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The American Association of Physicists in Medicine began the Medical Physics Leadership Academy Journal Club in the fall of 2020. The initiative was launched to provide a forum for medical physicists to learn about leadership topics using published material, discuss and reflect on the material, and consider incorporating the discussed skills into their professional practice. This report presents the framework for the MPLA Journal Club program, describes the lessons learned over the last 2 years, summarizes the data collected from attendees, and highlights the roadmap for the program moving forward.

Characterizing the interplay between exposures shaping the human exposome is vital for uncovering the etiology of complex diseases. For example, cancer risk is modified by a range of multifactorial external environmental exposures. Environmental, socioeconomic, and lifestyle factors all shape lung cancer risk. However, epidemiological studies of radon aimed at identifying populations at high risk for lung cancer often fail to consider multiple exposures simultaneously. For example, moderating factors, such as PM2.5, may affect the transport of radon progeny to lung tissue. This ecological analysis leveraged a population-level dataset from the National Cancer Institute's Surveillance, Epidemiology, and End-Results data (2013–17) to simultaneously investigate the effect of multiple sources of low-dose radiation (gross γ activity and indoor radon) and PM2.5 on lung cancer incidence rates in the USA. County-level factors (environmental, sociodemographic, lifestyle) were controlled for, and Poisson regression and random forest models were used to assess the association between radon exposure and lung and bronchus cancer incidence rates. Tree-based machine learning (ML) method perform better than traditional regression: Poisson regression: 6.29/7.13 (mean absolute percentage error, MAPE), 12.70/12.77 (root mean square error, RMSE); Poisson random forest regression: 1.22/1.16 (MAPE), 8.01/8.15 (RMSE). The effect of PM2.5 increased with the concentration of environmental radon, thereby confirming findings from previous studies that investigated the possible synergistic effect of radon and PM2.5 on health outcomes. In summary, the results demonstrated (1) a need to consider multiple environmental exposures when assessing radon exposure's association with lung cancer risk, thereby highlighting (1) the importance of an exposomics framework and (2) that employing ML models may capture the complex interplay between environmental exposures and health, as in the case of indoor radon exposure and lung cancer incidence. [ABSTRACT FROM AUTHOR]

In our attempt to comprehensively understand the nature of association of variants at 11q23.3 apolipoprotein gene cluster region, we genotyped a prioritized set of 96 informative SNPs using Fluidigm customized SNP genotyping platform in a sample of 508 coronary artery disease (CAD) cases and 516 controls. We found 12 SNPs as significantly associated with CAD at P

Fifty-eight percent of respondents to KPMG's 2020 Healthcare and Life Sciences Investment Outlook expect to see an increase in deal volume this year compared to 2019. Investment activity will continue [...]

Neutron stimulated emission computed tomography (NSECT) is being developed as a non-invasive spectroscopic imaging technique to determine element concentrations in the human body. NSECT uses a beam of fast neutrons that scatter inelastically from atomic nuclei in tissue, causing them to emit characteristic gamma photons that are detected and identified using an energy-sensitive gamma detector. By measuring the energy and number of emitted gamma photons, the system can determine the elemental composition of the target tissue. Such determination is useful in detecting several disorders in the human body that are characterized by changes in element concentration, such as breast cancer. In this paper we describe our experimental implementation of a prototype NSECT system for the diagnosis of breast cancer and present experimental results from sensitivity studies using this prototype. Results are shown from three sets of samples: (a) excised breast tissue samples with unknown element concentrations, (b) a multi-element calibration sample used for sensitivity studies, and (c) a small-animal specimen, to demonstrate detection ability from in-vivo tissue. Preliminary results show that NSECT has the potential to detect elements in breast tissue. Several elements were identified common to both benign and malignant samples, which were confirmed through neutron activation analysis (NAA). Statistically significant differences were seen for peaks at energies corresponding to [sup.37]Cl, [sup.56]Fe, [sup.58]Ni, [sup.59]Co, [sup.66]Zn, [sup.79]Br and [sup.87]Rb. The spectrum from the small animal specimen showed the presence of [sup.12]C from tissue, [sup.40]Ca from bone, and elements [sup.39]K, [sup.27]Al, [sup.37]Cl, [sup.56]Fe, [sup.68]Zn and [sup.25]Mg. Threshold sensitivity for the four elements analyzed was found to range from 0.3 grams to 1 gram, which is higher than the microgram sensitivity required for cancer detection. Patient dose levels from NSECT were found to be comparable to those of screening mammography. Index Terms--Breast cancer detection, gamma-ray spectroscopy, neutron, NSECT, tomography.