Victor Neuhaus1, Nils Große Hokamp2, Nuran Abdullayev2, Robert Rau2, Anastasios Mpotsaris2, David Maintz2, Jan Borggrefe2. 1. Department of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937 Cologne, Germany. Electronic address: victor-frederic.neuhaus@uk-koeln.de. 2. Department of Diagnostic and Interventional Radiology, University Hospital Cologne, Kerpener Str. 62, 50937 Cologne, Germany.
Abstract
OBJECTIVE: The aim of the study was to investigate the performance and diagnostic value of metal artifact reduction in virtual monoenergetic images generated from dual-layer computed tomography (DLCT). METHODS:35 patients that received a DLCT at the University Hospital Cologne and had an orthopedic implant in the examined region were included in this study. For each DLCT virtual monoenergetic images of different energy levels (64keV, 70keV, 105keV, 140keV, 200keV and an optimized photon energy) were reconstructed and analyzed by three blinded observers. Images were analyzed with regard to subjective criteria (extent of artifacts, diagnostic image quality) and objective criteria (width and density of artifacts). RESULTS:21 patients had implants in the spine, 8 in the pelvis and 6 patients in the extremities. Diagnostic image quality improved significantly at high photon energies from a Likert-score of 4.3 (±0.83) to 2.3 (±1.02) and artifacts decreased significantly from a score of 4.3 (±0.66) to 2.6 (±2.57). The average optimized photon energy was 149.2±39.4keV. The density as well as the width of the most pronounced artifacts decreased from-374.6±251.89HU to -12.5±205.84HU and from 14.5±8.74mm to 6.4±10.76mm, respectively. CONCLUSION: Using virtual monoenergetic images valuable improvements of diagnostic image quality can be achieved by reduction of artifacts associated with metal implants. As preset for virtual monoenergetic images, 140keV appear to provide optimal artifact reduction. In 20% of the patients, individually optimized keV can lead to a further improvement of image quality compared to 140keV.
RCT Entities:
OBJECTIVE: The aim of the study was to investigate the performance and diagnostic value of metal artifact reduction in virtual monoenergetic images generated from dual-layer computed tomography (DLCT). METHODS: 35 patients that received a DLCT at the University Hospital Cologne and had an orthopedic implant in the examined region were included in this study. For each DLCT virtual monoenergetic images of different energy levels (64keV, 70keV, 105keV, 140keV, 200keV and an optimized photon energy) were reconstructed and analyzed by three blinded observers. Images were analyzed with regard to subjective criteria (extent of artifacts, diagnostic image quality) and objective criteria (width and density of artifacts). RESULTS: 21 patients had implants in the spine, 8 in the pelvis and 6 patients in the extremities. Diagnostic image quality improved significantly at high photon energies from a Likert-score of 4.3 (±0.83) to 2.3 (±1.02) and artifacts decreased significantly from a score of 4.3 (±0.66) to 2.6 (±2.57). The average optimized photon energy was 149.2±39.4keV. The density as well as the width of the most pronounced artifacts decreased from-374.6±251.89HU to -12.5±205.84HU and from 14.5±8.74mm to 6.4±10.76mm, respectively. CONCLUSION: Using virtual monoenergetic images valuable improvements of diagnostic image quality can be achieved by reduction of artifacts associated with metal implants. As preset for virtual monoenergetic images, 140keV appear to provide optimal artifact reduction. In 20% of the patients, individually optimized keV can lead to a further improvement of image quality compared to 140keV.
Authors: Tommaso D'Angelo; Giuseppe Cicero; Silvio Mazziotti; Giorgio Ascenti; Moritz H Albrecht; Simon S Martin; Ahmed E Othman; Thomas J Vogl; Julian L Wichmann Journal: Br J Radiol Date: 2019-04-09 Impact factor: 3.039
Authors: Kai Roman Laukamp; Simon Lennartz; Victor-Frederic Neuhaus; Nils Große Hokamp; Robert Rau; Markus Le Blanc; Nuran Abdullayev; Anastasios Mpotsaris; David Maintz; Jan Borggrefe Journal: Eur Radiol Date: 2018-05-03 Impact factor: 5.315
Authors: Nils Große Hokamp; Brendan Eck; Florian Siedek; Daniel Pinto Dos Santos; Jasmin A Holz; David Maintz; Stefan Haneder Journal: Quant Imaging Med Surg Date: 2020-05
Authors: Jan Borggrefe; Victor-Frederic Neuhaus; Markus Le Blanc; Nils Grosse Hokamp; Volker Maus; Anastasios Mpotsaris; Simon Lennartz; Daniel Pinto Dos Santos; David Maintz; Nuran Abdullayev Journal: Eur Radiol Date: 2018-12-06 Impact factor: 5.315
Authors: Hildegard M Wichtmann; Kai R Laukamp; Sebastian Manneck; Konrad Appelt; Bram Stieltjes; Daniel T Boll; Matthias R Benz; Markus M Obmann Journal: Abdom Radiol (NY) Date: 2022-09-30
Authors: Kai Roman Laukamp; David Zopfs; Simon Lennartz; Lenhard Pennig; David Maintz; Jan Borggrefe; Nils Große Hokamp Journal: Eur Radiol Date: 2019-01-16 Impact factor: 5.315