Graphical monitoring of the state of the system patient-apparatus for artificial lung ventilation (MLV) provides instant and illustrative information about the state of the system, which is particularly important under conditions of resuscitation and intensive care. Graphs of time dependence of gas pressure in respiratory pathways, gas flow rate, and changes of lung volume during respiration cycle provide on-line information about ventilation mode and patient state including lungs, respiratory pathways, positive pressure at the end of exhalation, etc. These curves allow MLV efficacy to be monitored and improved. Under certain conditions the capnogram shape provides an opportunity for objective evaluation of ventilation adequacy and patient state. The shapes of the curves in the norm and various pathology are considered. This graphical information is concluded to be important for effective use of modern MLV apparatuses for intensive care and resuscitation.
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Radiology
January 2025
Stanford University School of Medicine, Department of Radiation Oncology, Stanford, CA, US.
Background Detection and segmentation of lung tumors on CT scans are critical for monitoring cancer progression, evaluating treatment responses, and planning radiation therapy; however, manual delineation is labor-intensive and subject to physician variability. Purpose To develop and evaluate an ensemble deep learning model for automating identification and segmentation of lung tumors on CT scans. Materials and Methods A retrospective study was conducted between July 2019 and November 2024 using a large dataset of CT simulation scans and clinical lung tumor segmentations from radiotherapy plans.
View Article and Find Full Text PDFFront Pharmacol
January 2025
Department of Pulmonary and Critical Care Medicine II, Emergency General Hospital, Beijing, China.
Existing studies indicate that dysregulation or abnormal expression of small nucleolar RNA (snoRNA) is closely associated with various diseases, including lung cancer. Furthermore, these diseases often involve multiple targets, making the redevelopment of traditional medicines highly promising. Accurate prediction of potential snoRNA therapeutic targets is essential for early disease intervention and the redevelopment of traditional medicines.
View Article and Find Full Text PDFTransl Lung Cancer Res
December 2024
Center for Cancer Diagnosis and Treatment, The Second Affiliated Hospital of Soochow University, Suzhou, China.
Background: Prognosis prediction is crucial for non-small cell lung cancer (NSCLC) treatment planning. While tumor hypoxia significantly impacts patient outcomes, identifying hypoxic genomic markers remains challenging. This study sought to identify hypoxic computed tomography (CT) radiomic features and create an artificial intelligence (AI) model for NSCLC through the integration of multi-modal data.
View Article and Find Full Text PDFTransl Lung Cancer Res
December 2024
Department of Physics and Center for Complexity and Biosystems, Università degli Studi di Milano and INFN, Milano, Italy.
Background: Non-small cell lung cancers (NSCLCs) with fusions are effectively treated with tyrosine kinase inhibitors (TKIs). The widespread use of next-generation sequencing (NGS) assays to study the molecular profile of NSCLCs, can identify rare fusion partners of . Therapy decisions are made without considering which fusion partner is present and its potential oncogenic properties.
View Article and Find Full Text PDFTransl Lung Cancer Res
December 2024
Division of Pulmonology, Allergy and Critical Care Medicine, Department of Internal Medicine, Yongin Severance Hospital, Yonsei University College of Medicine, Yongin, Republic of Korea.
Background: Despite the importance of early diagnosis of lung cancer and wide availability of chest radiography, the detection of operable stage lung cancer on chest radiographs (CXRs) remains challenging. This study aimed to investigate the effectiveness of artificial intelligence (AI)-based CXR analysis for detecting operable lung cancers.
Methods: Patients who underwent lung cancer surgery at two referral hospitals between March 2020 and February 2021 were retrospectively included in this study.
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