Longitudinal registration of thoracic CT images with radiation-induced lung diseases: A divide-and-conquer approach based on component structure wise registration using coherent point drift.

Background And Objective: Registration of pulmonary computed tomography (CT) images with radiation-induced lung diseases (RILD) was essential to investigate the voxel-wise relationship between the formation of RILD and the radiation dose received by different tissues. Although various approaches had been developed for the registration of lung CTs, their performances remained clinically unsatisfactory for registration of lung CT images with RILD. The main difficulties arose from the longitudinal change in lung parenchyma, including RILD and volumetric change of lung cancers, after radiation therapy, leading to inaccurate registration and artifacts caused by erroneous matching of the RILD tissues.

The clinical impacts of lung microbiome in bronchiectasis with fixed airflow obstruction: a prospective cohort study.

Background: Airflow obstruction is a hallmark of disease severity and prognosis in bronchiectasis. The relationship between lung microbiota, airway inflammation, and outcomes in bronchiectasis with fixed airflow obstruction (FAO) remains unclear. This study explores these interactions in bronchiectasis patients, with and without FAO, and compares them to those diagnosed with chronic obstructive pulmonary disease (COPD).

Bullous Parametric Response Map for Functional Localization of COPD.

Advanced bronchoscopic lung volume reduction treatment (BLVR) is now a routine care option for treating patients with severe emphysema. Patterns of low attenuation clusters indicating emphysema and functional small airway disease (fSAD) on paired CT, which may provide additional insights to the target selection of the segmental or subsegmental lobe of the treatments, require further investigation. The low attenuation clusters (LACS) were segmented to identify the scalar and spatial distribution of the lung destructions, in terms of 10 fractions scales of low attenuation density (LAD) located in upper lobes and lower lobes.

Predictive Modelling of Lung Function using Emphysematous Density Distribution.

Target lung tissue selection remains a challenging task to perform for treating severe emphysema with lung volume reduction (LVR). In order to target the treatment candidate, the percentage of low attenuation volume (LAV%) representing the proportion of emphysema volume to whole lung volume is measured using computed tomography (CT) images. Although LAV% have shown to have a correlation with lung function in patients with chronic obstructive pulmonary disease (COPD), similar measurements of LAV% in whole lung or lobes may have large variations in lung function due to emphysema heterogeneity.

Extraction of radiomic values from lung adenocarcinoma with near-pure subtypes in the International Association for the Study of Lung Cancer/the American Thoracic Society/the European Respiratory Society (IASLC/ATS/ERS) classification.

Introduction: Histological subtypes of lung adenocarcinomas (ADCs) classified by the International Association for the Study of Lung Cancer/American Thoracic Society/European Respiratory Society (IASLC/ATS/ERS) system have been investigated using radiomic approaches. However, the results have had limitations since <80% of invasive lung ADCs were heterogeneous, with two or more subtypes. To reduce the influence of heterogeneity during radiomic analysis, computed tomography (CT) images of lung ADCs with near-pure ADC subtypes were analyzed to extract representative radiomic features of different subtypes.

Anatomy packing with hierarchical segments: an algorithm for segmentation of pulmonary nodules in CT images.

Background: This paper proposes a semantic segmentation algorithm that provides the spatial distribution patterns of pulmonary ground-glass nodules with solid portions in computed tomography (CT) images.

Methods: The proposed segmentation algorithm, anatomy packing with hierarchical segments (APHS), performs pulmonary nodule segmentation and quantification in CT images. In particular, the APHS algorithm consists of two essential processes: hierarchical segmentation tree construction and anatomy packing.