We compared interexamination variability of CT lung nodule volumetry with six currently available semi-automated software packages to determine the minimum change needed to detect the growth of solid lung nodules. We had ethics committee approval. To simulate a follow-up examination with zero growth, we performed two low-dose unenhanced CT scans in 20 patients referred for pulmonary metastases. Between examinations, patients got off and on the table. Volumes of all pulmonary nodules were determined on both examinations using six nodule evaluation software packages. Variability (upper limit of the 95% confidence interval of the Bland-Altman plot) was calculated for nodules for which segmentation was visually rated as adequate. We evaluated 214 nodules (mean diameter 10.9 mm, range 3.3 mm-30.0 mm). Software packages provided adequate segmentation in 71% to 86% of nodules (p < 0.001). In case of adequate segmentation, variability in volumetry between scans ranged from 16.4% to 22.3% for the various software packages. Variability with five to six software packages was significantly less for nodules >or=8 mm in diameter (range 12.9%-17.1%) than for nodules <8 mm (range 18.5%-25.6%). Segmented volumes of each package were compared to each of the other packages. Systematic volume differences were detected in 11/15 comparisons. This hampers comparison of nodule volumes between software packages.
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http://dx.doi.org/10.1007/s00330-008-1229-x | DOI Listing |
J Cancer Res Ther
December 2024
Department of Colorectal Surgery, Shanghai Cancer Center, Fudan University, Xuhui District, Shanghai, China.
Objective: Carbohydrate antigen 19-9 (CA19-9) and carcinoembryonic antigen (CEA) serve as pivotal tumor markers in colorectal cancer (CRC). However, uncertainty persists regarding the prognostic significance of the two tumor markers when falling within the normal range. We attempt to compare the prognostic differences of tumor markers at different levels within the reference range.
View Article and Find Full Text PDFJ Phys Chem B
January 2025
Department of Physiology and Biophysics, Weill Cornell Medical College, New York, New York 10065, United States.
ModeHunter is a modular Python software package for the simulation of 3D biophysical motion across spatial resolution scales using modal analysis of elastic networks. It has been curated from our in-house Python scripts over the last 15 years, with a focus on detecting similarities of elastic motion between atomic structures, coarse-grained graphs, and volumetric data obtained from biophysical or biomedical imaging origins, such as electron microscopy or tomography. With ModeHunter, normal modes of biophysical motion can be analyzed with various static visualization techniques or brought to life by dynamics animation in terms of single or multimode trajectories or decoy ensembles.
View Article and Find Full Text PDFObjectives: To identify cuproptosis- and ferroptosis-related genes involved in nonalcoholic fatty liver disease and to determine the diagnostic value of hub genes.
Methods: The gene expression dataset GSE89632 was retrieved from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) between the non-alcoholic steatohepatitis (NASH) group and the healthy group using the 'limma' package in R software and weighted gene co-expression network analysis. Gene ontology, kyoto encyclopedia of genes and genomes pathway, and single-sample gene set enrichment analyses were performed to identify functional enrichment of DEGs.
Mol Cell Proteomics
January 2025
Department of Pharmaceutical Chemistry, University of California, San Francisco.
Glycosylation is the most common and diverse modification of proteins. It can affect protein function and stability and is associated with many diseases. While proteomic methods to study most post-translational modifications are now quite mature, glycopeptide analysis is still a challenge, particularly from the aspect of data analysis.
View Article and Find Full Text PDFBioinformatics
January 2025
Department of Computer Science, City University of Hong Kong, Hong Kong, China.
Motivation: Proteoforms are the different forms of a proteins generated from the genome with various sequence variations, splice isoforms, and post-translational modifications. Proteoforms regulate protein structures and functions. A single protein can have multiple proteoforms due to different modification sites.
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