Multi-center Korean cohort study based on RNA-sequencing data targeting COPD patients.

In 2023, WHO ranked chronic obstructive pulmonary disease (COPD) as the third leading cause of death, with 3.23 million fatalities in 2019. The intricate nature of the disease, which is influenced by genetics, environment, and lifestyle, is evident.

Clinical usability of 3D gradient-echo-based ultrashort echo time imaging: Is it enough to facilitate diagnostic decision in real-world practice?

Background: With recent advances in magnetic resonance imaging (MRI) technology, the practical role of lung MRI is expanding despite the inherent challenges of the thorax. The purpose of our study was to evaluate the current status of the concurrent dephasing and excitation (CODE) ultrashort echo-time sequence and the T1-weighted volumetric interpolated breath-hold examination (VIBE) sequence in the evaluation of thoracic disease by comparing it with the gold standard computed tomography (CT).

Methods: Twenty-four patients with lung cancer and mediastinal masses underwent both CT and MRI including T1-weighted VIBE and CODE.

Predictions of PD-L1 Expression Based on CT Imaging Features in Lung Squamous Cell Carcinoma.

Purpose: To develop models to predict programmed death ligand 1 (PD-L1) expression in pulmonary squamous cell carcinoma (SCC) using CT.

Materials And Methods: A total of 97 patients diagnosed with SCC who underwent PD-L1 expression assay were included in this study. We performed a CT analysis of the tumors using pretreatment CT images.

CT-Derived Deep Learning-Based Quantification of Body Composition Associated with Disease Severity in Chronic Obstructive Pulmonary Disease.

Purpose: Our study aimed to evaluate the association between automated quantified body composition on CT and pulmonary function or quantitative lung features in patients with chronic obstructive pulmonary disease (COPD).

Materials And Methods: A total of 290 patients with COPD were enrolled in this study. The volume of muscle and subcutaneous fat, area of muscle and subcutaneous fat at T12, and bone attenuation at T12 were obtained from chest CT using a deep learning-based body segmentation algorithm.

Erratum: Correction of Affiliations in the Article "Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019".

This corrects the article on p. e413 in vol. 35, PMID: 33258333.

Correction: Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study.

[This corrects the article DOI: 10.2196/42717.].

Deep Learning With Chest Radiographs for Making Prognoses in Patients With COVID-19: Retrospective Cohort Study.

Background: An artificial intelligence (AI) model using chest radiography (CXR) may provide good performance in making prognoses for COVID-19.

Objective: We aimed to develop and validate a prediction model using CXR based on an AI model and clinical variables to predict clinical outcomes in patients with COVID-19.

Methods: This retrospective longitudinal study included patients hospitalized for COVID-19 at multiple COVID-19 medical centers between February 2020 and October 2020.

A Pictorial Review of Radiologic Findings of Foreign Bodies in the Thorax.

Thoracic foreign bodies (FBs) are serious and relatively frequent in emergency departments. Thoracic FBs may occur in association with aspiration, ingestion, trauma, or iatrogenic causes. Imaging plays an important role in the identification of FBs and their dimensions, structures, and locations, before the initiation of interventional treatment.

Genome-Wide Association Study of Airway Wall Thickening in a Korean Chronic Obstructive Pulmonary Disease Cohort.

Airway wall thickening (AWT) plays an important pathophysiological role in airway diseases such as chronic obstructive pulmonary disease (COPD). There are only a few studies on the genetic components contributing to AWT in the Korean population. This study aimed to identify AWT-related single-nucleotide polymorphisms (SNPs) using a genome-wide association study (GWAS).

How Many Private Data Are Needed for Deep Learning in Lung Nodule Detection on CT Scans? A Retrospective Multicenter Study.

Early detection of lung nodules is essential for preventing lung cancer. However, the number of radiologists who can diagnose lung nodules is limited, and considerable effort and time are required. To address this problem, researchers are investigating the automation of deep-learning-based lung nodule detection.

Incidence and risk factors for sternal osteomyelitis after median sternotomy.

Background: Sternal osteomyelitis (OM) after median sternotomy is the rarest form of deep sternal wound infections (DSWIs). A retrospective study was implemented to evaluate the incidence and potential risk factors of sternal OM after median sternotomy.

Methods: We analyzed 3,410 consecutive patients who underwent cardiothoracic surgery via median sternotomy from January 2005 to December 2019 at our institution.

Structural and functional alterations of subjects with cement dust exposure: A longitudinal quantitative computed tomography-based study.

Cement dust exposure (CDE) can be a risk factor for pulmonary disease, causing changes in segmental airways and parenchymal lungs. This study investigates longitudinal alterations in quantitative computed tomography (CT)-based metrics due to CDE. We obtained CT-based airway structural and lung functional metrics from CDE subjects with baseline CT and follow-up CT scans performed three years later.

Analysis of treatment pattern of anti-dementia medications in newly diagnosed Alzheimer's dementia using OMOP CDM.

Anti-dementia medications are widely prescribed to patients with Alzheimer's dementia (AD) in South Korea. This study investigated the pattern of medical management in newly diagnosed patients with AD using a standardized data format-the Observational Medical Outcome Partnership Common Data Model from five hospitals. We examined the anti-dementia treatment patterns from datasets that comprise > 5 million patients during 2009-2019.

Quantitative assessment the longitudinal changes of pulmonary vascular counts in chronic obstructive pulmonary disease.

Background: Chest computed tomography (CT) is a widely used method to assess morphological and dynamic abnormalities in chronic obstructive pulmonary disease (COPD). The small pulmonary vascular cross-section (CSA), quantitatively extracted from volumetric CT, is a reliable indicator for predicting pulmonary vascular changes. CSA is associated with the severity of symptoms, pulmonary function tests (PFT) and emphysema and in COPD patients the severity increases over time.

Association between plasma sRAGE and emphysema according to the genotypes of AGER gene.

Background: Higher soluble receptor for advanced glycation end product (sRAGE) levels are considered to be associated with severe emphysema. However, the relationship remains uncertain when the advanced glycation end-product specific receptor (AGER) gene is involved. We aimed to analyse the association between sRAGE levels and emphysema according to the genotypes of rs2070600 in the AGER gene.

Quantitative computed tomography imaging-based classification of cement dust-exposed subjects with an artificial neural network technique.

Background And Objective: Cement dust exposure is likely to affect the structural and functional alterations in segmental airways and parenchymal lungs. This study develops an artificial neural network (ANN) model for identifying cement dust-exposed (CDE) subjects using quantitative computed tomography-based airway structural and functional features.

Methods: We obtained the airway features in five central and five sub-grouped segmental regions and the lung features in five lobar regions and one total lung region from 311 CDE and 298 non-CDE (NCDE) subjects.

Word Embedding Reveals Cyfra 21-1 as a Biomarker for Chronic Obstructive Pulmonary Disease.

Background: Although patients with chronic obstructive pulmonary disease (COPD) experience high morbidity and mortality worldwide, few biomarkers are available for COPD. Here, we analyzed potential biomarkers for the diagnosis of COPD by using word embedding.

Methods: To determine which biomarkers are likely to be associated with COPD, we selected respiratory disease-related biomarkers.

A genome-wide association study of quantitative computed tomographic emphysema in Korean populations.

Emphysema is an important feature of chronic obstructive pulmonary disease (COPD). Genetic factors likely affect emphysema pathogenesis, but this question has predominantly been studied in those of European ancestry. In this study, we sought to determine genetic components of emphysema severity and characterize the potential function of the associated loci in Korean population.

Computed tomography-based visual assessment of chronic obstructive pulmonary disease: comparison with pulmonary function test and quantitative computed tomography.

Background: Chronic obstructive pulmonary disease (COPD) has variable subtypes involving mixture of large airway inflammation, small airway disease, and emphysema. This study evaluated the relationship between visually assessed computed tomography (CT) subtypes and clinical/imaging characteristics.

Methods: In total, 452 participants were enrolled in this study between 2012 and 2017.

A comparative study of chest CT findings regarding the effects of regional dust exposure on patients with COPD living in urban areas and rural areas near cement plants.

Background: The clinical and radiological presentation of chronic obstructive pulmonary disease (COPD) is heterogenous depending on the characterized sources of inflammation. This study aimed to evaluate COPD phenotypes associated with specific dust exposure.

Methods: This study was designed to compare the characteristics, clinical outcomes and radiological findings between two prospective COPD cohorts representing two distinguishing regions in the Republic of Korea; COPD in Dusty Area (CODA) and the Korean Obstructive Lung Disease (KOLD) cohort.

A 3D-CNN model with CT-based parametric response mapping for classifying COPD subjects.

Chronic obstructive pulmonary disease (COPD) is a respiratory disorder involving abnormalities of lung parenchymal morphology with different severities. COPD is assessed by pulmonary-function tests and computed tomography-based approaches. We introduce a new classification method for COPD grouping based on deep learning and a parametric-response mapping (PRM) method.

Tuberculosis-Infected Giant Bulla Treated by Percutaneous Drainage Followed by Obliteration of the Pulmonary Cavity Using Talc: Case Report.

Tuberculosis (TB)-infected giant bullae are rare. A 55-year-old man was referred when an infected bulla did not respond to empirical treatment. Computed tomography showed a giant bulla in the right upper lobe with an air-fluid level and surrounding infiltrate.

Establishment of a Nationwide Korean Imaging Cohort of Coronavirus Disease 2019.

Background: The Korean Society of Thoracic Radiology (KSTR) recently constructed a nation-wide coronavirus disease 2019 (COVID-19) database and imaging repository, referred to the Korean imaging cohort of COVID-19 (KICC-19) based on the collaborative efforts of its members. The purpose of this study was to provide a summary of the clinico-epidemiological data and imaging data of the KICC-19.

Methods: The KSTR members at 17 COVID-19 referral centers retrospectively collected imaging data and clinical information of consecutive patients with reverse transcription polymerase chain reaction-proven COVID-19 in respiratory specimens from February 2020 through May 2020 who underwent diagnostic chest computed tomography (CT) or radiograph in each participating hospital.

Long-term exposure to PM and NO in relation to lung function and imaging phenotypes in a COPD cohort.

Background: Ambient air pollution can contribute to the development and exacerbation of COPD. However, the influence of air pollution on objective COPD phenotypes, especially from imaging, is not well studied. We investigated the influence of long-term exposure to air pollution on lung function and quantitative imaging measurements in a Korean cohort of participants with and without COPD diagnosis.

Computed tomographic findings of chest injuries following cardiopulmonary resuscitation: More complications for prolonged chest compressions?

Chest injuries are common and inevitable complications of chest compressions during cardiopulmonary resuscitation (CPR). This study aimed to investigate lung parenchymal and thoracic skeletal injuries after CPR by using computed tomography (CT) and to analyze the correlation between the duration of CPR and related complications.We examined 43 non-traumatic cardiac arrest patients who were successfully resuscitated after CPR and had chest CT scans within 24 hours of CPR.