Screening-Detected versus Interval Lung Cancer in the Biennial Korean National Lung Cancer Screening Program: Proportion, Characteristics, and Mortality.

Introduction: Interval lung cancers (ILCs) are key indicators of lung cancer screening (LCS) performance. However, data on the proportion, characteristics, and mortality of ILCs under biennial screening in Asian populations remain limited.

Methods: We analyzed participants from the baseline biennial Korean national LCS program between 2019 and 2020.

Artificial Intelligence Analysis of Chest Radiographs for Predicting Major Adverse Events in Patients Visiting the Emergency Department With Acute Cardiopulmonary Symptoms.

Objective: In this study, we investigated whether artificial intelligence (AI) analysis of chest radiographs (CXRs) can predict major adverse clinical events in patients visiting the emergency department (ED) with acute cardiopulmonary symptoms.

Materials And Methods: This secondary analysis of a previous clinical trial included patients who visited the ED with symptoms suggestive of acute cardiopulmonary disease and underwent chest radiography between June 2020 and December 2021. All patients underwent triage upon arrival at ED according to the Korean Triage and Acuity Scale (KTAS).

Low-Dose Chest CT Lung Cancer Screening for School Cafeteria Workers: A Position Paper from the Korean Society of Thoracic Radiology.

The Korean Society of Thoracic Radiology (KSTR) conducted an assessment on the necessity of low-dose chest CT (LDCT) lung cancer screening for Korean school cafeteria workers. This assessment was prompted by growing concerns about the potential risk of lung cancer due to exposure to carcinogenic cooking fumes. To reach a consensus on various aspects of LDCT screening for Korean school cafeteria workers, thoracic radiologists were involved in a survey that utilized the Delphi method.

External Testing of a Deep Learning Model for Lung Cancer Risk from Low-Dose Chest CT.

Background Sybil, an open-source deep learning model that uses low-dose CT (LDCT) for lung cancer prediction, requires rigorous external testing to confirm generalizability. Additionally, its utility in identifying individuals with high risk who never smoked or have light smoking histories remains unanswered. Purpose To externally test Sybil for identifying individuals with high risk for lung cancer within an Asian health checkup cohort.

Risk factors and prognostic indicators for progressive fibrosing interstitial lung disease: a deep learning-based CT quantification approach.

Objectives: To investigate the value of deep learning-based quantitative CT (QCT) in predicting progressive fibrosing interstitial lung disease (PF-ILD) and assessing prognosis.

Materials And Methods: This single-center retrospective study included ILD patients with CT examinations between January 2015 and June 2021. Each ILD finding (ground-glass opacity (GGO), reticular opacity (RO), honeycombing) and fibrosis (sum of RO and honeycombing) was quantified from baseline and follow-up CTs.

Chest CT in the Evaluation of COPD: Recommendations of Asian Society of Thoracic Radiology.

Chronic Obstructive Pulmonary Disease (COPD) is a significant public health challenge globally, with Asia facing unique burdens due to varying demographics, healthcare access, and socioeconomic conditions. Recognizing the limitations of pulmonary function tests (PFTs) in early detection and comprehensive evaluation, the Asian Society of Thoracic Radiology (ASTR) presents this recommendations to guide the use of chest computed tomography (CT) in COPD diagnosis and management. This document consolidates evidence from an extensive literature review and surveys across Asia, highlighting the need for standardized CT protocols and practices.

Clinical Outcomes of Interstitial Lung Abnormalities Detected in the Korean National Lung Cancer CT Screening Program.

Background Limited evidence exists on the prevalence and outcomes of interstitial lung abnormalities (ILAs) in lung cancer screening populations, particularly Asian populations. Purpose To investigate the prevalence of ILAs and the association of ILAs with lung cancer, idiopathic pulmonary fibrosis (IPF), and mortality outcomes in an Asian population. Materials and Methods In this nationwide, population-based retrospective study, baseline screenings from the Korean National Lung Cancer Screening Program performed between August 2019 and December 2020 were analyzed.

Artificial Intelligence for Low-Dose CT Lung Cancer Screening: Comparison of Utilization Scenarios.

. Artificial intelligence (AI) tools for evaluating low-dose CT (LDCT) lung cancer screening examinations are used predominantly for assisting radiologists' interpretations. Alternate utilization scenarios (e.

Emerging Trends and Innovations in Radiologic Diagnosis of Thoracic Diseases.

Over the past decade, Investigative Radiology has published numerous studies that have fundamentally advanced the field of thoracic imaging. This review summarizes key developments in imaging modalities, computational tools, and clinical applications, highlighting major breakthroughs in thoracic diseases-lung cancer, pulmonary nodules, interstitial lung disease (ILD), chronic obstructive pulmonary disease (COPD), COVID-19 pneumonia, and pulmonary embolism-and outlining future directions.Artificial intelligence (AI)-driven computer-aided detection systems and radiomic analyses have notably improved the detection and classification of pulmonary nodules, while photon-counting detector CT (PCD-CT) and low-field MRI offer enhanced resolution or radiation-free strategies.

Prevalence of Airflow Limitation and Emphysema in Lung Cancer Screening Populations: A Systematic Review and Meta-Analysis.

Background: Early detection and treatment of COPD are becoming important for improving the prognosis of individuals who have a history of heavy tobacco use. Despite the higher risk of COPD among individuals participating in lung cancer screening, many of these patients continue to show rates of underdiagnosis of lung cancer.

Research Question: How many participants in lung cancer screening have emphysema or airflow limitation? If spirometry is incorporated into the screening, how many additional patients with airflow limitation could be identified?

Study Design And Methods: The Ovid-MEDLINE and Embase databases were searched from inception through November 30, 2023.

AI Applications for Thoracic Imaging: Considerations for Best Practice.

Artificial intelligence (AI) technology is rapidly being introduced into thoracic radiology practice. Current representative use cases for AI in thoracic imaging show cumulative evidence of effectiveness. These include AI assistance for reading chest radiographs and low-dose (1.

Diagnostic Performance of the Modified Lung CT Screening Reporting and Data System in a TB-Endemic Country: The Korean National Lung Cancer Screening Program.

Background: In 2019, Korea initiated the world's first national low-dose CT imaging lung cancer screening (LCS) program, adapting the Lung CT Screening Reporting and Data System (Lung-RADS) to counteract the high false-positive rates driven by prevalent TB.

Research Question: Does the modified Lung-RADS enhance screening specificity while maintaining sensitivity?

Study Design And Methods: This nationwide, retrospective cohort study included high-risk individuals aged 54 to 74 years with active tobacco use of at least 30 pack-years participating in the national LCS program from 2019 through 2020. The modified Lung-RADS 1.

Optimizing prone CT use for suspected interstitial lung abnormalities.

Objectives: We investigated whether supine chest CT alone suffices for diagnosing ILAs, thereby reducing the need for prone chest CT.

Materials And Methods: Patients who underwent prone chest CT for suspected ILAs from January 2021 to July 2023, with matching supine CT within 1 year, were retrospectively evaluated. Five multinational thoracic radiologists independently rated ILA suspicion and fibrosis scores (1 to 5-point) and ILA extent (1-100%) using supine CT first, then combined supine-prone CT after a 1-month washout.

Low-Dose CT Screening in East Asian Women Who Have Never Smoked: Association between Family History of Lung Cancer and Ground-Glass Nodule Prevalence and Growth.

Background Characteristics of ground-glass nodules (GGNs) in Asian women who have never smoked with family history of lung cancer (FHLC) remain unexamined. Purpose To investigate the differences in GGN progression to lung cancer at low-dose CT (LDCT) screening between Asian women who have never smoked with and without FHLC, and to examine associations between FHLC and GGN prevalence and growth. Materials and Methods This single-center retrospective study included East Asian women who had never smoked and had no personal history of lung cancer who underwent baseline LDCT for a health checkup between January 2011 and December 2015.

Clinical Utility of a CT-based AI Prognostic Model for Segmentectomy in Non-Small Cell Lung Cancer.

Background Currently, no tool exists for risk stratification in patients undergoing segmentectomy for non-small cell lung cancer (NSCLC). Purpose To develop and validate a deep learning (DL) prognostic model using preoperative CT scans and clinical and radiologic information for risk stratification in patients with clinical stage IA NSCLC undergoing segmentectomy. Materials and Methods In this single-center retrospective study, transfer learning of a pretrained model was performed for survival prediction in patients with clinical stage IA NSCLC who underwent lobectomy from January 2008 to March 2017.

Measurement Variability of Same-Day CT Quantification of Interstitial Lung Disease: A Multicenter Prospective Study.

Purpose To investigate quantitative CT (QCT) measurement variability in interstitial lung disease (ILD) on the basis of two same-day CT scans. Materials and Methods Participants with ILD were enrolled in this multicenter prospective study between March and October 2022. Participants underwent two same-day CT scans at an interval of a few minutes.

Association between body fat decrease during the first year after diagnosis and the prognosis of idiopathic pulmonary fibrosis: CT-based body composition analysis.

Background: The prognostic role of changes in body fat in patients with idiopathic pulmonary fibrosis (IPF) remains underexplored. We investigated the association between changes in body fat during the first year post-diagnosis and outcomes in patients with IPF.

Methods: This single-center, retrospective study included IPF patients with chest CT scan and pulmonary function test (PFT) at diagnosis and a one-year follow-up between January 2010 and December 2020.

Fleischner Society: Glossary of Terms for Thoracic Imaging.

Members of the Fleischner Society have compiled a glossary of terms for thoracic imaging that replaces previous glossaries published in 1984, 1996, and 2008, respectively. The impetus to update the previous version arose from multiple considerations. These include an awareness that new terms and concepts have emerged, others have become obsolete, and the usage of some terms has either changed or become inconsistent to a degree that warranted a new definition.

Prospective evaluation of deep learning image reconstruction for Lung-RADS and automatic nodule volumetry on ultralow-dose chest CT.

Purpose: To prospectively evaluate whether Lung-RADS classification and volumetric nodule assessment were feasible with ultralow-dose (ULD) chest CT scans with deep learning image reconstruction (DLIR).

Methods: The institutional review board approved this prospective study. This study included 40 patients (mean age, 66±12 years; 21 women).

Sixty-four-fold data reduction of chest radiographs using a super-resolution convolutional neural network.

Objectives: To develop and validate a super-resolution (SR) algorithm generating clinically feasible chest radiographs from 64-fold reduced data.

Methods: An SR convolutional neural network was trained to produce original-resolution images (output) from 64-fold reduced images (input) using 128 × 128 patches (n = 127 030). For validation, 112 radiographs-including those with pneumothorax (n = 17), nodules (n = 20), consolidations (n = 18), and ground-glass opacity (GGO; n = 16)-were collected.