Recurrence and Prevention of Nonimmediate Hypersensitivity Reactions to Iodinated Contrast Media: An 11-Year Cohort Study.

Background: With the increasing use of low-osmolar contrast media (LOCM), hypersensitivity reactions (HSRs) to LOCM have become more common. Although guidelines for the preventive measure for immediate reactions are well established, evidence-based strategies for nonimmediate HSRs remain limited.

Objective: To determine effective prophylactic strategies for patients with nonimmediate HSRs to LOCM.

Best Practice: International Multisociety Consensus Statement for Post-COVID-19 Residual Abnormalities on Chest CT Scans.

Residual lung abnormalities on CT scans after COVID-19 respiratory infection may be associated with persistent or progressive respiratory symptoms and frequently correlate with abnormal pulmonary function testing results. These abnormalities have been described using varying terms in numerous publications. Chest CT lung abnormalities after COVID-19 infection tend to stabilize or regress over time, indicating that they are nonprogressive and postinfectious in nature.

Evaluation of Vision-Language Models for Detection and Deidentification of Medical Images with Burned-In Protected Health Information.

Background Advances in vision-language models (VLMs) may enable detection and deidentification of burned-in protected health information (PHI) on medical images. Purpose To investigate the ability of commercial and open-source VLMs to detect burned-in PHI on medical images, confirm full deidentification, and obscure PHI where present. Materials and Methods In this retrospective study, records of deceased patients aged 18 years or older who died during admission at a tertiary hospital between January and June 2021 were randomly selected.

Deep Learning-Based Adrenal Gland Volumetry for the Prediction of Diabetes.

Background: The long-term association between adrenal gland volume (AGV) and type 2 diabetes (T2D) remains unclear. We aimed to determine the association between deep learning-based AGV and current glycemic status and incident T2D.

Methods: In this observational study, adults who underwent abdominopelvic computed tomography (CT) for health checkups (2011-2012), but had no adrenal nodules, were included.

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.

Deep learning for automatic volumetric bowel segmentation on body CT images.

Objectives: To develop a deep neural network for automatic bowel segmentation and assess its applicability for estimating large bowel length (LBL) in individuals with constipation.

Materials And Methods: We utilized contrast-enhanced and non-enhanced abdominal, chest, and whole-body CT images for model development. External testing involved paired pre- and post-contrast abdominal CT images from another hospital.

Effects of Printing Paths on Compressive Strength of 3D-Printed Continuous Fiber-Reinforced Composite Lattice Unit Cell.

Three-dimensional printing is a highly promising manufacturing technology that enables easy production of complex shapes. Composite lattice structures are highly efficient, having the advantages of fiber-reinforced composites and the excellent structural performance of lattice configurations. Highly efficient structures can be developed by combining the benefits of 3D printing and composite lattice structures.

Prognostic impact of low muscle mass on clinical outcomes in patients who undergo lung transplant.

Background: Low muscle mass (LMM) is recognized as a poor prognostic factor in various chronic lung diseases. However, its prognostic impact on recipients of lung transplants remains inconclusive.

Methods: We retrospectively analyzed patients who underwent lung transplantation at a tertiary referral center in South Korea.

Erratum: Correction of Fig. 2 in the Article "Temporal Radiographic Trajectory and Clinical Outcomes in COVID-19 Pneumonia: A Longitudinal Study".

This corrects the article on p. e25 in vol. 40, PMID: 40065711.

Comparison of metastasis and treatment patterns among different histopathologic types of lung cancer: analysis of 6 years of nationwide lung cancer cohort data in Korea.

Background: Personalized management of stage IV lung cancer requires a deeper understanding of metastatic patterns and the potential benefits of localized treatments for each histologic type. This study aims to identify patterns of both intrathoracic and extrathoracic metastases across various histologic types of lung cancer using a nationwide Korean lung cancer database.

Methods: The study analyzed data from patients diagnosed with lung cancer between 2014 and 2019, sourced from the Korean Association of Lung Cancer Registry (KALC-R).

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.

Availability and transparency of artificial intelligence models in radiology: a meta-research study.

Objectives: This meta-research study explored the availability of artificial intelligence (AI) models from development studies published in leading radiology journals in 2022, with availability defined as the transparent reporting of relevant technical details, such as model architecture and weights, necessary for independent replication.

Materials And Methods: A systematic search of Ovid Medline and Embase was conducted to identify AI model development studies published in five leading radiology journals in 2022. Data were extracted on study characteristics, model details, and code and model-sharing practices.

Temporal Radiographic Trajectory and Clinical Outcomes in COVID-19 Pneumonia: A Longitudinal Study.

Background: Currently, little is known about the relationship between the temporal radiographic latent trajectories, which are based on the extent of coronavirus disease 2019 (COVID-19) pneumonia and clinical outcomes. This study aimed to elucidate the differences in the temporal trends of critical laboratory biomarkers, utilization of critical care support, and clinical outcomes according to temporal radiographic latent trajectories.

Methods: We enrolled 2,385 patients who were hospitalized with COVID-19 and underwent serial chest radiographs from December 2019 to March 2022.

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.

CXR-LLaVA: a multimodal large language model for interpreting chest X-ray images.

Objective: This study aimed to develop an open-source multimodal large language model (CXR-LLaVA) for interpreting chest X-ray images (CXRs), leveraging recent advances in large language models (LLMs) to potentially replicate the image interpretation skills of human radiologists.

Materials And Methods: For training, we collected 592,580 publicly available CXRs, of which 374,881 had labels for certain radiographic abnormalities (Dataset 1) and 217,699 provided free-text radiology reports (Dataset 2). After pre-training a vision transformer with Dataset 1, we integrated it with an LLM influenced by the LLaVA network.

Accuracy of Fully Automated and Human-assisted Artificial Intelligence-based CT Quantification of Pleural Effusion Changes after Thoracentesis.

Quantifying pleural effusion change at chest CT is important for evaluating disease severity and treatment response. The purpose of this study was to assess the accuracy of artificial intelligence (AI)-based volume quantification of pleural effusion change on CT images, using the volume of drained fluid as the reference standard. Seventy-nine participants (mean age ± SD, 65 years ± 13; 47 male) undergoing thoracentesis were prospectively enrolled from October 2021 to September 2023.

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.

Ultraviolet Irradiation Surface Treatment to Enhance the Bonding Strength of Polyamide-Based Carbon Fiber-Reinforced Thermoplastic Polymers.

Adhesive bonding is a suitable joining method to satisfy the increasing industrial demand for carbon fiber-reinforced polymers without the need for a machining process. However, thermoplastic-based carbon fiber-reinforced polymers have small adhesive strength with structural thermoset adhesives. In this study, an ultraviolet irradiation surface treatment was developed to improve the adhesive bonding strength for polyamide-based carbon fiber-reinforced polymer.

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.

Automated abdominal organ segmentation algorithms for non-enhanced CT for volumetry and 3D radiomics analysis.

Purpose: To develop fully-automated abdominal organ segmentation algorithms from non-enhanced abdominal CT and low-dose chest CT and assess their feasibility for automated CT volumetry and 3D radiomics analysis of abdominal solid organs.

Methods: Fully-automated nnU-Net-based models were developed to segment the liver, spleen, and both kidneys in non-enhanced abdominal CT, and the liver and spleen in low-dose chest CT. 105 abdominal CTs and 60 low-dose chest CTs were used for model development, and 55 abdominal CTs and 10 low-dose chest CTs for external testing.

Association of Shorter Time to Recurrence and Recurrence-Free Survival with Transthoracic Lung Biopsy in Stage I Lung Cancer.

Purpose: We aim to determine whether preoperative percutaneous needle aspiration or biopsy (PCNA/Bx) increases recurrence risk and reduces survival in stage I lung cancer patients, using a nationwide lung cancer registry.

Materials And Methods: We retrospectively included 3,452 patients diagnosed with stage I lung cancer who underwent curative surgery between 2014 and 2019, as recorded in the Korean Association of Lung Cancer Registry. To balance the characteristics of patients with and without PCNA/Bx, we applied inverse probability of treatment weighting.