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Abdominal aortic aneurysm (AAA) is a localized dilatation of the aortic wall. Accurate measurements of its geometric characteristics are critical for a reliable estimate of AAA rupture risk. However, current imaging modalities do not provide sufficient contrast to distinguish thrombus from surrounding tissue thus making the task of segmentation quite challenging. The main objective of this paper is to address this problem and accurately extract the thrombus and outer wall boundaries from cross sections of a 3D AAA image data set (CTA). This is achieved by new geometrical methods applied to the boundary curves obtained by a Level Set Method (LSM). Such methods address the problem of leakage of a moving front into sectors of similar intensity and that of the presence of calcifications. The versatility of the methods is tested by creating artificial images which simulate the real cases. Segmentation quality is quantified by comparing the results with a manual segmentation of the slices of ten patient data sets. Sensitivity to the parameter settings and reproducibility are analyzed. This is the first work to our knowledge that utilizes the level set framework to extract both the thrombus and external AAA wall boundaries.
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http://dx.doi.org/10.1016/j.cmpb.2011.06.009 | DOI Listing |
Alzheimers Dement
September 2025
Department of Population Health Sciences, University of Texas Health Science Center at San Antonio, San Antonio, Texas, USA.
Introduction: We compared and measured alignment between the Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard used by electronic health records (EHRs), the Clinical Data Interchange Standards Consortium (CDISC) standards used by industry, and the Uniform Data Set (UDS) used by the Alzheimer's Disease Research Centers (ADRCs).
Methods: The ADRC UDS, consisting of 5959 data elements across eleven packets, was mapped to FHIR and CDISC standards by two independent mappers, with discrepancies adjudicated by experts.
Results: Forty-five percent of the 5959 UDS data elements mapped to the FHIR standard, indicating possible electronic obtainment from EHRs.
Front Genet
August 2025
Department of Gastrointestinal and Hernia Surgery, Ganzhou Hospital-Nanfang Hospital, Southern Medical University, Ganzhou, China.
Background: Gastric cancer (GC) is a leading cause of cancer-related mortality; however, biomarkers predicting its immunotherapy resistance remain scarce. Vascular cell adhesion molecule ()-, an immune cell adhesion mediator, is implicated in tumor progression; however, its prognostic and immunomodulatory roles in GC remain unclear.
Methods: In this study, we analyzed expression and its clinical relevance in GC using RNA-sequencing data from The Cancer Genome Atlas.
Biochem Biophys Rep
June 2025
The Affiliated Traditional Chinese Medicine Hospital, Guangzhou Medical University, Guangzhou, Guangdong Province, China.
Background: SLC16A3, a highly expressed H + -coupled symporter, facilitates lactate transport via monocarboxylate transporters (MCTs), contributing to acidosis. Although SLC16A3 has been implicated in tumor development, its role in tumor immunity remains unclear.
Methods: A pan-cancer analysis was conducted using datasets from The Cancer Genome Atlas, Cancer Cell Line Encyclopedia, and Genotype-Tissue Expression projects.
Appl Biosaf
August 2025
Environmental Science and Health, University of Nevada, Reno, Nevada, USA.
Introduction: This study examines demographic trends among biosafety professionals from 2013 to 2024, focusing on changes in age, race, education, experience, and income. The goal is to inform educational and targeted interventions for the evolving needs of the biosafety profession.
Methods: Surveys were conducted in 2013, 2016, 2020, 2023, and 2024 among ABSA International affiliates and Institutional Biosafety Committee contacts.
Rev Cardiovasc Med
August 2025
Department of Cardiovascular Medicine, University Hospital Leuven, 3000 Leuven, Belgium.
Intravascular optical coherence tomography (OCT) has represented a revolutionary invasive imaging method, offering high-resolution cross-sectional views of human coronary arteries, thereby promoting a significant evolution in the understanding of vascular biology in both acute and chronic coronary pathologies. Since the development of OCT in the early 1990s, this technique has provided detailed insights into vascular biology, enabling a more thorough assessment of coronary artery disease (CAD) and the impact of percutaneous coronary intervention (PCI). Moreover, a series of recent clinical trials has consistently demonstrated the clinical benefits of intravascular imaging (IVI) and OCT-guided PCI, showing improved outcomes compared to angiography-guided procedures, particularly in cases of complex coronary pathology.
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