Nils Große Hokamp1, R Gilkeson2, M K Jordan3, K R Laukamp2, Victor-Frederick Neuhaus4, S Haneder4, S S Halliburton5, A Gupta2. 1. IUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, Cologne, Germany; Department of Radiology, Case Western Reserve University, Cleveland, OH, USA; Department of Radiology, University Hospitals Medical Center, Cleveland, OH, USA. Electronic address: nils.grosse-hokamp@uk-koeln.de. 2. Department of Radiology, Case Western Reserve University, Cleveland, OH, USA; Department of Radiology, University Hospitals Medical Center, Cleveland, OH, USA. 3. Department of Radiology, Case Western Reserve University, Cleveland, OH, USA. 4. IUniversity of Cologne, Faculty of Medicine and University Hospital Cologne, Institute for Diagnostic and Interventional Radiology, Cologne, Germany. 5. Philips Healthcare, Clinical Science CT, Cleveland OH, USA.
Abstract
OBJECTIVE: This study aimed to identify the energy level of virtual monoenergetic images (VMI) that closest represents conventional images (CI) in order to demonstrate that these images provide improved image quality in terms of noise and Signal-to-noise ratio (SD/SNR) while attenuation values (HU) remain unaltered as compared to CI. METHODS: 60 and 30 patients with contrast-enhanced (CE) and non-enhanced (NCE) spectral detector CT (SDCT) of the abdomen were included in this retrospective, IRB-approved study. CI and VMI of 66-74 keV as well as quantitative iodine maps were reconstructed (Q-IodMap). Two regions of interest were placed in each: pulmonary trunk, abdominal aorta, portal vein, liver, pancreas, renal cortex left/right, psoas muscle, (filled) bladder and subcutaneous fat. For each reconstruction, HU and SD were averaged. ΔHU and SNR (SNR = HU/SD) were calculated. Q-IodMap were considered as confounder for ΔHU. In addition, two radiologists compared VMI of 72 keV and CI in a forced-choice approach regarding image quality. RESULTS: In NCE studies, no significant differences for any region was found. In CE studies, VMI72keV images showed lowest ΔHU (HUliver CI/VMI72keV: 104 ± 18/103 ± 17, p ≥ 0.05). Iodine containing voxels as indicated by Q-IodMap resulted in an over- and underestimation of attenuation in lower and higher VMI energies, respectively. Image noise was lower in VMI images (e.g. muscle: CI/ VMI72keV: 15.3 ± 3.3/12.3 ± 2.9 HU, p ≤ 0.05). Hence, SNR was significantly higher in VMI72keV compared to CI (e.g. liver 3.8 ± 0.6 vs 3.0 ± 0.8, p ≤ 0.05). In visual analysis, VMI72keV were preferred over CI at all times. CONCLUSIONS: VMI72keV show improved SD/SNR characteristics while the attenuation remains unaltered as compared to CI.
OBJECTIVE: This study aimed to identify the energy level of virtual monoenergetic images (VMI) that closest represents conventional images (CI) in order to demonstrate that these images provide improved image quality in terms of noise and Signal-to-noise ratio (SD/SNR) while attenuation values (HU) remain unaltered as compared to CI. METHODS: 60 and 30 patients with contrast-enhanced (CE) and non-enhanced (NCE) spectral detector CT (SDCT) of the abdomen were included in this retrospective, IRB-approved study. CI and VMI of 66-74 keV as well as quantitative iodine maps were reconstructed (Q-IodMap). Two regions of interest were placed in each: pulmonary trunk, abdominal aorta, portal vein, liver, pancreas, renal cortex left/right, psoas muscle, (filled) bladder and subcutaneous fat. For each reconstruction, HU and SD were averaged. ΔHU and SNR (SNR = HU/SD) were calculated. Q-IodMap were considered as confounder for ΔHU. In addition, two radiologists compared VMI of 72 keV and CI in a forced-choice approach regarding image quality. RESULTS: In NCE studies, no significant differences for any region was found. In CE studies, VMI72keV images showed lowest ΔHU (HUliver CI/VMI72keV: 104 ± 18/103 ± 17, p ≥ 0.05). Iodine containing voxels as indicated by Q-IodMap resulted in an over- and underestimation of attenuation in lower and higher VMI energies, respectively. Image noise was lower in VMI images (e.g. muscle: CI/ VMI72keV: 15.3 ± 3.3/12.3 ± 2.9 HU, p ≤ 0.05). Hence, SNR was significantly higher in VMI72keV compared to CI (e.g. liver 3.8 ± 0.6 vs 3.0 ± 0.8, p ≤ 0.05). In visual analysis, VMI72keV were preferred over CI at all times. CONCLUSIONS: VMI72keV show improved SD/SNR characteristics while the attenuation remains unaltered as compared to CI.
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: Simon Lennartz; Nils Große Hokamp; Charlotte Zäske; David Zopfs; Grischa Bratke; Andreas Glauner; David Maintz; Thorsten Persigehl; De-Hua Chang; Tilman Hickethier Journal: Br J Radiol Date: 2020-07-24 Impact factor: 3.039
Authors: Juliane Conzelmann; Felix Benjamin Schwarz; Bernd Hamm; Michael Scheel; Paul Jahnke Journal: J Appl Clin Med Phys Date: 2020-07-28 Impact factor: 2.102
Authors: Jasmin A Holz; Hatem Alkadhi; Kai R Laukamp; Simon Lennartz; Carola Heneweer; Michael Püsken; Thorsten Persigehl; David Maintz; Nils Große Hokamp Journal: Sci Rep Date: 2020-12-09 Impact factor: 4.379
Authors: Robert Peter Reimer; Nils Große Hokamp; Julius Niehoff; David Zopfs; Simon Lennartz; Mariam Heidar; Roger Wahba; Dirk Stippel; David Maintz; Daniel Pinto Dos Santos; Christian Wybranski Journal: PLoS One Date: 2021-06-15 Impact factor: 3.240