Characterizing incidental mass lesions in abdominal dual-energy CT compared to conventional contrast-enhanced CT

Jack Junchi Xu*, Peter Sommer Ulriksen, Camilla Wium Bjerrum, Michael Patrick Achiam, Timothy Andrew Resch, Lars Lönn, Kristoffer Lindskov Hansen

*Corresponding author for this work

Abstract

BACKGROUND: Incidental findings are common in abdominal computed tomography (CT) and often warrant further investigations with economic implications as well as implications for patients.

PURPOSE: To evaluate the potential of dual-energy CT (DECT) in the identification and/or characterization of abdominal incidental mass lesions compared to conventional contrast-enhanced CT.

MATERIAL AND METHODS: This retrospective study from a major tertiary hospital included 96 patients, who underwent contrast-enhanced abdominal DECT. Incidental lesions in adrenals, kidneys, liver, and pancreas were evaluated by two board-certified abdominal radiologists. Observer 1 only had access to standard CT reconstructions, while observer 2 had access to standard CT as well as DECT reconstructions. Disagreements were resolved by consensus review and used as a reference for observers using McNemar's test.

RESULTS: Observers 1 and 2 identified a total of 40 and 34 findings, respectively. Furthermore, observer 1 registered 13 lesions requiring follow-up, of which seven (two renal and five adrenal lesions) were resolved following consensus review using DECT (P = 0.008). The inter-observer agreement was near perfect (κ = 0.82).

CONCLUSION: DECT has the potential to improve the immediate characterization of incidental findings when compared to conventional CT for abdominal imaging.

Original languageEnglish
JournalActa Radiologica
Volume64
Issue number3
Pages (from-to)945-950
Number of pages6
ISSN0284-1851
DOIs
Publication statusPublished - Mar 2023

Keywords

  • Abdomen/diagnostic imaging
  • Contrast Media
  • Humans
  • Liver
  • Radiography, Dual-Energy Scanned Projection/methods
  • Retrospective Studies
  • Tomography, X-Ray Computed/methods

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