Purpose Of Review: Current imaging techniques (X-ray, computed tomography scan, ultrasound) have limitations in the identification and quantification of pulmonary diseases, in particular, on highly detailed level. The purpose of this review is to provide an overview of the current knowledge of innovative light- and laser-based imaging techniques that might fill this gap.
Recent Findings: Optical coherence tomography (OCT) and confocal laser endomicroscopy (CLE) are high-resolution imaging techniques, which, combined with bronchoscopy, provide 'near histology' detailed imaging of the airway wall, lung parenchyma, mediastinal lymph nodes, and pulmonary vasculature. This article reviews the technical background of OCT and CLE, summarizes study results, and discusses its potential clinical applications for various pulmonary diseases.
Summary: Although investigational at the moment, OCT and CLE are promising innovative high-resolution optical imaging techniques for the airway wall, lung parenchyma, mediastinal lymph nodes, and pulmonary vasculature. Clinical applications might contribute to improved disease identification and quantification, guidance for interventions/biopsies, and patient selection for treatments. Development of validated identification and quantification image-analysis systems is key for the future application of these imaging techniques in pulmonary medicine.
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http://dx.doi.org/10.1097/MCP.0000000000000375 | DOI Listing |
Lab Anim
January 2025
Institute of Preclinical Sciences, Veterinary Faculty, University of Ljubljana, Slovenia.
Blood sampling is often performed during animal studies. This is more challenging in mice than in larger animal species owing to their size and lack of blood vessel visibility. Guidelines for blood sampling in mice and papers on animal welfare often refer to the submandibular, cheek, buccal, and anterior facial veins.
View Article and Find Full Text PDFExpert Opin Drug Discov
January 2025
Department of Radiology, Molecular Imaging Innovations Institute (MI3), Weill Cornell Medicine, New York, NY, USA.
Introduction: Technological advancements in virtual screening (VS) have rapidly accelerated its application in drug discovery, as reflected by the exponential growth in VS-related publications. However, a significant gap remains between the volume of computational predictions and their experimental validation. This discrepancy has led to a rise in the number of unverified 'claimed' hits which impedes the drug discovery efforts.
View Article and Find Full Text PDFFuture Sci OA
December 2025
Gastroenterology Department, La Rabta Hospital, Tunis, Tunisia.
Background: Colonic stenosis in Crohn's disease (CD) is uncommon, and data on surgery-free survival are limited. This study aimed to determine surgery-free survival rates and identify associated factors.
Patients And Methods: A retrospective study was conducted from 2003 to 2022, including patients with CD complicated by colonic stenosis.
Comput Biol Med
January 2025
Emerging Technologies Research Lab (ETRL), College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia; Department of Computer Science, College of Computer Science and Information Systems, Najran University, Najran, 61441, Saudi Arabia. Electronic address:
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View Article and Find Full Text PDFComput Biol Med
January 2025
School of Computer Science, Chungbuk National University, Cheongju 28644, Republic of Korea. Electronic address:
The fusion index is a critical metric for quantitatively assessing the transformation of in vitro muscle cells into myotubes in the biological and medical fields. Traditional methods for calculating this index manually involve the labor-intensive counting of numerous muscle cell nuclei in images, which necessitates determining whether each nucleus is located inside or outside the myotubes, leading to significant inter-observer variation. To address these challenges, this study proposes a three-stage process that integrates the strengths of pattern recognition and deep-learning to automatically calculate the fusion index.
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