Recent results of the searches for Supersymmetry in final states with one or two leptons at CMS are presented. Many Supersymmetry scenarios, including the Constrained Minimal Supersymmetric extension of the Standard Model (CMSSM), predict a substantial amount of events containing leptons, while the largest fraction of Standard Model background events -which are QCD interactions -gets strongly reduced by requiring isolated leptons. The analyzed data was taken in 2011 and corresponds to an integrated luminosity of approximately L = 1 fb −1 . The center-of-mass energy of the pp collisions was √ s = 7 TeV.

Background This study retrospectively evaluated the capability of computed-tomography (CT) based radiomic features to predict EGFR mutation status in surgically-resected peripheral lung adenocarcinomas in an Asian cohort of patients. Materials and Methods 298 patients with surgically resected peripheral lung adenocarcinomas were investigated in this institutional review board-approved retrospective study with waived consent. 219 quantitative 3D features were extracted from segmented volumes of each tumor, and 59 of these which were considered as independent features were included in the analysis. Clinical and pathological information were obtained from the institutional database. Results Mutant EGFR was significantly associated with female gender (p=0.0005); never smoker status (p<0.0001), lepidic predominant adenocarcinomas (p=0.017), and low or intermediate pathologic grade (p=0.0002). Statistically significant differences were found in 11 radiomic features between EGFR mutant and wild type groups on univariate analysis. Mutant EGFR status could be predicted by a set of five radiomic features that fall in three broad groups: CT attenuation energy, tumor main direction and texture defined by wavelets and Laws (AUC 0.647). Multiple logistic regression model showed that adding radiomic features to a clinical model resulted in a significant improvement of predicting power, as the AUC increased from 0.667 to 0.709 (p<0.0001). Conclusions CT based radiomic features of peripheral lung adenocarcinomas can capture useful information regarding tumor phenotype, and the model we built can be useful to predict the presence of EGFR mutations in peripheral lung adenocarcinoma in Asian patients when mutational profiling is not available or possible.

PURPOSE Determine if quantitative analyses (“radiomics”) of low dose CT lung cancer screening images at baseline can predict subsequent emergence of cancer. PATIENTS AND METHODS Public data from the National Lung Screening Trial (ACRIN 6684) were assembled into two cohorts of 104 and 92 patients with screen detected lung cancer (SDLC), then matched to cohorts of 208 and 196 screening subjects with benign pulmonary nodules (bPN). Image features were extracted from each nodule and used to predict the subsequent emergence of cancer. RESULTS The best models used 23 stable features in a Random Forest classifier, and could predict nodules that will become cancerous 1 and 2 years hence with accuracies of 80% (AUC 0.83) and 79% (AUC 0.75), respectively. Radiomics outperformed Lung-RADS and volume. McWilliams’ risk assessment model was commensurate. CONCLUSION Radiomics of lung cancer screening CTs at baseline can be used to assess risk for development of cancer.

Purpose:To investigate the intersession reliability of selected kinematic and kinetic variables during countermovement vertical jumps (CMJs).Methods:Thirty-five men and 35 women performed CMJs on a force platform during four testing sessions each separated by 1 wk. Kinematic variables included time in the air (TIA), take-off velocity (TOV), total vertical displacement of the center of mass (TJH). and countermovement depth, whereas kinetic variables included positive impulse, negative impulse, vertical stiffness, and rates of force development. Systematic bias was assessed by calculating the 90% confidence interval of the change in the mean between consecutive testing sessions and between the first and final testing session for each variable. Coefficients of variation (CV) and intraclass correlation coefficients (ICC) were also calculated.Results:Systematic bias was observed only for peak rate of force development during the concentric phase of the movement. For TIA, TOV, and TJH, CV values ranged from 1.7% to 6.6%, with ICC values ranging from 0.82 to 0.97. The other variables showed greater variation (CV range: 1.7% to 39.9%; ICC range: 0.04 to 0.99). Only slight gender differences were found in the reliability statistics, and the reliability of most of the variables was diminished as the time between the testing sessions was increased.Conclusion:Even though practitioners can expect good reliability for jump height measured from a force platform in men and women, other kinematic and kinetic variables often assessed during vertical jumps may not be reliable.

Purpose To investigate whether imaging features from pre-treatment planning CT scans are associated with overall survival (OS), recurrence-free survival (RFS), and loco-regional recurrence-free survival (LR-RFS) after stereotactic body radiotherapy (SBRT) among non-small-cell lung cancer (NSCLC) patients. Patients and methods A total of 92 patients (median age: 73 years) with stage I or IIA NSCLC were qualified for this study. A total dose of 50 Gy in 5 fractions was the standard treatment. Besides clinical characteristics, 24 “semantic” image features were manually scored based on a point scale (up to 5) and 219 computer-derived “radiomic” features were extracted based on whole tumor segmentation. Statistical analysis was performed using Cox proportional hazards model and Harrell’s C-index, and the robustness of final prognostic model was assessed using ten-fold cross validation by dichotomizing patients according to the survival or recurrence status at 24 months. Results Two-year OS, RFS and LR-RFS were 69.95%, 41.3% and 51.85%, respectively. There was an improvement of Harrell’s C-index when adding imaging features to a clinical model. The model for OS contained the Eastern Cooperative Oncology Group (ECOG) performance status (Hazard Ratio [HR] = 2.78, 95% Confidence Interval [CI]: 1.37 – 5.65), pleural retraction (HR = 0.27, 95% CI: 0.08 – 0.92), F2 (short axis × longest diameter, HR = 1.72, 95% CI: 1.21 – 2.44) and F186 (Hist-Energy-L1, HR = 1.27, 95% CI: 1.00 - 1.61); The prognostic model for RFS contained vessel attachment (HR = 2.13, 95% CI: 1.24 – 3.64) and F2 (HR = 1.69, 95% CI: 1.33 – 2.15); and the model for LR-RFS contained the ECOG performance status (HR = 2.01, 95% CI: 1.12 – 3.60) and F2 (HR = 1.67, 95% CI: 1.29 – 2.18). Conclusions Imaging features derived from planning CT demonstrate prognostic value for recurrence following SBRT treatment, and might be helpful in patient stratification.