Large Language Models for CAD-RADS 2.0 Extraction From Semi-Structured Coronary CT Angiography Reports: A Multi-Institutional Study.

Objective: To evaluate the accuracy of large language models (LLMs) in extracting Coronary Artery Disease-Reporting and Data System (CAD-RADS) 2.0 components from coronary CT angiography (CCTA) reports, and assess the impact of prompting strategies.

Materials And Methods: In this multi-institutional study, we collected 319 synthetic, semi-structured CCTA reports from six institutions to protect patient privacy while maintaining clinical relevance.

Mucus plug and lung cancer incidence in patients with COPD.

Airway mucus plugs are frequently observed on chest computed tomography (CT) scans in patients with chronic obstructive pulmonary disease (COPD). However, the association between the presence of mucus plugs and the risk of lung cancer in COPD patients has not been thoroughly investigated. This study aimed to determine whether mucus plugs are associated with an increased risk of lung cancer in COPD patients.

Therapeutic approaches for pulmonary artery pseudoaneurysms and analysis of outcomes.

Objectives: To evaluate the therapeutic approaches for pulmonary artery pseudoaneurysms (PAPs) with various etiologies and types, and outcomes.

Materials And Methods: Between March 2010 and March 2024, 30 PAPs were identified in 29 patients. We analyzed the medical records of 29 PAPs in 28 patients whose etiologies were confirmed.

Comparing large scale and selected feature learning for community acquired pneumonia prognosis prediction using clinical data: a stacked ensemble approach.

This study investigated and validated all-cause in-hospital death prediction models for hospitalized pneumonia patients based on large-scale clinical data, including diagnoses, medication prescriptions, and laboratory test codes. Feature selection was performed using both large-scale feature learning with a Common Data Model (CDM) and specific pneumonia-related risk factors. A stacked ensemble mixed machine-learning model was compared with traditional machine-learning models.

Distinct risks of exacerbation and lung function decline between never-smokers and ever-smokers with COPD.

Background: Chronic obstructive pulmonary disease (COPD) can occur in patients without a history of smoking, which is a strong risk factor for COPD. However, few studies have focused on the prognosis of never-smokers with COPD. We investigated the difference of the longitudinal clinical outcomes between never-smokers and ever-smokers with COPD.

Diagnostic performance of radiologists in distinguishing post-COVID-19 residual abnormalities from interstitial lung abnormalities.

Objective: Distinguishing post-COVID-19 residual abnormalities from interstitial lung abnormalities (ILA) on CT can be challenging if clinical information is limited. This study aimed to evaluate the diagnostic performance of radiologists in distinguishing post-COVID-19 residual abnormalities from ILA.

Methods: This multi-reader, multi-case study included 60 age- and sex-matched subjects with chest CT scans.

Mucus Plugs as Precursors to Exacerbation and Lung Function Decline in COPD Patients.

Background: Mucus plugs identified through chest computed tomography (CT) scans have emerged as potential prognostic factors in chronic obstructive pulmonary disease (COPD). This 5-year longitudinal study investigated their impact on exacerbations and FEV decline.

Methods: COPD patients with baseline chest CT and spirometric assessments were categorized based on mucus plug presence.

Cluster analysis of thoracic muscle mass using artificial intelligence in severe pneumonia.

Severe pneumonia results in high morbidity and mortality despite advanced treatments. This study investigates thoracic muscle mass from chest CT scans as a biomarker for predicting clinical outcomes in ICU patients with severe pneumonia. Analyzing electronic medical records and chest CT scans of 778 ICU patients with severe community-acquired pneumonia from January 2016 to December 2021, AI-enhanced 3D segmentation was used to assess thoracic muscle mass.

Automatic Mechanical Ventilation vs Manual Bag Ventilation During CPR: A Pilot Randomized Controlled Trial.

Background: There is insufficient evidence supporting the theory that mechanical ventilation can replace the manual ventilation method during CPR.

Research Question: Is using automatic mechanical ventilation (MV) feasible and comparable to the manual ventilation method during CPR?

Study Design And Methods: This pilot randomized controlled trial compared MV and manual bag ventilation (BV) during CPR after out-of-hospital cardiac arrest (OHCA). Patients with medical OHCA arriving at the ED were randomly assigned to two groups: an MV group using a mechanical ventilator and a BV group using a bag valve mask.

Diffusing capacity as an independent predictor of acute exacerbations in chronic obstructive pulmonary disease.

A weak correlation between diffusing capacity of the lung for carbon monoxide (DL) and emphysema has been reported. This study investigated whether impaired DL in chronic obstructive pulmonary disease (COPD) is associated with increased risk of acute exacerbation independent of the presence or extent of emphysema. This retrospective cohort study included patients with COPD between January 2004 and December 2019.

Effectiveness of COVID-19 Vaccines Over Time Against Clinical and Radiologic Outcomes Related to Severe SARS-CoV-2 Infection.

Background The impact of waning vaccine effectiveness on the severity of COVID-19-related findings discovered with radiologic examinations remains underexplored. Purpose To evaluate the effectiveness of vaccines over time against severe clinical and radiologic outcomes related to SARS-CoV-2 infections. Materials and Methods This multicenter retrospective study included patients in the Korean Imaging Cohort of COVID-19 database who were hospitalized for COVID-19 between June 2021 and December 2022.

Establishment and characterization of BMC-PDC-019: a novel patient-derived cell line of EGFR-mutant pulmonary adenocarcinoma transformed into small-cell lung cancer.

Transformed small-cell lung cancer (tSCLC) from EGFR-mutant adenocarcinoma is a rare and aggressive form of lung cancer that can occur when the tumor develops resistance to EGFR targeted therapy and the cancer cells acquire additional genomic alterations that cause them to transform into SCLC. Treatment for tSCLC has not been established yet, and chemotherapy regimens for de novo SCLC are mostly recommended. However, these treatments showed disappointing outcome, and novel anti-cancer agents and immunological approaches are currently being developed.

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.].

[Expert Opinion Questionnaire About Chest CT Scan Using A Negative Pressure Isolation Strecher in COVID-19 Patients: Image Quality and Infection Risk].

Purpose: To survey perceptions of certified physicians on the protocol of chest CT in patients with coronavirus (COVID-19) using a negative pressure isolation stretcher (NPIS).

Materials And Methods: This study collected questionnaire responses from a total of 27 certified physicians who had previously performed chest CT with NPIS in COVID-19 isolation hospitals.

Results: The nine surveyed hospitals performed an average of 116 chest CT examinations with NPIS each year.

Machine learning-based prediction of in-ICU mortality in pneumonia patients.

Conventional severity-of-illness scoring systems have shown suboptimal performance for predicting in-intensive care unit (ICU) mortality in patients with severe pneumonia. This study aimed to develop and validate machine learning (ML) models for mortality prediction in patients with severe pneumonia. This retrospective study evaluated patients admitted to the ICU for severe pneumonia between January 2016 and December 2021.

Chest Radiography of Tuberculosis: Determination of Activity Using Deep Learning Algorithm.

Background: Inactive or old, healed tuberculosis (TB) on chest radiograph (CR) is often found in high TB incidence countries, and to avoid unnecessary evaluation and medication, differentiation from active TB is important. This study develops a deep learning (DL) model to estimate activity in a single chest radiographic analysis.

Methods: A total of 3,824 active TB CRs from 511 individuals and 2,277 inactive TB CRs from 558 individuals were retrospectively collected.

Risk of thyroid cancer in a lung cancer screening population of the National Lung Screening Trial according to the presence of incidental thyroid nodules detected on low-dose chest CT.

Purpose: This study evaluated thyroid cancer risk in a lung cancer screening population according to the presence of an incidental thyroid nodule (ITN) detected on low-dose chest computed tomography (LDCT).

Methods: Of 47,837 subjects who underwent LDCT, a lung cancer screening population according to the National Lung Screening Trial results was retrospectively enrolled. The prevalence of ITN on LDCT was calculated, and the ultrasonography (US)/fine-needle aspiration (FNA)-based risk of thyroid cancer according to the presence of ITN on LDCT was compared using the Fisher exact or Student t-test as appropriate.

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.

Artificial Intelligence Solution for Chest Radiographs in Respiratory Outpatient Clinics: Multicenter Prospective Randomized Clinical Trial.

Artificial intelligence (AI)-assisted diagnosis imparts high accuracy to chest radiography (CXR) interpretation; however, its benefit for nonradiologist physicians in detecting lung lesions on CXR remains unclear. To investigate whether AI assistance improves the diagnostic performance of physicians for CXR interpretation and affects their clinical decisions in clinical practice. We randomly allocated eligible patients who visited an outpatient clinic to the intervention (with AI-assisted interpretation) and control (without AI-assisted interpretation) groups.

Different treatment response to systemic corticosteroids according to white blood cell counts in severe COVID-19 patients.

Background: Limited data are available in COVID-19 patients on the prediction of treatment response to systemic corticosteroid therapy based on systemic inflammatory markers. There is a concern whether the response to systemic corticosteroid is different according to white blood cell (WBC) counts in COVID-19 patients. We aimed to assess whether WBC count is related with the clinical outcomes after treatment with systemic corticosteroids in severe COVID-19.

Chest Radiographs and CT Findings during Healthcare Workers' Tuberculosis Screening Using Interferon-Gamma Release Assay: Retrospective Observational Study.

Purpose: To investigate the incidence of tuberculosis (TB) in healthcare workers (HCWs) with positive interferon-gamma release assay (IGRA) results based on chest X-ray (CXR) and CT findings and determine the role of imaging in the diagnosis of TB.

Materials And Methods: Among 1976 hospital personnel screened for TB using IGRA, IGRA-positive subjects were retrospectively investigated. Clustered nodular and/or linear streaky opacities in the upper lung zone were considered positive on CXR.

[Korean Clinical Imaging Guidelines for Justification of Diagnostic Imaging Study for COVID-19].

To develop Korean coronavirus disease (COVID-19) chest imaging justification guidelines, eight key questions were selected and the following recommendations were made with the evidence-based clinical imaging guideline adaptation methodology. It is appropriate not to use chest imaging tests (chest radiograph or CT) for the diagnosis of COVID-19 in asymptomatic patients. If reverse transcription-polymerase chain reaction testing is not available or if results are delayed or are initially negative in the presence of symptoms suggestive of COVID-19, chest imaging tests may be considered.