Biomass fuels (wood) are commonly used indoors in underventilated environments for cooking in the developing world, but the impact on lung physiology is poorly understood. Quantitative computed tomography (qCT) can provide sensitive metrics to compare the lungs of women cooking with wood vs. liquified petroleum gas (LPG). We prospectively assessed (qCT and spirometry) 23 primary female cooks (18 biomass, 5 LPG) with no history of cardiopulmonary disease in Thanjavur, India. CT was obtained at coached total lung capacity (TLC) and residual volume (RV). qCT assessment included texture-derived ground glass opacity [GGO: Adaptive Multiple Feature Method (AMFM)], air-trapping (expiratory voxels ≤ -856HU) and image registration-based assessment [Disease Probability Measure (DPM)] of emphysema, functional small airways disease (%AirTrap), and regional lung mechanics. In addition, within-kitchen exposure assessments included particulate matter <2.5 μm(PM), black carbon, β-(1, 3)-d-glucan (surrogate for fungi), and endotoxin. Air-trapping went undetected at RV via the threshold-based measure (voxels ≤ -856HU), possibly due to density shifts in the presence of inflammation. However, DPM, utilizing image-matching, demonstrated significant air-trapping in biomass vs. LPG cooks ( = 0.049). A subset of biomass cooks (6/18), identified using k-means clustering, had markedly altered DPM-metrics: greater air-trapping ( < 0.001), lower TLC-RV volume change ( < 0.001), a lower mean anisotropic deformation index (ADI; < 0.001), and elevated % GGO ( < 0.02). Across all subjects, a texture measure of bronchovascular bundles was correlated to the log-transformed β-(1, 3)-d-glucan concentration ( = 0.026, = 0.46), and black carbon ( = 0.04, = 0.44). This pilot study identified environmental links with qCT-based lung pathologies and a cluster of biomass cooks (33%) with significant small airways disease. Quantitative computed tomography has identified a cluster of women (33%) cooking with biomass fuels (wood) with image-based markers of functional small airways disease and associated alterations in regional lung mechanics. Texture and image registration-based metrics of lung function may allow for early detection of potential inflammatory processes that may arise in response to inhaled biomass smoke, and help identify phenotypes of chronic lung disease prevalent in nonsmoking women in the developing world.
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http://dx.doi.org/10.1152/japplphysiol.00286.2022 | DOI Listing |
Sci Rep
December 2024
Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
View Article and Find Full Text PDFJTO Clin Res Rep
December 2024
Mayo Clinic, Rochester, Minnesota.
Introduction: The spatially complex nature of mesothelioma and interventions like pleurodesis, surgery, and radiation often complicate imaging-based assessment. Further, cell-free DNA (cfDNA) based monitoring strategies are inadequate for mesothelioma, given the presence of a few recurring nonsynonymous somatic variants. However, patient-specific chromosomal rearrangements are commonly found in mesothelioma.
View Article and Find Full Text PDFJTO Clin Res Rep
December 2024
Department of Pulmonary Diseases, GROW Research Institute for Oncology and Reproduction, Maastricht University Medical Center+, Maastricht, The Netherlands.
This review discusses the current data on predictive and prognostic biomarkers in oligometastatic NSCLC and discusses whether biomarkers identified in other stages and widespread metastatic disease can be extrapolated to the oligometastatic disease (OMD) setting. Research is underway to explore the prognostic and predictive value of biological attributes of tumor tissue, circulating cells, the tumor microenvironment, and imaging findings as biomarkers of oligometastatic NSCLC. Biomarkers that help define true OMD and predict outcomes are needed for patient selection for oligometastatic treatment, and to avoid futile treatments in patients that will not benefit from locoregional treatment.
View Article and Find Full Text PDFEBioMedicine
December 2024
CeMM Research Centre for Molecular Medicine of the Austrian Academy of Sciences, Vienna, Austria; Centre for Physiology and Pharmacology, Medical University of Vienna; Vienna, Austria. Electronic address:
Background: High content imaging-based functional precision medicine approaches have been developed and successfully applied in the field of haemato-oncology. For rheumatoid arthritis (RA), treatment selection is still based on a trial-and-error principle, and biomarkers for patient stratification and drug response prediction are needed.
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EJNMMI Res
December 2024
μNEURO Research Centre of Excellence, Universiteitsplein 1, University of Antwerp, Antwerp, Belgium.
Background: Huntington's disease (HD) is a rare neurodegenerative disorder caused by an expansion of the CAG trinucleotide repeat in the huntingtin gene which encodes the mutant huntingtin protein (mHTT) that is associated with HD-related neuropathophysiology. Noninvasive visualization of mHTT aggregates in the brain, with positron emission tomography (PET), will allow to reliably evaluate the efficacy of therapeutic interventions in HD. This study aimed to assess the radiation burden of [F]CHDI-650, a novel fluorinated mHTT radioligand, in humans based on both in vivo and ex vivo biodistribution in mice and subsequent determination of dosimetry for dosing in humans.
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