Introduction: Lung cancer has the highest mortality rate of all types of cancers both in developed countries and Hungary.
Aim: To obtain experience and facilitate the application of low-dose computed tomography-based lung cancer screening as a targeted public health screening procedure.
Method: Volunteers without thoracic complaints above the age of 40 years (n = 963) were screened for lung cancer using digital chest radiography and low-dose computed tomography.
Results: Two lung cancers were found among the participants screened with digital chest radiography (0.2%). After informed consent, 173 individuals with normal chest radiography findings (n = 943) took the opportunity to voluntarily participate in low-dose computed tomography screening for lung cancer. After 3 or 12 months, 65 individuals had follow up control examinations based on the size and characteristics of the detected lesions. Among them, one participant was found to have lung cancer using low-dose computed tomography.
Conclusions: These results indicate that low-dose computed tomography-based lung cancer screening as a public health screening procedure can enhance the success of screening with 50% (from 0.2% to 0.3%). The cost-benefit ratio can be raised if chest radiography is performed prior to the low-dose computed tomography examination.
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http://dx.doi.org/10.1556/OH.2014.29845 | DOI Listing |
BMJ Open
December 2024
Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, USA.
Introduction: Early lung cancer screening (LCS) through low-dose CT (LDCT) is crucial but underused due to various barriers, including incomplete or inaccurate patient smoking data in the electronic health record and limited time for shared decision-making. The objective of this trial is to investigate a patient-centred intervention, MyLungHealth, delivered through the patient portal. The intervention is designed to improve LCS rates through increased identification of eligible patients and informed decision-making.
View Article and Find Full Text PDFInt J Cardiovasc Imaging
January 2025
Artificial Intelligence Center, China Medical University Hospital, China Medical University, Taichung, Taiwan.
Coronary artery calcification (CAC) is a key marker of coronary artery disease (CAD) but is often underreported in cancer patients undergoing non-gated CT or PET/CT scans. Traditional CAC assessment requires gated CT scans, leading to increased radiation exposure and the need for specialized personnel. This study aims to develop an artificial intelligence (AI) method to automatically detect CAC from non-gated, freely-breathing, low-dose CT images obtained from positron emission tomography/computed tomography scans.
View Article and Find Full Text PDFCureus
December 2024
Family Health Unit New Directions, Unidade Local de Saúde do Alto Ave, Vizela, PRT.
Lung cancer is highly prevalent worldwide and is the leading cause of cancer-related death in Portugal. There is increasing evidence that low-dose computed tomography (LDCT) screening reduces mortality; however, few countries have implemented screening strategies. This review aims to gather the best evidence to assess the relevance of implementing lung cancer screening.
View Article and Find Full Text PDFClin Radiol
December 2024
Department of Radiology, The First Affiliated Hospital of Soochow University, Suzhou, Jiangsu, 215006, China. Electronic address:
Aim: To assess transmural remission in patients with Crohn's disease using low-dose small bowel computed tomography (CT) perfusion scans.
Materials And Methods: Forty six patients were divided into active and remission phases based on Crohn's Disease Activity Index (CDAI) and C-reactive protein (CRP). Dual-source CT enterography with low-dose perfusion scans was conducted to generate perfusion parameter maps, including blood flow (BF), blood volume (BV), time to peak (TTP), mean transit time (MTT), and permeability of surface (PS).
J Thorac Oncol
January 2025
Department of General Internal Medicine and Pulmonary Medicine, The University of Texas MD Anderson Cancer Center, Houston, TX, USA.
Hypothesis: To evaluate how comorbidities affect mortality benefits of lung cancer screening (LCS) with low-dose computed-tomography (LDCT).
Methods: We developed a comorbidity index (PLCO-ci) using LCS-eligible participants' data from the Prostate Lung Colorectal and Ovarian (PLCO) trial (training set) and the National Lung Screening Trial (NLST) (validation set). PLCO-ci predicts 5-year non-lung cancer (LC) mortality using a regularized Cox model; with performance evaluated by the area under the ROC curve (ROC).
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