Download full-text PDF |
Source |
---|
Nagoya J Med Sci
November 2024
Department of Thoracic Surgery, Nagoya University Graduate School of Medicine, Nagoya, Japan.
Peribronchiolar metaplasia is an uncommon lesion characterized by fibrosis and bronchiolar epithelial cell proliferation along the peribronchiolar alveolar walls, primarily in response to bronchiolar and peribronchiolar injuries. Peribronchiolar metaplasia usually appears as ground glass nodules or sub-solid nodules on computed tomography. However, we present an exceptional case of peribronchiolar metaplasia that appeared as a solitary solid nodule on computed tomography.
View Article and Find Full Text PDFNat Protoc
January 2025
Department of Molecular Metabolism, Harvard T.H. Chan School of Public Health, Boston, MA, USA.
Premetastatic cancer cells often spread from the primary lesion through the lymphatic vasculature and, clinically, the presence or absence of lymph node metastases impacts treatment decisions. However, little is known about cancer progression via the lymphatic system or of the effect that the lymphatic environment has on cancer progression. This is due, in part, to the technical challenge of studying lymphatic vessels and collecting lymph fluid.
View Article and Find Full Text PDFCancer Commun (Lond)
January 2025
Institute of Molecular Medicine, Section for RNA biology and pathogenesis, Faculty of Medicine, Martin Luther University Halle-Wittenberg, Halle (Saale), Germany.
J Cardiothorac Surg
January 2025
Department of Pathology, Xiangtan Central Hospital, Xiangtan, 411100, Hunan Province, China.
Introduction: Primary pulmonary meningioma is a rare disease. There have been only a little over 50 cases of primary pulmonary meningioma (PPM) reported in previous literature. The pathogenesis of PPM is still unclear.
View Article and Find Full Text PDFDiagnostics (Basel)
December 2024
Department of Respiratory Medicine, JSS Medical College, JSS Academy of Higher Education & Research (JSS AHER), Mysore 570004, Karnataka, India.
Thin-section CT (TSCT) is currently the most sensitive imaging modality for detecting bronchiectasis. However, conventional TSCT or HRCT may overlook subtle lung involvement such as alveolar and interstitial changes. Artificial Intelligence (AI)-based analysis offers the potential to identify novel information on lung parenchymal involvement that is not easily detectable with traditional imaging techniques.
View Article and Find Full Text PDFEnter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!