Neuroimaging feature extraction using a neural network classifier for imaging genetics.

Background: Dealing with the high dimension of both neuroimaging data and genetic data is a difficult problem in the association of genetic data to neuroimaging. In this article, we tackle the latter problem with an eye toward developing solutions that are relevant for disease prediction. Supported by a vast literature on the predictive power of neural networks, our proposed solution uses neural networks to extract from neuroimaging data features that are relevant for predicting Alzheimer's Disease (AD) for subsequent relation to genetics.

Investigating the relationship between the Bayes factor and the separation of credible intervals.

We examined the relationship between the Bayes factor and the separation of credible intervals in between- and within-subject designs under a range of effect and sample sizes. For the within-subject case, we considered five intervals: (1) the within-subject confidence interval of Loftus and Masson (1994); (2) the within-subject Bayesian interval developed by Nathoo et al. (2018), whose derivation conditions on estimated random effects; (3) and (4) two modifications of (2) based on a proposal by Heck (2019) to allow for shrinkage and account for uncertainty in the estimation of random effects; and (5) the standard Bayesian highest-density interval.

CD8 + T cell infiltration is associated with improved survival and negatively correlates with hypoxia in clear cell ovarian cancer.

Unlike other histological types of epithelial ovarian carcinoma, clear cell ovarian carcinoma (CCOC) has poor response to therapy. In many other carcinomas, expression of the hypoxia-related enzyme Carbonic anhydrase IX (CAIX) by cancer cells is associated with poor prognosis, while the presence of CD8 + tumor-infiltrating lymphocytes (TIL) is positively prognostic. We employed [F]EF5-PET/CT imaging, transcriptome profiling, and spatially-resolved histological analysis to evaluate relationships between CAIX, CD8, and survival in CCOC.

Improving Rates of Germline Mutation Testing for Patients With Ovarian Cancer in Vancouver Island, British Columbia, Canada.

Purpose: Despite more than a decade of endorsement from multiple international cancer authorities advocating all women with ovarian cancer be offered germline breast cancer () gene testing, British Columbia Cancer Victoria was not meeting this target. A quality improvement project was undertaken with the aim of increasing completed testing rates for all eligible patients seen at British Columbia Cancer Victoria to > 90% by 1 year from April 2016.

Methods: A current state analysis was completed, and multiple change ideas were developed, including education of medical oncologists, referral process update, initiating a group consenting seminar, and engagement of a nurse practitioner to lead the seminar.