Objective: We aimed to evaluate the usefulness of computed tomographic (CT) fluoroscopy guidance for transthoracic needle biopsies.
Methods And Material: CT fluoroscopy-guided biopsies were performed in 81 patients with thoracic mass lesions. Interrupted CT fluoroscopy technique was used with 50-130 mA at 120 kV exposure parameters and slice thickness of 10 mm. We used aspirating needle in 41 patients, cutting needle in 28 patients, and both in 12 patients. We obtained adequate biopsy material in 69 patients at first attempt. Mean fluoroscopy time was 15.17 s and maximum procedure time was 18 min.
Results: Adequate samples for pathological diagnosis were obtained in all lesions. Pathological diagnoses were malignant in 41 patients, benign in 27 patients, and suspiciously malignant in 13 patients. There was no significant difference between diagnostic accuracy of the needles in malignant and benign lesions. Complications were observed in 11 patients (13.5%).
Discussion And Conclusion: CT fluoroscopy-guided technique provides effective real-time needle biopsy in patients with small tumor size and with tumor located near blood vessels, and in non-compliant patients for diagnosing thoracic lesions.
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http://dx.doi.org/10.1016/S0720-048X(02)00348-0 | DOI Listing |
JMIR Form Res
January 2025
Larner College of Medicine, University of Vermont, Burlington, VT, United States.
Background: Social media has become a widely used way for people to share opinions about health care and medical topics. Social media data can be leveraged to understand patient concerns and provide insight into why patients may turn to the internet instead of the health care system for health advice.
Objective: This study aimed to develop a method to investigate Reddit posts discussing health-related conditions.
JMIR Form Res
January 2025
Northwestern Medicine, Chicago, IL, United States.
Background: Patient recruitment and data management are laborious, resource-intensive aspects of clinical research that often dictate whether the successful completion of studies is possible. Technological advances present opportunities for streamlining these processes, thus improving completion rates for clinical research studies.
Objective: This paper aims to demonstrate how technological adjuncts can enhance clinical research processes via automation and digital integration.
JMIR Serious Games
January 2025
School of Computing, Engineering and Mathematical Sciences, Optus Chair Digital Health, La Trobe University, Melbourne, Australia.
Background: This review explores virtual reality (VR) and exercise simulator-based interventions for individuals with attention-deficit/hyperactivity disorder (ADHD). Past research indicates that both VR and simulator-based interventions enhance cognitive functions, such as executive function and memory, though their impacts on attention vary.
Objective: This study aimed to contribute to the ongoing scientific discourse on integrating technology-driven interventions into the management and evaluation of ADHD.
JMIR AI
January 2025
Department of Information Systems and Business Analytics, Iowa State University, Ames, IA, United States.
Background: In the contemporary realm of health care, laboratory tests stand as cornerstone components, driving the advancement of precision medicine. These tests offer intricate insights into a variety of medical conditions, thereby facilitating diagnosis, prognosis, and treatments. However, the accessibility of certain tests is hindered by factors such as high costs, a shortage of specialized personnel, or geographic disparities, posing obstacles to achieving equitable health care.
View Article and Find Full Text PDFJMIR Med Inform
January 2025
Department of Systems Design Engineering, Faculty of Engineering, University of Waterloo, Waterloo, ON, Canada.
Background: While expert optometrists tend to rely on a deep understanding of the disease and intuitive pattern recognition, those with less experience may depend more on extensive data, comparisons, and external guidance. Understanding these variations is important for developing artificial intelligence (AI) systems that can effectively support optometrists with varying degrees of experience and minimize decision inconsistencies.
Objective: The main objective of this study is to identify and analyze the variations in diagnostic decision-making approaches between novice and expert optometrists.
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