The goal of this updated 2022 CAD-RADS 2.0 is to improve the initial reporting system for CCTA by considering new technical developments in Cardiac CT, including data from recent clinical trials and new clinical guidelines. Electronic address: Artery Disease Reporting and Data System (CAD-RADS) was created to standardize reporting system for patients undergoing coronary CT angiography (CCTA) and to guide possible next steps in patient management.
Electronic address: 2 Department of Radiology, University of British Columbia, Vancouver, BC, Canada. Electronic address: 1 Miami Cardiac and Vascular Institute and Baptist Health of South Florida, Miami FL, USA. 21 Division of Cardiology, University of Virginia Health System, Charlottesville, VA, USA.20 University of Maryland, College Park, MD, USA.19 Department of Radiology, Mayo Clinic, Rochester, MN, USA.18 University of Edinburgh, Edinburgh, UK.17 Icahn School of Medicine at Mount Sinai, New York, NY, USA.16 Department of Radiology, University of Cincinnati College of Medicine, Cincinnati, OH, USA.15 Department of Medical Imaging, University of Arizona, Tucson, AZ, USA.14 Department of Radiology, Naval Medical Center, Portsmouth, VA, USA.13 Division of Cardiology, Minneapolis Heart Institute, Minneapolis, MN, USA.12 Department of Radiology, Duke University, Durham, NC, USA.11 NYU Langone Medical Center, New York, NY, USA.10 Department of Radiology, Massachusetts General Hospital, Boston, MA, USA.9 The George Washington University School of Medicine, Washington, DC, USA.8 Beaumont Hospital, Royal Oak, MI, USA.7 David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.6 Division of Cardiology, University of Pittsburgh, Pittsburgh, PA, USA.
5 Cedars-Sinai Medical Center, Los Angeles, CA, USA.4 Friedrich-Alexander-Universität, Department of Cardiology, Erlangen, Germany.3 Department of Radiology, UT Southwestern Medical Center, Dallas, TX, USA.1 Miami Cardiac and Vascular Institute and Baptist Health of South Florida, Miami FL, USA.Identification of Unique Neoantigen Qualities in Long-Term Survivors of Pancreatic Cancer. VDJdb in 2019: Database Extension, New Analysis Infrastructure and a T-Cell Receptor Motif Compendium. A., Samir J., Stervbo U., Rius C., Dolton G., et al. Accurate Pan-specific Prediction of Peptide-MHC Class II Binding Affinity with Improved Binding Core Identification. 10.1093/nar/gkn673Īndreatta M., Karosiene E., Rasmussen M., Stryhn A., Buus S., Nielsen M. CTdatabase: a Knowledge-Base of High-Throughput and Curated Data on Cancer-Testis Antigens. A Loss of Antitumor Therapeutic Activity of CEA DNA Vaccines Is Associated with the Lack of Tumor Cells' Antigen Presentation to Ag-specific CTLs in a colon Cancer Model. A platform, Cancer Antigens Database (CAD, ), was designed to facilitate users to perform a complete exploration of cancer antigens online.Ĭancer antigen neoantigen prediction model tumor-associated antigens (TAAs) tumor-specific antigens (TSAs).Ĭopyright © 2022 Yu, Wang, Kong, Cao, Zhang, Sun, Liu, Wang, Shen, Bo and Feng.Īhn E., Kim H., Han K. Then, we discussed the role of each dataset for algorithm improvement in cancer antigen research, especially neoantigen prediction.
Here, we recruited verified cancer antigen peptides and collected as much relevant peptide information as possible. However, due to the lack of verified neoantigen datasets and insufficient research on the properties of neoantigens, neoantigen prediction algorithms still need to be improved. The rapid prediction and filtering of neoantigen peptides are crucial to the development of neoantigen-based cancer vaccines. With the development of next-generation sequencing technologies and related algorithms, pipelines based on sequencing and machine learning methods have become mainstream in cancer antigen prediction of particular focus are neoantigens, mutation peptides that only exist in tumor cells that lack central tolerance and have fewer side effects. Cancer vaccines have gradually attracted attention for their tremendous preclinical and clinical performance.
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