Normanalbrechtsen6494

To develop an image processing methodology for noninvasive three-dimensional (3D) quantification of microwave thermal ablation zones in vivo using x-ray computed tomography (CT) imaging without injection of a contrast enhancing material.

Six microwave (MW) thermal ablation procedures were performed in three pigs. The ablations were performed with a constant heating duration of 8min and power level of 30W. During the procedure images from sixty 1mm thick slices were acquired every 30s. At the end of all ablation procedures for each pig, a contrast-enhanced scan was acquired for reference. Special algorithms for addressing challenges stemming from the 3D in vivo setup and processing the acquired images were prepared. The algorithms first rearranged the data to account for the oblique needle orientation and for breathing motion. Then, the gray level variance changes were analyzed, and optical flow analysis was applied to the treated volume in order to obtain the ablation contours and reconstruct the ablationges listed above. Clinical implementation of the developed methodology could potentially provide real time noninvasive 3D accurate monitoring of MW thermal ablation in-vivo, provided that the radiation dose can be reduced.

The developed algorithms provide highly accurate detailed contours in vivo (average error less then 2.5 mm) and cope well with the challenges listed above. Clinical implementation of the developed methodology could potentially provide real time noninvasive 3D accurate monitoring of MW thermal ablation in-vivo, provided that the radiation dose can be reduced.Social networks can vary in their organization and dynamics, with implications for ecological and evolutionary processes. Understanding the mechanisms that drive social network dynamics requires integrating individual-level biology with comparisons across multiple social networks. Testosterone is a key mediator of vertebrate social behaviour and can influence how individuals interact with social partners. Although the effects of testosterone on individual behaviour are well established, no study has examined whether hormone-mediated behaviour can scale up to shape the emergent properties of social networks. We investigated the relationship between testosterone and social network dynamics in the wire-tailed manakin, a lekking bird species in which male-male social interactions form complex social networks. We used an automated proximity system to longitudinally monitor several leks and we quantified the social network structure at each lek. this website Our analysis examines three emergent properties of the networks-socialhitecture of social groups. Groups with high average testosterone exhibit social network properties that are predicted to impede the evolution of cooperation.Predicting oncologic outcome is challenging due to the diversity of cancer histologies and the complex network of underlying biological factors. In this study, we determine whether machine learning (ML) can extract meaningful associations between oncologic outcome and clinical trial, drug-related biomarker and molecular profile information. We analyzed therapeutic clinical trials corresponding to 1102 oncologic outcomes from 104 758 cancer patients with advanced colorectal adenocarcinoma, pancreatic adenocarcinoma, melanoma and nonsmall-cell lung cancer. For each intervention arm, a dataset with the following attributes was curated line of treatment, the number of cytotoxic chemotherapies, small-molecule inhibitors, or monoclonal antibody agents, drug class, molecular alteration status of the clinical arm's population, cancer type, probability of drug sensitivity (PDS) (integrating the status of genomic, transcriptomic and proteomic biomarkers in the population of interest) and outcome. A total of 467 progression-free survival (PFS) and 369 overall survival (OS) data points were used as training sets to build our ML (random forest) model. Cross-validation sets were used for PFS and OS, obtaining correlation coefficients (r) of 0.82 and 0.70, respectively (outcome vs model's parameters). A total of 156 PFS and 110 OS data points were used as test sets. The Spearman correlation (rs ) between predicted and actual outcomes was statistically significant (PFS rs = 0.879, OS rs = 0.878, P  less then  .0001). The better outcome arm was predicted in 81% (PFS N = 59/73, z = 5.24, P  less then  .0001) and 71% (OS N = 37/52, z = 2.91, P = .004) of randomized trials. The success of our algorithm to predict clinical outcome may be exploitable as a model to optimize clinical trial design with pharmaceutical agents.The contribution of positional asphyxia in opioid-related deaths is currently unknown. Diagnostic criteria for positional asphyxia include finding the decedent in a position that does not allow for adequate respiration and an inability to extricate themselves from the position due to various conditions. Our primary objective was to assess whether positional asphyxia and the resulting airway compromise were a contributing factor to death due to the toxic effects of opioids. We evaluated 225 deaths where the death scene investigation contained adequate information to evaluate for positional asphyxia and performed a Pearson chi-square test to determine if the proportion of deaths found in an airway compromising position was higher when opioid(s) caused the death. The proportion of decedents found in a potential airway compromising position was greater when the death was related to opioid use (p less then 0.0001). Further, narrowing the dataset to decedents who were definitely in an airway compromising position [Yes (24.49%) vs. No (11.02%)] showed a statistically significant association between positional asphyxia and deaths related to opioid use (p = 0.0021). Carefully documenting the position in which the decedent was initially found may be a significant factor in accurate reporting and in harm reduction efforts to decrease the opioid mortality rate.

As per the eighth edition of the American Joint Committee on Cancer (AJCC) staging system for differentiated thyroid carcinoma (DTC), minimal extrathyroidal extension (mETE) has been removed. Instead, gross ETE (gETE) invading only strap muscles has been designated as a new T3b category. Our objective was to investigate the impact of the T3b category on survival in order to establish its prognostic value in DTC.

In this retrospective study, we included patients who had undergone thyroidectomy between 2004 and 2012. Data from the Surveillance, Epidemiology and End Results (SEER) database were examined.

We used the Kaplan-Meier method and log-rank test to analyse overall survival (OS) and cancer-specific survival (CSS). The effect of potential predictors associated with survival were estimated using the Cox regression model. To minimize selection bias, propensity-score matching (PSM) was performed.

A total of 63315 patients were included in our study. During the average follow-up duration of nearly 78months, significant differences were observed in cancer-specific survival among patients with no ETE, mETE, gETE invading only strap muscles (T3b) and gETE invading perithyroidal structures other than strap muscles (T4) (P<.