Comparison of enhancement quantification from virtual unenhanced images to true unenhanced images in multiphase renal Dual‐Energy computed tomography: A phantom study

Abstract

Multiphase computed tomography (CT) exams are a commonly used imaging technique for the diagnosis of renal lesions and involve the acquisition of a true unenhanced (TUE) series followed by one or more postcontrast series. The difference in CT number of the mass in pre-and postcontrast images is used to quantify enhancement, which is an important criterion used for diagnosis. This study soughtThis is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

Comparison of virtual to true unenhanced abdominal computed tomography images acquired using rapid kV-switching dual energy imaging

“…Previous studies have reported inconsistent results for CT numbers measured in virtual unenhanced images. A phantom study by Popnoe et al found that measured enhancement was significantly lower when using VUE images compared to TUE images when any amount of iodine contrast was present [13]. However, accuracy for classifying lesions as "non-enhancing" (< 15 HU) or "enhancing" (> 15 HU) was negatively impacted only for enhancing lesions, as incomplete removal of iodine content tended to make CT numbers in VUE images higher than those in TUE images.…”

“…Currently, there are five commercially-available technologies used to acquire and reconstruct DECT data, including rapid kVp-switching [11][12][13] dual source CT [5-7, 9, 10], single source sequential scanning, split filter CT [14], and detection based DECT using a dual layer detector [15].…”

Spectral CT in Oncology

“…Numerous studies were able to demonstrate an excellent correlation between the density values of VNC images and true non-contrast image data with density differences < 5 HU 11 44 45 46 47 48 49 50 51 52 . However, it should be noted that the density values for VNC images are subject to various influencing factors, e. g. patient habitus or the contrast phase, with some differences between VNC and true non-contrast image data being significant, which can result in an incorrect classification of lesions 11 52 .…”

“…Insgesamt konnten zahlreiche Studien eine exzellente Korrelation zwischen den Dichtewerten der VNC und den echten nativen Bilddaten mit Dichtedifferenzen < 5 HU demonstrieren 11 44 45 46 47 48 49 50 51 52 . Jedoch ist anzumerken, dass die Dichtewerte in VNC-Bildern verschiedenen Einflusswerten wie z.…”