V A Sahni1, A B Shinagare, S G Silverman. 1. Division of Abdominal Imaging and Intervention, Department of Radiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02115, USA. vsahni@partners.org
Abstract
AIM: To determine how representative virtual unenhanced (VNE) images are of true unenhanced (TNE) images when performing computed tomography (CT) urography on a dual-energy CT (DECT) system, and whether the images are affected by the contrast material phase. MATERIALS AND METHODS: In this retrospective, institutional review board-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant study, TNE were compared with VNE images derived from the nephrographic (VNEn) and excretory (VNEe) phases in 100 consecutive CT urograms. Two readers in consensus measured attenuation values of abdominal organs, fat, and renal lesions (>1 cm). Image noise was correlated with patient thickness. Detectability of renal stones was evaluated. Image quality and acceptability was assessed using a five-point scale. Expected dose saving by removing the TNE phase was calculated. RESULTS: VNE attenuation values of liver, renal parenchyma, and aorta were significantly different to TNE values (p < 0.05); spleen and fat attenuation values showed no significant difference. No significant difference was found between VNEn and VNEe images. Image noise was significantly greater in TNE images (p < 0.0001) and correlated with patient thickness. VNEn and VNEe images had sensitivities of 76.6 and 65.6% for detection of stones, identifying all stones greater than 3 and 4 mm, respectively. Both VNE images received significantly lower image quality scores than TNE images (p < 0.0001); however, the majority of images were deemed acceptable. The mean theoretical dose saving by removing the TNE phase was 35%. CONCLUSION: Although VNE images demonstrate high reader acceptability, accuracy of attenuation values and detection of small stones is limited. The contrast material phase, however, does not affect attenuation values. Further validation of VNE images is recommended prior to clinical implementation.
AIM: To determine how representative virtual unenhanced (VNE) images are of true unenhanced (TNE) images when performing computed tomography (CT) urography on a dual-energy CT (DECT) system, and whether the images are affected by the contrast material phase. MATERIALS AND METHODS: In this retrospective, institutional review board-approved, Health Insurance Portability and Accountability Act (HIPAA)-compliant study, TNE were compared with VNE images derived from the nephrographic (VNEn) and excretory (VNEe) phases in 100 consecutive CT urograms. Two readers in consensus measured attenuation values of abdominal organs, fat, and renal lesions (>1 cm). Image noise was correlated with patient thickness. Detectability of renal stones was evaluated. Image quality and acceptability was assessed using a five-point scale. Expected dose saving by removing the TNE phase was calculated. RESULTS: VNE attenuation values of liver, renal parenchyma, and aorta were significantly different to TNE values (p < 0.05); spleen and fat attenuation values showed no significant difference. No significant difference was found between VNEn and VNEe images. Image noise was significantly greater in TNE images (p < 0.0001) and correlated with patient thickness. VNEn and VNEe images had sensitivities of 76.6 and 65.6% for detection of stones, identifying all stones greater than 3 and 4 mm, respectively. Both VNE images received significantly lower image quality scores than TNE images (p < 0.0001); however, the majority of images were deemed acceptable. The mean theoretical dose saving by removing the TNE phase was 35%. CONCLUSION: Although VNE images demonstrate high reader acceptability, accuracy of attenuation values and detection of small stones is limited. The contrast material phase, however, does not affect attenuation values. Further validation of VNE images is recommended prior to clinical implementation.
Authors: Anushri Parakh; Simon Lennartz; Chansik An; Prabhakar Rajiah; Benjamin M Yeh; Frank J Simeone; Dushyant V Sahani; Avinash R Kambadakone Journal: Radiographics Date: 2021 Jan-Feb Impact factor: 5.333
Authors: Frederik Vandenbroucke; Steven Van Hedent; Gert Van Gompel; Nico Buls; Gordon Craggs; Jef Vandemeulebroucke; Pablo R Ros; Johan de Mey Journal: Insights Imaging Date: 2015-05-05