) received CABG with SVR and MVR. Mortality in the operating room (OR) was 0.3 %, within the first 36h was 1.0%, and at 30d was 5.1%. The rate of in-hospital acute myocardial infarction was 0.8%, stroke 1.6%, mediastinitis 1.7%, worsening renal insufficiency 8.4%, and return to OR was 6.9%. Inotropes were used in 43.6% and intra-aortic balloon pump in 18.6%. At 36h, 148 pts (10.2%) remained intubated. Among pts who survived to 36h, a robust multivariable model (Table, c-statistic 0.89) was developed to predict 30d mortality. A prolonged intubation time (>36h) was the strongest marker of 30d mortality (odds ratio 7.4, 95% CI 3.8, 14.5, p<0.0001). Conclusions: Among pts with ischemic heart failure, CABG can be performed with a low rate of complications and intra-operative mortality. Prolonged intubation time (>36h) after CABG is an integrated clincal marker that may serve to identify those pts with the least likelihood of survival to 30d.

Background —Coronary arteries respond to hypoxia with transient relaxations, which increases coronary blood flow, in part, by release of nitric oxide. We hypothesized that increased expression of nitric oxide synthase might further augment blood vessel relaxation during hypoxia. The present study examined the effect of adenovirus-mediated transfer of bovine endothelial nitric oxide synthase (eNOS) on hypoxia-induced transient relaxations in canine coronary arteries. Methods and Results —Paired segments of coronary arteries were exposed to vehicle (phosphate-buffered saline with albumin) or an adenovirus encoding either E coli β-galactosidase (Ad.CMVLacZ, viral control; 10 10 pfu/mL) or eNOS (Ad.CMVeNOS; 10 10 pfu/mL) for 2 hours at 37°C. Immunohistochemistry with a monoclonal antibody specific for eNOS documented both endothelial and adventitial expression in Ad.CMVeNOS arteries, whereas vehicle and viral controls demonstrated only constitutive expression. Levels of cGMP were increased 5-fold in Ad.CMVeNOS arteries compared with controls. In arteries exposed to Ad.CMVeNOS, maximum contraction to prostaglandin F 2α was reduced compared with viral controls, and this effect was eliminated by pretreatment with a competitive inhibitor of eNOS ( N G -monomethyl- l -arginine, 10 −3 mol/L). Hypoxia-induced transient relaxation (95% N 2 -5% CO 2 ) in Ad.CMVeNOS arteries (45.2±8.8%, n=6) was augmented compared with vehicle (26.3±6.0%) or viral (27.2±7.1%) controls. Conclusions —Adenovirus-mediated gene transfer of nitric oxide synthase reduces receptor-dependent contractions and augments hypoxia-induced relaxations in canine coronary arteries; this method of augmentation of NO production might be advantageous for reduction of coronary artery vasospasm.

Introduction: Whether echocardiographic (echo) markers of left ventricular (LV) remodeling and diastolic dysfunction contribute incremental and independent prognostic information to clinical risk markers in patients (Pts) with coronary artery disease and severe LV systolic dysfunction is unclear. We sought to determine which echo variables provide the greatest prognostic value in the Surgical Treatment for Ischemic Heart Failure (STICH) population. Methods: Pts enrolled in STICH for whom transmitral Doppler (E/A ratio) was available on a baseline echo interpreted by an echo core laboratory blinded to treatment and outcomes formed the analysis cohort. Comprehensive datasets to account for missing echo data were created by multiple imputation and the impact on all-cause mortality was determined with the Cox’s regression model. Results: E/A ratio could be measured in 1511 of the 2136 Pts enrolled in STICH. Amongst markers of diastolic dysfunction, E/A ratio was the most significant predictor of mortality (χ 2 41.05, p <0.001) with a non-linear, u-shaped, relationship. Mortality was lowest with E/A ratio = 1.0, and increased for E/A ratio <0.6 and >1.0 up to 2.3, beyond which there was no further increase in risk. The combination of larger LV end-systolic volume index (LVESVI), low or high E/A ratio, and mitral regurgitation severity grade, had highly significant incremental negative effects on mortality (χ 2 69.65, p<0.001) when added to a multivariable model with clinical risk markers. Overall, creatinine (χ 2 30.00, p <0.001), followed by LVESVI (χ 2 27.26, p<0.001), age, and E/A ratio (χ 2 12.46, p<0.001) were among the most significant predictors of mortality and accounted for 74% of the total prognostic information. LVESVI and E/A ratio were stronger predictors of poor prognosis than New York Heart Association (NYHA) functional class, hemoglobin, diabetes, stroke, or atrial fibrillation. Conclusions: Echo markers of advanced LV remodeling and diastolic dysfunction add incremental prognostic value to clinical risk markers and are more predictive of poor prognosis than advanced NYHA functional class or anemia. LVESVI and E/A ratio outperformed other echo markers and should be considered standard in assessing risk in Pts with ischemic LV dysfunction.

Introduction: Idiopathic Dilated (DCM) and hypertrophic cardiomyopathies (HCM) are leading causes of sudden cardiac death. The incidence and prevalence of both DCM and HCM were originally estimated in Olmsted County, MN over 1975-1984. Incidence was 6.0 and prevalence was 36.5 per 100,000 person-years, for DCM; with incidence and prevalence rates of 2.5 and 19.7 per 100,000 person-years for HCM. This study aims to determine the incidence and mortality rates of individuals diagnosed with HCM and DCM in Olmsted County, MN from 1984 to 2016. Methods: The Rochester Epidemiology Project is a validated long term medical record linkage system that collects and links medical information for the approximately 145000 residents of Olmsted County, Minnesota. Using this database and the Electronic Health Record systems at Mayo Clinic and Olmsted Medical Center in Rochester, MN, we manually reviewed and validated the medical records of 4440 patients. This cohort includes all patients with any mention of a cardiomyopathy based on ICD and HICDA codes during the period 1984 to 2016. Data were summarized with mean and standard deviation, frequency and percentage and compared between groups using two sample t-test for continuous data and chi-square for proportions. Survival was computed using Kaplan-Meier methods and compared to expected survival based on age and gender. Incidence was computed using Olmsted County population numbers during the time period and adjusted to the US 1980 white population to allow for comparison with the previous study. Results: The calculated crude incidence rate for DCM and HCM are 10.1 and 7.8 per 100,000 respectively. Incidence rates adjusted for comparison to US 1980 white population (age and sex adjusted) are 10.4 (95% CI: 9.3-11.4) and 8.0 (95% CI: 7.1-8.8) per 100,000 person-years, respectively. The observed number of deaths in this cohort (HCM and DCM) was 420 vs 194 expected. Conclusions: Calculated incidence, both crude and adjusted rates are higher than previously estimated rates. The crude incidence rate for HCM is almost 4-fold higher than that for DCM is 2.4 times higher than the original estimate by Codd et al. Individuals with cardiomyopathies were found to have a higher overall mortality rate than the general population with an observed to expected hazard ratio of 1.73 (95% CI 1.49-2.01, p<0.001) for DCM and 1.44 (95% CI 1.21-1.71, p<0.001) for HCM. Our findings suggest that previous studies may have underestimated the true burden of HCM and DCM in the population which has important implications for healthcare provision and cost.

Background: Fundamental advances in stroke care will require pooling imaging phenotype data from multiple centers, to complement the current aggregation of genomic, environmental, and clinical information. Sharing clinically acquired MRI data from multiple hospitals is challenging due to inherent heterogeneity of clinical data, where the same MRI series may be labeled differently depending on vendor and hospital. Furthermore, the de-identification process may remove data describing the MRI series, requiring human review. However, manually annotating the MRI series is not only laborious and slow but prone to human error. In this work, we present a recurrent convolutional neural network (RCNN) for automated classification of the MRI series. Methods: We randomly selected 1000 subjects from the MRI-GENetics Interface Exploration study and partitioned them into 800 training, 100 validation and 100 testing subjects. We categorized the MRI series into 24 groups (see Table). The RCNN used a modified AlexNet to extract features from 2D slices. AlexNet was pretrained on ImageNet photographs. Since clinical MRI are 3D and 4D, a gated recurrent unit neural network was used to aggregate information from multiple 2D slices to make the final prediction. Results: We achieved a classification accuracy (correct/total cases) of 99.8%, 98.5% and 97.5% on the training, validation and testing set, respectively. The averaged F1-score (percent overlap between predicted cases and actual cases) over all categories were 99.8% 98.2% and 94.4% on the training, validation and testing set. Conclusion: We showed that automated annotation of MRI series by repurposing deep-learning techniques used for photographic image recognition tasks is feasible. Such methods can be used to facilitate high throughput curation of MRI data acquired across multiple centers and enable scientifically productive collaboration by researchers and, ultimately enhancing big data stroke research.

Introduction: White matter hyperintensity volume (WMHv) is an important and highly heritable cerebrovascular phenotype; however, manual or semi-automated approaches to clinically acquired MRI analysis hinder large-scale studies in acute ischemic stroke (AIS). In this work, we develop a high-throughput, fully automated WMHv analysis pipeline for clinical fluid-attenuated inversion recovery (FLAIR) images to facilitate rapid genetic discovery in AIS. Methods: Automated WMHv extraction from multiple subjects relies on significant pre-processing of medical scans, including co-registration of the images. To reduce the effects of anisotropic voxel sizes, each FLAIR image is upsampled using bi-cubic interpolation. Brain extraction is performed using RObust Brain EXtraction (ROBEX). Images are then registered to an in-house FLAIR template using Advanced Normalization Tools (ANTs). The spatial covariation of WMH is learned through principal component analysis (PCA) of manual outlines from 100 subjects. Areas of leukoaraiosis are identified and separated from other lesions using the PCA modes. Volumes are then computed using non-interpolated slices for each subject. Standard deviation (SD) in WMHv (9 subjects; 6 raters each) is calculated as a measure of variability. Good agreement between automated and manual outlines is assessed in 358 subjects (automated WMHv within 3SD of manual WMHv). Results: As part of the MRI - Gen etics I nterface E xploration (MRI-GENIE) study, WMHv were calculated on a set of 2703 FLAIR images of patients from 12 independent AIS cohorts (sites). Results are shown in Figure 1. Comparing manual and automated WMHv shows that 88% of the automated WMHv fall within 3 SD from the manual WMHv, suggesting good agreement. Conclusion: WMHv segmentation using a fully-automated pipeline for analysis of clinical MRIs is both feasible and accurate. Ongoing analysis of the extracted WMHv is expected to advance current knowledge of risks and outcomes in AIS.

Introduction: Even though neuroinflammation is increasingly recognized as an essential contributor to ischemic brain injury, the exact underlying mechanisms remain unclear. Higher expression of the vascular cell adhesion molecule 1 (VCAM-1) increases leukocyte-brain endothelium interaction and has been associated with larger infarct size following acute ischemic stroke (AIS). The activation of the TGF-β signaling pathways can down-regulate VCAM-1 expression and ameliorate deleterious tissue outcome during neuroinflammation. Hypothesis: We sought to investigate whether genetic variation in the TGF-beta pathway and adhesion molecule genes is associated with acute stroke lesion size. Methods: We completed genome-wide association (GWA) testing and diffusion-weighted imaging lesion volume (DWIv) analysis in a discovery cohort of 532 AIS patients of European ancestry enrolled within 48 hours of symptom onset. An independent European ancestry cohort of 724 AIS patients with GWA data and automated DWIv served as replication cohort. GWA testing per SNP was performed using linear regression modeling of natural log-transformed DWIv adjusted for age, sex and relevant principal components. We selected 42 inflammatory genes in the TGF-beta pathway for a gene-based analysis using VEGAS (Versatile Gene-based -Association Study) software. A pre-specified discovery phase Bonferroni-corrected threshold was set at p<0.001. In the replication phase, 14 SNPs overlapping were tested at the Bonferroni-corrected p-value threshold of p<0.004. Results: Of all genes in the TGF-beta pathway, VCAM1 (p=0.0006) was significantly associated with DWIv in the discovery AIS cohort (age: 66 ± 14.9 years, sex: 63.4% male, DWIv: 2.2cm 3 (IQR: 0.6-11.7cm 3 )). A single SNP within the VCAM1 gene boundaries (rs3176876 (BETA=0.2341, p=0.003)) was significantly associated with DWIv in the replication AIS cohort (age: 65 ± 14.1 years, sex: 68.6% male, DWIv: 4cm 3 (IQR: 1.3-17.2cm 3 )). Conclusion: The genetic variant rs3176876 in the VCAM1 gene is associated with larger infarct lesion size measured on brain MRI of AIS patients. These findings suggest genetic contribution to the pro-inflammatory mechanisms in acute cerebral ischemia and warrant further investigation.

Introduction: White matter hyperintensity (WMH) is a highly heritable trait and a significant contributor to stroke risk and severity. Vascular risk factors contribute to WMH severity; however, knowledge of the determinants of WMH in acute ischemic stroke (AIS) is still limited. Hypothesis: WMH volume (WMHv) varies across AIS subtypes and is modified by vascular risk factors. Methods: We extracted WMHv from the clinical MRI scans of 2683 AIS subjects from the MRI-Genetics Interface Exploration (MRI-GENIE) study using a novel fully-automated, volumetric analysis pipeline. Demographic data, stroke risk factors and stroke subtyping for the Causative Classification of Stroke (CCS) were performed at each of the 12 international study sites. WMHv was natural log-transformed for linear regression analyses. Results: Median WMHv was 5.7cm 3 (interquartile range (IQR): 2.2-12.8cm 3 ). In univariable analysis, age (63.1 ± 14.7 years, β=0.04, SE=0.002), prior stroke (10.2%, β=0.66, SE=0.08), hypertension (65.4%, β=0.75, SE=0.05), diabetes mellitus (23.1%, β=0.35, SE=0.06), coronary artery disease (17.6%, β=0.04, SE=0.002), and atrial fibrillation (14.6%, β=0.48, SE=0.07) were significant predictors of WMHv (all p<0.0001), as well as smoking status (52.2%, β=0.15, SE=0.05, p=0.005), race (16.5% Non-Caucasian, β=0.25, SE=0.07) and ethnicity (8.2% Hispanic, β=0.30, SE=0.11) (all p<0.01). In multivariable analysis, age (β=0.04, SE=0.002), prior stroke (β=0.56, SE=0.08), hypertension (β=0.33, SE=0.05), smoking status (β=0.16, SE=0.05), race (β=0.42, SE=0.06), and ethnicity (β=0.34, SE=0.09) were independent predictors of WMHv (all p<0.0001), as well as diabetes mellitus (β=0.13, SE=0.06, p=0.02). WMHv differed significantly (p<0.0001, unadjusted) across CCS stroke subtypes: cardioembolic stroke (8.0cm 3 , IQR: 4.2-15.4cm 3 ), large-artery stroke (6.9cm 3 , IQR: 3.1-14.7cm 3 ), small-vessel stroke (5.8cm 3 , IQR: 2.5-13.5cm 3 ), stroke of undetermined (4.7cm 3 , IQR: 1.6-11.0cm 3 ) or other (2.55cm 3 , IQR: 0.9-8.8cm 3 ) causes. Conclusion: In this largest-to-date, multicenter hospital-based cohort of AIS patients with automated WMHv analysis, common vascular risk factors contribute significantly to WMH burden and WMHv varies by CCS subtype.

Introduction: The MRI-Genetics Interface Exploration (MRI-GENIE) study is the first international collaboration that aims to facilitate genetic discoveries in clinical cohorts of patients with acute ischemic stroke (AIS). We have amassed the largest-to-date collection of AIS cases with brain MRI scans and genome-wide genotyping to test the role of genetic susceptibility in MRI-based cerebrovascular traits. Objective/Hypothesis: To elucidate the genetic architecture of white matter hyperintensity (WMH) burden in AIS patients. Methods: Using a novel automated algorithm, we extracted WMH volume (WMHv) from clinical MRI scans of 2704 AIS patients (age 63.1 ± 14.7 years, 60.6% male) of European ancestry. Quality control (QC) measures were undertaken per subject and per SNP, excluding subjects with non-European ancestry and poor genotyping, as well as SNPs deviating from Hardy-Weinberg equilibrium and high levels of missingness. Imputation to the Haplotype Reference Consortium (HRC version r1.1) was conducted for 1712 remaining subjects with 2.8 million SNPs on the Michigan Imputation Server. After exclusion of poorly imputed SNPs (R 2 <0.5) and SNPs with minor allele frequency < 1%, 7.7 million SNPs remained for further analysis. Genome-wide association testing of natural log-transformed WMHv on the allelic dosage per SNP was adjusted for age, sex and principal components 1-10. Results: Genome-wide association testing has identified a novel locus on chromosome 2 (T allele at rs72856504) near the LDL Receptor related Protein 1B gene (LRP1B) that was significantly associated with WMHv burden in AIS (β=0.54, SE=0.098, p=3.65*10 -8 ). Conclusion: We have identified a novel locus (T allele rs72856504) on chromosome 2 near the LRP1B gene, which is specific for WMH in AIS and has not been previosuly described in stroke-free WMH cohorts. A replication effort involving additional independent cohorts of AIS patients with brain MRI and genome-wide genotyping is ongoing.