BACKGROUND: New technology combining dual-energy CT with the latest gemstone detectors for spectral imaging (GSI) can be used to synthesize monochromatic images that mimic images as if different monochromatic x-ray sources were used. OBJECTIVE: The aim of the study was to evaluate the optimal combination of monochromatic image energy and adaptive statistical iterative reconstruction (ASiR) for monochromatic reconstruction of coronary CT angiography (CTA) images with the use of GSI. METHODS: Twenty consecutive patients underwent coronary CTA on a GSI capable 64-slice CT scanner (Discovery CT 750 High Definition, GE Healthcare). In 7 sets of monochromatic images (60, 65, 70, 75, 80, 90, and 110 keV; each with increasing contributions of ASiR, ie, 0%, 20%, 40%, 60%, and 80%; n = 35 reconstructions per patient), signal-to-noise (aortic root) and contrast-to-noise (left main artery) ratios were assessed. Signal-to-noise ratio, contrast-to-noise ratio, and image quality (graded on a 5-point Likert scale) were assessed in all above monochromatic reconstructions and compared with the respective standard (conventional polychromatic) image. RESULTS: Compared with conventional polychromatic images, reconstructions with 60 keV and 80% ASiR showed the highest improvement in contrast-to-noise (144%; P < 0.001) and signal-to-noise ratio (173%; P < 0.001). Image quality reached a plateau at 65-75 keV with 40%-60% ASiR blending, yielding a maximal image quality score improvement of 50% compared with conventional imaging (P < 0.001). CONCLUSION: In coronary CTA with low radiation technique (mean radiation dose, 1.8 ± 0.7 mSv), GSI with monochromatic reconstructions (65-75 keV) and ASiR (40%-60%) offers significant noise reduction and image quality improvement.
BACKGROUND: New technology combining dual-energy CT with the latest gemstone detectors for spectral imaging (GSI) can be used to synthesize monochromatic images that mimic images as if different monochromatic x-ray sources were used. OBJECTIVE: The aim of the study was to evaluate the optimal combination of monochromatic image energy and adaptive statistical iterative reconstruction (ASiR) for monochromatic reconstruction of coronary CT angiography (CTA) images with the use of GSI. METHODS: Twenty consecutive patients underwent coronary CTA on a GSI capable 64-slice CT scanner (Discovery CT 750 High Definition, GE Healthcare). In 7 sets of monochromatic images (60, 65, 70, 75, 80, 90, and 110 keV; each with increasing contributions of ASiR, ie, 0%, 20%, 40%, 60%, and 80%; n = 35 reconstructions per patient), signal-to-noise (aortic root) and contrast-to-noise (left main artery) ratios were assessed. Signal-to-noise ratio, contrast-to-noise ratio, and image quality (graded on a 5-point Likert scale) were assessed in all above monochromatic reconstructions and compared with the respective standard (conventional polychromatic) image. RESULTS: Compared with conventional polychromatic images, reconstructions with 60 keV and 80% ASiR showed the highest improvement in contrast-to-noise (144%; P < 0.001) and signal-to-noise ratio (173%; P < 0.001). Image quality reached a plateau at 65-75 keV with 40%-60% ASiR blending, yielding a maximal image quality score improvement of 50% compared with conventional imaging (P < 0.001). CONCLUSION: In coronary CTA with low radiation technique (mean radiation dose, 1.8 ± 0.7 mSv), GSI with monochromatic reconstructions (65-75 keV) and ASiR (40%-60%) offers significant noise reduction and image quality improvement.
Authors: Stefanie Mangold; Carlo N De Cecco; U Joseph Schoepf; Ricardo T Yamada; Akos Varga-Szemes; Andrew C Stubenrauch; Damiano Caruso; Stephen R Fuller; Thomas J Vogl; Konstantin Nikolaou; Thomas M Todoran; Julian L Wichmann Journal: Eur Radiol Date: 2016-03-09 Impact factor: 5.315
Authors: Jack W Lambert; Yuxin Sun; Karen G Ordovas; Robert G Gould; Sizhe Wang; Benjamin M Yeh Journal: J Comput Assist Tomogr Date: 2018 May/Jun Impact factor: 1.826
Authors: Wei-Hua Yin; Hong-Yue Wang; Yan Zhang; Bin Lu; Yang Sun; Xiang-Nan Li; Zhong-Fei Lu; Yun-Qiang An; Zhi-Hui Hou; Jie Zhang; Xin-Shuang Ren; U Joseph Schoepf Journal: Quant Imaging Med Surg Date: 2022-05