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1000 Titel
  • Value of virtual non-contrast images to identify uncomplicated cystic renal lesions: photon-counting detector CT vs. dual-energy integrating detector CT
1000 Autor/in
  1. Rau, Stephan |
  2. Rau, Alexander |
  3. Stein, Thomas |
  4. Hagar, Muhammad Taha |
  5. Faby, Sebastian |
  6. Bamberg, Fabian |
  7. Weiss, Jakob |
1000 Verlag Springer Milan
1000 Erscheinungsjahr 2024
1000 Publikationstyp
  1. Artikel |
1000 Online veröffentlicht
  • 2024-03-21
1000 Erschienen in
1000 Quellenangabe
  • 129(5):669-676
1000 Copyrightjahr
  • 2024
1000 Lizenz
1000 Verlagsversion
  • https://doi.org/10.1007/s11547-024-01801-2 |
  • https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11088563/ |
1000 Publikationsstatus
1000 Begutachtungsstatus
1000 Sprache der Publikation
1000 Abstract/Summary
  • <jats:title>Abstract</jats:title><jats:sec> <jats:title>Purpose</jats:title> <jats:p>To investigate the value of photon-counting detector CT (PCD-CT) derived virtual non-contrast (VNC) reconstructions to identify renal cysts in comparison with conventional dual-energy integrating detector (DE EID) CT-derived VNC reconstructions.</jats:p> </jats:sec><jats:sec> <jats:title>Material and methods</jats:title> <jats:p>We prospectively enrolled consecutive patients with simple renal cysts (Bosniak classification—Version 2019, density ≤ 20 HU and/or enhancement ≤ 20 HU) who underwent multiphase (non-contrast, arterial, portal venous phase) PCD-CT and for whom non-contrast and portal venous phase DE EID-CT was available. Subsequently, VNC reconstructions were calculated for all contrast phases and density as well as contrast enhancement within the cysts were measured and compared. MRI and/or ultrasound served as reference standards for lesion classification.</jats:p> </jats:sec><jats:sec> <jats:title>Results</jats:title> <jats:p>19 patients (1 cyst per patient; age 69.5 ± 10.7 years; 17 [89.5%] male) were included. Density measurements on PCD-CT non-contrast and VNC reconstructions (arterial and portal venous phase) revealed no significant effect on HU values (<jats:italic>p</jats:italic> = 0.301). In contrast, a significant difference between non-contrast vs. VNC images was found for DE EID-CT (<jats:italic>p</jats:italic> = 0.02). For PCD-CT, enhancement for VNC reconstructions was &lt; 20 HU for all evaluated cysts. DE EID-CT measurements revealed an enhancement of &gt; 20 HU in five lesions (26.3%) using the VNC reconstructions, which was not seen with the non-contrast images.</jats:p> </jats:sec><jats:sec> <jats:title>Conclusion</jats:title> <jats:p>PCD-CT-derived VNC images allow for reliable and accurate characterization of simple cystic renal lesions similar to non-contrast scans whereas VNC images calculated from DE EID-CT resulted in substantial false characterization. Thus, PCD-CT-derived VNC images may substitute for non-contrast images and reduce radiation dose and follow-up imaging.</jats:p> </jats:sec>
1000 Sacherschließung
lokal Female [MeSH]
lokal Kidney Diseases, Cystic/diagnostic imaging [MeSH]
lokal Aged, 80 and over [MeSH]
lokal Aged [MeSH]
lokal Humans [MeSH]
lokal Prospective Studies [MeSH]
lokal X-Ray Computed
lokal Photon-Counting CT
lokal Middle Aged [MeSH]
lokal Tomography, X-Ray Computed/methods [MeSH]
lokal Abdominal Radiology
lokal Tomography
lokal Photons [MeSH]
lokal Male [MeSH]
lokal Renal lesions
lokal Radiography, Dual-Energy Scanned Projection/methods [MeSH]
lokal Virtual non-contrast
1000 Fächerklassifikation (DDC)
1000 Liste der Beteiligten
  1. https://orcid.org/0000-0002-8992-2401|https://frl.publisso.de/adhoc/uri/UmF1LCBBbGV4YW5kZXI=|https://frl.publisso.de/adhoc/uri/U3RlaW4sIFRob21hcw==|https://frl.publisso.de/adhoc/uri/SGFnYXIsIE11aGFtbWFkIFRhaGE=|https://frl.publisso.de/adhoc/uri/RmFieSwgU2ViYXN0aWFu|https://frl.publisso.de/adhoc/uri/QmFtYmVyZywgRmFiaWFu|https://frl.publisso.de/adhoc/uri/V2Vpc3MsIEpha29i
1000 Hinweis
  • DeepGreen-ID: 00a52aca93c847608aa1104df2efab94 ; metadata provieded by: DeepGreen (https://www.oa-deepgreen.de/api/v1/), LIVIVO search scope life sciences (http://z3950.zbmed.de:6210/livivo), Crossref Unified Resource API (https://api.crossref.org/swagger-ui/index.html), to.science.api (https://frl.publisso.de/), ZDB JSON-API (beta) (https://zeitschriftendatenbank.de/api/), lobid - Dateninfrastruktur für Bibliotheken (https://lobid.org/resources/search) ;
1000 Label
1000 Förderer
  1. Ministerium für Wirtschaft, Arbeit und Wohnungsbau Baden-Württemberg |
  2. Siemens Healthineers |
  3. Universitätsklinikum Freiburg |
1000 Fördernummer
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  3. -
1000 Förderprogramm
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  3. -
1000 Dateien
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    1000 Förderer Ministerium für Wirtschaft, Arbeit und Wohnungsbau Baden-Württemberg |
    1000 Förderprogramm -
    1000 Fördernummer -
  2. 1000 joinedFunding-child
    1000 Förderer Siemens Healthineers |
    1000 Förderprogramm -
    1000 Fördernummer -
  3. 1000 joinedFunding-child
    1000 Förderer Universitätsklinikum Freiburg |
    1000 Förderprogramm -
    1000 Fördernummer -
1000 Objektart article
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1000 Erstellt am 2025-07-06T06:25:21.661+0200
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1000 Objekt bearb. Mon Aug 04 09:57:10 CEST 2025
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