PURPOSE: To evaluate the potential of full-iterative reconstruction (IR) for improving image quality of the cystic artery on CT angiography and to assess observer performance. METHODS: Thirty patients who underwent both liver dynamic CT and conventional angiography were included in this retrospective study. All CT data were reconstructed through filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR3D), and forward-projected, model-based, iterative reconstruction solution (FIRST), respectively. In objective study, we analyzed mean ΔCT numbers (the difference between the HU peak of the vessel and the background) and full-width at tenth-maximum (FWTM) of three parts of the cystic artery by profile curve method comparing the three reconstructions. Subjectively, visualization was evaluated using a four-point scale performed by two blinded observers. ANOVA was used for statistical analysis. RESULTS: In all parts of the cystic artery, the mean ΔCT number of FIRST was shown to be significantly better than that of FBP and AIDR3D (p < 0.05). FWTM in FIRST was the smallest in all of the vessels. The mean visualization score was significantly better with FIRST than with other CT reconstructions (p < 0.05). CONCLUSIONS: The FIRST algorithm led to improved CTA visualization of the cystic artery.
PURPOSE: To evaluate the potential of full-iterative reconstruction (IR) for improving image quality of the cystic artery on CT angiography and to assess observer performance. METHODS: Thirty patients who underwent both liver dynamic CT and conventional angiography were included in this retrospective study. All CT data were reconstructed through filtered back projection (FBP), adaptive iterative dose reduction 3D (AIDR3D), and forward-projected, model-based, iterative reconstruction solution (FIRST), respectively. In objective study, we analyzed mean ΔCT numbers (the difference between the HU peak of the vessel and the background) and full-width at tenth-maximum (FWTM) of three parts of the cystic artery by profile curve method comparing the three reconstructions. Subjectively, visualization was evaluated using a four-point scale performed by two blinded observers. ANOVA was used for statistical analysis. RESULTS: In all parts of the cystic artery, the mean ΔCT number of FIRST was shown to be significantly better than that of FBP and AIDR3D (p < 0.05). FWTM in FIRST was the smallest in all of the vessels. The mean visualization score was significantly better with FIRST than with other CT reconstructions (p < 0.05). CONCLUSIONS: The FIRST algorithm led to improved CTA visualization of the cystic artery.
Authors: Annemarie M Den Harder; Martin J Willemink; Quirina M B De Ruiter; Pim A De Jong; Arnold M R Schilham; Gabriel P Krestin; Tim Leiner; Ricardo P J Budde Journal: Br J Radiol Date: 2015-11-12 Impact factor: 3.039
Authors: Annemarie M den Harder; Martin J Willemink; Quirina M B de Ruiter; Arnold M R Schilham; Gabriel P Krestin; Tim Leiner; Pim A de Jong; Ricardo P J Budde Journal: Eur J Radiol Date: 2015-07-17 Impact factor: 3.528
Authors: Sonja Gordic; Lotus Desbiolles; Martin Sedlmair; Robert Manka; André Plass; Bernhard Schmidt; Daniela B Husarik; Francesco Maisano; Simon Wildermuth; Hatem Alkadhi; Sebastian Leschka Journal: Eur Radiol Date: 2015-06-03 Impact factor: 5.315
Authors: William P Shuman; Doug E Green; Janet M Busey; Orpheus Kolokythas; Lee M Mitsumori; Kent M Koprowicz; Jean-Baptiste Thibault; Jiang Hsieh; Adam M Alessio; Eunice Choi; Paul E Kinahan Journal: AJR Am J Roentgenol Date: 2013-05 Impact factor: 3.959