Impact of the COVID-19 pandemic on lung cancer screening utilization and outcome: a health examination center retrospective study.

Background: The coronavirus disease 2019 (COVID-19) pandemic has disrupted healthcare systems, significantly affecting preventive services such as low-dose computed tomography (LDCT) for lung cancer screening. We aimed to evaluate the pandemic's impact on LDCT screening practices at Kaohsiung Veterans General Hospital, focusing on the changes in participation rates, Lung-RADS categories, and lung cancer diagnoses to guide the development of interventions for improving screening programs and early detection during health crises.

Materials And Methods: A retrospective cohort of 56,730 individuals who underwent health examinations between 2017 and 2023 was analyzed.

Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection-Precision Screening for Lung Cancer.

Lung cancer remains the leading cause of cancer-related mortality globally, largely due to late-stage diagnoses. While low-dose computed tomography (LDCT) has improved early detection and reduced mortality in high-risk populations, traditional screening strategies often adopt a one-size-fits-all approach based primarily on age and smoking history. This can lead to limitations, such as overdiagnosis, false positives, and the underrepresentation of non-smokers, which are especially prevalent in Asian populations.

Editorial: Advancements and Challenges in Lung Cancer Screening, Diagnosis, and Management.

The study highlights a significant issue in detecting the EGFR S768I mutation using the Idylla qPCR system, with a high false-positive rate [...

Understanding East-West differences in subsolid nodules: prevalence and overdiagnosis implications in lung cancer screening.

Background: Owing to the widespread opportunistic LDCT screening leading to increased overdiagnosis in Asian countries, such as South Korea, mainland China, and Taiwan, this study seeks to analyze the divergence in SSN prevalence between Eastern and Western nations, focusing on the influence of SSN on the growing overdiagnosis trend, notably among females.

Methods: This retrospective study collected data from 4166 participants who underwent baseline LDCT in a hospital-based cohort between January 2014 and August 2021. Clinical parameters, including age, sex, lung imaging reporting and data system (Lung-RADS) categories, smoking history, pack-year dose, and SSN characteristics, were extracted from electronic medical records.

A simple and user-friendly machine learning model to detect osteoporosis in health examination populations in Southern Taiwan.

Background: Osteoporosis is a growing public health concern in aging populations such as Taiwan, where limited utilization of dual-energy X-ray absorptiometry (DXA) often leads to underdiagnosis and even delayed treatment. Therefore, we leveraged machine learning (ML) and aimed to develop a simple and easily accessible model that effectively identifies individuals at high risk of osteoporosis.

Methods: This retrospective analysis enrolled 5510 men aged ≥50 years and 4720 postmenopausal women who underwent DXA at the Kaohsiung Veterans General Hospital, with another cohort of 610 men and 523 women for validation.

New look at the power of zero coronary artery calcium (CAC) in Asian population: a systemic review and meta-analysis.

Background: Numerous studies have validated a 5-year warranty period for heart health in Western populations with a coronary artery calcium (CAC) score of zero. While the calcium score is a crucial cardiovascular risk indicator, its interpretation in Asian populations remains unclear. This meta-analysis aimed to clarify the uncertainty surrounding the prevalence, warranty period, and prognostic implications of zero CAC scores in Asian populations.

Impact of annual trend volume of low-dose computed tomography for lung cancer screening on overdiagnosis, overmanagement, and gender disparities.

Background: With the increasing prevalence of nonsmoking-related lung cancer in Asia, Asian countries have increasingly adopted low-dose computed tomography (LDCT) for lung cancer screening, particularly in private screening programs. This study examined how annual LDCT volume affects lung cancer stage distribution, overdiagnosis, and gender disparities using a hospital-based lung cancer database.

Methods: This study analyzed the annual utilized LDCT volume, clinical characteristics of lung cancer, stage shift distribution, and potential overdiagnosis.

Prediction of the stage shift growth of early-stage lung adenocarcinomas by volume-doubling time.

Background: Prediction of subsolid nodule (SSN) interval growth is crucial for clinical management and decision making in lung cancer screening program. To the best of our knowledge, no study has investigated whether volume doubling time (VDT) is an independent factor for predicting SSN interval growth, or whether its predictive power is better than that of traditional semantic methods, such as nodular diameter or type. This study aimed to investigate whether VDT could provide added value in predicting the long-term natural course of SSNs (<3 cm) regarding stage shift.

Comparison between one-stage and two-stage CT-guided localization of lung nodules with surgical resection: a single medical center experience.

Background: This retrospective study aimed to compare the efficacy and safety of one-stage computed tomography (OSCT)- to that of two-stage computed tomography (TSCT)-guided localization for the surgical removal of small lung nodules.

Methods: We collected data from patients with ipsilateral pulmonary nodules who underwent localization before surgical removal at Veteran General Hospital Kaohsiung between October 2017 and January 2022. The patients were divided into the OSCT and TSCT groups.

Evaluating Efficiency and Adherence in Asian Lung Cancer Screening: Comparing Self-paid and Clinical Study Approaches in Taiwan.

Rationale And Objectives: This study aimed to assess how different screening methods, specifically self-paid screening versus participation in clinical studies, affect screening efficiency and adherence in a real-world Asian lung cancer screening population.

Materials And Methods: This study collected 4166 participants from our hospital imaging database who underwent baseline low-dose computed tomography (LDCT) between January 2014 and August 2021. Adherence status was determined by counting CT scans, with one check indicating non-adherence and two or more checks indicating adherence.

LASSO-derived model for the prediction of lean-non-alcoholic fatty liver disease in examinees attending a routine health check-up.

Background: Lean individuals with non-alcohol fatty liver disease (NAFLD) often have normal body size but abnormal visceral fat. Therefore, an alternative to body mass index should be considered for prediction of lean-NAFLD. This study aimed to use representative visceral fat links with other laboratory parameters using the least absolute shrinkage and selection operator (LASSO) method to construct a predictive model for lean-NAFLD.

Impact of Voxel Normalization on a Machine Learning-Based Method: A Study on Pulmonary Nodule Malignancy Diagnosis Using Low-Dose Computed Tomography (LDCT).

Lung cancer (LC) stands as the foremost cause of cancer-related fatality rates worldwide. Early diagnosis significantly enhances patient survival rate. Nowadays, low-dose computed tomography (LDCT) is widely employed on the chest as a tool for large-scale lung cancer screening.

Managing Persistent Subsolid Nodules in Lung Cancer: Education, Decision Making, and Impact of Interval Growth Patterns.

With the popularization of lung cancer screening, many persistent subsolid nodules (SSNs) have been identified clinically, especially in Asian non-smokers. However, many studies have found that SSNs exhibit heterogeneous growth trends during long-term follow ups. This article adopted a narrative approach to extensively review the available literature on the topic to explore the definitions, rationale, and clinical application of different interval growths of subsolid pulmonary nodule management and follow-up strategies.

Eplerenone improves hyperglycemia and sympathetic excitation in chronic renocardiac syndrome in rats.

We aimed to assess the efficacy of eplerenone, a steroidal mineralocorticoid receptor antagonist known to reduce blood pressure and mitigate cardiovascular disease (CVD) progression, in retarding the progression of chronic kidney disease (CKD) and CVD in a rat model of type 4 cardiorenal syndrome (CRS). We grouped rats into four experimental categories: sham surgery, sham treatment with eplerenone, nephrectomy without eplerenone (Nx), and nephrectomy with eplerenone (Nx + EP). For the Nx + EP group, rats received five-sixths nephrectomy, inducing CKD and CVD conditions such as renal hypertension and hyperglycemia, and were then treated with eplerenone (100 mg/kg/day, orally) over 4 weeks after an initial 4-week observation period.

Gender Differences in Subclinical Coronary Atherosclerosis in the Asian Population With a Coronary Artery Calcium Score of Zero.

There is little evidence on whether gender difference influences the incidence of subclinical coronary atherosclerosis in Asian populations with a 0 score. In this study, we investigated the influence of age and gender on the extent of subclinical coronary atherosclerotic burden within a healthy Asian population with a 0 coronary artery calcium (CAC) score. A total of 934 participants (320 women and 614 men) from Taiwan's Han Chinese population with an initial CAC score of 0 were included in this study.

Corrigendum: Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

[This corrects the article DOI: 10.3389/fonc.2023.

Clinical radiomics-based machine learning versus three-dimension convolutional neural network analysis for differentiation of thymic epithelial tumors from other prevascular mediastinal tumors on chest computed tomography scan.

Purpose: To compare the diagnostic performance of radiomic analysis with machine learning (ML) model with a convolutional neural network (CNN) in differentiating thymic epithelial tumors (TETs) from other prevascular mediastinal tumors (PMTs).

Methods: A retrospective study was performed in patients with PMTs and undergoing surgical resection or biopsy in National Cheng Kung University Hospital, Tainan, Taiwan, E-Da Hospital, Kaohsiung, Taiwan, and Kaohsiung Veterans General Hospital, Kaohsiung, Taiwan between January 2010 and December 2019. Clinical data including age, sex, myasthenia gravis (MG) symptoms and pathologic diagnosis were collected.

Prediction of Interval Growth of Lung Adenocarcinomas Manifesting as Persistent Subsolid Nodules ≤3 cm Based on Radiomic Features.

Rationales And Objectives: To investigate the prognostic value of the radiomic-based prediction model in predicting the interval growth rate of persistent subsolid nodules (SSNs) with an initial size of ≤ 3 cm manifesting as lung adenocarcinomas.

Materials And Methods: A total of 133 patients (mean age, 59.02 years; male, 37.

An integrated nomogram combined semantic-radiomic features to predict invasive pulmonary adenocarcinomas in subjects with persistent subsolid nodules.

Background: Patients with persistent pulmonary subsolid nodules have a relatively high incidence of lung adenocarcinoma. Preoperative early diagnosis of invasive pulmonary adenocarcinoma spectrum lesions could help avoid extensive advanced cancer management and overdiagnosis in lung cancer screening programs.

Methods: In total, 260 consecutive patients with persistent subsolid nodules ≤30 mm (n=260) confirmed by surgical pathology were retrospectively investigated from February 2016 to August 2020 at the Kaohsiung Veterans General Hospital.