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Computed Tomography Urography: State of the Art and Beyond
Computed Tomography Urography (CTU) is a multiphase CT examination optimized for imaging kidneys, ureters, and bladder, complemented by post-contrast excretory phase imaging. Different protocols are available for contrast administration and image acquisition and timing, with different strengths and...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10204399/ https://www.ncbi.nlm.nih.gov/pubmed/37218935 http://dx.doi.org/10.3390/tomography9030075 |
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author | Cellina, Michaela Cè, Maurizio Rossini, Nicolo’ Cacioppa, Laura Maria Ascenti, Velio Carrafiello, Gianpaolo Floridi, Chiara |
author_facet | Cellina, Michaela Cè, Maurizio Rossini, Nicolo’ Cacioppa, Laura Maria Ascenti, Velio Carrafiello, Gianpaolo Floridi, Chiara |
author_sort | Cellina, Michaela |
collection | PubMed |
description | Computed Tomography Urography (CTU) is a multiphase CT examination optimized for imaging kidneys, ureters, and bladder, complemented by post-contrast excretory phase imaging. Different protocols are available for contrast administration and image acquisition and timing, with different strengths and limits, mainly related to kidney enhancement, ureters distension and opacification, and radiation exposure. The availability of new reconstruction algorithms, such as iterative and deep-learning-based reconstruction has dramatically improved the image quality and reducing radiation exposure at the same time. Dual-Energy Computed Tomography also has an important role in this type of examination, with the possibility of renal stone characterization, the availability of synthetic unenhanced phases to reduce radiation dose, and the availability of iodine maps for a better interpretation of renal masses. We also describe the new artificial intelligence applications for CTU, focusing on radiomics to predict tumor grading and patients’ outcome for a personalized therapeutic approach. In this narrative review, we provide a comprehensive overview of CTU from the traditional to the newest acquisition techniques and reconstruction algorithms, and the possibility of advanced imaging interpretation to provide an up-to-date guide for radiologists who want to better comprehend this technique. |
format | Online Article Text |
id | pubmed-10204399 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-102043992023-05-24 Computed Tomography Urography: State of the Art and Beyond Cellina, Michaela Cè, Maurizio Rossini, Nicolo’ Cacioppa, Laura Maria Ascenti, Velio Carrafiello, Gianpaolo Floridi, Chiara Tomography Review Computed Tomography Urography (CTU) is a multiphase CT examination optimized for imaging kidneys, ureters, and bladder, complemented by post-contrast excretory phase imaging. Different protocols are available for contrast administration and image acquisition and timing, with different strengths and limits, mainly related to kidney enhancement, ureters distension and opacification, and radiation exposure. The availability of new reconstruction algorithms, such as iterative and deep-learning-based reconstruction has dramatically improved the image quality and reducing radiation exposure at the same time. Dual-Energy Computed Tomography also has an important role in this type of examination, with the possibility of renal stone characterization, the availability of synthetic unenhanced phases to reduce radiation dose, and the availability of iodine maps for a better interpretation of renal masses. We also describe the new artificial intelligence applications for CTU, focusing on radiomics to predict tumor grading and patients’ outcome for a personalized therapeutic approach. In this narrative review, we provide a comprehensive overview of CTU from the traditional to the newest acquisition techniques and reconstruction algorithms, and the possibility of advanced imaging interpretation to provide an up-to-date guide for radiologists who want to better comprehend this technique. MDPI 2023-04-30 /pmc/articles/PMC10204399/ /pubmed/37218935 http://dx.doi.org/10.3390/tomography9030075 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Cellina, Michaela Cè, Maurizio Rossini, Nicolo’ Cacioppa, Laura Maria Ascenti, Velio Carrafiello, Gianpaolo Floridi, Chiara Computed Tomography Urography: State of the Art and Beyond |
title | Computed Tomography Urography: State of the Art and Beyond |
title_full | Computed Tomography Urography: State of the Art and Beyond |
title_fullStr | Computed Tomography Urography: State of the Art and Beyond |
title_full_unstemmed | Computed Tomography Urography: State of the Art and Beyond |
title_short | Computed Tomography Urography: State of the Art and Beyond |
title_sort | computed tomography urography: state of the art and beyond |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10204399/ https://www.ncbi.nlm.nih.gov/pubmed/37218935 http://dx.doi.org/10.3390/tomography9030075 |
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