CT imaging provides physicians valuable insights when diagnosing disease in a clinical setting. In order to provide an accurate diagnosis, is it important to have a high accuracy with controlled variability across CT scans from different scanners and imaging parameters. The purpose of this study was to analyze variability of lung imaging biomarkers across various scanners and parameters using a customized version of a commercially available anthropomorphic chest Phantom (Kyoto Kagaku) with several experimental sample inserts. The phantom was across 10 different CT scanners with a total of 209 imaging conditions. An algorithm was developed to compute different imaging biomarkers. Variability across images from the same scanner and from different scanners was analyzed by computing coefficients of variation (CV) and standard deviations of HU values. LAA -950 and LAA -856 biomarkers had the highest levels of variability, while the majority of other biomarkers had variability less than 10 HU or 10% CV in both inter and intra-scan measurements. There was no clear trend present between the biomarker measurements and CTDIvol. The results of this study demonstrates the existing variability in CT quantifications for lung imaging, which prompt further studies on how to reduce such variation.
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http://dx.doi.org/10.1117/12.2613191 | DOI Listing |
JCO Clin Cancer Inform
January 2025
Machine Learning Department, H. Lee Moffit Cancer Center and Research Institute, Tampa, FL.
Purpose: Adaptive radiotherapy accounts for interfractional anatomic changes. We hypothesize that changes in the gross tumor volumes identified during daily scans could be analyzed using delta-radiomics to predict disease progression events. We evaluated whether an auxiliary data set could improve prediction performance.
View Article and Find Full Text PDFMuscle Nerve
January 2025
Division of Neurology, Department of Medicine, University of Saskatchewan, Saskatoon, Saskatchewan, Canada.
Introduction/aims: Spirometry is the conventional means to measure lung function in amyotrophic lateral sclerosis (ALS), but is dependent on patient effort and bulbar strength. We aimed to use electric impedance tomography (EIT), an emerging non-invasive imaging modality, to measure dynamic lung volume changes.
Methods: Twenty-one patients with ALS underwent sitting and supine spirometry for forced vital capacity (FVC), and sitting and supine EIT.
Cancer Rep (Hoboken)
January 2025
Department of Thoracic Surgery, Affiliated Hospital of Zunyi Medical College, Zunyi, People's Republic of China.
Background: Neuroendocrine tumors of the thymus (NETT) are rare and malignant tumors that arise in the anterior mediastinum. These tumors can exhibit aggressive behavior and may involve surrounding critical structures, such as the superior vena cava. This case contributes to the literature by presenting a recurrent thymic carcinoma with invasion of major blood vessels, including the superior vena cava, and the complexities involved in its surgical management.
View Article and Find Full Text PDFThorac Cancer
January 2025
Department of Thoracic Surgery and Lung Transplantation, The Fifth Affiliated Hospital of Sun Yat-Sen University, Zhuhai, Guangdong, China.
Background: The mycobiome in the tumor microenvironment of non-smokers with early-stage lung adenocarcinoma (ES-LUAD) has been minimally investigated.
Methods: In this study, we conducted ultra-deep metagenomic and transcriptomic sequencing on 128 samples collected from 46 nonsmoking ES-LUAD patients and 41 healthy controls (HC), aiming to characterize the tumor-resident mycobiome and its interactions with the host.
Results: The results revealed that ES-LUAD patients exhibited fungal dysbiosis characterized by reduced species diversity and significant imbalances in specific fungal abundances.
Intensive Care Med
January 2025
Medical Intensive Care Unit, AP-HP, Saint-Louis Hospital, Paris-Cité University, INSERM UMR1342 Institut de Recherche Saint-Louis, Paris, France.
Purpose: Invasive pulmonary aspergillosis (IPA) is a life-threatening opportunistic infection in immunocompromised patients. The diagnosis is often made late, with mortality reaching 90% when mechanical ventilation is needed. We sought to develop and validate a risk prediction model for the diagnosis of IPA.
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