OBJECTIVES: The aim of this study was to investigate the impact of virtual monoenergetic imaging (VMI+) and dual-energy computed tomography perfusion maps (DECT-PMs) on reader confidence and diagnostic accuracy in dual-energy computed tomography pulmonary angiography (DE-CTPA) studies with suboptimal contrast attenuation, compared with standard linearly blended reconstruction series. MATERIALS AND METHODS: Dual-energy computed tomography pulmonary angiography examinations with suboptimal contrast attenuation of 68 patients with suspected pulmonary embolism (PE) were included in this institutional review board-approved retrospective study. Virtual monoenergetic imaging series at 40 keV, DECT-PM, and linearly blended images (M_0.6, 60% 90-kV spectrum) were reconstructed. Contrast-to-noise ratio and signal-to-noise ratio within the pulmonary trunk were calculated. Four independent radiologists assessed the presence of PE and their diagnostic confidence using 3 DE-CTPA reconstruction protocols: protocol 1, M_0.6 images; protocol 2, M_0.6 series and DECT-PM; and protocol 3, M_0.6, DECT-PM, and VMI+ series. Receiver operating characteristic (ROC) analysis was performed. RESULTS: Fourteen patients showed central and 29 segmental PE. Greater contrast-to-noise ratio and signal-to-noise ratio values were measured in VMI+ series at 40 keV in comparison to M_0.6 images (P < 0.001). Diagnostic accuracy for segmental PE detection was as follows: protocol 1 (69.1%); protocol 2 (86.8%); and protocol 3 (92.6%). Protocol 3 resulted in a significantly greater area under the curve for diagnosing segmental PE (0.991, P ≤ 0.033), compared with protocol 1 and 2 (0.897 and 0.951, respectively), and provided the highest diagnostic confidence (P < 0.001). CONCLUSIONS: A reconstruction protocol including 40-keV VMI+ series and DECT-PM improves reader confidence and diagnostic accuracy for segmental PE detection compared with standard M_0.6 images in DE-CTPA with suboptimal contrast attenuation.
OBJECTIVES: The aim of this study was to investigate the impact of virtual monoenergetic imaging (VMI+) and dual-energy computed tomography perfusion maps (DECT-PMs) on reader confidence and diagnostic accuracy in dual-energy computed tomography pulmonary angiography (DE-CTPA) studies with suboptimal contrast attenuation, compared with standard linearly blended reconstruction series. MATERIALS AND METHODS: Dual-energy computed tomography pulmonary angiography examinations with suboptimal contrast attenuation of 68 patients with suspected pulmonary embolism (PE) were included in this institutional review board-approved retrospective study. Virtual monoenergetic imaging series at 40 keV, DECT-PM, and linearly blended images (M_0.6, 60% 90-kV spectrum) were reconstructed. Contrast-to-noise ratio and signal-to-noise ratio within the pulmonary trunk were calculated. Four independent radiologists assessed the presence of PE and their diagnostic confidence using 3 DE-CTPA reconstruction protocols: protocol 1, M_0.6 images; protocol 2, M_0.6 series and DECT-PM; and protocol 3, M_0.6, DECT-PM, and VMI+ series. Receiver operating characteristic (ROC) analysis was performed. RESULTS: Fourteen patients showed central and 29 segmental PE. Greater contrast-to-noise ratio and signal-to-noise ratio values were measured in VMI+ series at 40 keV in comparison to M_0.6 images (P < 0.001). Diagnostic accuracy for segmental PE detection was as follows: protocol 1 (69.1%); protocol 2 (86.8%); and protocol 3 (92.6%). Protocol 3 resulted in a significantly greater area under the curve for diagnosing segmental PE (0.991, P ≤ 0.033), compared with protocol 1 and 2 (0.897 and 0.951, respectively), and provided the highest diagnostic confidence (P < 0.001). CONCLUSIONS: A reconstruction protocol including 40-keV VMI+ series and DECT-PM improves reader confidence and diagnostic accuracy for segmental PE detection compared with standard M_0.6 images in DE-CTPA with suboptimal contrast attenuation.
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
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Authors: Giuseppe Cicero; Giorgio Ascenti; Moritz H Albrecht; Alfredo Blandino; Marco Cavallaro; Tommaso D'Angelo; Maria Ludovica Carerj; Thomas J Vogl; Silvio Mazziotti Journal: Radiol Med Date: 2020-01-10 Impact factor: 3.469
Authors: Kishore Rajendran; Martin Petersilka; André Henning; Elisabeth R Shanblatt; Bernhard Schmidt; Thomas G Flohr; Andrea Ferrero; Francis Baffour; Felix E Diehn; Lifeng Yu; Prabhakar Rajiah; Joel G Fletcher; Shuai Leng; Cynthia H McCollough Journal: Radiology Date: 2021-12-14 Impact factor: 11.105
Authors: Ioannis Vlahos; Megan C Jacobsen; Myrna C Godoy; Konstantinos Stefanidis; Rick R Layman Journal: Br J Radiol Date: 2021-09-24 Impact factor: 3.039
Authors: Lukas Lenga; Franziska Trapp; Moritz H Albrecht; Julian L Wichmann; Addison A Johnson; Ibrahim Yel; Tommaso D'Angelo; Christian Booz; Thomas J Vogl; Simon S Martin Journal: Eur Radiol Date: 2019-01-21 Impact factor: 5.315
Authors: Hao Gong; Jeffrey F Marsh; Karen N D'Souza; Nathan R Huber; Kishore Rajendran; Joel G Fletcher; Cynthia H McCollough; Shuai Leng Journal: J Med Imaging (Bellingham) Date: 2021-04-19