PURPOSE: To evaluate virtual-non-contrast (VNC) images obtained from clinical triphasic scans with a dual-layer spectral computed tomography system regarding accuracy of iodine subtraction. MATERIAL AND METHODS: From September to December 2016, 62 consecutive patients who underwent a clinical routine triphasic CT examination were included into this retrospective study. VNC images based on the arterial and portal venous phase were generated. For every patient and every contrast phase, a region-of-interest (ROI) was defined in aorta, liver, renal cortex, spongious bone, fat, muscle and fluid (i.e. gallbladder, urinary bladder), resulting in 2170 ROIs. VNC images were compared to true-non-contrast (TNC) images regarding difference in attenuation. Consistency between VNC images obtained from the arterial and portal venous phase as well as the influence of the initial attenuation on respective VNC images were evaluated. RESULTS: Comparison of HU in VNC and TNC images showed a high accuracy of iodine elimination. Mean difference between TNC and VNC images was only 0.5 ± 8.5 HU and >90% of all comparisons showed a difference of less than 15 HU. For all tissues but spongious bone, mean absolute difference between TNC and VNC images was below 10 HU. VNC images derived from the arterial and the portal venous phase showed excellent correlation. The quality of iodine removal in VNC images was not influenced by the original contrast enhancement. However, VNC images cannot be used for evaluation of iodine removal in bone as bone and iodine can hardly be differentiated via spectral CT. CONCLUSION: VNC imaging in DL-CT is a promising tool for daily clinical routine. As non-enhanced CT images are essential in multiple clinical situations, the permanent availability of VNC images with dual-layer spectral CT will result in a substantial reduction of radiation exposure and an increased diagnostic value of monophasic contrast-enhanced CT scans.
PURPOSE: To evaluate virtual-non-contrast (VNC) images obtained from clinical triphasic scans with a dual-layer spectral computed tomography system regarding accuracy of iodine subtraction. MATERIAL AND METHODS: From September to December 2016, 62 consecutive patients who underwent a clinical routine triphasic CT examination were included into this retrospective study. VNC images based on the arterial and portal venous phase were generated. For every patient and every contrast phase, a region-of-interest (ROI) was defined in aorta, liver, renal cortex, spongious bone, fat, muscle and fluid (i.e. gallbladder, urinary bladder), resulting in 2170 ROIs. VNC images were compared to true-non-contrast (TNC) images regarding difference in attenuation. Consistency between VNC images obtained from the arterial and portal venous phase as well as the influence of the initial attenuation on respective VNC images were evaluated. RESULTS: Comparison of HU in VNC and TNC images showed a high accuracy of iodine elimination. Mean difference between TNC and VNC images was only 0.5 ± 8.5 HU and >90% of all comparisons showed a difference of less than 15 HU. For all tissues but spongious bone, mean absolute difference between TNC and VNC images was below 10 HU. VNC images derived from the arterial and the portal venous phase showed excellent correlation. The quality of iodine removal in VNC images was not influenced by the original contrast enhancement. However, VNC images cannot be used for evaluation of iodine removal in bone as bone and iodine can hardly be differentiated via spectral CT. CONCLUSION: VNC imaging in DL-CT is a promising tool for daily clinical routine. As non-enhanced CT images are essential in multiple clinical situations, the permanent availability of VNC images with dual-layer spectral CT will result in a substantial reduction of radiation exposure and an increased diagnostic value of monophasic contrast-enhanced CT scans.
Authors: Kai Roman Laukamp; Simon Lennartz; Vivian Ho; Nils Große Hokamp; David Zopfs; Amit Gupta; Frank Philipp Graner; Jan Borggrefe; Robert Gilkeson; Nikhil Ramaiya Journal: Br J Radiol Date: 2020-01-02 Impact factor: 3.039
Authors: David Zopfs; Simon Lennartz; Charlotte Zaeske; Martin Merkt; Kai Roman Laukamp; Robert Peter Reimer; David Maintz; Jan Borggrefe; Nils Grosse Hokamp Journal: Br J Radiol Date: 2020-03-04 Impact factor: 3.039
Authors: Andreas P Sauter; Nadav Shapira; Felix K Kopp; Juliane Aichele; Jannis Bodden; Andreas Knipfer; Ernst J Rummeny; Peter B Noël Journal: Eur J Radiol Open Date: 2020-05-07
Authors: Kai Roman Laukamp; Simon Lennartz; Ahmad Hashmi; Markus Obmann; Vivian Ho; Nils Große Hokamp; Frank Philipp Graner; Robert Gilkeson; Thorsten Persigehl; Amit Gupta; Nikhil Ramaiya Journal: Sci Rep Date: 2020-04-24 Impact factor: 4.379