Micro-nodule analysis by severity of pneumoconiosis using 3D CT images

Pneumoconiosis, an occupational respiratory illness triggered by inhaling mineral dust with increasing prevalence and severity worldwide. Chest radiograph plays a vital role in the screening of pneumoconiosis. The pneumoconiosis staging mainly depends on the small opacity in the lung fields, and early-stage pneumoconiosis staging has been a challenging task, necessitating quantitative diagnostics. Thoracic Computed Tomography (CT) images represent the gold-standard modality for evaluating local abnormalities and understanding structure-function relationships in an organ. The thoracic CT images have the potential to provide an essential feature for distinguishing subtle morphological patterns of micro-nodule distributions in the lungs through quantitative analyses. This study investigates whether quantitative representations based on topological data analysis can capture particulate shadows' three-dimensional (3D) distribution properties in pneumoconiosis in volumetric CT images.