Citations

Introduction: The composition of acute ischemic stroke (AIS) blood clots can impact their successful removal via endovascular therapy. Identification of the clot composition prior to endovascular treatment may influence the optimal treatment strategy. In this study, we aimed to investigate the relationship between the Hounsfield Unit intensity on CT and machine-learned characterization of clot composition. Methods: Prior to endovascular treatment, each patient had a non-contrast CT performed. Histopathological analysis of the clots was performed and clot composition was quantified via standard thresholding techniques using Adobe Photoshop. In addition, following representative cell labeling by an expert pathologist, image segmentation algorithms (Orbital Image Analysis, Actelion Ltd.) were trained on each case to quantify composition by cell type. The clots were categorized into 3 groups: red blood cell (RBC) dominant (>50%), RBC proportion equal to fibrin and fibrin dominant (>50%). Correlations between clot composition and Hounsfield Units (HU) density on CT were assessed. A positive Hyperdense Artery Sign was defined as ≥50 HU. Results: Twenty patients were included in the study. There was a significant correlation between clots quantified using Adobe Photoshop Image-Pro and Orbit image analysis ( ρ = 0.837, p < 0.001). A significant relationship was found between clot composition and the presence of a HAS sign, ( X 2 (2) = 6.496, p = 0.039). There is a significant positive correlation between percentage of RBC in the clot and the presence of a HAS sign ( ρ = 0.632, p = 0.002**). There is also a significant positive correlation between the presence of fibrin-rich and the absence of a HAS sign ( ρ = 0.600, p = 0.004**). Conclusion: Machine learning software can accurately quantify AIS clot composition. The Hounsfield unit density of an AIS clot on a non-contrast CT correlates with the composition of the clot. Measuring the HU of the clot on CT prior to endovascular intervention may inform the clinician of the clot type and help to determine the most appropriate treatment strategy for that clot.

Background Chronic kidney disease ( CKD ) is a common comorbidity in patients with atrial fibrillation. The presence of CKD complicates drug selection for stroke prevention and rhythm control. Methods and Results Patients enrolled in ORBIT AF (Outcomes Registry for Better Informed Treatment of Atrial Fibrillation) with baseline renal function and follow‐up data were included (N=9019). CKD was defined as an estimated creatinine clearance <60 mL /min. Patient characteristics were compared by CKD status, and Cox proportional hazards modeling was used to examine the association between oral anticoagulant ( OAC ) use and outcomes and antiarrhythmic drug use and outcomes stratified by CKD stages. At enrollment, 3490 (39%) patients had an estimated creatinine clearance <60 mL /min. Patients with CKD were older and had higher CHA 2 DS 2 VAS c and Anticoagulant and Risk Factors in Atrial Fibrillation (ATRIA) scores. A rhythm control strategy was selected less frequently in patients with CKD , while OAC use was lower among Stage IV and V CKD patients. After adjustment, no significant interaction was noted for OAC and CKD on all‐cause mortality ( P =0.5442) or cardiovascular death ( P =0.1233), although a trend for increased major bleeding ( P =0.0608) and stroke, systemic embolism or transient ischemic attack ( P =0.0671) was observed. No interaction was noted for antiarrhythmic drug use and CKD status on all‐cause mortality ( P =0.9706), or stroke, systemic embolism or transient ischemic attack ( P =0.4218). Conclusions Patients with atrial fibrillation and CKD are less likely to be treated with rhythm control. Patients with advanced CKD are less likely to receive OAC . Finally, outcomes with OAC in patients with advanced CKD may be materially different with higher rates of both bleeding and stroke.

Abstract Several concepts, which in the aggregate get might be used to account for “resilience” against age‐ and disease‐related changes, have been the subject of much research. These include brain reserve, cognitive reserve, and brain maintenance. However, different investigators have use these terms in different ways, and there has never been an attempt to arrive at consensus on the definition of these concepts. Furthermore, there has been confusion regarding the measurement of these constructs and the appropriate ways to apply them to research. Therefore the reserve, resilience, and protective factors professional interest area, established under the auspices of the Alzheimer's Association, established a whitepaper workgroup to develop consensus definitions for cognitive reserve, brain reserve, and brain maintenance. The workgroup also evaluated measures that have been used to implement these concepts in research settings and developed guidelines for research that explores or utilizes these concepts. The workgroup hopes that this whitepaper will form a reference point for researchers in this area and facilitate research by supplying a common language.

11559 Background: Paraneoplastic neurologic disease (PND) is an aberrant immune-mediated response against the nervous system triggered by occult malignancy. Given the rarity of this disease, a paucity of data exists describing breast cancer (BC)-related PND; thus, we sought to further examine this specific population of patients. Methods: Using an institution specific clinical search tool, we identified all patients at our institution from 1997-2016 with a diagnosis of BC-related PND, verified by an international expert. Retrospective review was used to record tumor and treatment factors associated with PND and BC. A descriptive analysis was performed of the characteristics associated with BC-related PND. Results: BC-related PND was diagnosed in 58 female patients. Average age at BC diagnosis was 54.0±10.3 years. Most had invasive cancer of Stage II or higher [Stage 0 (10.3%), I (10.3%), II (44.8%), III (13.8%), IV (6.9%), unknown (13.8%)]. Most patients were hormone receptor (HR)+ (63.8%), while 4 (6.9%) were HR-, and 17 (29.3%) were unknown. Of the 34 patients where Her2/neu (Her2) data was available, 7 (20.6%) were Her2+ and 27 (79.4%) were Her2-. The majority (62.1%) had neurological symptoms prior to BC, 5.2% were concurrent, and 32.7% developed PND after initial BC. The interquartile range for time from PND to BC diagnosis was -8.5 to 10.5 months. Of the 58 patients, 29 (50%) had autoantibodies detected: Purkinje Cell Cytoplasmic Autoantibody Type-1 (PCA-1[anti-Yo]) (10), amphiphysin-IgG (n = 9), Anti-Neuronal Nuclear Autoantibody Type-2 (ANNA-2[anti-Ri]) (n = 5), and other (n = 5). The most common syndromes were cerebellar ataxia (n = 14), myelopathy (n = 11), and myopathy (n = 11). Immunotherapy was used for PND in 53 of 58 (91.4%) patients; benefit from immunotherapy was assessed as complete 0 (0%), robust 11 (20.8%), mild to moderate 28 (52.8%), none 9 (17%), and indeterminate 5 (9.4%). Conclusions: BC-related PND is rare, with only 58 cases over 20 years at a large academic institution. Paraneoplastic symptoms often present prior to BC diagnosis and BC characteristics are typical of the general population. Over 75% of patients benefit from immunotherapy. These data may provide helpful information to providers treating this population of patients.