Virtual unenhanced images at dual-energy CT

• Verfasst von: Meyer, Mathias [VerfasserIn]
• Verfasst von: Henzler, Thomas [VerfasserIn]
• Verfasst von: Schönberg, Stefan [VerfasserIn]
• Titel: Virtual unenhanced images at dual-energy CT
• Titelzusatz: influence on renal lesion characterization
• Verf.angabe: Mathias Meyer, Rendon C. Nelson, Federica Vernuccio, Fernando González, Alfredo E. Farjat, Bhavik N. Patel, Ehsan Samei, Thomas Henzler, Stefan O. Schoenberg, Daniele Marin
• E-Jahr: 2019
• Jahr: Mar 12 2019
• Umfang: 10 S.
• Fussnoten: Gesehen am 04.07.2019
• Titel Quelle: Enthalten in: Radiology
• Ort Quelle: Oak Brook, Ill. : Soc., 1923
• Jahr Quelle: 2019
• Band/Heft Quelle: 291(2019), 2, Seite 381-390
• ISSN Quelle: 1527-1315
• DOI: doi:10.1148/radiol.2019181100
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1668587459

Abstract

BackgroundDual-energy (DE) CT allows reconstruction of virtual noncontrast (VNC) images from a single-phase contrast agent-enhanced examination, potentially reducing the need for multiphasic CT to characterize renal lesions. However, data regarding diagnostic performance of VNC images for the characterization of renal lesions are limited.PurposeTo determine whether renal mass CT performed by using VNC images allows for reliable identification of renal lesions and differentiation of contrast-enhanced from unenhanced lesions, compared with unenhanced images.Materials and MethodsThis is a retrospective study of 293 patients (105 women [mean age, 65 years; age range, 18-91 years] and 188 men [mean age, 66 years; age range, 23-90 years] with 379 renal lesions [craniocaudal diameter, 1.0-4.0 cm]) who underwent a single-energy unenhanced CT examination followed by a nephrographic-phase DE CT between June 2013 and October 2017 by using one of four different DE CT platforms from two vendors. VNC images were calculated by using vendor-specific algorithms. Each lesion was classified in a blinded and independent fashion by using the VNC or unenhanced image in combination with the nephrographic images. Attenuation measurements were obtained on the VNC, unenhanced, and nephrographic images. Unenhanced images and pathologic or imaging follow-up for more than 24 months served as reference standard.ResultsThere was strong overall agreement between VNC and unenhanced images for renal lesion characterization (Cramer V = 0.85). VNC images yielded a high diagnostic performance (area under the receiver operating characteristic curve, 0.91; 95% confidence interval: 0.86, 0.95) for facilitation of differentiation of contrast-enhanced from unenhanced renal lesions. However, there was a reduction in diagnostic performance for depicting contrast-enhanced renal lesions by using VNC compared with unenhanced images (area under the receiver operating characteristic curve, 0.91 [95% confidence interval: 0.86, 0.95] vs 0.96 [95% confidence interval: 0.93, 0.99]; P < .001). Mean absolute difference between the VNC and unenhanced attenuation was 9.2 HU ± 8.7.ConclusionVirtual noncontrast images enabled accurate renal lesion characterization, albeit with a reduction in diagnostic performance for contrast-enhanced lesion characterization.© RSNA, 2019Online supplemental material is available for this article.