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Comparing multi-texture fibrosis analysis versus binary opacity-based abnormality detection for quantitative assessment of idiopathic pulmonary fibrosis.
Sci Rep
January 2025
Department of Diagnostic and Interventional Radiology, University Hospital Bonn, Venusberg-Campus 1, 53127, Bonn, Germany.
Automated tools for quantification of idiopathic pulmonary fibrosis (IPF) can aid in ensuring reproducibility, however their complexity and costs can differ substantially. In this retrospective study, two automated tools were compared in 45 patients with biopsy proven (12/45) and imaging-based (33/45) IPF diagnosis (mean age 74 ± 9 years, 37 male) for quantification of pulmonary fibrosis in CT. First, a tool that identifies multiple characteristic lung texture features was applied to measure multi-texture fibrotic lung (MTFL) by combining the amount of ground glass, reticulation, and honeycombing.
View Article and Find Full Text PDFArtificial Intelligence Unveils the Unseen: Mapping Novel Lung Patterns in Bronchiectasis via Texture Analysis.
Diagnostics (Basel)
December 2024
Department of Respiratory Medicine, JSS Medical College, JSS Academy of Higher Education & Research (JSS AHER), Mysore 570004, Karnataka, India.
Thin-section CT (TSCT) is currently the most sensitive imaging modality for detecting bronchiectasis. However, conventional TSCT or HRCT may overlook subtle lung involvement such as alveolar and interstitial changes. Artificial Intelligence (AI)-based analysis offers the potential to identify novel information on lung parenchymal involvement that is not easily detectable with traditional imaging techniques.
View Article and Find Full Text PDFAssessing the Severity of Connective Tissue-Related Interstitial Lung Disease Using Computed Tomography Quantitative Analysis Parameters.
J Comput Assist Tomogr
November 2024
From the Department of Medical Imaging, Jiangyin Hospital Affiliated to Nanjing University of Chinese Medicine, Jiangyin City, Jiangsu Province, China.
Objectives: The aims of the study are to predict lung function impairment in patients with connective tissue disease (CTD)-associated interstitial lung disease (ILD) through computed tomography (CT) quantitative analysis parameters based on CT deep learning model and density threshold method and to assess the severity of the disease in patients with CTD-ILD.
Methods: We retrospectively collected chest high-resolution CT images and pulmonary function test results from 105 patients with CTD-ILD between January 2021 and December 2023 (patients staged according to the gender-age-physiology [GAP] system), including 46 males and 59 females, with a median age of 64 years. Additionally, we selected 80 healthy controls (HCs) with matched sex and age, who showed no abnormalities in their chest high-resolution CT.
Improving functional correlation of quantification of interstitial lung disease by reducing the vendor difference of CT using generative adversarial network (GAN) style conversion.
Eur J Radiol
December 2024
Department of Radiology and Research Institute of Radiology, University of Ulsan College of Medicine, Asan Medical Center, Seoul, Republic of Korea.
Objective: To assess whether CT style conversion between different CT vendors using a routable generative adversarial network (RouteGAN) could minimize variation in ILD quantification, resulting in improved functional correlation of quantitative CT (QCT) measures.
Methods: Patients with idiopathic pulmonary fibrosis (IPF) who underwent unenhanced chest CTs with vendor A and a pulmonary function test (PFT) were retrospectively evaluated. As deep-learning based ILD quantification software was mainly developed using vendor B CT, style-converted images from vendor A to B style were generated using RouteGAN.
Factors associated with interstitial lung disease and the progressive fibrosing phenotype in rheumatoid arthritis-related interstitial lung disease.
Med J Armed Forces India
December 2024
Professor (Pulmonary Medicine), PGIMER, Chandigarh, India.
Background: The risk factors for interstitial lung disease (ILD) in rheumatoid arthritis (RA) are inconsistent among previous studies. Furthermore, the factors associated with the emergence of the recently defined progressive fibrosing (PF) phenotype are unknown. Herein, we analyze the risk factors for ILD in RA.
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