Purpose: Radiomics is the extraction of multidimensional imaging features, which when correlated with genomics, is termed radiogenomics. However, radiogenomic biological validation is not sufficiently described in the literature. We seek to establish causality between differential gene expression status and MRI-extracted radiomic-features in glioblastoma.Experimental Design: Radiogenomic predictions and validation were done using the Cancer Genome Atlas and Repository of Molecular Brain Neoplasia Data glioblastoma patients (n = 93) and orthotopic xenografts (OX; n = 40). Tumor phenotypes were segmented, and radiomic-features extracted using the developed radiome-sequencing pipeline. Patients and animals were dichotomized on the basis of Periostin (POSTN) expression levels. RNA and protein levels confirmed RNAi-mediated POSTN knockdown in OX. Total RNA of tumor cells isolated from mouse brains (knockdown and control) was used for microarray-based expression profiling. Radiomic-features were utilized to predict POSTN expression status in patient, mouse, and interspecies.Results: Our robust pipeline consists of segmentation, radiomic-feature extraction, feature normalization/selection, and predictive modeling. The combination of skull stripping, brain-tissue focused normalization, and patient-specific normalization are unique to this study, providing comparable cross-platform, cross-institution radiomic features. POSTN expression status was not associated with qualitative or volumetric MRI parameters. Radiomic features significantly predicted POSTN expression status in patients (AUC: 76.56%; sensitivity/specificity: 73.91/78.26%) and OX (AUC: 92.26%; sensitivity/specificity: 92.86%/91.67%). Furthermore, radiomic features in OX were significantly associated with patients with similar POSTN expression levels (AUC: 93.36%; sensitivity/specificity: 82.61%/95.74%; P = 02.021E−15).Conclusions: We determined causality between radiomic texture features and POSTN expression levels in a preclinical model with clinical validation. Our biologically validated radiomic pipeline also showed the potential application for human–mouse matched coclinical trials.

Purpose of review: Optimal treatment requires a thorough understanding of all factors contributing to pain in the individual patient. In this review, we investigate the influence of cultural frameworks on pain experience and management. Recent Findings: The loosely defined concept of culture in pain management integrates a predisposing set of diverse biological, psychological and social characteristics shared within a group. Cultural and ethnic background strongly influence the perception, manifestation, and management of pain. In addition, cultural, racial and ethnic differences continue to play a major role in the disparate treatment of acute pain. Summary: A holistic and culturally sensitive approach is likely to improve pain management outcomes, will better cover the needs of diverse patient populations and help reduce stigma and health disparities. Mainstays include awareness, self-awareness, appropriate communication, and training.

BACKGROUND: Health care worker (HCW) safety is of pivotal importance during a pandemic such as coronavirus disease 2019 (COVID-19), and employee health and well-being ensure functionality of health care institutions. This is particularly true for an intensive care unit (ICU), where highly specialized staff cannot be readily replaced. In the light of lacking evidence for optimal staffing models in a pandemic, we hypothesized that staff shortage can be reduced when staff scheduling takes the epidemiology of a disease into account. METHODS: Various staffing models were constructed, and comprehensive statistical modeling was performed. A typical routine staffing model was defined that assumed full-time employment (40 h/wk) in a 40-bed ICU with a 2:1 patient-to-staff ratio. A pandemic model assumed that staff worked 12-hour shifts for 7 days every other week. Potential in-hospital staff infections were simulated for a total period of 120 days, with a probability of 10%, 25%, and 40% being infected per week when at work. Simulations included the probability of infection at work for a given week, of fatality after infection, and the quarantine time, if infected. RESULTS: Pandemic-adjusted staffing significantly reduced workforce shortage, and the effect progressively increased as the probability of infection increased. Maximum effects were observed at week 4 for each infection probability with a 17%, 32%, and 38% staffing reduction for an infection probability of 0.10, 0.25, and 0.40, respectively. CONCLUSIONS: Staffing along epidemiologic considerations may reduce HCW shortage by leveling the nadir of affected workforce. Although this requires considerable efforts and commitment of staff, it may be essential in an effort to best maintain staff health and operational functionality of health care facilities and systems.

The current COVID-19 pandemic is testing political leaders and healthcare systems worldwide, exposing deficits in crisis communication, leadership, preparedness and flexibility. Extraordinary situations abound, with global supply chains suddenly failing, media communicating contradictory information, and politics playing an increasingly bigger role in shaping each country's response to the crisis. The pandemic threatens not just our health but also our economy, liberty, and privacy. It challenges the speed at which we work, the quality of our research, and the effectiveness of communication within the scientific community. It can impose ethical dilemmas and emotional stress on healthcare workers. Nevertheless, the pandemic also provides an opportunity for healthcare organizations, leaders, and researchers to learn from their mistakes and to place their countries and institutions in a better position to face future challenges.

Purpose of Review: We review the relevance of quantitative sensory testing (QST) in light of acute and chronic postoperative pain and associated challenges. Recent Findings: Predicting the occurrence of acute and chronic postoperative pain with QST can help identify patients at risk and allows proactive preventive management. Generally, central QST testing, such as temporal summation of pain (TSP) and conditioned pain modulation (CPM), appear to be the most promising modalities for reliable prediction of postoperative pain by QST. Overall, QST testing has the best predictive value in patients undergoing orthopedic procedures. Summary: Current evidence underlines the potential of preoperative QST to predict postoperative pain in patients undergoing elective surgery. Implementing QST in routine preoperative screening can help advancing traditional pain therapy toward personalized perioperative pain medicine.