Citations

Introduction: Low rates of enrollment into stroke clinical trials are an ongoing challenge for the stroke research community. We sought to retrospectively describe the association between medical eligibility and recruitment rates for two acute clinical trials. Methods: Within a population of 1.3 million, we screened local hospital admissions in 2010 using ICD-9 discharge codes 430-436, and performed chart review. Within the region are 15 adult acute care hospitals, all of which are covered by the same stroke team for clinical care and trial enrollment. Medical eligibility, the number of eligible patients/total number of patients, was calculated for the IMS-III trial and the CLEAR-ER trials using their inclusion/exclusion criteria. The number of patients enrolled in the trial per month of open enrollment was determined for each hospital. Statistical analysis included paired signed rank test and regression. Results: In 2010, 2035 ischemic strokes (IS) were hospitalized in the region. Regional medical eligibility was 1.7% for IMS III and 4.5% for CLEARER (p=0.001), overall regional hospital enrollment/month was 0.81 for IMS III and 1.84 for CLEAR-ER (p=0.001). Eligibility rates per hospital ranged from 0-9.5%, and recruitment rates per hospital/mo ranged from 0-0.38. Hospital-level eligibility and recruitment rates were significantly correlated (see figure for both trials combined, adjusted r2 = 0.57, p<0.001.) Discussion: Within our population, medical eligibility explained 57% of the variability in hospital-level enrollment rates for two acute IS trials. The use of population-based epidemiology in trial planning may identify optimal trial enrollment criteria, which must be weighed against proper patient selection. Many other factors impact enrollment rates, such as competing trials, which were not considered here. Further evaluation of our population-based eligibility rates in sites outside our region and with additional clinical trials is needed.

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.

5526 Background: HR-HPV DNA testing, with or without cervical cytology, provides excellent sensitivity for detection of cervical cancer (CC) and its precursors; negative test results indicate that risk of disease is extremely low and enable women to undergo reduced screening with safety. However, management of women who screen positive remains challenging as many will prove to have self-limited HR-HPV infections. DNA methylation is an early event in carcinogenesis that could enhance CC screening specificity. Methods: For discovery, DNA from 70 FFPE CC (36 squamous, 34 adenocarcinoma) tissues that were reviewed microscopically, 18 fresh frozen benign cervicovaginal (BCV) tissues collected at the time of benign hysterectomy, and 18 buffy coats from cancer-free women underwent reduced representation bisulfite sequencing (RRBS) to identify MDMs associated with CC. Candidate MDM selection was based on area under the receiver operating characteristic curve (AUC) discrimination, methylation fold change, and low background methylation among benign controls. Candidate MDMs were re-tested using methylation-specific PCR (MSP) to confirm performance. Blinded biological validation was performed using MSP on DNA extracted from independent FFPE CC (38 squamous, 43 adenocarcinoma) and BCV (40) tissues. The performance of CC MDMs was also tested in DNA extracted from cervical dysplasia (36 adenocarcinoma in situ (AIS), 32 cervical intraepithelial neoplasia (CIN) 2/3, 11 CIN 1) FFPE tissues. Results: From RRBS discovery and technical validation via MSP, 30 candidate MDMs showed marked methylation fold changes (10 to >1000) across both CC histologies compared to BCV tissue from cancer-free women. Each of the 30 MDMs highly discriminated CC from BCV tissue with 9 MDMs having an AUC >0.90 (Table). CC MDMs also highly discriminated AIS from BCV but did not perform well in CIN 2/3 and CIN 1 (Table). Conclusions: Whole methylome sequencing, stringent filtering criteria, and biological validation have yielded outstanding candidate MDMs for CC that highly discriminate CC from BCV, notably with high specificity. Performance in cervical dysplasias varied with higher positivity rates in AIS than in CIN 2/3 and CIN 1. Translation to testing these novel MDMs in lower genital tract biospecimens and the addition of HR-HPV to the CC panel are warranted.[Table: see text]

Background and Aims Recurrent primary sclerosing cholangitis (rPSC) following liver transplant (LT) has a negative impact on graft and patient survival; little is known about risk factors for rPSC or disease course in children. Approach and Results We retrospectively evaluated risk factors for rPSC in 140 children from the Pediatric PSC Consortium, a multicenter international registry. Recipients underwent LT for PSC and had >90 days of follow‐up. The primary outcome, rPSC, was defined using Graziadei criteria. Median follow‐up after LT was 3 years (interquartile range 1.1‐6.1). rPSC occurred in 36 children, representing 10% and 27% of the subjects at 2 years and 5 years following LT, respectively. Subjects with rPSC were younger at LT (12.9 vs. 16.2 years), had faster progression from PSC diagnosis to LT (2.5 vs. 4.1 years), and had higher alanine aminotransferase (112 vs. 66 IU/L) at LT (all P < 0.01). Inflammatory bowel disease was more prevalent in the rPSC group (86% vs. 66%; P = 0.025). After LT, rPSC subjects had more episodes of biopsy‐proved acute rejection (mean 3 vs. 1; P < 0.001), and higher prevalence of steroid‐refractory rejection (41% vs. 20%; P = 0.04). In those with rPSC, 43% developed complications of portal hypertension, were relisted for LT, or died within 2 years of the diagnosis. Mortality was higher in the rPSC group (11.1% vs. 2.9%; P = 0.05). Conclusions The incidence of rPSC in this cohort was higher than previously reported, and was associated with increased morbidity and mortality. Patients with rPSC appeared to have a more aggressive, immune‐reactive phenotype. These findings underscore the need to understand the immune mechanisms of rPSC, to lay the foundation for developing new therapies and improve outcomes in this challenging population.

Abstract Introduction Current non-invasive treatments for erectile dysfunction (ED) include oral medications, intracavernosal injections, and vacuum-assisted devices. Though these therapies work well for many, a subset of patients have contraindications or are unsatisfied with these options. Restorative therapies for ED are a new frontier of treatments focused on regenerating diseased tissue and providing a potential “cure” for ED. Aim The aim of this position statement is to examine existing clinical trial data for restorative therapies and identify elements that require further research before widespread adoption. Methods A literature review was performed to identify all clinical trials performed with regenerative therapy for ED. This includes treatments such as stem cell therapy (SCT), platelet rich plasma (PRP), and restorative related technologies like low-intensity shockwave therapy (LiSWT). Main Outcome Measures Most clinical trials in restorative therapies were assessed for safety, feasibility, or efficacy. This included recording adverse events, changes in sexual function and erectile function questionnaires, and diagnostics measures. Results To date there is an absence of robust clinical data supporting the efficacy of restorative therapies regarding ED, though technologies such as LiSWT have established relative safety. Conclusions Restorative therapies are a promising technology that represents a new frontier of treatment geared towards reversing disease pathology rather than just treating symptoms. However, current published clinical studies are limited. Future work needs to be adequately powered, multi-center, randomized, sham/placebo-controlled trials in well-characterized patient populations to ensure safety and demonstrate efficacy. Until these studies are done, restorative therapies should be reserved for clinical trials and not offered in routine clinical practice.