Nils Große Hokamp1, K R Laukamp2, S Lennartz2, D Zopfs2, N Abdullayev2, V F Neuhaus2, D Maintz2, J Borggrefe2. 1. Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany; Department of Radiology, University Hospitals Cleveland, Cleveland, OH, USA; Department of Radiology, School of Medicine, Case Western Reserve University, Cleveland, OH, USA. Electronic address: nils.grosse-hokamp@uk-koeln.de. 2. Institute of Diagnostic and Interventional Radiology, University Hospital Cologne, Cologne, Germany.
Abstract
OBJECTIVES: Image quality in head and neck imaging is often severely hampered by artifacts arising from dental implants. This study evaluates metal artifact (MA) reduction using virtual monoenergetic images (VMI) compared to conventional CT images (CI) from spectral-detector computed tomography (SDCT). METHODS: 38 consecutive patients with dental implants were included in this retrospective study. All examinations were performed using a SDCT (IQon, Philips, Best, The Netherlands). Images were reconstructed as conventional images (CI) and as VMI in a range of 40-200 keV (10 keV increment). Quantitative image analysis was performed ROI-based by measurement of attenuation (HU) and standard deviation in most pronounced hypo- and hyperdense artifact, fat and soft tissue with presence of artifacts. Qualitatively, extent of artifact reduction, assessment of soft palate and cheeks were rated on 5-point Likert-scales by two radiologists. Statistical data evaluation included ANOVA and Wilcoxon-test with correction for multiple comparisons; interrater-agreement was determined by intraclass-correlation coefficient (ICC). RESULTS: The hypo- and hyperattenuating artifacts showed an increase and decrease of HU-values in VMIhigh (CI/VMI200 keV: -218.7/-174.4 HU, p = 0.1; and 309.8/119.2, p ≤ 0.05, respectively). Artifacts in the fat, as depicted by image noise did also decrease in VMIhigh (CI/VMI200 keV: 23.9/16.4, p ≤ 0.05). Qualitatively, hyperdense artifacts were decreased significantly in VMI ≥100 keV (e.g. CI/VMI200 keV: 2(1-3)/3(1-5), p ≤ 0.05). Artifact reduction resulted in improved assessment of the soft palate and cheeks (e.g. CI/VMI200 keV: 2(1-4)/3(1-5) and 2(1-5)/3(1-5), p ≤ 0.05). Overall interrater agreement was good (ICC = 0.77). CONCLUSIONS: Virtual monoenergetic images from SDCT reduce metal artifacts from dental implants and improve diagnostic assessment of surrounding soft tissue.
OBJECTIVES: Image quality in head and neck imaging is often severely hampered by artifacts arising from dental implants. This study evaluates metal artifact (MA) reduction using virtual monoenergetic images (VMI) compared to conventional CT images (CI) from spectral-detector computed tomography (SDCT). METHODS: 38 consecutive patients with dental implants were included in this retrospective study. All examinations were performed using a SDCT (IQon, Philips, Best, The Netherlands). Images were reconstructed as conventional images (CI) and as VMI in a range of 40-200 keV (10 keV increment). Quantitative image analysis was performed ROI-based by measurement of attenuation (HU) and standard deviation in most pronounced hypo- and hyperdense artifact, fat and soft tissue with presence of artifacts. Qualitatively, extent of artifact reduction, assessment of soft palate and cheeks were rated on 5-point Likert-scales by two radiologists. Statistical data evaluation included ANOVA and Wilcoxon-test with correction for multiple comparisons; interrater-agreement was determined by intraclass-correlation coefficient (ICC). RESULTS: The hypo- and hyperattenuating artifacts showed an increase and decrease of HU-values in VMIhigh (CI/VMI200 keV: -218.7/-174.4 HU, p = 0.1; and 309.8/119.2, p ≤ 0.05, respectively). Artifacts in the fat, as depicted by image noise did also decrease in VMIhigh (CI/VMI200 keV: 23.9/16.4, p ≤ 0.05). Qualitatively, hyperdense artifacts were decreased significantly in VMI ≥100 keV (e.g. CI/VMI200 keV: 2(1-3)/3(1-5), p ≤ 0.05). Artifact reduction resulted in improved assessment of the soft palate and cheeks (e.g. CI/VMI200 keV: 2(1-4)/3(1-5) and 2(1-5)/3(1-5), p ≤ 0.05). Overall interrater agreement was good (ICC = 0.77). CONCLUSIONS: Virtual monoenergetic images from SDCT reduce metal artifacts from dental implants and improve diagnostic assessment of surrounding soft tissue.
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: 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
Authors: Amit Gupta; Verena Carola Obmann; Michelle Jordan; Simon Lennartz; Markus Michael Obmann; Nils Große Hokamp; David Zopfs; Lenhard Pennig; Gina Fürtjes; Nikhil Ramaiya; Robert Gilkeson; Kai Roman Laukamp Journal: Quant Imaging Med Surg Date: 2021-01
Authors: Lukas Lenga; Marvin Lange; Simon S Martin; Moritz H Albrecht; Christian Booz; Ibrahim Yel; Christophe T Arendt; Thomas J Vogl; Doris Leithner Journal: Br J Radiol Date: 2021-04-29 Impact factor: 3.039
Authors: Lenhard Pennig; David Zopfs; Roman Gertz; Johannes Bremm; Charlotte Zaeske; Nils Große Hokamp; Erkan Celik; Lukas Goertz; Marcel Langenbach; Thorsten Persigehl; Amit Gupta; Jan Borggrefe; Simon Lennartz; Kai Roman Laukamp Journal: Eur Radiol Date: 2021-02-25 Impact factor: 5.315
Authors: Boyuan Li; Derrek Spronk; Yueting Luo; Connor Puett; Christina R Inscoe; Donald A Tyndall; Yueh Z Lee; Jianping Lu; Otto Zhou Journal: PLoS One Date: 2022-02-03 Impact factor: 3.240