Automated chest CT three-dimensional quantification of body composition: adipose tissue and paravertebral muscle.

This retrospective study developed an automated algorithm for 3D segmentation of adipose tissue and paravertebral muscle on chest CT using artificial intelligence (AI) and assessed its feasibility. The study included patients from the Boston Lung Cancer Study (2000-2011). For adipose tissue quantification, 77 patients were included, while 245 were used for muscle quantification.

Leveraging Deep Learning of Chest Radiograph Images to Identify Individuals at High Risk for Chronic Obstructive Pulmonary Disease.

Background: This study assessed whether deep learning applied to routine outpatient chest X-rays (CXRs) can identify individuals at high risk for incident chronic obstructive pulmonary disease (COPD).

Methods: Using cancer screening trial data, we previously developed a convolutional neural network (CXR-Lung-Risk) to predict lung-related mortality from a CXR image. In this study, we externally validated CXR-Lung-Risk to predict incident COPD from routine CXRs.

Ambient beta particle radioactivity and lung cancer survival: Results from the Boston Lung Cancer Study.

Background: Exposure to ionizing radiation is known to increase the risk of lung cancer. However, studies on the effect of environmental radiation associated with ambient particle air pollution on lung cancer survival are limited. We investigated the association between ambient beta particle radioactivity (PR-β) after a diagnosis and lung cancer survivals.

Arsenic exposure is associated with elevated sweat chloride concentration and airflow obstruction among adults in Bangladesh: a cross sectional study.

Arsenic is associated with lung disease and experimental models suggest that arsenic-induced degradation of the chloride channel CFTR (cystic fibrosis transmembrane conductance regulator) is a mechanism of arsenic toxicity. We examined associations between arsenic exposure, sweat chloride concentration (measure of CFTR function), and pulmonary function among 285 adults in Bangladesh. Participants with sweat chloride ≥ 60 mmol/L had higher arsenic exposures than those with sweat chloride < 60 mmol/L (water: median 77.

Potentially functional variants of PARK7 and DDR2 in ferroptosis-related genes predict survival of non-small cell lung cancer patients.

Ferroptosis, a form of regulated cell death, is characterized by iron-dependent lipid peroxidation. It is recognized increasingly for its pivotal role in both cancer development and the response to cancer treatments. We assessed associations between 370,027 single-nucleotide polymorphisms (SNPs) within 467 ferroptosis-related genes and survival of non-small cell lung cancer (NSCLC) patients.

Arsenic exposure and measures of glucose tolerance in Bangladeshi adults: A cross-sectional study.

Background: Arsenic has been associated with diabetes and impaired glucose tolerance in many studies, although some reports have shown null findings.

Methods: We conducted a cross-sectional study among 300 adults in Bangladesh. Participants were randomly selected from a roster of 1800 people who previously participated in studies of arsenic and skin lesions.

ARTEMIS: An independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions.

Introduction: Breast cancer, a heterogeneous disease, is influenced by multiple genetic and epigenetic factors. The majority of prognostic models for breast cancer focus merely on the main effects of predictors, disregarding the crucial impacts of gene-gene interactions on prognosis.

Objectives: Using DNA methylation data derived from nine independent breast cancer cohorts, we developed an independently validated prognostic prediction model of breast cancer incorporating epigenetic biomarkers with main effects and gene-gene interactions (ARTEMIS) with an innovative 3-D modeling strategy.

Vaping habits and respiratory symptoms using a smartphone app platform.

Background: Widespread use of e-cigarette (EC) or vaping products causes respiratory disorders including the nationwide outbreak of e-cigarette or vaping product use-associated lung injury (EVALI) in 2019. Chronic adverse health effects are now being reported as well. To address this important public health issue, an innovative approach of epidemic control and epidemiologic study is required.

Assessing the prognostic utility of clinical and radiomic features for COVID-19 patients admitted to ICU: challenges and lessons learned.

Severe cases of COVID-19 often necessitate escalation to the Intensive Care Unit (ICU), where patients may face grave outcomes, including mortality. Chest X-rays play a crucial role in the diagnostic process for evaluating COVID-19 patients. Our collaborative efforts with Michigan Medicine in monitoring patient outcomes within the ICU have motivated us to investigate the potential advantages of incorporating clinical information and chest X-ray images for predicting patient outcomes.

Ambient PM temporal variation and source apportionment in Mbarara, Uganda.

Air pollution is the leading environmental cause of death globally, and most mortality occurs in resource-limited settings such as sub-Saharan Africa. The African continent experiences some of the worst ambient air pollution in the world, yet there are relatively little African data characterizing ambient pollutant levels and source admixtures. In Uganda, ambient PM levels exceed international health standards.

Additional impact of genetic ancestry over race/ethnicity to prevalence of KRAS mutations and allele-specific subtypes in non-small cell lung cancer.

The KRAS mutation is the most common oncogenic driver in patients with non-small cell lung cancer (NSCLC). However, a detailed understanding of how self-reported race and/or ethnicity (SIRE), genetically inferred ancestry (GIA), and their interaction affect KRAS mutation is largely unknown. Here, we investigated the associations between SIRE, quantitative GIA, and KRAS mutation and its allele-specific subtypes in a multi-ethnic cohort of 3,918 patients from the Boston Lung Cancer Survival cohort and the Chinese OrigiMed cohort with an independent validation cohort of 1,450 patients with NSCLC.

Serial platelet count as a dynamic prediction marker of hospital mortality among septic patients.

Background: Platelets play a critical role in hemostasis and inflammatory diseases. Low platelet count and activity have been reported to be associated with unfavorable prognosis. This study aims to explore the relationship between dynamics in platelet count and in-hospital morality among septic patients and to provide real-time updates on mortality risk to achieve dynamic prediction.

Arsenic modifies the effect of folic acid in spina bifida prevention, a large hospital-based case-control study in Bangladesh.

Background: Spina bifida, a developmental malformation of the spinal cord, is associated with high rates of mortality and disability. Although folic acid-based preventive strategies have been successful in reducing rates of spina bifida, some areas continue to be at higher risk because of chemical exposures. Bangladesh has high arsenic exposures through contaminated drinking water and high rates of spina bifida.

Lung cancer clustering by identification of similarities and discrepancies of DNA copy numbers using maximal information coefficient.

Lung cancer is the second most diagnosed cancer and the first cause of cancer related death for men and women in the United States. Early detection is essential as patient survival is not optimal and recurrence rate is high. Copy number (CN) changes in cancer populations have been broadly investigated to identify CN gains and deletions associated with the cancer.